Home Healthcare Diabetic Patients
I need the attached project revised and corrected as indicated in the comments. There are two of the same paper. Please correct the one with Chair’s comments but also look at the second one with AQR’s revision and help made corrections in the main paper.
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Improving Medication Adherence among Type II Home Healthcare Diabetic Patients
Submitted by
Bola Odusola-Stephen
A Direct Practice Improvement Project Presented in Partial Fulfillment
of the Requirements for the Degree
Doctor of Nursing Practice
Grand Canyon University
Phoenix, Arizona
April 6, 2021
© Bola Odusola-Stephen, 2020
All rights reserved.
GRAND CANYON UNIVERSITY
Improving Medication Adherence among Type II Home Healthcare Diabetic Patients
by
Bola Odusola-Stephen
has been approved.
April 6, 2021
APPROVED:
Maria Thomas., DNP., DPI Project Chairperson
Bamidele Jokodola., DNP., DPI Project Mentor
ACCEPTED AND SIGNED:
________________________________________
Lisa Smith, PhD, RN, CNE
Dean and Professor, College of Nursing and Health Care Professions
_________________________________________
Date
Abstract
Patient medication adherence is essential in their disease management for home health Type II diabetic patients. At the project site, there was no standardized process for identifying and addressing the patient’s medication adherence. The purpose of this quantitative quasi-experimental project is to determine to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The nursing theory and change model that will guide this project is Orem’s Self-Care Deficit Theory and Diffusion of Infusion Model. Data will be collected on the medication adherence rates pre-and-post-implementation of the project. It will be analyzed utilizing an independent t-test to determine the statistical significance. The clinical significance could be found in the nurses being consistent in performing the medication adherence screenings and providing the patient-centered strategy for the patient to remain compliant. The findings should suggest that implementing the medication adherence program could improve patient compliance rates. This project’s recommendation is to conduct it using larger populations of home health patients for a longer timeframe.
Keywords: diabetes mellitus type II, home-based care, medication adherence, MAP resources, quantitative approach
Dedication
An optional dedication may be included here. While a practice improvement project is an objective, scientific document, this is the place to use the first person and to be subjective. The dedication page is numbered with a Roman numeral, but the page number does not appear in the Table of Contents. It is only included in the final practice improvement project and is not part of the proposal. If this page is not to be included, delete the heading, the body text, and the page break below.
Acknowledgments
An optional acknowledgements page can be included here. This is another place to use the first person. If it applies, acknowledge and identify grants and other means of financial support. Also acknowledge supportive colleagues who rendered assistance. The acknowledgments page is numbered with a Roman numeral, but the page number does not appear in the Table of Contents. This page provides a formal opportunity to thank family, friends, and faculty members who have been helpful and supportive. The acknowledgements page is only included in the final practice improvement project and is not part of the proposal. If this page is not to be included, delete the heading, the body text, and the page break below. If you cannot see the page break, click on the Show/Hide button (go to the Home tab and then to the Paragraph toolbar).
Table of Contents
Chapter 1: Introduction to the Project 1
Advancing Scientific Knowledge. 7
Nature of the Project Design. 11
Assumptions, Limitations, Delimitations. 14
Summary and Organization of the Remainder of the Project 15
Chapter 2: Literature Review.. 18
Population and Sample Selection. 37
Instrumentation or Sources of Data 39
Data Collection Procedures. 41
Potential Bias and Mitigation. 43
Chapter 4: Data Analysis and Results. 68
Chapter 5: Summary, Conclusions, and Recommendations. 81
Summary of Findings and Conclusion. 83
Recommendations for Future Projects. 87
Recommendations for Practice. 88
The Parts of a Practice Improvement Project 92
What is my DPI project design?. 94
Power Analysis Using G Power 96
Example SPSS Dataset & Variable View.. 97
How to Make APA Format Tables and Figures Using Microsoft Word. 98
Writing up your statistical results. 108
Table 1. Characteristics of Variables. 42
Table 2. Type of Methodology and Rationale for Selecting It 45
Table 3. A Sample Data Table Showing Correct Formatting. 71
Table 4. t-Test for Equality of Emotional Intelligence Mean Scores by Gender 75
Table 5. The Servant Leader 76
(Note: single-space table titles; use “Add a Space After Paragraph” (12pt) in Line Spacing Options between table titles)
Figure 1. Approaches to Collecting the Data to Answer the Clinical Questions. 43
Figure 2. Parametric Statistics for Analysis of Ratio or Interval Level Dependent Variable. 58
Figure 3. Non-Parametric Statistics for Analysis of Nominal or Ordinal Level Dependent Variable 59
Figure 4. Scattor Plot Example – Strong Negative Correlation. 78
(Note: single-space figure titles; use “Add a Space After Paragraph” (12pt) in Line Spacing Options between table titles) double-space between entries)
Chapter 1: Introduction to the Project
According to the Centers for Disease Control and Prevention (2020), diabetes impacts one in ten Americans. Furthermore, the prevalence of diabetes continues to rise and is projected to increase by 0.3% per year until 2030 (Lin et al., 2018). For individuals with Type II diabetes, proper and effective medication adherence is critical (Kvarnström et al., 2017). This is particularly significant among healthcare patients because diabetes is one of the leading diagnoses for admission into a home health care facility (Sertbas et al., 2019). The home health service is increasing due to the aging population (Sertbas et al., 2019). In this population, approximately 45% of the patients fail to maintain glycemic control (HgbA1c < 7%) (Polonsky & Henry, 2016). This is attributed to poor medication adherence (Polonsky & Henry, 2016). Poor medication adherence is linked with increased morbidity and mortality rates, increased financial expenses for the patient, hospital, and insurance companies, frequent hospitalizations, and lower quality of life (Polonsky & Henry, 2016).
Various researchers have denoted the critical role that home healthcare providers play in promoting enhanced medication adherence (Bussell et al., 2017). Healthcare providers must assess the patient’s current situation and explore all options to improve the barriers associated with poor medication adherence (Nikitara et al., 2019). Furthermore, they must understand their roles in diabetes care and what obstacles they have when performing their responsibilities (Nikitara et al., 2019).
At the project site, the primary investigator, in collaboration with the stakeholders, noted that the healthcare providers documented ten percent of the patients were not adhering to their medication regimen. This prompted frequent hospitalizations, infections, and other diabetic complications. In further investigation, it was found that there was not a standardized method for the healthcare providers to evaluate the patients regarding medication adherence. Hence, the introduction of the MAP resources and education intervention will be implemented.
The project is worth conducting because the primary investigator focuses on diabetic home health patients who are not the focal point of many literature reviews. Furthermore, little information is noted regarding the impact the healthcare team plays in addressing this population’s lack of medication adherence. The primary investigator aims to introduce a standardized method of addressing patient’s medication adherence using the MAP resources and education to minimize frequent hospitalizations, infections and increase their quality of life. For this project’s purpose, the primary investigator (PI) will examine the impact/role healthcare team members play in addressing patient-related factors that affect medication adherence among home healthcare diabetic patients.
Chapter 1 introduces the project, background, and problem statements. Other segments include the purpose of the project, clinical question, advancing scientific knowledge, and project significance. The last sections consist of the rationale for using a quantitative method and quasi-experimental design, definition of operational terms, assumptions, limitations, and delimitations. The last few sentences are transitional ones providing a preview into Chapter 2.
Background of the Project
Home-based healthcare has existed since 1909 (Choi et al., 2019). Since its inception, home-based healthcare has been perceived as a more costly method of patient care than expenses associated with hospitalization (Singletary, 2019). In the early 20th century, home-based healthcare was mainly practiced due to financial disparities, specifically since many individuals could not afford hospitalized care. Furthermore, home-based healthcare was also practiced due to medical inaccessibility, which often existed in African American communities due to limited access to resources (Choi et al., 2019).
Present-day, home-based healthcare is often selected due to an individual’s personal preferences. There are some situations in which individuals prefer the comforts of their own home compared to that of a hospital or group home (Bryant, 2018). As older generations continue to age, they often prefer to remain in their home for as long as possible. Given the needs of older generations and the impact of advances in healthcare and technology, the prevalence of home-based healthcare has exponentially grown (Wong et al., 2020). While home-based healthcare is not appropriate for all patients, Szanton et al. (2016) noted that this care option is best when an individual’s condition can be managed without admission to a hospital. Patients who have diabetes or hypertension are often recipients of home-based healthcare (Wong et al., 2020).
Adhering to diabetes medication regimen requirements can be complex. A study conducted by Raoufi et al. (2018) noted that ten percent of diabetic patients did not correctly monitor their glucose levels, nor did they adhere to medication requirements. Patients with diabetes often express difficulties adhering to medication regimens, thereby reinforcing the critical role of receiving education from home healthcare providers (Wong et al., 2020). This is in part to the patients not having sufficient knowledge and education regarding diabetes and proper management of the disease (Wong et al., 2020). With diabetes being one of the leading diagnoses for patients needing home health services, healthcare agencies must educate their staff to evaluate the factors prohibiting patients from adhering to their medication regimen.
Problem Statement
It is not known if or to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The population affected are home health Type II diabetic patients in an urban healthcare agency in Texas. The stakeholders have cited that medication adherence among diabetic patients is lacking. According to data obtained from the site’s electronic health record (EHR), home healthcare providers documented that ten percent of diabetic home healthcare patients are not adhering to their medication regimen. Although this percentage four to six percent lower than other percentages cited in the literature for medication non-adherence, in terms of chronic disease management, various researchers have noted the implications associated with lacking adherence to medication regimens (Camacho et al., 2020; Hamrahian, 2020; Misquitta, 2020).
The lack of medication adherence can be attributed to inadequate drug-related knowledge, medication costs, poor understanding of medication regimen, etc., reinforcing the need for this quality improvement project (Heath, 2019; Sharma et al., 2020). Kvarnström et al. (2017) emphasized healthcare providers play a critical role in ensuring medication adherence. To promote medication adherence among patients of a home healthcare facility, the primary investigator will introduce a standardized method for the healthcare providers to assess the patient’s medication adherence. The staff will achieve greater insight by using MAP resources and an education intervention created by Starr and Sacks (2010). The tools utilized in this study, which are from Starr and Sacks’s (2010) MAP Toolkit and Training Guide resources, include: (1) the questions to ask poster, (2) an adherence assessment pad, and (3) my medications list.
The project contributes to solving the problem by introducing a standardized method of evaluating the patient’s medication adherence. It will improve the healthcare provider’s knowledge and awareness regarding the obstacles or factors the patient may face in maintaining a medication regimen. This would help the facility adhere to the current Centers for Disease Control and Prevention (2020) guidelines in controlling their HgbA1c levels, deter healthcare costs, frequent hospitalizations, and infections.
Purpose of the Project
The purpose of this quantitative quasi-experimental project is to determine to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and educational intervention. The dependent variable is medication adherence rates. A quantitative methodology will be used for the project to learn about this population (home health patients) (Allen, 2017). Furthermore, it will allow the primary investigator to determine the relationship between the independent variable (MAP resources and educational intervention) and the dependent variable (medication adherence rates) withi the home health patients (Allen, 2017). A quasi-experimental design will be used to establish a cause-and-effect relationship between the variables. It will also be used for practical reasons (Leedy & Ormrod, 2014).
The specific population that will be addressed are home health patients ages 35 to 64 years old. The selected site serves approximately 100 patients annually, and 30 patients are diagnosed with Type II diabetes. The inclusion criteria are males and females diagnosed with Type II diabetes, oral medication or insulin, and home health patients. The exclusion criteria are individuals with language or cognitive deficits and diagnosed with Type I diabetes. Five staff nurses will help to implement the quality improvement project. They are individuals who are registered nurses, work full-time, and have been employed with the facility over one year.
The geographic location of the project is in an urban area of Houston, Texas. The County statistics show that approximately 17.6% of the population have Type II diabetes (Houston, 2021). During 2016-2018, 20.2% of the population was hospitalized due to diabetic complications (Houston, 2021). There are over 700 000 Medicare participants in a three-county radius, which is higher than the national average (Understanding Houston, 2021). Data further showed that preventable hospital stays occur in older adults 65 and above (Understanding Houston, 2021). This suggested a trend to overuse the hospitals as a primary source of care (Understanding Houston, 2021).
The project contributes to the nursing field by increasing the healthcare providers’ knowledge and awareness of the obstacles and other risk factors involved in a patient not adhering to their medication regimen. Furthermore, it would help increase dialogue between the provider and patient in sharing the details of their behavior (Bussell et al., 2017). The details of medication nonadherence are frequently hidden (Bussell et al., 2017). In a qualitative study conducted by Brown et al. (2016), they suggested that the approach used by healthcare providers asking a patient about their medication-taking behaviors is critical in discovering their medication nonadherence. Educating healthcare providers to discuss the situation using a nonjudgmental approach could uncover the obstacles (Bussell et al., 2017). This creates a positive, blame-free atmosphere allowing the patients to discuss their medication-taking behavior (Bussell et al., 2017).
Clinical
A well-developed clinical question must be related and relevant to patient care. This helps the primary investigator search for evidence-based answers. The clinical question that will direct this quality improvement project is: To what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and educational intervention. The dependent variable is the medication adherence rates.
Advancing Scientific Knowledge
This direct practice improvement project seeks to enhance medication adherence among diabetic home healthcare patients using the MAP resources. As previously noted, at the selected project site, medication adherence among home healthcare patients is lacking. Polonsky and Henry (2016) emphasized that of all the home healthcare patients, diabetes patients have the highest rates of medication non-adherence. According to information gathered from the home healthcare’s EHR, from 2018 to 2019, ten percent of the diabetic patients did not adhere to their prescribed medication regimen. Issues for non-adherence included worry about high medical bills for future management, limited glycemic control, and using the emergency room as a primary care source (Polonsky & Henry, 2016).
Various researchers have cited the benefits associated with patient-provider engagement and collaboration to improve medication adherence. Therefore, to answer a call by researchers, it is necessary to improve medication adherence among diabetic patients (Ong et al., 2018; Polonsky & Henry, 2016; Wong et al., 2017). The advancement of a small step forward at the clinical site is that by improving medication adherence among diabetic patients’ positive patient-related outcomes will likely occur using the MAP protocol. This DPI project targets diabetes patients; hence, the findings might provide insight into improving medication adherence among other home-based care populations (i.e., those with hypertension or heart disease). This will add to the current literature and address the gap found regarding non-medication factors among home health diabetic patients.
The theoretical framework that will be used in this quality improvement project is Orem’s self-care deficit theory. The primary expectations of the theory are that a person should be self-reliant and responsible for their care (RenpenningcN et al., 2003). The theory also notes that nursing is an action described as an interaction between two or more individuals (RenpenningcN et al., 2003). The third assumption is that an individual who successfully meets the self-care conditions understands that it is a primary component in health prevention and illness (RenpenningcN et al., 2003). Hence, their knowledge promotes positive self-care behaviors. The theory is comprised of three related sections: theory of self-care, self-care deficit, and the nursing system (RenpenningcN et al., 2003). It fits the project because it includes healthcare providers assisting patients in their self-care and management to improve their function at a home level (RenpenningcN et al., 2003). The patients cannot effectively manage medication adherence for diabetes, which affects their quality of life and health.
The change model that will be used is the Diffusion of Innovation Model developed by Rogers (2003). There are five stages:
- Knowledge or awareness- the individual is exposed to the change and lacks information.
- Persuasion or interest-the individual becomes interested in the new idea and seeks more information.
- Decision or evaluation- the individual mentally applies the idea to their present and future situation, hence deciding whether to try it.
- Implementation or trial-the individual uses the idea fully.
- Confirmation or adoption- the individual continues to use the idea in their everyday life and health practices.
Utilizing these methods will help the project advance by helping the healthcare providers to implement a standardized method in evaluating the patient’s medication-taking behaviors.
Significance of the Project
The significance of the project is that there continues to be a steady rise in chronic diseases has resulted in more patient care options (Polonsky & Henry, 2016). To meet various population groups’ unique needs, home-based care has gained popularity (Holly, 2020). Type II diabetes patients who qualify for home-based care options must demonstrate their willingness to work with the home healthcare agency at the selected project site. When patients who receive home-based care fail to adhere to the care requirements set forth, adverse outcomes can ensue (Polonsky & Henry, 2016).
The possible results based on the clinical question and problem statement should increase patient compliance related to medication adherence. The project also helps to empower healthcare providers to adequately address medication questions and patient concerns and ensure the patients keep track of their medication regimen, resulting in a reduction in adverse events. Holecki et al. (2018), when the MAP resources were utilized, medication adherence increased significantly.
The findings noted by Holecki et al. (2018) reinforce the beneficial nature of implementing the MAP resources, as this can improve the quality of patient care received. For this quality improvement project, it fits within helping to correct the gap noted in the literature (regarding medication adherence) for this population. Furthermore, it contributes to the clinical site by helping the patients maintain their medication regimen. Hence, decreasing potential infections, hospitalizations, and incurring financial costs to (patients and the facility).
Rationale for Methodology
The methodology chosen for this quality improvement project is quantitative.
Creswell and Creswell (2017) noted a quantitative methodology is best suited for projects that require data in numerical form. In this project, the numerical data will be presented using charts and graphs. These charts and graphs will allow readers to compare medication adherence rates pre-project implementation and post-project implementation.
While qualitative research studies are beneficial, they examine experiences, perspectives, and beliefs about a specific issue (Creswell & Creswell, 2017). The data collection used in this type of methodology is interviews (semi-structured, one-on-one, and focus groups). For this project, the primary investigator is not seeking to understand the participants’ feelings, behaviors, or lived experiences related to medication adherence.
The clinical question for this project is: To what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and educational intervention and the dependent variable is the medication adherence rates. The clinical question will be answered using collected retrospective data prior to the project’s implementation (four weeks) from the electronic medical record and four week’s post-implementation. This strategy will use statistical data that concentrates on the numbers collected and analyzed using an independent t-test.
Nature of the Project Design
A quasi-experimental design will be used for this project. Quasi-experimental designs are used to compare data before and after the implementation of an initiative/intervention. Price et al. (2017), “In a pretest-posttest design, the dependent variable is measured once before the treatment is implemented and once after it is implemented” (Chapter 7, para. 6). Often, these designs are used when research occurs in a controlled environment. While this project will not happen in a controlled environment, the primary investigator selected a quasi-experimental design since it is more cost-effective than an experimental project design (Schweizer et al., 2016). Furthermore, since data pre-project implementation and post-project implementation need to be collected and analyzed to explore the intervention’s impact, a quasi-experimental design is most appropriate.
A correlational design was considered but not appropriate for the project because the primary investigator is not seeking to understand the relationships occurring among the variables (Creswell & Creswell, 2017). This design is typically descriptive relying on a hypothesis (Leedy & Ormord, 2014). The primary investigator will not seek the relationships between the independent variable (MAP resources and education intervention) and the dependent variable (medication adherence rates).
The targeted population are home health patients ages 35 to 64 years old. The selected site serves approximately 100 patients annually, and 30 patients are diagnosed with Type II diabetes. The inclusion criteria are males and females diagnosed with Type II diabetes, oral medication or insulin, and home health patients. The exclusion criteria are individuals with language or cognitive deficits and diagnosed with Type I diabetes.
The data collection process will begin once approved by Grand Canyon University IRB. Recruitment will occur from informational flyers given to the patients during their home health visits with the providers. The nurses will answer any questions regarding the project’s risks, benefits, and purpose and be instructed that the participation is voluntary. The primary investigator will use a convenience sample because of the access to the participants.
Data will be collected retrospectively four weeks prior to project implementation from the electronic medical records (Cradle Solutions) (medication adherence rates). In the last portion of the first week, the primary investigator will educate the healthcare providers regarding using the MAP resources. The staff will begin implementing the tool, and the post medication adherence rates will be assessed four weeks post-implementation. The primary investigator will document the data in a Microsoft Excel 2016 codebook developed by the primary investigator. Once completed, it will be exported into the SPSS-27 and analyzed using an independent t-test. A five-item demographic questionnaire will be used for descriptive statistics of the population. The survey will include (age, gender, years with Type II diabetes, oral or insulin, and education).
Pre-intervention and post-intervention data will be obtained via the project site’s EHR. The questions that will be analyzed are: (1) “Have you experienced any increase in thirst?” (2) “How often do you urinate?” (3) “Do you often feel fatigued even when doing little tasks?” and (4) “Do you experience blurred vision?” In addition to the aforementioned questions, home healthcare providers will ask the patient “Are you taking your medications?” Any information attained from the question and due to probing, observation of patient’s medications, and patient-related medication adherence will be documented in the project site’s EHR. The data will be analyzed using an independent t-test to determine the statistical significance.
Definition of Terms
Adherence Assessment Pad. The Adherence Assessment Pad is part of the MAP resources that explores answers via the patient perspectives. Using the Adherence Assessment Pad, nursing staff members will be able to explore the concerns of patients and adjust, pending further project team review, to the patient’s medication regimen (Starr & Sacks, 2010).
Diabetes. For this project, Type II diabetes is the topic of exploration. It is described as an impairment of the body regulating and using glucose as a fuel source. Type II diabetes is a chronic condition where an excess amount of sugar is circulating in the blood stream (Mayo Clinic, 2019).
Home-based healthcare. The term home-based healthcare or home healthcare references the medical care that is provided to patients in the comfort of the patient’s home (Polonsky & Henry, 2016). Home-based healthcare services differ depending on a patient’s needs, diagnosis, and other factors.
Medication adherence. The term medication adherence references the extent to which a patient, caregiver, or home nurse follows the recommended guidelines on managing a medical condition (Ahmed et al., 2018).
My Medications List. Is a list that provides a breakdown of the patient’s medications, in an easy-to-follow chart format, thereby improving patient medication adherence (Starr & Sacks, 2010).
Questions to Ask Poster. Is a part of the MAP toolkit, which will be utilized during this project. When using the Questions to Ask Poster, home healthcare providers answer six questions to patients about medication adherence and medication knowledge. The questions that providers will answer include: (1) “Why do I need to take this medicine?,” (2) “Is there a less expensive medicine that would work was well?,” (3) “What are the side-effects and how can I deal with them?,” (4) “Can I stop taking any of my other medicines?,” (5) “Is it okay to take my medicine with over-the-counter drugs, herbs, or vitamins?,” and (6) “How can I remember to take my medicine?” Providers must answer all of the questions and should assume that individuals have no medication knowledge, thereby confirming that patients know and understand these critical answers (Starr & Sacks, 2010).
Assumptions, Limitations, Delimitations
As with all practice improvement projects, there are assumptions, limitations, and delimitations that must be addressed. For this project, the first assumption is that medical non-adherence among diabetes patients is caused by lacking medication-specific knowledge, inaccessibility to resources (i.e., physical, or financial), and inadequate information about the benefits of medications. The second assumption is that after the healthcare providers engage in dialogue with patients and thoroughly addressing their concerns, medication-related barriers will be minimized. The third assumption is that medication adherence will improve when patients are provided with a detailed schedule, which is patient-driven and provider-supported, using the MAP resource entitled “My Medications List.”
The limitations of the project are self-reporting of medication adherence by the patients. The second limitation is the healthcare organization being impacted by the COVID-19 pandemic. The new COVID-19 guidelines have affected the current healthcare delivery model. The third limitation is the location of the project and its setting. The fourth limitation is the time to conduct the project (four weeks). A longer timeframe would help the primary investigator analyze the site’s challenges, trends, and sustainability.
One project delimitation noted is the inclusion criteria of the participants. Patients with diabetes, ages 35 to 64, are included in the project. Since this project’s focus is to explore medication adherence among diabetes patients, which is a concern at the project site, it has narrowed the field to learn about other patients and their compliance issues. The second delimitation is the project being conducted in one urban area, located in the southeastern region of the United States, thereby impacting the generalizability of any findings.
Summary and Organization of the Remainder of the Project
The aging population continues to grow at an increasing rate in the United States, hence snowballing the number of individuals taking medications to manage their Type II diabetes. Kyarnstrom et al. (2017) emphasized that for Type II diabetics it is essential that proper and effective medication adherence be maintained. For home healthcare patients 45% of this population fail to maintain glycemic control < 7% (Polonsky & Henry, 2016). This is attributed to poor medication adherence (Polonsky & Henry, 2016). Healthcare providers are a critical component in making a difference by helping patients learn and maintain medication adherence.
The quality improvement project will use a quantitative methodology. The rationale for using this method is to collect numerical data that can be statistically analyzed. A quasi-experimental design will answer the clinical question to determine if the outcome impacted the medication adherence rates. The project will be guided by Orem’s self-care deficit theory and Diffusion of innovation model developed by Rogers (2003).
Chapter 1 provided detailed support for utilizing the MAP resources to improve medication adherence among diabetic patients of the project site. A quantitative, quasi-experimental design will be utilized to explore the impact of the MAP intervention on improving medication adherence among type II diabetes patients of the selected project site. The project site has a history of lacking medication adherence among diabetic patients, which is due to many factors (e.g., lacking medication knowledge, inadequate understanding of medication regimen requirements, etc.). Through utilizing the MAP resources, which foster communication among home healthcare providers and patients and equipping patients to use the My Medications List, medication adherence will likely improve.
Chapter 2 provides a detailed summary of the literature collected related to the project’s clinical question. Information about the theoretical framework and change model is detailed. The chapter comprises five sections, which highlight information about literature obtained from 2016 to 2021. The information presented provides readers in-depth knowledge and the importance of each chosen section.
Chapter 3 presents research methodology details, which the PI will employ. The information presented in the chapter includes the selected research design, the target population, and the sample size. Furthermore, data collection tools (specifically the MAP’s resources) and data analysis procedures are discussed. The reliability and validity of the project instruments are detailed. Finally, ethical considerations for collecting data are addressed.
Chapter 4 will present research findings, which will be analyzed using statistical methods. Results regarding the descriptive and inferential data analyses will be offered. Furthermore, a brief discussion of project-related findings will be provided. Information in Chapter 4 will be presented using graphics and tables. Chapter 5 will present conclusions and recommendations drawn from the project’s results. The impact of the findings, in terms of practical and theoretical knowledge, will be offered.
Chapter 2: Literature
Diabetes mellitus (DM) is a global epidemic in this era, and many diabetic patients comprise Type II diabetes mellitus (Rana et al., 2019). Medication adherence is a critical component and key determinant in obtaining therapeutic success and reducing diabetic complications (Rana et al., 2019). For Type II diabetic home health patients, this is vital in self-care and management of the disease. Unfortunately, approximately 30% to 50% of patients adhere to their medication regimen (Hennessey & Peters, 2019).
Diabetes is a lifestyle disease, which can be prevented or avoided by making lifestyle changes. Disease management can also occur through adhering to one’s prescribed medication regimen(s). Medication adherence is important since it can help to reduce the likelihood of diabetes-related challenges and complications.
In the United States (U.S.), the problem is associated with increased morbidity and mortality rates, with approximately 125,000 deaths and 10% of hospitalizations annually (Hennessey & Peters, 2019). Furthermore, medication nonadherence costs the U.S. healthcare systems roughly $100 billion to $317 billion yearly (Kini & Ho, 2018). The purpose of this quantitative quasi-experimental project is to determine to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks.
The primary investigator conducted a literature review utilizing peer-reviewed articles from 2016 to current. The inclusion criteria were articles written in English, topics specific to the project such as barriers to medication adherence, MAP resources, medication adherence, and Type II diabetes. The exclusion criteria were articles not written in English, more than six years, Type I diabetes, or involved children. Databases reviewed were PubMed, Google Scholar, CINAHL, Cochrane Library, EBSCOhost, and Grand Canyon University online library. The review revealed over 632,000 plus results; however, the primary investigator selected 30 articles for this chapter for this project.
One of the most problematic issues associated with home care for diabetes patients is adherence to medications. According to Bonney (2016), patients take their medication as prescribed only 50% of the time. Furthermore, patients are often reluctant to share medication compliance details, thereby resulting in health-related complications. This project hopes to enhance medication adherence, at the project site, which offers home-based care to diabetes patients. This project will also analyze the role of educating patients on medication adherence in improving their medication adherence.
Chapter 2 reintroduces the project’s subject matter, background, theoretical framework, and change model. Other segments include a review of literature on previous and current empirical research related to medication adherence in Type II diabetic home health patients. The chapter’s themes are related to patient-related factors (non-pharmacological and pharmacological lifestyle changes, patient beliefs). Socio-economic factors (medication costs, health literacy, lack of social support), health system factors (trust in the healthcare provider, complicated medication regimen), and interventions (patient education, motivational interviewing, and MAP resources).
Type II diabetes mellitus is at an epidemic proportion globally (Centers for Diseases and Prevention Control, 2020). The incidence of the disease will continue to rise from 382 million individuals to 417 million by 2035 (Polonsky & Henry, 2016; Rana et al., 2019). Healthcare experts are becoming increasingly concerned because of the costs, morbidity, and mortality rates linked with the disease (Polonsky & Henry, 2016). One of the elements contributing to the problem is poor medication adherence (Rana et al., 2019). This is particularly true in-home health Type II diabetic patients. Medication adherence in adults with chronic conditions is roughly between 30% to 50% (Kini & Ho, 2018; Neiman et al., 2017). Furthermore, the healthcare system associated with medication nonadherence is costing the U.S. healthcare system $100 billion to $317 billion annually (Rana et al., 2019).
As adults in this country age, many are afflicted with chronic diseases such as diabetes (Type II). It is one of the main reasons for admission to home health agencies (Sertbas et al., 2020; Wong et al., 2020). Home health agencies have been in existence for over 30 years (Choi et al., 2019). These organizations will continue to grow and impact medical advances and technology (Wong et al., 2020). Hence, there is a need for healthcare providers to become familiar with strategies and barriers linked with medication adherence for this population. Many home health patients have difficulty adhering to their medication regimens. They often express difficulty adhering to the regimens, which reinforces the critical role of home healthcare providers (Wong et al., 2020). This is partly due to them not having knowledge and education related to the disease and proper self-management (Wong et al., 2020).
Theoretical Foundations
Orem’s self-care deficit theory was selected to guide this quality improvement project. The theory was chosen because of its expectations that an individual must be self-reliant and responsible for their care (Orem, 1985). Dorothea Orem’s theory states self-care is an activity that a person engages in to maintain, restore, or enhance their health (Orem, 1985). The theory further states that nurses should not consider patients as inactive or sheer recipients of healthcare; instead, they should be considered reliable, responsible individuals who can make informed decisions and be active in their health care (Orem, 1985).
This theory describes nursing as an action between two or more individuals (RenpenningcN et al., 2003). Furthermore, it assumes that a successful patient with self-care understands it is a primary element in health prevention and illness (RenpenningcN et al., 2003). The theory fits the project because the healthcare providers are in supportive educational roles, which assists the patient when they are ready to learn or cannot complete a task without guidance (Orem, 1985). Also, the theory relates to healthcare providers assisting patients in their self-care and management to improve their function at a home level (RenpenningcN et al., 2003). The theory has been used in multiple studies regarding patients with chronic diseases (Borji et al., 2017; Afrasiabifar et al., 2016; Khademian et al., 2020).
The change model that will be used is the Diffusion of Innovation Model developed by Rogers (2003). There are five stages:
- Knowledge or awareness- the individual is exposed to the change and lacks information.
- Persuasion or interest-the individual becomes interested in the new idea and seeks more information.
- Decision or evaluation- the individual mentally applies the idea to their present and future situation, hence deciding whether to try it.
- Implementation or trial-the individual uses the idea fully.
- Confirmation or adoption- the individual continues to use the idea in their everyday life and health practices.
Utilizing these methods will help the project advance by helping the healthcare providers to implement a standardized method in evaluating the patient’s medication-taking behaviors.
Review of the Literature
Diabetes is prevalent in the United States and globally (Rana et al., 2019). Medication adherence remains a challenge for Type II diabetic home health patients, which can impact their quality of life. Medication adherence among this population deserves a higher level of attention from healthcare providers. Healthcare professionals who understand medication adherence related to patient-related, socioeconomic, condition-related, health system factors, and interventions.
Medication adherence is a major healthcare challenge that impacts a patient’s quality of life. Researchers are constantly exploring ways to minimize medication non-adherence and continue to develop evidence-based strategies to improve medication adherence among patients. Medication non-adherence is a critical issue that deserves a higher level of attention. Understanding medication adherence-related barriers, addressing those barriers, and inspiring patients to change their actions/beliefs is an important step in improving health among patients.
At the selected project site, healthcare workers, who work directly with diabetic patients, believe it is critical to ensure medication adherence. Patients present with unique health-related challenges, thereby reinforcing the importance of minimizing health-related threats. Lacking medication adherence can mean the difference between life and death (Rathish et al., 2019). Adherence to antiretroviral therapy is considered a predictor of effective clinical outcomes among diabetic patients, which is one of the reasons why medication adherence is essential.
Patient-related Factors
The World Health Organization (2017) stated patient related factors encompass an individual’s resources, knowledge levels, belief system, perspectives, and expectations. These factors can vary dependent on the non-pharmacologic and pharmacologic lifestyle changes that the person maintains (Nduaguba et al., 2017). Type II diabetes management involves not just medication adherence but observance to monitoring diet and exercise, follow-up, and self-care (Nduaguba et al., 2017).
Medication adherence.
Medication adherence is a term that refers to one taking medication as prescribed by their healthcare practitioner (Ahmed et al., 2018). Healthcare providers must ensure that the prescriptions provided to patients are suitable to the individual’s conditions.
While medication adherence is important, there is a plethora of literature available that expresses the prevalence of medication non-adherence among patients. Various factors continue to impact medication adherence, which includes, but are not limited to, fear, costs, misunderstanding, too many medications, lack of symptoms, mistrust, worry, and depression (American Medical Association [AMA], 2020). To prevent medication non-adherence, providers can seek to understand the needs of patients and provide them with resources that can aid in overcoming non-adherence.
Ahmed et al. (2018) emphasized that the quality of healthcare can be influenced by the body’s ability to respond to the treatment. A study conducted by Rana et al. (2019) was related to exploring medication adherence to prescribed treatments as a crucial factor for hospitalized Type II diabetic patients in a Bangladesh hospital. The quantitative, descriptive cross-sectional study involved 112 Type II diabetic patients recruited from medical and endocrinology wards. Much of the sample size age was 57.46, 60.7% were male and married. The patient’s medication adherence was measured using the 7-item MCQ scale modified by Ahmad et al. (2013). Data were analyzed using SPSS-21. Descriptive statistics were used to measure the participants’ demographics. An independent sample t-test and one-way ANOVA with post hoc comparisons were used to evaluate the relationships between the variables (p =.05).
The results from the Rana et al. (2019) study showed 72.3% of the participants forgot to take their medications, 96.4% chose not to take the medication or miss a dose when feeling better. Most of the patients, 81.3%, did not take their medications with them when traveling. The mean scores of the MCQ were 26.46 (SD =1.58). The study’s results concluded that the level of medication adherence among Type II diabetic patients was suboptimal (Rana et al., 2019). The authors recommended that more attention needed to be given to varied age groups related to medication adherence.
Lee et al. (2017) conducted a quantitative study to determine the medication adherence among Type II diabetic patients in an Asian community. This cross-sectional study involved 382 Asian participants from a primary outpatient care clinic in Singapore. The patient’s medication adherence was measured using a five-item Medication adherence report scale (MARS-5). A low medication adherence score was <25. The sample size was predominately female, with a mean age of 62 years. Using univariate analysis, the results showed 57% of the participants had a low medication adherence score, which was attributed to them being married or widowed, taking fewer than four medications daily, and poor glucose control. The study concluded that younger patients were susceptible to low medication adherence scores (Lee et al., 2017).
Both studies involved participants of Oriental descent and had an adequate sample size. Although the studies were conducted in different settings (primary care and hospital), the results demonstrated a need for healthcare providers to focus on different age groups and their reasons for not adhering to their medication regimen. The studies were cross-sectional, which indicated the authors were unable to evaluate the participant’s habits and trends. This could have changed if they could assist the patients with barriers they faced during the studies.
To handle the issue of medication adherence among the diabetic patients who have had an issue with adherence to medication needs to come up with a variety of strategies that have been attained from scholarly reviews as well as journals for purposes of well researched data on the concept. Appropriate types of medications are usually considered to be the identified cornerstone regarding the prevention as well as disease treatment yet according to numerous research carried out, there is solely about half of the individual patients who adhere to the instructions of their prescribed medication (Bosworth, 2015). This usually causes a common as well as costly public health-associated challenge especially for the healthcare system in the US.
Since the aspect and issue of inappropriate as well as inefficient medication adherence are considered to be a complex change with a variety of contributing causes, there is no universal solution (Rodriguez-Saldana, 2019). The following theme breaks down into three subcategories that form the basis of the sub-themes associated with this theme. The sub-themes are used to offer a comprehensive analysis of all the vital types of interventions that are effective in enhancing medication adherence among diabetic patients but are also considered to be potentially scalable, that is they are easy to implement in any given scenario and population (Bosworth, 2015). Key traits that make these interventions effective are discussed throughout the DPI. The information offered under each sub-theme is vital to explain, as it can result in enhanced medication adherence through the implementation of documented and cost-effective solutions.
Non-pharmacological indicators.
There are many medications used for the effective management of diabetes (Raveendran et al., 2018). Effective non-pharmacological therapy should be explored with all Type II diabetics. The measures could include nutrition and exercise. Nutrition interventions are critical in a person with diabetes maintaining an optimal glucose level (80-120mg). The dietary pattern that must be encouraged is consuming fruits, vegetables, low-fat dairy foods, whole grains, and minimal red meat (Asif, 2014).
Pharmacological factors.
Type II diabetic patients typically take multiple medications for their condition and other comorbidities (Kirkman et al., 2015). Following one’s medication regimen and treatment improves patient outcomes, reduces healthcare costs, hospitalizations, and mortality (Kirkman et al., 2015). A retrospective study conducted by Kirkman et al. (2015) determined patient, medication, and prescriber factors that influenced diabetic patients and medication adherence. A sample size of 200,000 participants (from 50 states, including the Virgin Islands) was extracted from a pharmacy database (Medco Health Solutions). The participants’ eligibility was based on the medication, benefits, and prescription history. Each patient was followed for one year from the medication date to post-implementation of the study.
Medication adherence was described as a medication possession ratio > 0.8 (Kirkman et al., 2015). Logistic regression analyses were conducted to evaluate factors independently linked with adherence. The results demonstrated that 69% of the participants were adherent. Other findings illuminated that adherence was associated with one’s age (older), male, higher education and income, and the use of the mail order versus retail pharmacies. Individuals with a new diagnosis of diabetes were less likely to be compliant with their medication regimen.
The authors concluded that demographic, clinical, and system-level factors influenced the participants’ medication adherence regimen (Kirkman et al., 2015). The authors emphasized that younger individuals, newly diagnosed and had minimal medications to take, were at a higher risk for non-adherence. Individuals who used mail-order pharmacies resulted in higher medication adherence due to lower out-of-pocket costs (Kirkman et al., 2015).
Patient’s belief system.
One’s culture influences a patient’s beliefs regarding medications, which ultimately affects their medication adherence (Lemay et al., 2018). This remains a challenge for healthcare providers in helping patients to understand the significance of medication adherence (Shahin et al., 2019). A study conducted by Shanin et al. (2019) used a systematic review to determine the importance of an individual’s cultural belief influenced medication adherence. A total of 2,646 articles were selected from various databases such as PubMed, CINAHL, EMBASE, and PsychINFO. Twenty-five of them met the inclusion criteria. The studies focus on diabetes or hypertension.
The study results from Shanin et al. (2019) revealed personal and cultural factors linked with medication adherence. Ten articles (40%) demonstrated an individual’s perception of the illness, five (20%) were affiliated with health literacy, four (16%) cultural beliefs, three (12%) self-efficacy, and five (20%) knowledge illness (Shanin et al., 2019). Shanin et al. (2019) study concluded that one’s cultural influences affect their perception of the importance of medication adherence. Healthcare providers must understand their patients’ pre-existing perspectives of diabetes before offering new information. This is an opportunity for healthcare professionals and patients to have a dialogue to diffuse misconceptions related to the patient’s perceptions. The authors suggested that future research should identify the religious beliefs associated with disease knowledge and medication adherence.
Strengthening the Relationships with Patients
Patients usually consider their healthcare providers (HCPs) as the most dependable source of data regarding their health condition and treatment. Patients are highly likely to effectively follow the treatment plan when they are involved in having a good relationship with their HCP due to the confidence and trust that has been built over time. Relationship building in healthcare is a vital aspect in the day to day lives of healthcare practitioners due to the nature of their job, which necessitates that they maintain long-term relationships with their patients for enhanced medication and treatment outcomes (Heston, 2018).
Trust is critical to developing, specifically since patients can experience improve health-related outcomes when they value relationships with their HCPs. Patients who have trust in their HCP often believe that their provider has a high level of competence and truly cares about their health-related outcomes (Heston, 2018). Mistrust develops when the patients attain unrealistic, inconsiderate, or insensitive advice from their HCPs, as well as feel emotional distance from them.
Socioeconomic Factors
Socioeconomic-related factors that affect medication adherence include one’s location of residence, medical costs of treatment, and finances (Yeam et al., 2018). Other factors that could influence medication adherence are low health literacy, education level, lack of social support, living conditions, and medication costs (Hennessey & Peters, 2019). Health care providers must conduct a thorough assessment before providing a patient the prescription and consider any of the factors as mentioned above.
Medication costs.
Kang et al. (2018) conducted a quantitative, longitudinal study to examine factors that affected cost-related medication nonadherence. Cost-related medication nonadherence (CRMN) is defined as taking medication then indicated or prescribed due to costs (Kang et al., 2018). Unknown sample size noted, but the Behavioral Risk Factor Surveillance System data for 2013–2014 was used to identify individuals with diabetes and their CRMN. Weighted multivariable logistic regressions were used, and analyses were conducted using the Survey suite of programs in Stata SE version 14. The survey weights were used to obtain population-level estimates and subpopulation methods to estimate standard errors for the subgroup’s analyses (Kang et al., 2018).
The results demonstrated that CRMN among American adults was 16.5% (Kang et al., 2018). Individuals with an annual income of < $50k and without health insurance had the highest rates of CRMN. Insulin users had a 1.24 times higher risk of CRN than those not using insulin. Factors influencing CRMN were diabetes care and lifestyle factors, depression, arthritis, and asthma (Kang et al., 2018). Health insurance was the most significant factor for the participants < 65 years of age and depression for respondents > 65 years (Kang et al., 2018).
The authors (Kang et al., 2018) concluded that one’s annual income and health insurance status were the most significant factors for younger adults, while depression was for older adults > 65 years. When the younger and older groups were combined, it showed the largest impact of CRMN affecting individuals < 55years of age and having higher rates of non-medication adherence (Kang et al., 2018). Recommendations were for healthcare organizations to develop policies, resources, and support systems that address the factors to help improve CRMN.
Health literacy.
Health literacy is described as one’s ability to obtain, communicate, process, and comprehend basic health information and navigate health services to make an informed decision (Sawkin et al., 2015). Medication adherence is broadly identified as a patient’s ability to follow a prescribed medical treatment (Sawkin et al., 2015). Researchers Glanz et al. (2015) have explored the impact of low health literacy rates on patient compliance with medications and health-related advice. The authors stated that approximately 35% of American adults possess basic or below basic health literacy levels (Glanz et al., 2015). Chima et al. (2020) conducted a systematic review to evaluate the impact of health literacy and medication adherence. Literature searches were performed using Ovid Medline, CINAHL, EMBASE, Scopus, and PsycInfo. The inclusion criteria for the articles were conducted in the United States, 18 years or older with a diagnosis of Type I or II diabetes, medication adherence was an outcome variable, quantifiable measure reported, and was a full text journal article. Articles were graded using Joanna Briggs Institute Critical Appraisal Checklists, which is appropriate for the respective study designs identified. Thirteen articles were retained in the review, most of which used a cross-sectional design.
The results demonstrated four of the 11 studies found a positive association between health literacy and medication adherence (Chima et al., 2020). Two of the four studies had methodological shortcomings. The authors concluded there was some evidence that health literacy is linked with medication adherence among diabetic adults in the United States. Recommendation for future research to design and execute longitudinal studies to determine a deeper relationship between the variables (health literacy and medication adherence (Chima et al., 2020).
Given inadequate literacy rates, among members of the general population, world practitioners continue to create unique strategies that can be used to reduce lacking health adherence among patients with diabetes. Improved literacy is a theme that should be of the utmost priority, specifically since it creates the foundation for long-term sustained profitability. Furthermore, as patients can understand the importance of medication compliance, adherence to medication regimens improves (Glanz et al., 2015).
Using universally implemented and published resources that can improve medication adherence is important. Tools and resources can be utilized by HCPs to identify patients who are not taking their prescribed medications. Prescriptions need to be taken seriously for exceptional results and for the continued well-being of patients who have critical illnesses like diabetes.
The use of simple language by HCPs, as well as by medication manufacturers, can encourage providers to meet patients where they are and utilize teach-back techniques to ensure a patient’s understanding of his/her prescribed medication regimen. Teach-back methods have been utilized to enhance medication adherence among many types of non-adhering patients. Most of the time people opt to not take their medication as they cannot read all the instructions written on the medicine and are afraid that they will die, especially in the cases that they mistake those drugs for poison or some drug that may look like a famous poison causing death. This is a key issue that has left most of the people victims of non-adherence (National Academies of Sciences, Engineering, and Medicine, 2018).
Huang et al. (2020) conducted a cross-sectional study aimed to identify patient factors linked with diabetes medication adherence and health literacy levels. One hundred and seventy-five participants were involved in the study and recruited from two family medical clinics. All the participants were over the age of 20, diagnosed with Type II diabetes, taken one oral diabetic medication, and understood English. The authors evaluated the participants’ health literacy levels using the Newest Vital Sign, a six-item questionnaire, and an eight-item Morisky Medication Adherence Scale.
The results showed a self-reported status of (β = 0.17, p = 0.015) and medication self-efficacy (β = 0.53, p, 0.001), which were positively associated with diabetes and medication adherence (Huang et al., 2020). Health literacy was neither associated with diabetes medication adherence (β = −0.04, p = 0.586). The authors concluded that health literacy measured using the Newest Vital Sign did not correlate with medication adherence or glucose control among Type II diabetics. They recommended that healthcare clinics develop interventions to improve their patients’ self-efficacy of medication to improve the medication adherence rates (Huang et al., 2020).
Reading instructions and making a patient understand what is written on a medicine bottle or package should never be taken for granted as it is key for determining how patients will effectively or ineffectively adhere to the given drugs for treatment and disease control purposes. For the medical practitioner to be aware and sure that what they have explained to the patients has been delivered safely and appropriately, there is the need for a verification test. The patients as well as their identified support individuals need to be asked to explain in their own words stating what they have understood from everything the practitioner has told them regarding their health, along with drug management and intake. This teaching back method is vital in offering additional data on the key topic of interest; thus, it should be used often.
Concerns associated with the issues of side effects can be challenges to medication regimen adherence, especially when the given advantages associated with taking the medication are not properly comprehended. To minimize the potential concerns that are associated with the side effects of drugs, since this can be identified as one of the reasons why patients may opt to not adhere to medications in fear that they will experience the side effects and be greatly inconvenienced, there is the need for HCPs to offer the relevant data regarding the common types of side effects when they are in the prescription process.
There have been issues of people and patients dying or experiencing very negative and disturbing side effects when it comes to them taking the medication prescribed by their doctors. These cases have always been used as examples to explain the reason why people have been reluctant to take medications for prolonged periods. When an individual has a critical illness, it is not uncommon that he/she needs to take the prescribed medication for a long period, as this can result in improved medication efficiency. Lacking understanding of medication-related details has caused patients to withdraw from their prescribed medication regimen, which is due to lacking knowledge and prolonged side effect issues that are associated with their medication (Institute of Medicine [IOM], 2016). For example, when offering metformin, to enable adherence to the drug there is a need to inform patients that are suffering from diarrhea during their time of prescription to anticipate that the loose bowel issues will be over in about a week if the drug is continued. It is also vital to offer brief explanations about medication side effects and benefits due to time limitations. If a patient cannot have additional time with his/her provider, then other members of the health care team should aid in answering their questions and provide additional education. Education can be in the form of printed handouts, websites, or a teaching module that should be readily available for use with the identified patient.
Tools/Support Strategies for Improving Self-Efficacy and Medication Adherence
Using tools and instruments that are considered effective and appropriate is vital in supporting adherence in different ways and in achieving self-efficacy among the various patients. Positive family and social support are considered to be vital aspects associated with adherence to the issue of diabetes management (Rodríguez-Saldana, 2019). The engagement of family members can enhance self-care activities for patients suffering from diabetes, including eating effective and healthy foods, keeping fit, monitoring blood glucose, and adhering to medication.
A web-based portal is an innovative resource that can be used to assist patients. This web-based portal can improve medication reconciliation processes among patients and providers. The web-based portal can help patients with various regimens navigate challenges. Furthermore, this medication information, available through the portal can help individuals understand medication requirements, as the portal often helps to clarify and verify inaccuracies. The web portal aims to enhance medication adherence and prevent the improved use of the medication (Forman & Shahidullah, 2018).
When patients can verify information in their electronic medical records to ensure proper medication adherence, this can enhance patient well-being. The EMR provides an accurate list of a patient’s medications and provides detailed medication information (e.g., type of drug, what the drug is used to treat, frequency of drug use, etc.). Also, the use of screening tests is vital in understanding how well patients are taking their drugs. If there is no consistency in medication-taking then motivation aspects should be utilized to enhance adherence (Eskola, Waisanen, Viik, & Hyttinen, 2018).
When dealing with patients who are reluctant to take their medications, various care concepts must be understood. Through improving one’s literacy, knowledge about the medication, and offering patient-specific details, enhanced outcomes can occur. Improved medication adherence can result in enhanced patient outcomes, thereby reinforcing positive long-term health-related outcomes. The following themes noted below, provided comprehensive knowledge, as well as in-depth illustrations, about the distinct components associated with clinical control for patients who have been diagnosed with diabetes. The review offers effective clinical practice guidelines, which must be considered, to enhance population health. It is important to note that to ensure identified optimal outcomes (discussed below), individualized patient care is critical.
Patient-Centeredness. Patient-centeredness entails ensuring that all the identified interventions described in the first theme are focused on the individual patient who is being helped to effectively adhere to the given medication during home care settings. Patients who have been diagnosed with various critical illnesses and have been asked to go home for home-based care have been associated with poor adherence to the medications they are given when they are discharged from the hospital (Steinberg & Miller, 2015).
Practice recommendations, whether they are focused on evidence or expert opinion, are intended to offer the desired guidance on an overall approach to care (da Costa, van Mil, & Alvarez-Risco, 2018). The science, as well as the art associated with medicine, usually come together when the identified clinician is experiencing or has experienced some sort of situation whereby, they have to make treatment recommendations for any patient who would be considered to not have effectively met the eligibility criteria for the studies on which the given guidelines were based.
Diabetes Across the Life Span. An increment in the identified proportion associated with patients that suffer from diabetes is usually considered to be mostly adults (Balogh, Miller, & Ball, 2015). For the less salutary reasons, the identified incidences associated with type II diabetes are considered to be highly increasing in the creating in the children as well as the young adults. Patients that possess type II diabetes as well as those that have type I diabetes are considered to have good lives even in their older age, which is regarded as a stage of life whereby there is minimal evidence from the identified clinical traits to be used in the guidance of therapy (Bonney, 2016). All these toes of demographic alterations are usually involved in highlighting another key challenge to high-quality diabetic patient care. In this case, the identified need is usually considered to be the enhancement of the coordination between clinical teams as well as patients in the effective transitioning via the dysfunction phases enticed in life span (Corcora & Roberts, 2015).
Advocacy for Individuals with Diabetes. Advocacy is a vital aspect in healthcare since it addresses the needs of the patient who need the utmost help and care, thereby allowing them to go back to their previous health state (D’Onofrio, Sancarlo, & Greco, 2018). Advocacy is an aspect that can be referred to as active support, as well as engagement, that aims to effectively develop a cause as well as a policy (Mollaoglu, 2018). Furthermore, advocacy is usually needed to enhance the lives of individuals suffering from diabetes. The various issues that diabetic patients experience, such as obesity, physical inactivity, and societal challenges reinforce the need for advocacy (Firstenberg & Stanislaw, 2017).
In summary, health literacy was chosen because the level of health literacy is high among Americans. This contributes significantly to the challenges healthcare providers face in caring for Type II diabetic patients. The subject emphasizes the need for healthcare professionals to assess their patient’s health literacy abilities and educate them according to their level. An educated patient will better understand what actions to take and improve their quality of life.
Summary
The prevalence of Type II diabetes is affecting one in ten Americans (Ahmed et al., 2018). The disease is expected to continue rising higher by 2030 (Lin et al., 2018). Medication adherence for Type II diabetic home health patients is critical in decreasing the poor patient outcomes associated with the disease. Medication adherence with Type II diabetic patients remains a challenge for many healthcare professionals. Education for the healthcare providers and the patients can make a difference in this population’s lives.
Chapter 2 discussed reintroduced the topic and presented the theoretical framework and change model to guide the project. Other sections include the literature review related to patient-related, socio-economic, and health system factors.
A summary of the chapter was provided with an introductory sentence that previews Chapter 3.
Chapter 3 will reinstate the select topic. Other segments will present project methodology, design, population, and sample selection. A discussion of the MAP resource and the electronic medical record. The validity and reliability of the instrument was demonstrated, data collection and data analysis procedures, potential bias. The last few sections discuss the ethical considerations, limitations, and a summary that leads into Chapter 4.
Chapter 3: Methodology
Medication adherence is a critical component in minimizing adverse patient-related outcomes among individuals with chronic illnesses (Type II diabetic patients). Ahmed et al. (2018) stated medication adherence for this quality improvement project refers to the extent to which a home healthcare patient can correctly take their medications in the absence of their health care providers. Medication adherence requires an individual to adhere and comply with all the medical instructions provided (Bellou et al., 2018).
Type II diabetes affects one in ten Americans (Ahmed et al., 2018). Furthermore, due to the increase in older-aged adults and the rising prevalence of the disease, it is expected to elevate higher by 2030 (Lin et al., 2018). The home health services continue to grow, hence illuminating the need for education regarding medication adherence. Roughly 45% of the patients cannot maintain their glucose levels (Polonsky & Henry, 2016). Poor medication adherence is associated with higher financial obligations for the patient, hospital, and insurance companies. Polonsky and Henry (2016) emphasized the adverse outcomes cause frequent hospitalizations and lower quality of life for patients and their families.
Chapter 3 will reinstate the selected topic. Other sectors include the statement of the problem, clinical question, project methodology (quantitative), and project design (quasi-experimental). The chapter describes the population and sample selection, the instrumentation (MAP resources), validity, reliability, and data collection procedures. The last few segments include the data analysis procedures, potential bias, ethical considerations, limitations, and a summary.
Statement of the Problem
It is not known if or to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The targeted population is Type II diabetic patients in an urban healthcare facility in urban Texas. In collaboration with the stakeholders, it was noted that medication adherence among the patients was lacking. The information will be obtained from the electronic medical records (Cradle Solutions), which showed that ten percent of the diabetic patients were not adhering to their medication regimen.
Factors that influence poor medication adherence are numerous and include poor knowledge or awareness of the disease, medication costs, and lack of understanding of the medication treatment, which reinforced the project’s purpose (Heath, 2019; Sharma et al., 2020). Healthcare providers play an essential role in assisting patients with medication adherence. The primary investigator will introduce a standardized strategy for the facility’s healthcare providers to assess the patients’ medication adherence using MAP resources (Starr & Sacks, 2010).
Using a standardized method will help to solve the facility’s problem with medication adherence rates. It will also help improve the healthcare providers’ knowledge levels and awareness regarding the barriers associated with medication adherence. Complying with the new guidelines developed by the Centers for Disease Control and Prevention (2020) could help patients control their glucose levels, minimize healthcare costs, hospitalizations, and potential infections.
Clinical Question
The clinical question that will direct the primary investigator’s answer is: To what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and educational intervention. The dependent variable is the medication adherence rates.
The data collection process will not begin before approval is received by Grand Canyon University IRB. The primary investigator will develop informational flyers for the nurses to give their patients during their home health visits. The staff will answer any questions related to the project regarding risks, benefits, and purpose while instructing that participation is voluntary. A convenience sample will be used because of the easy access to the participants for the primary investigator.
The primary investigator will collect data retrospectively (four weeks) prior to implementation of the project. The data will be collected from the electronic medical records using Cradle Solutions for the impact of the MAP resources and medication adherence rates. In the first week, the primary investigator will educate the staff to use the MAP resources. Once the staff begins to implement the tool, post-medication rates will be assessed post-four weeks. The data will be inserted into a Microsoft Excel 2016 codebook developed by the primary investigator. It will then be exported into SPSS-27 and analyzed by using an independent t-test. The five-item demographic survey will collect the descriptive statistics of the home healthcare patients. The questionnaire comprises (age, gender, years with Type II diabetes, oral or insulin, and education).
Project Methodology
A quantitative methodology will be used for this quality improvement project. According to Creswell and Creswell (2017), a quantitative methodology is appropriate for projects that use data in its numerical form. For this project, the data will be presented using figures, graphs, charts, and tables. This will allow the readers to compare the medication adherence rates pre-implementation and post-implementation of the project.
A qualitative methodology was considered but not used, although they are beneficial. It explores the patient’s experiences, perspectives, and lived experiences regarding a phenomenon (Creswell & Creswell, 2017). Data collected using this methodology is semi-structured interviews, one-on-one interviews, and focus groups (Creswell & Creswell, 2017). The primary investigator aims not to understand the home health participants’ emotions, behaviors, or experiences related to medication adherence.
A quantitative methodology supports the project because it will permit the primary investigator to remain objective in providing the project’s findings (Leedy & Ormord, 2014). Furthermore, the methodology allows the primary investigator to summarize the data that could support generalizations for a larger or similar population. The methodology is less costly with easy replication for future quality improvement projects to obtain the same results.
Project Design
Quasi-experimental designs are utilized to compare data before and post-implementation of an intervention (Price et al., 2017). The design is frequently used in a controlled environment. For this project, the design was chosen because it is cost-effective versus an experimental project design (Schweizer et al., 2016). A quasi-experimental design allows the primary investigator to analyze the impact of MAP resources on medication adherence rates.
An experimental design was not considered because the primary investigator is not seeking to conduct the project under a controlled environment (Leedy & Ormrod, 2014). This design observes the independent variable (MAP resources) and the dependent variable (medication nonadherence rates). It is a simple test that is performed in various physical and natural settings (Leedy & Ormrod, 2014).
A correlational design was considered but not appropriate for the project because the primary investigator is not seeking to understand the relationships occurring among the variables (Creswell & Creswell, 2017). This design is typically descriptive relying on a hypothesis (Leedy & Ormord, 2014). The primary investigator will not seek the relationships between the independent variable (MAP resources and education intervention) and the dependent variable (medication adherence rates).
The targeted population are home health patients ages 35 to 64 years old. The selected site serves approximately 100 patients annually, and 30 patients are diagnosed with Type II diabetes. The inclusion criteria are males and females diagnosed with Type II diabetes, oral medication or insulin, and home health patients. The exclusion criteria are individuals with language or cognitive deficits and diagnosed with Type I diabetes. Five registered nurses will help to implement the project. They are individuals who work full-time and have been employed over a year.
The data collection process will begin once approved by Grand Canyon University IRB. Recruitment will occur from informational flyers given to the patients during their home health visits with the providers. The nurses will answer any questions regarding the project’s risks, benefits, and purpose and be instructed that the participation is voluntary. The primary investigator will use a convenience sample because of the access to the participants.
Data will be collected retrospectively four weeks prior to project implementation from the electronic medical records (Cradle Solutions) (medication adherence rates). In the last portion of the first week, the primary investigator will educate the healthcare providers regarding using the MAP resources. The staff will begin implementing the tool, and the post medication adherence rates will be assessed four weeks post-implementation. The primary investigator will document the data in a Microsoft Excel 2016 codebook developed by the primary investigator. Once completed, it will be exported into the SPSS-27 and analyzed using an independent t-test. A five-item demographic questionnaire will be used for descriptive statistics of the population. The survey will include (age, gender, years with Type II diabetes, oral or insulin, and education).
Pre-intervention and post-intervention data will be obtained using the MAP resources. The questions that will be analyzed are: (1) “Have you experienced any increase in thirst?” (2) “How often do you urinate?” (3) “Do you often feel fatigued even when doing little tasks?” and (4) “Do you experience blurred vision?” In addition to the questions, home healthcare providers will ask the patient “Are you taking your medications?” Any information attained from the question and due to probing, observation of patient’s medications, and patient-related medication adherence will be documented in the project site’s EHR. The data will be analyzed using an independent t-test to determine the statistical significance.
The electronic medical record that will be used to collect data is Cradle Solutions a software for home health companies. It serves the specialized needs of home health care providers that give a web-based point-of-contact information entry and management (Cradle Solution, 2021). It is compliant with HIPPA security features for billing, reporting, administrating, and managing patient information (Cradle Solution, 2021). Liss et al. (2020) emphasized that electronic health records can be used for quality measures as a snapshot or calendar year. The primary investigator will obtain the measurement of the medication adherence rates and align it with new protocols and guidelines developed by the facility.
Population and Sample Selection
The specific population that will be addressed are home health patients ages 35 to 64 years old. The selected site serves approximately 100 patients annually, and 30 patients are diagnosed with Type II diabetes. A G* power analysis was conducted using version 3.1.9.2, the alpha measure of 0.05, effect size of 0.5, power of 80% to calculate the lowest sample size needed, which was (n=34). The inclusion criteria are males and females diagnosed with Type II diabetes, oral medication or insulin, and home health patients. The exclusion criteria are individuals with language or cognitive deficits and diagnosed with Type I diabetes. Five staff nurses will help to implement the quality improvement project. They are individuals who are registered nurses, work full-time, and have been employed with the facility over one year, and have access to Cradle Solution EHR system.
The geographical location of the project is in a metropolitan area of Houston, Texas. The County statistics show that approximately 17.6% of the population have Type II diabetes (Houston, 2021). During 2016-2018, 20.2% of the population was hospitalized due to diabetic complications (Houston, 2021). There are over 700 000 Medicare participants in a three-county radius, which is higher than the national average (Understanding Houston, 2021). Data further showed that preventable hospital stays occur in older adults 65 and above (Understanding Houston, 2021). This suggested a trend to overuse the hospitals as a primary source of care (Understanding Houston, 2021).
The informed consent process will consist of the nurses explaining the project’s purpose, risks, and benefits. The participants will be informed that participation is voluntary and can withdraw without repercussions to their professional or personal lives. No compensation will be provided to the participants in the project. The participants’ identities and privacy will be protected throughout the project by the primary investigator not using their names or other identifiable information. The participants will be assigned a random number for security purposes. The primary investigator will abide by the University’s IRB guidelines and the Belmont Report (justice, respect for persons, and beneficence) (U.S. Department of Health & Human Services, 2018).
Hard copies of the data will be stored on a flash drive and kept in the primary investigator’s home office (in a locked file cabinet). The data files will be kept on the primary investigator’s laptop, which is digitally protected. The data will be stored for three years according to Grand Canyon University procedures (June 2023). Once the project is completed and the requirements met, the primary investigator will destroy the information using Iron Mountain shredding services and software ERASER on the laptop.
Instrumentation or Sources of Data
The instruments to be used in the project are the MAP Toolkit and Training Guide resources, which includes (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list. The questions to ask poster encourages patients to ask the provider about their medication. For this project, the nurses will review the medications with the Type II diabetic patients. Six questions will be asked (1) Why do I need to take this medicine, (2) Is there a less expensive medicine that would work as well, (3) What are the side-effects and how can I deal with them, (4) Can I stop taking any of my medicines, (5) Is it okay to take my medicine with over the counter drugs, herbs, or vitamins, and (6) How can I remember to take my medicine?
The second section, the Adherence assessment pad, explores answers the barriers to the patient’s maintaining medication adherence. The questions include (1) makes me feel sick, (2) I cannot remember, (3) too many pills, (4) costs, (5) nothing, and (6) other.
The third component is my medication list. It provides detailed information in chart form, which is discussed between the patient and the healthcare provider. It comprises of (1) name and doses of my medicine, (2) this medication is for my diabetes, (3) when do I take and how much (options include: morning, noon, evening, or bedtime), and (4) I will remember to take my medicine (a blank that will be filled in).
The source of data for this project is the electronic medical record. The facility uses Cradle Solutions, software for home health companies. It serves the specialized needs of home health care providers that give a web-based point-of-contact information entry and management (Cradle Solution, 2021). It is compliant with HIPPA security features for billing, reporting, administrating, and managing patient information (Cradle Solution, 2021). Liss et al. (2020) emphasized that electronic health records can be used for quality measures as a snapshot or calendar year. The primary investigator will measure the medication adherence rates and align them with new protocols and guidelines developed by the facility.
Validity
Validity conveys how accurately a method is measured (Creswell & Creswell, 2018). If the method measures what it should and the findings correspond closely, it is considered valid. There are four types of validity are constructs, content, face, and criterion (Creswell & Creswell, 2018). For this project, construct and face validity is applicable to the instrument. A group of professionals developed the tool, which consisted of physicians, pharmacists, nurses, and medical assistants (Starr & Sacks, 2010). It was based on their years of work experience in their perspective fields. The toolkit’s improvements were adjusted and in alignment with the CDC and other healthcare governing bodies.
Reliability
Reliability refers to the consistency of instrument measuring something (Creswell & Creswell, 2018). If the same results occur regularly by using the same procedures under the same conditions, the measurement is reliable (Creswell & Creswell, 2018). For this project, the MAP toolkit reliability was confirmed by inter-rater reliability (Starr & Sacks, 2010). The observers noted the same results associated with using the instrument, which aligned with the literature findings regarding collecting data for medication adherence rates.
A study conducted by Harrell (2017), occurred over 90 days, where weekly medication adherence rates were assessed. Seventy-eight percent of the patients prior to the study’s implementation did not adhere to their prescribed medication regimen. Post three-months of the project, 56% of the patients improved regarding medication adherence rates. For this project, test-rest reliability will be noted, because the nurses will be using the MAP toolkit over time (two different times) (Creswell & Creswell, 2018).
Data Collection Procedures
The data collection process will begin once approved by Grand Canyon University IRB. Recruitment will occur from informational flyers given to the patients during their home health visits with the providers. The nurses will answer any questions regarding the project’s risks, benefits, and purpose and be instructed that the participation is voluntary. The primary investigator will use a convenience sample because of the access to the participants.
Other recruitment strategies include the primary investigator reaching out to the nurses at the project site to assist in the educational intervention. The training sessions will be offered twice so that the nurses working on the weekends can participate. The primary investigator will offer two 45-minute Zoom training sessions. During these sessions, the primary investigator will provide information regarding using the MAP toolkit and resources. A 10-minute PowerPoint presentation will be included during the 45-minute training session, along with a MAP toolkit binder for each participant.
The primary investigator will work with the information technology department, who will ensure that the three MAP resources are inserted into the Cradle Solution documentation software. During week one, the nurses will provide the patients with informed consent, answer questions related to the project, a five-item demographic survey, and a pre-MAP survey. The second to fourth week, the nurses will examine the patient’s medication list and adherence (ten minutes). Each week the nurses will record the medication adherence information in the patient’s electronic medical record.
Week four, all input by the nursing staff will be completed. If the patient expresses, they have not adhered to the medication regimen; it will be recorded in the system. Post scores will be collected by the primary investigator regarding the medication adherence rates. The results will be entered into the Microsoft Excel 2016 codebook developed by the primary investigator. The data will be exported into SPSS-27 be analyzed using an independent t-test.
Data Analysis Procedures
The primary investigator will collect retrospective data four weeks prior implementation regarding medication adherence rates. Descriptive statistics will use to determine the demographics of the participants, which will be illustrated using graphs, tables, and figures. The pre-and post-intervention scores will be entered into the SPSS-27 for analysis. The data will be evaluated for missing data, which will be assigned -99. Pre- and post-surveys missing data will be discarded from the project.
The clinical question that is guiding the project is:
To what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The independent variable is the MAP resources and education intervention. The dependent variable is the medication adherence rates. The primary investigator will answer the clinical question by evaluating the mean scores of the pre-and-post implementation scores from the MAP resources using an independent t-test (parametric test). This statistical test compares two groups to determine the statistical significance (p <0.5). The Microsoft Excel spreadsheet (2016) and exported into SPSS-27 for the final analysis.
Potential Bias and Mitigation
Bias is described as any tendency that prevents impartial consideration of a clinical question (Pannucci & Wilkins, 2010). It can occur at any stage of the research, study design, data collection or analysis, and publication (Pannucci & Wilkins, 2010). One potential bias is related to the selection process. The primary investigator will avoid bias by selecting individuals and using strict inclusion and exclusion criteria previously developed for the project. The participants will originate from the specified population.
The second bias is related to recall bias, a systematic error that occurs when the participants do not remember prior events or experiences accurately (Creswell & Creswell, 2018). The project could be affected because the participants are self-reporting to the nurses using the MAP resources. To avoid this type of bias, the nurses will be trained to carefully train each participant using the same method, which will prevent influencing their responses (Creswell & Creswell, 2018).
Ethical Considerations
The primary investigator will abide by the University’s IRB and Belmont report guidelines while conducting the project. The three principles to be followed are respect for participants, justice, and beneficence (Belmont, 1979). The primary investigator and the nurses will show the participants respect by listening, validating their feelings, and answering the questions regarding the education or project. The primary investigator will occasionally monitor the nurse’s interaction with the participants throughout the project. The participants will be instructed that there are no repercussions to their personal or professional lives upon withdrawing from the project. Nor do they need to provide details on the reason they withdraw. The primary investigator and the nurses will always protect the participants’ privacy and confidentiality by not discussing the project, the participants, or its findings with anyone not involved in the project or without the participant’s permission.
Beneficence will be shown to the participants by informing the participants that the primary investigator or the nurses will stop the questioning immediately if they feel emotionally harmed. A psychological resource will be provided to participants who feel affected by the questions or project. All participants will be informed of the risks, benefits, and minimal harm that can occur to them, such as loss of data, social or emotional conflict with family and friends, and anxiety or depression.
The Belmont Report (1979) states justice is the “distribution of the burden.” During this project, it is possible that the participants could perceive unwanted stigma from the colleagues, family members, or friends. Each participant will be treated uniformly following their wishes, so it will not affect the project’s findings. There could be a potential conflict of interest with the project since the primary investigator works at the facility. To minimize the conflict, the primary investigator will not interact with the participants.
Limitations
The limitations of the project are self-reporting of medication adherence by the patients. To minimize this limitation, the primary investigator has validated the self-reporting instrument (MAP resources) before utilizing it for data collection (Althubaiti, 2016). Furthermore, the patient’s self-reporting will be compared to their fasting blood glucose levels, medical records, or reports from family and friends (Althubaiti, 2016).
The second limitation is the healthcare organization being impacted by the COVID-19 pandemic. The new COVID-19 guidelines have affected the current healthcare delivery model. The pandemic has caused the primary investigator to redirect resources and halt in-person training sessions for the nurses. The recruitment process has been limited to Zoom meetings and telephone calls. The third limitation is the location of the project and its setting. The project findings cannot be generalized to other home healthcare agencies of similar populations. The fourth limitation is the time to conduct the project (four weeks). A longer timeframe would help the primary investigator analyze the site’s challenges, trends, and sustainability.
Summary
Medication adherence among Type II diabetic home health patients remains a critical factor in their quality of life. The purpose of this quantitative quasi-experimental project is to determine to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the questions to ask poster, (2) adherence assessment pad, and (3) my medications list, impact patient medication adherence rates when compared to current practice among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. A quasi-experimental design allowed the primary investigator to evaluate the impact of the MAP resources and educational intervention on the dependent variable (medication adherence rates). The medication adherence rates will be collected before and after project implementation (four weeks). Data will be collected by the primary investigator and stored on the digitally protected laptop and hard copies will be locked in a secured file cabinet at the residence. Chapter 4 will reinstate the topic, along with descriptive data of the participants. Other sections will consist of the data analysis procedure, project findings, and summary.
Chapter 4: Data Analysis and Results
The purpose of this chapter is to summarize the collected data, how it was analyzed and then to present the results. This section of Chapter 4 briefly restates the problem statement, the methodology, the clinical question(s) or phenomena, and then offers a statement about what will be covered in this chapter. Chapter 4 should present the results of the project as clearly as possible, leaving the interpretation of the results for Chapter 5. Make sure this chapter is written in past tense and reflects how the project was actually conducted.
This chapter typically contains the analyzed data, often presented in both text and tabular or figure format. To ensure readability and clarity of findings, structure is of the utmost importance in this chapter. Sufficient guidance in the narrative should be provided to highlight the findings of greatest importance for the reader. Most investigators begin with a description of the sample and the relevant demographic characteristics presented in text or tabular format.
Ask the following general questions before starting this chapter:
- Is there sufficient data to answer each of the clinical question(s) asked in the project? (see Appendix C) One procedure for determining a sample size ahead of the project is a power analysis.
- Is there sufficient data to support the conclusions you will make in Chapter 5? (see Appendix D) If using SPSS version 26 to perform analyses, the data is entered and coded using numbers or numerical codes.
- Is the project written in the third person? Never use the first person.
- Is the data clearly explained using a table, graph, chart, or text? (see Appendix E)
Visual organizers, including tables and figures, must always be introduced, presented and discussed within the text first. Never insert them without these three steps. It is often best to develop all of the tables, graphs, charts, etc. before writing any text to further clarify how to proceed. Point out the salient results and present those results by table, graph, chart, or other form of collected data. See Appendix E for examples of APA formatted tables and figures.
| Criterion | Learner Score (0, 1, 2, or 3) |
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| INTRODUCTION (TOTHE CHAPTER)
This section of Chapter 4 briefly restates the problem statement, the methodology, the clinical question(s) or phenomena, and offers a statement about what will be covered in this chapter. |
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| Re-introduces the purpose of the practice project. | |||
| Briefly describes the project methodology and/or clinical question(s) tested. | |||
| Provides an orienting statement about what will be covered in the chapter. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). |
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Descriptive Data
This section of Chapter 4 provides a narrative summary of the population or sample characteristics and demographics of the participants in the project. It establishes the number of subjects, gender, age, education level or employee classification, (if appropriate), organization, or setting (if appropriate), and other appropriate sample characteristics (e.g. education level, program of project, employee classification etc.). The use of graphic organizers, such as tables, charts, histograms and graphs to provide further clarification and promote readability, is encouraged to organize and present coded data. Ensure this data cannot lead to anyone identifying individual participants in this section or identifying the data for individual participants in the data summary and data analysis that follows.
For numbers, equations, and statistics, spell out any number that begins a sentence, title, or heading – or reword the sentence to place the number later in the narrative. In general, use Arabic numerals (10, 11, 12) when referring to whole numbers 10 and above, and spell out whole numbers below 10. There are some exceptions to this rule:
- If small numbers are grouped with large numbers in a comparison, use numerals (e.g., 7, 8, 10, and 13 trials); but, do not do this when numbers are used for different purposes (e.g., 10 items on each of four surveys).
- Numbers in a measurement with units (e.g., 6 cm, 5-mg dose, 2%).
- Numbers that represent time, dates, ages, sample or population size, scores, or exact sums of money.
- Numbers that represent a specific item in a numbered series (e.g., Table 1).
A sample table in APA style is presented in Table 3. Be mindful that all tables fit within the required margins, and are clean, easy to read, and formatted properly using the guidelines found in Chapter 5 (Displaying Results) of the APA Publication Manual 7th Edition.
A Sample Data Table Showing Correct Formatting
| Column A
M (SD) |
Column B
M (SD) |
Column C
M (SD) |
|
| Row 1 | 10.1 (1.11) | 20.2 (2.22) | 30.3 (3.33) |
| Row 2 | 20.2 (2.22) | 30.3 (3.33) | 20.2 (2.22) |
| Row 3 | 30.3 (3.33) | 10.1 (1.11) | 10.1 (1.11) |
Note. Adapted from “Sampling and Recruitment in Studies of Doctoral Students,” by I.M. Investigator, 2010, Journal of Perspicuity, 25, p 100. Reprinted with permission.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| DESCRIPTIVE DATA
This section of Chapter 4 provides a narrative summary of the population or sample characteristics and demographics of the participants in the project. It establishes the number of subjects, gender, age, level (if appropriate), organization, or setting (if appropriate). The use of graphic organizers, such as tables, charts and graphs to provide further clarification and promote readability, is encouraged. |
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| Provides a narrative summary of the population or sample characteristics and demographics. | |||
| Graphic organizers are used as appropriate to organize and present coded data, as well as descriptive data such as tables, histograms, graphs, and/or charts. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present but needs some editing); 3 (publication ready). |
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Data Analysis Procedures
This section presents a description of the process that was used to analyze the data. If clinical question(s) guided the project, data analysis procedures can be framed relative to each clinical question. Data can also be organized by chronology of phenomena, by themes and patterns, or by other approaches as deemed appropriate according for the project. The key components included in this section are:
- A detailed description of the data analysis procedures.
- An explanation of how the raw data relates to the clinical questions(s) asked in the project for a quantitative project.
- A discussion of the identification of sources of error and their effect on the data.
- An explanation and justification of any differences in why the data analysis section does not match what was approved in Chapter 3 (if appropriate).
- An analysis of the reliability and validity of the data in statistical terms, for quantitative projects.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| DATA ANALYSIS PROCEDURES
This section presents a description of the process that was used to analyze the data. If clinical question(s) guided the project, data analysis procedures can be framed relative to each clinical question. Data can also be organized by chronology of phenomena, by themes and patterns, or by other approaches as deemed appropriate |
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| Describes in detail the data analysis procedures. | |||
| Explains and justifies any differences in why the data analysis section does not match what was approved in Chapter 3 (if appropriate). | |||
| Provides validity and reliability of the data in statistical terms for quantitative methodology. | |||
| Identifies sources of error and potential impact on the data. | |||
| For a quantitative project, justifies how the analysis aligns with the clinical question(s) and is appropriate for the DPI project design. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). |
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Results
This section, which is the primary section of this chapter, presents a summary and analysis of the data in a non-evaluative, unbiased, organized manner that relates to the clinical question(s). List the clinical question(s) as you are discussing them in order to ensure that the readers see that the question has been addressed. Answer the clinical question(s) in the order that they are listed for quantitative studies. The key components included in this section are:
- The data and the analysis of that data should be presented in a narrative, non-evaluative, unbiased, organized manner by clinical question(s).
- The section should also include appropriate graphic organizers, such as tables, charts, graphs, and figures.
- The amount and quality of the data or information is sufficient to answer the clinical question(s) is well presented and is intelligently interpreted.
- Quantitative: Findings are presented by clinical question using section titles. They are presented in order of significance, if appropriate.
- Quantitative: Results of each statistical test are presented in appropriate statistical format with tables, graphs, and charts.
- Quantitative: For inferential statistics, p-value and test statistics are reported.
- Quantitative: Control variables (if part of the design) are reported and discussed. Outliers, if found, were reported.
The results must be presented without implication, speculation, assessment, evaluation, or interpretation. Discussion of results and conclusions are left for Chapter 5. Refer to the APA Style Manual for additional lists and examples. In quantitative practice improvement projects, it is not required for all data analyzed to be presented; however, it is important to provide descriptive statistics and the results of the applicable statistic tests used in conducting the analysis of the data. It is also important that there are descriptive statistics provided on all variables. Nevertheless, it is also acceptable to put most of this in the Appendix if the chapter becomes too lengthy.
Required components include descriptive and inferential statistics. Descriptive statistics describe or summarize data sets using frequency distributions (e.g., to describe the distribution for the IQ scores in your class of 30 pupils) or graphical displays such as bar graphs (e.g., to display increases in a school district’s budget each year for the past five years), as well as histograms (e.g., to show spending per child in school and display mean, median, modes, and frequencies), line graphs (e.g., to display peak scores for the classroom group), and scatter plots (e.g., to display the relationship between two variables). Descriptive statistics also include numerical indexes such as averages, percentile ranks, measures of central tendency, correlations, measures of variability and standard deviation, and measures of relative standing.
Inferential statistics describe the numerical characteristics of data, and then go beyond the data to make inferences about the population based on the sample data. Inferential statistics also estimate the characteristics of populations about population parameters using sampling distributions, or estimation. Table 4 presents example results of an independent t test comparing Emotional Intelligence (EI) mean scores by gender.
t-Test for Equality of Emotional Intelligence Mean Scores by Gender
| t test for equality of means | |||
| t | Df | p | |
| EI | 1.908 | 34 | .065 |
After completing the first draft of Chapter 4, ask these general questions:
- Are the findings clearly presented, so any reader could understand them?
- Are all the tables, graphics or visual displays well-organized and easy to read?
- Are the important data described in the text?
- Is factual data information separate from analysis and evaluation?
- Are the data organized by clinical questions?
Chapter 4 can be challenging with regard to mathematical equations and statistical symbols or variables. When including an equation in the narrative, space the equation as you would words in a sentence: x + 5 = a. Punctuate equations that are in the paragraph, as you would a sentence. Remember to italicize statistical and mathematical variables, except Greek letters, and if the equation is long or complicated, set it off on its own line.
Refer to your APA manual for specific details on representation of statistical information. Basic guidelines include:
- Statistical symbols are italicized (t, F, N, n)
- Greek letters, abbreviations that are not variables and subscripts that function as identifiers use standard typeface, no bolding or italicization.
- Use parentheses to enclose statistical values (p = .026) and degrees of freedom t(36) = 3.85 or F(2, 52) = 3.85
- Use brackets to enclose limits of confidence intervals 95% CIs [- 5.25, 4.95]
Make sure to include appropriate graphics to present the results. Always introduce, present, and discuss the visual organizers in narrative form. Never insert a visual organizer without these three steps.
A figure is a graph, chart, map, drawing, or photograph. Below is an example of a figure labeled per APA style. Do not include a figure unless it adds substantively to the understanding of the results or it duplicates other elements in the narrative. If a figure is used, a label must be placed under the figure. As with tables, refer to the figure by number in the narrative preceding the placement of the figure. Make sure a table or figure is not split between pages. Below is another example of a table and figure for you to review. (see Table 5 and Figure 4)
The Servant Leader
| Trait | Descriptors |
| Values People | By believing in people
By serving other’s needs before his or her own By receptive, non-judgmental listening |
| Develops People
|
By providing opportunities for learning and growth
By modeling appropriate behavior By building up others through encouragement and affirmation |
|
Builds Community |
By building strong personal relationships By working collaboratively with others By valuing the differences of others |
|
Displays Authenticity
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By being open and accountable to others By a willingness to learn from others By maintaining integrity and trust |
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Provides Leadership
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By envisioning the future By taking initiative By clarifying goals |
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Shares Leadership
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By facilitating a shared vision By sharing power and releasing control By sharing status and promoting others
|
Note. Derived from Laub, J. (1999). Assessing the servant organization: Development of the servant organizational leadership assessment (SOLA) instrument (Doctoral Practice improvement project). Available from ProQuest Practice improvement project and Theses Database. (UMI No. 9921922)
Scattor Plot Example – Strong Negative Correlation
Note, an example of a strong negative correlation for SAT composite score and time spent on Facebook for 11th grade high school students enrolled in IMSmart SAT Prep Course.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| RESULTS
This section, which is the primary section of this chapter, presents an analysis of the data in a nonevaluative, unbiased, organized manner that relates to the clinical question(s). List the clinical question(s) as you are discussing them in order to ensure that the readers see that the question has been addressed. Answer the clinical question(s) in the order that they are listed. |
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| The analysis of the data is presented in a narrative, nonevaluative, unbiased, organized manner by clinical question(s). | |||
| Includes appropriate graphic organizers such as tables, charts, graphs, and figures. | |||
| The amount and quality of the data or information is sufficient to answer the clinical question(s) is well presented, and is intelligently analyzed. | |||
| Quantitative: Findings are presented by using section titles. They are presented in order of significance, if appropriate. | |||
| Quantitative: Results of each statistical test are presented in appropriate statistical format with tables, graphs, and charts. | |||
| Quantitative: For inferential statistics, p-value and test statistics are reported. | |||
| Quantitative: Control variables (if part of the design) are reported and discussed. Outliers, if found, were reported. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). |
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Summary
This section provides a concise summary of what was found in the project. It briefly restates essential data and data analysis presented in this chapter, and it helps the reader see and understand the relevance of the data and analysis to the clinical question(s). Finally, it provides a lead or transition into Chapter 5, where the implications of the data and data analysis relative to the clinical question(s) will be discussed. The summary of the data must be logically and clearly presented, with the factual information separated from interpretation. For quantitative studies, summarize the statistical data and results of statistical tests in relation to the clinical question(s). Finally, provide a concluding section and transition to Chapter 5.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| Summary
This section provides a concise summary of what was found in the project. It briefly restates essential data and data analysis presented in this chapter, and it helps the reader see and understand the relevance of the data and analysis to the clinical question(s). Finally, it provides a lead or transition into Chapter 5, where the implications of the data and data analysis relative to the clinical question(s) will be discussed. |
|||
| Summary of data is logically and clearly presented. | |||
| The factual information is separated from analysis. | |||
| Quantitative: Summarizes the statistical data and results of statistical tests in relation to the clinical question(s). | |||
| Provides a concluding section and transition to Chapter 5. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document. | |||
Chapter 5: Summary, Conclusions, and Recommendations
This section introduces Chapter 5 as a comprehensive summary of the entire project. It reminds the reader of the importance of the topic and briefly explains how the project intended to contribute to the body of knowledge on the topic. It informs the reader that conclusions, implications, and recommendations will be presented.
Chapter 5 is perhaps the most important chapter in the practice improvement project manuscript because it presents the investigator’s contribution to the body of knowledge. For many who read evidence-based literature, this may be the only chapter they will read. Chapter 5 typically begins with a brief summary of the essential points made in Chapters 1 and 3 of the original DPI project and includes why this topic is important and how this project was designed to contribute to the understanding of the topic. The remainder of the chapter contains a summary of the overall project, a summary of the findings and conclusions, recommendations for future practice, and a final section on implications derived from the project.
No new data or citations should be introduced in Chapter 5; however, references should be made to findings or citations presented in earlier chapters. The investigator can articulate new frameworks and new insights. The concluding words of Chapter 5 should emphasize both the most important points of the project and what the reader should take from them. This should be presented in the simplest possible form, making sure to preserve the conditional nature of the insights. Refer to the Grand Canyon University practice improvement project rubric for guidance on the content of this chapter.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| INTRODUCTION
Provides an overview of why the project is important and how the project was designed to contribute to our understanding of the topic. |
|||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). |
|||
Summary of the Project
This section provides a comprehensive summary of the overall project that describes the content of the project to the reader in the simplest possible terms. It should recap the essential points of Chapters 1-3, but it should remain a broad, comprehensive view of the project. It reminds the reader of the clinical question(s) and the main issues being evaluated, and provides a transition, explains what will be covered in the chapter and reminds the reader of how the project was conducted.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| SUMMARY OF THE PROJECT
Reminds the reader of the clinical question(s) and the main issues being evaluated. |
|||
| Provides a transition, explains what will be covered in the chapter and reminds the reader of how the project was conducted. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). |
|||
Summary of Findings and Conclusion
This section of Chapter 5 is organized by clinical question(s), and it conveys the specific findings of the project. The section presents conclusions made based on the data analysis and findings of the project and relates the findings back to the literature, significance of the project in Chapter 1, advancing scientific knowledge in Chapter 1. Significant themes/ findings are compared and contrasted, evaluated and discussed in light of the existing body of knowledge. The significance of every finding is analyzed and related to the significance section and advancing scientific knowledge section of Chapter 1. Additionally, the significance of the findings is analyzed and related back to Chapter 2 and ties the project together. The findings are bounded by the DPI project parameters described in Chapters 1 and 3, are supported by the data and theory, and directly relate to the clinical question(s). No unrelated or speculative information is presented in this section. This section of Chapter 5 should be organized by clinical question(s), theme, or any manner that allows summarizing the specific findings supported by the data and the literature. Conclusions represent the contribution to knowledge and fill in the gap in the knowledge. They should also relate directly to the significance of the project. The conclusions are major generalizations, and an answer to the practice problem developed in Chapters 1 and 2. This is where the project binds together. In this section, personal opinion is permitted, as long as it is backed with the data, grounded in the project methods and supported in the literature.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| Summary of Findings and Conclusions
This section is organized by clinical question(s), and it conveys the specific findings of the project. It presents all conclusions made based on the data analysis and findings of the project. It relates the findings back to the literature, significant chapters in Chapter 1, and advancing scientific knowledge in Chapter 1. |
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| Organized by the same section titles as Chapter 4, clinical question(s) or by themes. | |||
| Significant themes/ findings are compared and contrasted, evaluated and discussed in light of the existing body of knowledge. | |||
| Significance of every finding is analyzed and related to the significance section and advancing scientific knowledge section of Chapter 1. | |||
| The conclusion summarizes the findings, refers back to Chapter 1, and ties the project together. | |||
| The findings are bounded by the DPI project parameters described in Chapters 1 and 3. | |||
| The findings are supported by the data and theory, and directly relate to the clinical question(s). | |||
| No unrelated or speculative information is presented in this section. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). |
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Implications
This section should describe what could happen because of this project. It also tells the reader what the DPI project results imply theoretically, practically, and for the future. Additionally, it provides a retrospective examination of the theoretical framework presented in Chapter 2 in light of the practice improvement project’s findings. A critical evaluation of the strengths and weaknesses of the project, and the degree to which the conclusions are credible given the methodology, project design, and data, should also be presented. The section delineates applications of new insights derived from the practice improvement project to solve real and significant problems. Implications can be grouped into those related to theory or generalization, those related to practice, and those related to future projects. Separate sections with corresponding headings provide proper organization.
Theoretical Implications
Theoretical implications involve interpretation of the practice improvement project findings in terms of the clinical question(s) that guided the project. It is appropriate to evaluate the strengths and weaknesses of the project critically and include the degree to which the conclusions are credible given the method and data. It should also include a critical, retrospective examination of the framework presented in the Chapter 2 Literature Review section in light of the practice improvement project’s new findings.
Practical Implications
Practical implications should delineate applications of new insights derived from the practice improvement project to solve real and significant problems.
Future Implications
Two kinds of implications for future projects are possible: one based on what the project did find or do, and the other based on what the project did not find or do. Generally, future DPI projects could look at different kinds of subjects in different kinds of settings, interventions with new kinds of protocols or dependent measures, or new theoretical issues that emerge from the project. Recommendations should be included on which of these possibilities are likely to be most fruitful and why.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| Implications
This section should describe what could happen because of this DPI project results. It also tells the reader what the outcome and results implies theoretically, practically, and for the future. |
|||
| Provides a retrospective examination of the theoretical framework presented in Chapter 2 in light of the practice improvement project’s findings. | |||
| Critically evaluates the strengths and weaknesses of the project, and the degree to which the conclusions are credible given the methodology, project design, and data. | |||
| Delineates applications of new insights derived from the practice improvement project to solve real and significant problems. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). |
|||
Recommendations
Summarize the recommendations that result from the project. Each recommendation should trace directly to a conclusion.
Recommendations for Future Projects
This section should contain a minimum of four to six recommendations for future DPI projects, as well as a full explanation for why each recommendation is being made. Additionally, this section discusses the areas of project that need further examination or addresses gaps or new patient, or system needs the project found. The section ends with a discussion of “next steps” in forwarding this line of DPI project evaluations. Recommendations relate back to the project significance and advancing scientific knowledge sections in Chapter 1.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| Recommendations for Future PROJECTS
This section should contain a minimum of four to six recommendations for future DPI projects, as well as a full explanation for why each recommendation is being made. The recommended project methodology/design should also be provided. |
|||
| Contains a minimum of four to six recommendations for future projects. | |||
| Identifies and discusses the areas that need further examination, or addresses gaps or new patient or system needs the project found. | |||
| Suggests “next steps” in forwarding this line of evidence and clinical implications. | |||
| Recommendations relate back to the project significance and advancing scientific knowledge sections in Chapter 1. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your Chairperson and your committee and is ready to submit for AQR review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). |
|||
Recommendations for Practice
This section should contain two to five recommendations for future practice based on the results and findings of the project, as well as a full explanation for why each recommendation is being made. It provides a discussion of who will benefit from reading and implementing the results of the project and presents ideas based on the results that practitioners can implement in the work or educational setting. Unrelated or speculative information that is unsupported by data is clearly identified as such. Recommendations should relate back to the project significance section in Chapter 1.
| Criterion | Learner Score (0, 1, 2, or 3) |
Chairperson Score (0, 1, 2, or 3) |
Comments or Feedback |
| Recommendations for Future Practice
This section should contain two to five recommendations for future practice based on the results and findings of the project, as well as a full explanation for why each recommendation is being made. |
|||
| Contains two to five recommendations for future practice. | |||
| Discusses who will benefit from reading and implementing the results of the project. | |||
| Discusses ideas based on the results that practitioners can implement in the work or educational setting. | |||
| Unrelated or speculative information unsupported by data is clearly identified as such. | |||
| Recommendations relate back to the project significance section in Chapter 1. | |||
| Section is written in a way that is well structured, has a logical flow, uses correct paragraph structure, uses correct sentence structure, uses correct punctuation, and uses correct APA format. | |||
| NOTE: Once the document has been approved by your chairperson and your committee and is ready to submit for review, please remove all of these assessment tables from this document.
Score 0 (not present); 1(unacceptable; needs substantial edits); 2 (present, but needs some editing); 3 (publication ready). |
|||
References
Afrasiabifar, A., Mehri, Z., Javad, S., & Ghaffarian-Shirazi, H. (2016). The effect of Orem’s self-care model on fatigue in patients with multiple sclerosis: A single blind randomized clinical trial study. Iranian Red Crescent Medical Journal, 18(8), e31955. https://doi.org/10.5812/ircmj.31955
Ahmad, N., Ramli, A., Islahudin, F., & Paraidathathu, T. (2013). Medication adherence in patients with Type 2 diabetes mellitus treated at primary health clinics in Malaysia. Patient Prefer Adherence, 7, 525-530. https://doi.org/10.2147/ppa.s44698.
Asif M. (2014). The prevention and control the type-2 diabetes by changing lifestyle and
dietary pattern. Journal of Education and Health Promotion, 3, 1. https://doi.org/10.4103/2277-9531.127541
Borji, M., Sharifi, A., Otaghi, M., & Kazembeigi, s. (2017). The impact of Orem’s self-
care model on the quality of life in patients with type II diabetes in Ilam. Biomedical and Pharmacology Journal, 10(1), 213-220. https://doi.org/10.13005/bpj/1100
Camacho, G., Kalichman, S., & Katner, H. (2019). Anticipated HIV-related stigma and
HIV treatment adherence: The indirect effect of medication concerns. AIDS and Behavior, 24(1), 185-191. https://doi.org/10.1007/s10461-019-02644-z
Centers for Disease Control and Prevention. (2020, February). National Diabetes
statistics report, 2020. https://www.cdc.gov/diabetes/library/features/diabetes-stat-report.html
Centers for Disease Control and Prevention. (2020). Health care providers.
https://www.cdc.gov/diabetes/professional-info/health-care-providers.html
Chima, C., Abdelaziz, A., Asuzu, C., & Beech, B. (2020). Impact of health literacy on
medication engagement among adults with diabetes in the United States: A systematic review. The Diabetes Educator, 46(4), 335-349. https://doi.org/10.1177/0145721720932837
Choi, D., Choi, H., & Shon, D. (2019). Future changes to smart home based on AAL
healthcare service. Journal of Asian Architecture and Building Engineering, 18(3), 190-199. https://doi.org/10.1080/13467581.2019.1617718
Creswell, J.W. & Creswell, J.D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed). Sage Publications.
Glanz, K., Rimer, B., & Viswanath, K. (2015). Health behavior: Theory, research, and practice (5th ed). Jossey-Bass Publications.
Hamrahian, S. (2020). Medication non-adherence: A major cause of resistant hypertension. Current Cardiology Reports, 22(11). https://doi.org/10.1007/s11886-020-01400-3
Heath, S. (2018). How health coaching improving medication adherence, chronic care. Patient Access Care News. https://patientengagementhit.com/news/how-health-coaching-improves-medication-adherence-chronic-care#
Holecki, T., Romaniuk, P., Woźniak-Holecka, J., Szromek, A. R., & Syrkiewicz-Świtała, M. (2018). Mapping health needs to support health system management in Poland. Frontiers in Public Health, 6. https://doi.org/10.3389/fpubh.2018.00082
Holly, R. (2020, January). The top home health trends of 2020. Home Health Care News. https://homehealthcarenews.com/2020/01/the-top-home-health-trends-of-2020
Houston. (2021). Indicators: Adults with diabetes-County Harris.
https://www.houstonstateofhealth.com/indicators/index/view?indicatorId=81&localeId=2675
Huang, Y., Shiyanbola, O., Chan, H., & Smith, P. (2020). Patient factors associated with
diabetes medication adherence at different health literacy levels: A cross-sectional study at a family medicine clinic. Postgraduate Medicine, 132(4), 328-336. https://doi.org/10.1080/00325481.2020.1749499
Kang, H., Lobo, J., Kim, S., & Sohn, M. (2018). Cost-related medication non-adherence
among U.S. adults with diabetes. Diabetes Research and Clinical Practice, 143, 24–33. https://doi.org/10.1016/j.diabres.2018.06.01
Khademian, Z., Kazemi Ara, F., & Gholamzadeh, S. (2020). The effect of self-care
education based on Orem’s nursing theory on quality of life and self-efficacy in patients with hypertension: A quasi-experimental study. International Journal of Community-based Nursing and Midwifery, 8(2), 140-149. https://doi.org/10.30476/IJCBNM.2020.81690.
Kini, V., & Ho, P. (2018). Interventions to improve medication adherence: A review.
JAMA, 320, 2461-2473. https://journalce.powerpak.com/ce/medicationadherenceinpatientswithtype2d
Kvarnström, K., Airaksinen, M., & Liira, H. (2018). Barriers and facilitators to
medication adherence: A qualitative study with general practitioners. BMJ Open, 8(1), e015332. https://doi.org/10.1136/bmjopen-2016-015332
Lemay, J., Waheedi, M., Al-Sharqawi, S., & Bayoud, T. (2018). Medication adherence in
chronic illness: do beliefs about medications play a role? Patient Preference and Adherence, 12, 1687–1698. https://doi.org/10.2147/PPA.S169236
Lee, C., Tan, J., Sankari, U., Koh, Y., & Tan, N. (2017). Assessing oral medication
adherence among patients with type 2 diabetes mellitus treated with polytherapy in a developed Asian community: A cross-sectional study. BMJ Open, 7(9), e016317.
doi: 10.1136/bmjopen-2017-016317.
Lee, Y., Yu, H., You, M., & Son, Y. (2017). Impact of health literacy on medication
adherence in older people with chronic diseases. Collegian, 24(1),11-8. doi: 10.1016/j.colegn.2015.08.003
Lin, J., Thompson, T., Cheng, Y., Zhuo, X., Zhang, P., Gregg, E., & Rolka, D.
(2018). Projection of the future diabetes burden in the United States through 2060. Population Health Metrics, 16(1). https://doi.org/10.1186/s12963-018-0166-4
Liss, D. T., Peprah, Y. A., Brown, T., Ciolino, J. D., Jackson, K., Kho, A. N., Murakami, L., Walunas, T. L., & Persell, S. D. (2020). Using electronic health records to measure quality improvement efforts: Findings from a large practice facilitation initiative. The Joint Commission Journal on Quality and Patient Safety, 46(1), 11-17. https://doi.org/10.1016/j.jcjq.2019.09.006
Misquitta, C. (2020, December). Three challenges in medication adherence that can be
overcome by pharmacists. Pharmacy Times. https://www.pharmacytimes.com/view/three-challenges-in-medication-adherence-that-can-be-overcome-by-pharmacists
Nduaguba, S, Soremekun, R., Olugbake, O., & Barner, J. (2017). The relationship
between patient-related factors and medication adherence among Nigerian patients taking highly active anti-retroviral therapy. African Health Sciences, 17(3), 738–745. https://doi.org/10.4314/ahs.v17i3.16
Mayo Clinic. (2019). Type 2 diabetes: Symptoms and causes.
https://www.mayoclinic.org/diseases-conditions/type-2-diabetes/symptoms-causes/syc-20351193
Neiman, A., Ruppar, T., Ho, M., Garber, L., Weidle, P., Hong, Y., George, M., &
Thorpe, P. (2017). CDC grand rounds: Improving medication adherence for chronic disease management — Innovations and opportunities. MMWR. Morbidity and Mortality Weekly Report, 66(45), 1248-1251. https://doi.org/10.15585/mmwr.mm6645a2
Ong, S., Koh, J., Toh, S., Chia, K., Balabanova, D., McKee, M., Perel, P., & Legido-Quigley, H. (2018). Assessing the influence of health systems on type 2 diabetes mellitus awareness, treatment, adherence, and control: A systematic review. PLOS ONE, 13(3), e0195086. https://doi.org/10.1371/journal.pone.0195086
Orem, D. (1985). Nursing: Concepts of practice. McGraw-Hill Companies.
Pannucci, C., & Wilkins, E. (2010). Identifying and avoiding bias in research. Plastic and
Reconstructive Surgery, 126(2), 619-625. doi:10.1097/PRS.0b013e3181de24bc
Raveendran, A., Chacko, E., & Pappachan, J. (2018). Non-pharmacological treatment
options in the management of diabetes mellitus. European Endocrinology, 14(2), 31–39. https://doi.org/10.17925/EE.2018.14.2.31
Sawkin, M., Deppe, S., Thelen, J., Stoner, S., Dietz, C., & Rasu, R. (2015).
Health literacy and medication adherence among patients treated in a free health clinic. Health Services Research and Managerial Epidemiology, 2, 233339281558909. https://doi.org/10.1177/2333392815589094
Schweizer, M., Braun, B., & Milstone, A. (2016). Research methods in healthcare epidemiology and antimicrobial stewardship—quasi-experimental designs. Infection Control & Hospital Epidemiology, 37(10), 1135-1140. https://doi.org/10.1017/ice.2016.117
Shahin, W., Kennedy, G., & Stupans, I. (2019). The impact of personal and cultural
beliefs on medication adherence of patients with chronic illnesses: a systematic review. Patient Preference and Adherence, 13, 1019–1035. https://doi.org/10.2147/PPA.S212046
Sharma, S. K., Kant, R., Kalra, S., & Bishnoi, R. (2020). Prevalence of primary non-adherence with insulin and barriers to insulin initiation in patients with type 2 diabetes mellitus – An exploratory study in a tertiary care teaching public hospital. European Endocrinology, 16(2), 143. https://doi.org/10.17925/ee.2020.16.2.143
Sertbas, M., Guduk, O., Guduk, O., Yazici, Z., Dagci, S., & Sertbas, Y. (2019). Current situation analysis of diabetic home care patients. Northern clinics of Istanbul, 7(2), 140–145. https://doi.org/10.14744/nci.2019.59751
Singletary, M. (2019). For seniors hoping to age in place, the cost of in-home care just got a lot more expensive. The Washington Post. https://www.washingtonpost.com/business/personal-finance/for-seniors-hoping-to-age-in-place-the-cost-of-in-home-care-just-got-a-lot-more-expensive/2019/10/29
Starr, B., & Sacks, R. (2010). Improving outcomes for patients with chronic diseases: The medication adherence project (MAP). NYC Health. https://www.hfproviders.org/documents/root/pdf
Szanton, S. L., Leff, B., Wolff, J. L., Roberts, L., & Gitlin, L. N. (2016). Home-based care program reduces disability and promotes aging in place. Health Affairs, 35(9), 1558-1563. https://doi.org/10.1377/hlthaff.2016.0140
Understanding Houston. (2021). Access to healthcare in Houston. https://www.understandinghouston.org/topic/health/access-to-healthcare/#uninsured_rate_children
U.S. Department of Health & Human Services. (2018). Read the Belmont report.
https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/read-the-belmont-report/index.html
World Health Organization. (2017). Adherence to long-term therapies: Evidence for
action. http://apps.who.int/iris/bitstream/10665/42682/1/9241545992.pdf
Yeam, C., Chia, S., Tan, H., Kwan, Y., Fong, W., & Seng, J. (2018). Systematic
review of factors affecting medication adherence among patients with osteoporosis. Osteoporosis International, 29(12), 2623-2637. https://doi.org/10.1007/s00198-018-4759-3
Appendix A
The Parts of a Practice Improvement Project
GCU requires the Publication Manual of the American Psychological Association (7th ed.) as the style guide for writing and formatting Direct Practice Improvement (DPI) Projects. A DPI Project has three parts: preliminary pages, main text, and supplementary pages. Some preliminary or supplementary pages may be optional or not appropriate to a specific project. The learner should consult with his or her practice improvement project chairperson and committee regarding inclusion or exclusion of optional pages.
Preliminary Pages
The following preliminary pages precede the main text of the practice improvement project.
Title Page
Copyright Page (optional)
Approval Page
Abstract
Dedication Page (optional)
Acknowledgements (optional)
Table of Contents
List of Tables (if you have tables, a list is required)
List of Figures (if you have figures, a list is required)
Main Text
The main text is divided into five major chapters. Each chapter can be further subdivided into sections and subsections.
Chapter 1: Introduction to the Project
Chapter 2: Literature Review
Chapter 3: Methodology
Chapter 4: Data Analysis and Results (not included in the proposal)
Chapter 5: Summary, Conclusions, and Recommendations (not included in the proposal)
Supplementary Pages
Supplementary pages, which follow the body text, include reference materials and other required or optional addenda.
References
Appendices
Appendix A for the manuscript is the Grand Canyon University IRB Outcome Letter.
Appendix B is the Instruments/tool used.
Appendix C is permission to use the instrument/tool.
Appendix D is another tool if applicable (Appendix E is permission for second instrument/tool) otherwise you are done.
Keep in mind that most formatting challenges are encountered in the preliminary and supplementary pages. Allocate extra time and attention for these sections to avoid delays in the electronic submission process. In addition, as elementary as it may seem, run a spell check and grammar check of your entire document before submission.
Appendix B
What is my DPI project design?
| THIS IS NOT PART OF THE PAPER JUST A REFERENCE FOR THE LEARNER |
Appendix C
Power Analysis Using G Power
Note: Public source G-Power Software available https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower.html
Appendix D
Example SPSS Dataset & Variable View
The SPSS database is set up with all variables coded to compare between or within the comparison groups. A comparison may be made within the same individual and it coded 1 for before and 2 after the intervention. Or if measuring between individuals, the data would be coded the same 1 for before and 2 after as noted in the Group Column. Software supplied by Grand Canyon University.
Appendix E
How to Make APA Format Tables and Figures Using Microsoft Word
Tables vs. Figures
- See APA Publication Manual, Chapter 7 for additional details (APA, 2019).
- Tables consist of words and numbers where spatial relationships usually do not indicate any numerical information.
- Tables should be used to present information that would be too wordy, repetitive, or difficult to read as text.
- Figures typically communicate numerical information using spatial relations. For example, as you move up the Y axis of bar graph the scores usually go up.
- Examples of APA Tables
- Descriptive table
Table 1
Characteristics of Variables
| Variable | Variable Type | Level of Measurement |
| Group, Intervention or Tool | Independent | Nominal
|
| Rates or events | Dependent | Nominal
|
| Socio Economic Status or Categories in an order | Dependent | Ordinal
|
| Time, Temperature | Dependent | Interval
|
| Age, height, Scores of tests | Dependent | Ratio |
Note. Add notes here = (Provide any reference, 2019).
Table 1
Number of Handoff Per Groups
| Group | # of Handoffs (%) |
| Pre-Intervention Group (Baseline) | 150 (50%) |
| SBAR Group | 150 (50%) |
Note. SBAR handoff was defined as …. (IHI, 2020)
Table 1
Number of Hours Per Week Spent in Various Activities
| Group | Baseline
(n = 30) |
Post Intervention (n = 30) | Total Sample
(n = 60) |
| M (SD) | M (SD) | M (SD) | |
| Schoolwork | 18.23 (7.79) | 16.23 (3.99) | 17.63 (1.2) |
| Physical activities | 19.54 (3.63) | 14.23 (2.84)* | 18.67 (1.0) |
| Socializing | 16.23 (3.99) | 17.63 (1.2) | 18.23 (7.79) |
| Watching television | 14.23 (2.84) | 18.67 (1.0) | 19.54 (3.63) |
| Extracurricular activities | 19.54 (3.63) | 18.23 (7.79) | 19.22 (5.45) |
Note. Schoolwork was defined as time spent doing class work outside of regular class time.
*statistically significant at p <.05
- Chi-Square example (Group IV x Group DV)
Table 1
Crosstabulation of Gender and Chronic Pain
| Chronic
Pain |
Gender | ||||
| Female | Male | χ2 | Φ | ||
|
Yes |
2
(-2.7)
|
8
(2.7) |
7.20** | ,60 | |
|
No |
8
(2.7)
|
2
(-2.7) |
|||
Note. Adjusted standardized residuals appear in parentheses below group frequencies.
**= p < .01.
- t-Test Example (Dichotomous Group IV x Score DV) –Notice two separate t-test results have been reported.
Table 1
Chronic Paint Score and Exercise time for Males and Females
| Gender | |||||
| Female | Male | T | df | ||
|
Pain Score |
3.33 (1.70) |
3.75 (1.79) |
-2.20* | 175 | |
|
Exercise Time |
4.28 (.7509) |
3.87 (.9280) |
4.2** | 176 | |
Note. Standard Deviations appear in parentheses below means.
* = p < .05, *** = p < .001.
- One Way ANOVA with 3 Groups Example (Group IV x Score DV)
Remember with an ANOVA, you have to report paired comparisons associated with post hoc or planned comparisons) for significant analyses. The results of paired comparisons are indicated by the subscripts on the means within rows. Also, notice in this table that we report the results of four separate analyses. This is the real power of tables: we can convey a large amount of information very concisely.
Table 1
Analysis of Variance for Sleep Times and Experimental Groups
| Experimental Group | |||||
| Aerobic Exercise | Weight Lifting | No Exercise | F | η2 | |
| Total Sleep Time | 8.23a
(.55) |
7.93b
(.90) |
7.73ab
(.55) |
3.98***
|
.18 |
| Total Wake Time | 3.58a
(.70) |
3.62a
(.55) |
3.54a
(.90) |
.03 | .00 |
| Total Light Sleep | 3.19c
(.73) |
2.80a
(.72) |
3.02b
(.49) |
2.95* | .06 |
| Total Deep Sleep | 3.21b
(.19) |
3.10a
(.28) |
3.30a
(.19) |
.20 | .01 |
Standard deviations appear in parentheses bellow means. Means with differing subscripts within rows are significantly different at the p < .05 based on Fisher’s LSD post hoc paired comparisons.
* = p < .05, *** = p < .001.
- Factorial ANOVA Example 2 x 3 between subject’s design.
Notice that two tables are used here. The first table reports the overall results for the 2×3 factorial ANOVA, which includes the Main Effects for the two IV’s and the Interaction Effect for the two IV’s. The second table reports the means and simple effects tests for the significant interaction effect.
Table 1
Experimental Group x Sex Factorial Analysis of Variance for Sleep Scores
| Source | Df | F | η2 | p |
|
Experimental Group |
2 |
7.93 |
.17 |
.001 |
|
Sex
|
1
|
31.41
|
.34
|
.001
|
| Group x Sex (interaction)
|
2
|
7.85
|
.17
|
.002
|
| Error (within groups) | 30 |
Table 1
Analysis of Sleep Scores for Experimental Groups by Gender
| Aerobic Exercise | Weightlifting | No Exercise | Simple Effects:
F df (2, 30) |
|
|
Males |
10.37a
(2.50) |
10.30a
(2.34) |
10.33a
(1.63) |
.04 |
|
Females |
4.83a
(1.60) |
10.50b
(2.59) |
4.50a
(1.52) |
15.74** |
|
Simple Effects: F df (1, 30) |
23.56**
|
.00
|
23.56** |
Note. Standard deviations appear in parentheses bellow means. Means with differing subscripts within rows are significantly different at the p < .05 based on Fisher’s LSD post hoc paired comparisons.
** = p < .01
Notice that the simple effect comparing the 3 experiment groups only for females, requires follow up tests in order to determine which groups are significantly different. In this case, Fisher’s LSD test was used, and the results are represented with the different subscripts for each mean. In this case, female participants in the Aerobic exercise group did not differ from the no exercise group so they are given the same subscript (a). However, women in the control group and women in the Weightlifting group significantly differed from the Aerobic watching group and so the Weightlifting group was labeled with a different subscript (b). The male subjects did not differ from one another, so they all share the same subscript (a).
- Correlations (Scores IV x Scores IV)
Table 1
Pearson’s Product Moment Correlations for Chronic Pain Score, Exercise Attitude Scores and Physical Activity
| Demographic Influences on Exercise | ||
| Weight | Age | |
| Chronic Pain Score
Pain Level |
.39*** |
-.07 |
|
Pain Intensity |
.15 |
.22* |
|
Physical Exercise
Type of Exercise |
-.26** |
-.19† |
|
Time of Exercise |
-.13
|
-.21*
|
| Intent to Exercise | .02 | -.10 |
Note. N = 96 for all analyses.
† = p < .10, *= p < .05, **= p < .01, ***= p < .001.
- Examples of APA Figures
Generally, the same features apply to figures as have been previously provided for tables: They should be easy to read and interpret, consistent throughout the document when presenting the same type of figure, kept on one page if possible, and supplement the accompanying text or table.
Figure 1
Graph of Scores Before and After
Note: Reprinted from S. GCU. Or Adapted from or www.website.com. Reprinted with permission.
If the figure is not your own work, note the source or reference where you found the figure. Write, “Reprinted from” or “Adapted from,” followed by the title of the book, article, or website where you found the figure. Include the page number where you found the figure as well if you are citing a figure from a book. If you are citing a figure from a website, you may write, “Reprinted from The Huffington Post.” Or include the author’s first and second initial as well as their surname. Use the author’s first and second initial, if available, rather than the author’s full first name. Note their last name as well.
References:
American Psychological Association [APA]. (2019). Publication manual of the American Psychological Association. (7th ed.). Washington, DC; Author
Microsoft Word ®. (2019). Retrieved from https://products.office.com/
Appendix F
Writing up your statistical results
Identify the analysis technique.
In the results section (Chapter 4), your goal is to report the results of the data analyses used to answer your project question. To do this, you need to identify your data analysis technique, report your test statistic, and provide some interpretation of the results. Each analysis you run should be related to your clinical question or PICOT. If you analyze data that is exploratory or outside your clinical question, you need to indicate this in the results.
Format test statistics.
Test statistics and p values should be rounded to two decimal places (If you are providing precise p-values for future use in meta-analyses, 3 decimal places are acceptable). All statistical symbols (sample statistics) that are not Greek letters should be italicized (M, SD, t, p, etc.).
Indicate the direction of the significant difference.
When reporting a significant difference between two conditions, indicate the direction of this difference, i.e. which condition was more/less/higher/lower than the other condition(s). Assume that your audience has a professional knowledge of statistics. Do not explain how or why you used a certain test unless it is unusual (i.e., such as a non-parametric test).
How to report p values.
Report the exact p value (this is the preferred option if you want to make your data convenient for individuals conducting a meta-analysis on the topic).
Example: t(33) = 2.10, p = .03.
If your exact p value is less than .001, it is conventional to state merely p < .001. If you report exact p values, state early in the results section the alpha level used as a significance criterion for your tests. For example: “We used an alpha level of .05 for all statistical tests.”
If your results are in the predicted direction but are not significant, you can say your results were marginally significant. Example: Results indicated a marginally significant preference for pie (M = 3.45, SD = 1.11) over cake (M = 3.00, SD = .80), t(5) = 1.25, p = .08.
If your p-value is over .10, you can say your results revealed a non-significant trend in the predicted direction. Example: Results indicated a non-significant trending in the predicted direction indicating a preference for pie (M = 4.25, SD = 2.21) over cake (M = 3.25, SD = 2.60), t(5) = 1.75, p = .26.
Descriptive Statistics
Mean and Standard Deviation are most clearly presented in parentheses:
The sample as a whole was relatively young (M = 19.22, SD = 3.45).
The average age of students was 19.22 years (SD = 3.45).
Percentages are also most clearly displayed in parentheses with no decimal places:
Nearly half (49%) of the sample was married.
Frequencies or rates are reported including the range, mode, or median.
t-tests
There are several different designs that utilize a t-test for the statistical inference testing. The differences between one-sample t-tests, related measures t-tests, and independent samples t tests are clear to the knowledgeable reader so eliminate any elaboration of which type of t-test has been used. Additionally, the descriptive statistics provided will identify which variation was employed. It is important to note that we assume that all p values represent two-tailed tests unless otherwise noted and that independent samples t-tests use the pooled variance approach (based on an equal variances assumption) unless otherwise noted:
There was a significant effect for gender, t(54) = 5.43, p < .001, with men receiving
higher scores than women.
Results indicate a significant preference for pie (M = 3.45, SD = 1.11) over cake (M = 3.00, SD = .80), t(15) = 4.00, p = .001.
The 36 study participants had a mean age of 27.4 (SD = 12.6) were significantly older
than the university norm of 21.2 years, t(35) = 2.95, p = .01.
Students taking statistics courses in psychology at the University of Washington reported studying more hours for tests (M = 121, SD = 14.2) than did UW college students in general, t(33) = 2.10, p = .034.
The 25 participants had an average difference from pre-test to post-test anxiety scores of -4.8 (SD = 5.5), indicating the anxiety treatment resulted in a significant decrease in
anxiety levels, t(24) = -4.36, p = .005 (one-tailed).
The 36 participants in the treatment group (M = 14.8, SD = 2.0) and the 25 participants in the control group (M = 16.6, SD = 2.5), demonstrated a significance difference in
performance (t[59] = -3.12, p = .01); as expected, the visual priming treatment inhibited
performance on the phoneme recognition task.
UW students taking statistics courses in Psychology had higher IQ scores (M = 121, SD = 14.2) than did those taking statistics courses in Statistics (M = 117, SD = 10.3), t(44) =
1.23, p = .09.
Over a two-day period, participants drank significantly fewer drinks in the experimental group (M= 0.667, SD = 1.15) than did those in the wait-list control group (M= 8.00, SD= 2.00), t(4) = -5.51, p=.005.
ANOVA and post hoc tests.
ANOVAs are reported like the t test, but there are two degrees-of-freedom numbers to report. First report the between-groups degrees of freedom, then report the within-groups degrees of freedom (separated by a comma). After that report the F statistic (rounded off to two decimal places) and the significance level.
One-way ANOVA:
The 12 participants in the high dosage group had an average reaction time of 12.3.
seconds (SD = 4.1); the 9 participants in the moderate dosage group had an average
reaction time of 7.4 seconds (SD = 2.3), and the 8 participants in the control group had a
mean of 6.6 (SD = 3.1). The effect of dosage, therefore, was significant, F(2,26) = 8.76,
p=.012.
A one-way analysis of variance showed that the effect of noise was significant, F(3,27) = 5.94, p = .007. Post hoc analyses using the Scheffé post hoc criterion for significance indicated that the average number of errors was significantly lower in the white noise condition (M = 12.4, SD = 2.26) than in the other two noise conditions (traffic and industrial) combined (M = 13.62, SD = 5.56), F(3, 27) = 7.77, p = .042.
Tests of the four a priori hypotheses were conducted using Bonferroni adjusted alpha
levels of .0125 per test (.05/4). Results indicated that the average number of errors was
significantly lower in the silence condition (M = 8.11, SD = 4.32) than were those in both
the white noise condition (M = 12.4, SD = 2.26), F(1, 27) = 8.90, p =.011 and in the
industrial noise condition (M = 15.28, SD = 3.30), F (1, 27) = 10.22, p = .007. The
pairwise comparison of the traffic noise condition with the silence condition was nonsignificant.
The average number of errors in all noise conditions combined (M = 15.2, SD
= 6.32) was significantly higher than those in the silence condition (M = 8.11, SD = 3.30),
F(1, 27) = 8.66, p = .009.
Multiple Factor (Independent Variable) ANOVA
There was a significant main effect for treatment, F(1, 145) = 5.43, p < .01, and a
significant interaction, F(2, 145) = 3.13, p < .05.
The cell sizes, means, and standard deviations for the 3×4 factorial design are presented
in Table 1. The main effect of Dosage was marginally significant (F[2,17] = 3.23, p =
.067), as was the main effect of diagnosis category, F(3,17) = 2.87, p = .097. The
interaction of dosage and diagnosis, however, has significant, F(6,17) = 14.2, p = .0005.
Attitude change scores were subjected to a two-way analysis of variance having two
levels of message discrepancy (small, large) and two levels of source expertise (high,
low). All effects were statistically significant at the .05 significance level. The main
effect of message discrepancy yielded an F ratio of F(1, 24) = 44.4, p < .001, indicating
that the mean change score was significantly greater for large-discrepancy messages (M =
4.78, SD = 1.99) than for small-discrepancy messages (M = 2.17, SD = 1.25). The main
effect of source expertise yielded an F ratio of F(1, 24) = 25.4, p < .01, indicating that the
mean change score was significantly higher in the high-expertise message source (M =
5.49, SD = 2.25) than in the low-expertise message source (M = 0.88, SD = 1.21). The
interaction effect was non-significant, F(1, 24) = 1.22, p > .05.
A two-way analysis of variance yielded a main effect for the diner’s gender, F(1,108) =
3.93, p < .05, such that the average tip was significantly higher for men (M = 15.3%, SD
= 4.44) than for women (M = 12.6%, SD = 6.18). The main effect of touch was nonsignificant, F(1, 108) = 2.24, p > .05. However, the interaction effect was significant,
F(1, 108) = 5.55, p < .05, indicating that the gender effect was greater in the touch
condition than in the non-touch condition.
Chi Square
Chi-Square statistics are reported with degrees of freedom and sample size in parentheses, the Pearson chi-square value (rounded to two decimal places), and the significance level:
The percentage of participants that were married did not differ by gender, X2(1, N = 90) = 0.89, p > .05.
The sample included 30 respondents who had never married, 54 who were married, 26
who reported being separated or divorced, and 16 who were widowed. These frequencies
were significantly different, X2 (3, N = 126) = 10.1, p = .017.
As can be seen by the frequencies cross tabulated in Table xx, there is a significant
relationship between marital status and depression, X2 (3, N = 126) = 24.7, p < .001.
The relation between these variables was significant, X2 (2, N = 170) = 14.14, p < .01.
Catholic teens were less likely to show an interest in attending college than were
Protestant teens.
Preference for the three sodas was not equally distributed in the population, X2 (2, N =
55) = 4.53, p < .05.
Correlations
Correlations are reported with the degrees of freedom (which is N-2) in parentheses and the significance level:
The two variables were strongly correlated, r(55) = .49, p < .01.
Regression analyses
Regression results are often best presented in a table. A
PA doesn’t say much about how to report regression results in the text, but if you would like to report the regression in the text of your Results section, you should at least present the standardized slope (beta) along with the t-test and the corresponding significance level. (Degrees of freedom for the t-test is N-k-1 where k equals the number of predictor variables.) It is also customary to report the percentage of variance explained along with the corresponding F test.
Social support significantly predicted depression scores, b = -.34, t(225) = 6.53, p < .01. Social support also explained a significant proportion of variance in depression scores, R2 = .12, F(1, 225) = 42.64, p < .01.
Tables
Add a table or figure.
Adding a table of figure can be helpful to the reader. See the current APA Publication manual for examples. In reporting the results of statistical tests, report the descriptive statistics, such as means and standard deviations, as well as the test statistic, degrees of freedom, obtained value of the test, and the probability of the result occurring by chance (p value).
- APA style tables do not contain any vertical lines
- There are no periods used after the table number or title.
- When using columns with decimal numbers, make the decimal points line up.
- Use MS Word tables to create tables
American Psychological Association [APA]. (2019). Publication manual of the American Psychological Association (7th ed.). Washington, DC: Author.
Improving Medication Adherence among Type II Home Healthcare Diabetic Patients
Submitted by
Bola Odusola-Stephen
Direct Practice Improvement Project Proposal
Doctor of Nursing Practice
Grand Canyon University
Phoenix, Arizona
May 12, 2021
GRAND CANYON UNIVERSITY
Improving Medication Adherence among Type II Home Healthcare Diabetic Patients
by
Bola Odusola-Stephen
Proposed
May 12, 2021
DPI PROJECT COMMITTEE:
Maria Thomas, DNP, Manuscript Chair
Bamidele Jokodola, DNP, Committee Member
Abstract
Home healthcare programs are often effective since these programs offer techniques for improving health outcomes among diabetes patients. At the project site, although staff consistently assesses for patient medication adherence (MA), there is no standardized process for identifying and addressing MA. Medication Adherence Project (MAP) resources have been utilized in chronic disease management to improve MA. The purpose of this quantitative quasi-experimental project is to determine if or to what degree the implementation of Medication Adherence Project (MAP) resources, which include (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List, will impact medication adherence among type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. The theoretical frameworks that will guide this direct practice improvement (DPI) project include the social cognitive theory and the attachment theory. MA rates will be abstracted from the project site’s EHR, based on documentation provided by home health personnel, and will be compared to baseline MA rates.
Keywords: home-based care, MAP resources, quantitative approach, medication adherence, diabetes mellitus type II
Table of Contents
Chapter 1: Introduction to the Project 8
Advancing Scientific Knowledge. 16
Significance of the Project 18
Nature of the Project Design. 20
Assumptions, Limitations, Delimitations. 23
Summary and Organization of the Remainder of the Project 25
Chapter 2: Literature Review.. 27
Strengthening the Relationships with Patients. 35
Importance of Adhering to Medication Regimen. 36
Tools/Support Strategies for Improving Self-Efficacy and Medication Adherence. 39
Diabetes Across the Life Span. 41
Advocacy for Individuals with Diabetes. 42
Population and Sample Selection. 51
Data Collection Procedures. 56
Potential Bias and Mitigation. 59
Chapter 1: Introduction to the Project
According to the Centers for Disease Control and Prevention (2020), diabetes impacts one in ten Americans. Furthermore, the prevalence of diabetes continues to rise and is projected to increase by 0.3% per year until 2030 (Lin et al., 2018). Two types of diabetes plague a large proportion of Americans: Type I diabetes and Type II diabetes. Type I diabetes is dependent on insulin, whereby the pancreas produces minimal amounts of insulin (Bellouet al., 2018). Type II diabetes is an impairment related to the body’s ability to regulate glucose (Bellou et al., 2018). There are ways to curtail the onset of Type II diabetes; however, once individuals are diagnosed with diabetes, there is no cure (Kvarnström et al., 2017).
Among individuals with Type II diabetes, proper and effective medication adherence is critical (Kvarnström et al., 2017). According to the World Health Organization (WHO, 2003), “Increasing the effectiveness of adherence interventions may have a far greater impact on the health of the population than any improvements in specific medication treatment” (Brown & Bussell, 2011, para. 1). Furthermore, Kvarnström et al. (2017) stated that more than half of the population does not adhere to prescribed medication regimens, resulting in various health-related challenges. Health-related challenges associated with poor medication adherence include limited knowledge of health-related benefits, lack of proper technique for providing dosage, lack of patient self-management, and lifestyle constraints (Kvarnström et al., 2017). For individuals with Type II diabetes, lacking medication adherence can mean the difference between life and death (Rathish et al., 2019).
Various researchers have denoted the critical role that home healthcare providers play in promoting enhanced medication adherence (Bussell et al., 2017). Furthermore, the WHO, as cited by Brown and Bussell (2011), explained that five factors impact medication adherence, which include: (1) patient-related factors, (2) socioeconomic factors, (3) therapy-related factors, (4) condition-related factors, and (5) the health system/health care team-related factors. For this project’s purpose, the primary investigator (PI) will examine the impact/role that healthcare team members play in addressing patient-related factors that affect medication adherence among home healthcare diabetic patients. The health system/health care team-related factors.
The project was conducted to improve the patient’s adherence to medication to increase their overall health and wellbeing as it relates to diabetes mellitus. The primary investigator (PI) will also examine the impact/role that healthcare team members play in addressing patient-related factors that affect medication adherence among home healthcare diabetic patients. When diabetic patients do not adhere to their prescribed medication regime, they tend to have poor outcomes (Kvarnström et al., 2017).
Home-based healthcare has existed since 1909 (Choi et al., 2019). Since its inception, home-based healthcare has been perceived as a more costly method of patient care than expenses associated with hospitalization (Singletary, 2019). In the early 20th century, home-based healthcare was mainly practiced due to financial disparities, specifically since many individuals could not afford hospitalized care. Furthermore, home-based healthcare was also practiced due to medical inaccessibility, which often existed in African American communities due to limited access to resources (Choi et al., 2019).
Present-day, home-based healthcare is often selected due to an individual’s personal preferences. There are some situations in which individuals prefer the comforts of their own home compared to that of a hospital or group home (Bryant, 2018). As older generations continue to age, they often prefer to remain in their home for as long as possible. Given the needs of older generations and the impact of advances in healthcare and technology, the prevalence of home-based healthcare has exponentially grown (Wong et al., 2020). While home-based healthcare is not appropriate for all patients, Szanton et al. (2016) noted that this care option is best when an individual’s condition can be managed without admission to a hospital. Patients who have diabetes or hypertension are often recipients of home-based healthcare (Wong et al., 2020).
Home healthcare providers often visit patients and assess their blood pressure, cognitive functioning, and adherence to treatment proposals. During patient visits, home healthcare providers are responsible for biological assessments of patients (Wong et al., 2020). One of the vital functions of home healthcare providers is to ensure that patients are adhering to their medication regimen (Wong et al., 2020). According to Wong et al. (2020), medication adherence is predicated on medication understanding and education, which home healthcare providers should convey.
Adhering to diabetes medication regimen requirements can be complex. In fact, in a study by Raoufi et al. (2018), the researchers noted that 10% of diabetic patients did not correctly monitor their glucose levels, nor did they adhere to medication requirements. Dr. Goldbach, who is the Chief Medical Officer for Health Dialogue, stated, “There are programs that can be based on things like texting people, but what we’re highlighting is the fact that – especially for people with chronic illness that are facing challenges like depression, or transportation, or complexity of medication regimens – that these interpersonal, trusted interactions with a nurse tend to be very effective ” (Heath, 2018, para. 8). Patients with diabetes often express difficulties in adhering to medication regimens, thereby reinforcing the critical role of receiving education from home healthcare providers (Wong et al., 2020).
In a study by Wong et al. (2020), home healthcare patients expressed that they did not have sufficient knowledge about the requirements associated with diabetes treatment. Often, diabetic home healthcare patients fail to practice medication adherence, thereby resulting in health complications due to unmanaged health conditions .
It is not known if or to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List, will impact medication adherence among type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. At the selected project site, a home healthcare organization located in urban Texas, the stakeholders have cited that medication adherence among diabetic patients is lacking. In fact, according to data obtained from the site’s electronic health record (EHR), home healthcare providers have documented that 10% of diabetic home healthcare patients are not adhering to their medication regimen. Although this percentage is under 10 percent lower than other percentages cited in the literature for medication non-adherence, in terms of chronic disease management, various researchers have noted the implications associated with lacking adherence to medication regimens (Brown & Bussell, 2011; Camacho et al., 2020; Hamrahian, 2020; Misquitta, 2020; Wood, 2012). Lacking medication adherence is especially troubling among diabetic patients. It can be due to inadequate drug-related knowledge, medication costs, poor understanding of medication regimen, etc., thereby reinforcing the need for this direct practice improvement (DPI) project (Heath, 2019; Sharma et al., 2020).
Kvarnström et al. (2017) emphasized healthcare providers play a critical role in ensuring medication adherence. While there are many reasons for lacking adherence among patients, for this project, the WHO’s (2019) focus on the role of healthcare team members in enhancing medication adherence will be addressed. To promote medication adherence among patients of a home healthcare facility, the primary investigator will use MAP resources.
As previously noted, among diabetic patients at the project site, medication non-adherence is 10%. While this level of medication non-adherence seems exceptionally low, it is essential to note that false reporting among patients may occur (Tedla & Bautista, 2017). Tedla and Bautista (2017) explained that “self-reported medication adherence is known to overestimate true adherence.” Choo et al. (2001) demonstrated that 21% of patients expressed non-adherence when in fact, after measuring adherence with electronic cap bottles, non-adherence rates were 42%. In-home healthcare settings, lacking adherence to diabetic regimens is 14% (Ong et al., 2018). It is important to note that the project site’s non-adherence rates might be similar to that of the national average; however, often, patients are wary about disclosing true non-adherence due to embarrassment, forgetfulness, and lacking knowledge about the importance of medication adherence .
To improve patient-related outcomes and reduce preventable issues, home healthcare nursing staff members will utilize MAP tools, which were created by Starr and Sacks (2010). The tools utilized in this study, which are from Starr and Sacks’s (2010) MAP Toolkit and Training Guide resources, include: (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List. Before implementing these tools, the PI will provide a 30-minute information session on this project’s purpose and significance and provide detailed information about utilizing the MAP resources.
During the onset of this project, once home healthcare nursing staff members have attended the educational training session, the project will be implemented. Nursing staff members will first provide patients with the Questions to Ask Poster. The purpose of offering this poster to patients is to address the six questions about medication, thereby improving patients’ knowledge regarding their medication regimen and reasons for the regimen prescribed.
After addressing the six critical questions on the Questions to Ask Poster, patients will be provided with the Adherence Assessment Pad. The purpose of the Adherence Assessment Pad is to explore barriers that impact one’s adherence to the prescribed medication regimen. There are several factors, listed on the pad, that affect one’s medication adherence (e.g., [1] Makes me feel sick, [2] I cannot remember, [3] Too many pills, [4] Costs, [5] Nothing, and [6] Other). To further understand what might be preventing patients from adhering to their medication regimen, this resource is necessary to utilize.
Once barriers associated with medication adherence are identified, the nursing staff member will provide patients with the My Medications List. This list is essential to give the patients, as it allows providers and patients to converse about a schedule for taking one’s medication and details, in a sheet, when medication must be taken. According to Starr and Sacks (2010), “Filling out the Medication List may seem time-consuming. However, your initial investment will pay off, as patients better understand their regimens and adherence increases” (p. 17). In addition to the time-consuming nature of filling out the My Medications List, nursing staff members and patients might feel overwhelmed during this first session. However, it is important to note that subsequent nurse-patient home healthcare meetings will seem less intense after the first session because the My Medications List is the only MAP resource that will be consistently reviewed over the four weeks.
To evaluate the impact of the intervention, the PI will compare pre-project implementation medication non-adherence rates to post-project implementation medication non-adherence rates after implementing the MAP resources. Project participants will include Type II diabetes patients, ages 35-64, who are receiving home health services at the project site. Medication adherence data will be available through the project site’s EHR. This project will take place over four weeks.
The purpose of this quantitative quasi-experimental project is to determine if or to what degree the implementation of the MAP resources, which will be delivered by home healthcare nursing staff members, will impact medication adherence when compared to current practice among type II diabetic patients, ages 35 to 64 of a home healthcare setting in urban Texas. Medication adherence is the dependent variable explored in this project and will be measured using data attained through the project site’s EHR . The MAP resources, which serve as the independent variables explored in this project, include (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List.
Each month, the selected project site, which is located in urban Texas, serves an average of 100 patients. Of the total number of patients, approximately 30 patients have Type II diabetes. Patients with Type II diabetes, who are between the ages of 35 and 64 and are without cognitive or language deficits, will be the target population for this project. Exclusion criteria consists of age, gender, race, ethnicity, type of disease, treatment history, and other medical conditions. The project is significant since home-based healthcare services can enhance treatment initiative outcomes. Wong et al. (2020) stated that physicians visit patients to ensure proper status of patient’s blood pressure, cognitive functioning, and adherence to treatment proposals.
Starr and Sacks (2010) explained that engagement with healthcare providers is imperative, as these encounters can enhance patient-related health outcomes. Physical and cognitive assessments are conducted to ensure that patient-related home-based treatment approaches are effectively implemented. The project is vital as it may enhance positive healthcare outcomes, through improving medication adherence among Type II diabetic patients, using the MAP resources.
The problem described above was used to create a clinical question. The problem was it was unknown if or to what degree the implementation of the MAP resources, which will be delivered by home healthcare nursing staff members, will impact medication adherence when compared to current practice among type II diabetic patients, ages 35 to 64 of a home healthcare setting in urban Texas. The clinical question results will be determined using data collected on the diabetic patient self-reported documentation on their adherence to medication administration as prescribed by their clinician. A clinical question should be relevant to the problem being investigated and formed to facilitate an answer (Leedy & Ormrod, 2013).
A well-developed clinical question must be related and relevant to patient care. This helps the primary investigator search for evidence-based answers. The clinical question that will direct this quality improvement project is: To what degree does the implementation of Medication Adherence Project resources, which include the Questions to Ask Pad, the Questions to Ask Poster, an Adherence Assessment Pad, and the My Medications List impact medication adherence among Type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks?
This project’s independent variable was implementing the Medication Adherence Project resources, which include the Questions to Ask Pad, the Questions to Ask Poster, an Adherence Assessment Pad, and the My Medications List impact medication adherence. The dependent variable was the Medication adherence attained through the project site’s EHR. Medication adherence has the potential to decrease the likelihood of complications related to diabetes. The adherence to medication attained via the EHR will be counted and the use of the MAP resource will be documented.
Chapter 2: Literature Review
Diabetes is a medical condition that is characterized by high blood sugar levels, and is managed with drugs and insulin. Blood sugar serves as the major producer of energy in the body, therefore conditions/factors interfering with blood sugar levels and mechanisms disrupt normal body activities. Optimal diabetes control requires patient engagement in various types of self-care activities, including adhering to the identified medication regimens, adjusting to various lifestyle changes, and monitoring blood glucose levels (Jajarmi, Ghanbari, & Baleanu, 2019).
Diabetes is a lifestyle disease, which can be prevented or avoided by making lifestyle changes. Disease management can also occur through adhering to one’s prescribed medication regimen(s). Medication adherence is important since it can help to reduce the likelihood of diabetes-related challenges and complications.
One of the most problematic issues associated with home care for diabetes patients is adherence to medications. According to Bonney (2016), patients take their medication as prescribed only 50% of the time. Furthermore, patients are often reluctant to share medication compliance details, thereby resulting in health-related complications. This project hopes to enhance medication adherence, at the project site, which offers home-based care to diabetes patients. This project will also analyze the role of educating patients on medication adherence in improving their medication adherence.
Chapter 2 provides a theoretical framework and an empirical framework. Medication taking behaviors among home-based healthcare diabetes patients is investigated. The chapter is divided into theoretical and empirical sections. The theoretical section reviews the two theories that will guide this project, which include the attachment theory and social cognitive behavior theory. In the empirical section, literature from peer-reviewed studies and projects is explored. Furthermore, literature gaps are identified.
The primary investigator (PI) utilized various databases to conduct a thorough review of the literature. Specifically, the PI systematically searched for reviews that reported various aspects associated with medication adherence among diabetic patients. Eighteen systematic reviews, scoping reviews, and narratives were analyzed and are included in this chapter. Overall, the literature review revealed six main sub-themes and other sub-themes that promote the importance of this direct practice improvement (DPI) project. Each of the key sub-themes is comprehensively discussed and details about the importance of these sub-themes, in terms of the project’s focus, are explored.
Theoretical Foundations
According to Liu and Butler (2016), medication adherence is considered to be the largest challenge that healthcare workers and patients encounter. Medication adherence is a critical issue that requires more attention. Two key theories are explored during this project, which attempts to explain the relationship between medical non-adherence among patients and how medication adherence can be enhanced among diabetic patients through improved interventions.
Attachment theory. The first theory that will guide this project is the attachment theory. Bowlby (1958) proposed that attachment is adaptive as it improves the infant’s chance of survival. The attachment theory is defined as being a psychological, evolutionary, and ethological associated theory concerning the aspects of relationships between individuals. The attachment theory is famous and has been used in healthcare practices for many years. The most vital tenet of the attachment theory is that young children usually need to develop a relationship with, at minimum, a single primary caregiver. The child’s caregiver assists in offering social and emotional support. Within this theory, the term “attachment” is usually utilized to refer to an affection bond or tie that is between a person and their attachment figure, who in this case is considered to be the child’s caregiver (Liu & Butler, 2016). In this project, the attachment figure is the patient’s home healthcare provider, as providers can assist in creating the best interventions for enhancing medication adherence among diabetic patients.
The biological purpose for the use of attachment theory is the facilitation of survival, while the psychological purpose of the theory is to offer security, thus making it a suitable theory to use. Attachment theory does not provide an exhaustive description of human relationships. Furthermore, this theory is not synonymous with feelings of love or affection. In child-adult relationships, the child is usually referred to as the attachment while the caregiver is usually defined as being the reciprocal equivalent, who in this case is called to provide the caregiving bond (Hunter & Maunder, 2016).
The modern attachment theory focuses on bonding, which is an intrinsic human need that can assist in regulating emotions, such as fear, which can result in improve vitality and can promote development. Common attachment behaviors and emotions are usually displayed in most social primates, including humans, and are considered to be adaptive. The long-term evolution of social primates has aided in identifying social behaviors that enable people and groups to survive. The commonly observed types of attachment behavior in toddlers, such as staying near familiar individuals, are based on safety advantages. According to Bretherton (1992), Bowlby and Ainsworth perceived the environment associated with early adaptation as similar to hunter-gatherer communities. There is a survival advantage in the capacity to effectively sense dangerous conditions, like the issue of unfamiliarity, loneliness, and rapid approach, through guidance and support.
The advancement of attachment is considered to be a transactional process. Particular attachment behaviors start as predictable innate behaviors in the infancy stage of life. The behaviors are altered with age in various ways that are determined partly by experience, as well as the various sit-upon elements. As the various attachments are altered throughout life, they are shaped by relationships.
According to Hunter and Maunder (2016), there are two key reasons why the attachment theory is considered effective for the following DPI. First, the theory acts as a solid foundation for the enhanced comprehension regarding the identified development of ineffective coping techniques, as well as the underlying dynamics associated with the emotional difficulties of the person. Clinicians can help people who have attachment anxiety and fail to comprehend past experiences. Through the involvement of caregivers and/or significant others, individuals can help to reshape their coping patterns.
Clinicians can help people who have attachment anxiety and avoidance to find the best alternative way to meet their various needs. Most of the individuals who seek help want to learn how they can employ different strategies for coping with the dysfunction in their daily lives. Furthermore, individuals often express the desire to modify their dysfunctional and/or inappropriate coping techniques. The desire to change/modify techniques is an essential aspect needed to encourage medication adherence. Before delivering appropriate and patient-specific advice and interventions, to diabetic patients of the selected project site, individuals may express that they would like to adhere to their medication regimens. It is important to note that for effective outcomes to be realized, it is critical to ensure that all of a patient’s basic needs are effectively met. Therefore, through understanding barriers and challenges associated with medication adherence, strategies can be created, which can result in effective patient-related outcomes (Hunter & Maunder, 2016).
Social cognitive theory (SCT). The social cognitive theory (SCT) is a critical theory that will be utilized during this DPI project. The SCT is utilized to explain how human behavior is associated with dynamic, reciprocal, and progressive types of interactions that exist between the person and his/her given surrounding (Bosworth, 2015). Therefore, the SCT is famous because it often proposes that identified behavior aspects are an outcome of the cognitive processes that individuals usually develop. Cognitive processes are developed through social knowledge acquisition.
According to Bosworth (2015), the SCT bases its focus on the concept of behavioral capability, which states that before any individual acting in a certain situation, the individual needs to have knowledge on what they need to do and the manner in which they need to do it. Bandura’s (1986) conceptual model regarding reciprocal determinism is often utilized in addressing all the personal determinants associated with health. Bandura (1986) postulated people often engage in cognitive, vicarious, self-reflective, and self-regulatory processes in hopes of attaining a given goal. Individuals can often change by identifying their actions and proactively engaging in their change-related behaviors. When people exercise individual control over their behaviors, thoughts, procedures, and motivations, enhanced outcomes can be achieved (Bosworth, 2015).
Bandura (1986) asserted without having any kind of aspirations, individuals usually course through life unmotivated and uncertain regarding their specific capabilities. Nonetheless, Bandura also stated that people who take part in health-promoting behavior have self-belief, which enables them to fully take control over their thoughts, feelings, and actions (Badura, 1986). Bosworth (2015) explained that self-control should get promoted since it improves the ability of individuals to adopt healthy habits. According to Bandura (1986), although the SCT acknowledges that patients must understand health-associated risks and the benefits of treatment to effectively perform health-associated behaviors, understanding, in itself, is not adequate.
Self-influences can help an individual to achieve various changes that will result in desired health-associated outcomes. An individual’s belief in his/her ability to achieve certain outcomes is a concept that is referred to as self-efficacy. The two types of cognitive processes that are involved in influencing behavior in the SCT are self-efficacy and outcome expectations (Bosworth, 2015).
According to Hadler, Sutton, and Osterberg’s (2020) findings, SCT is essential to encourage patient change. Healthcare workers who counsel patients with chronic medical illnesses, like HIV or diabetes, found that providing patients with vital knowledge can enhance their likelihood of adhering to health/lifestyle changes. Support groups can utilize the SCT to empower patients to effectively approach and address various issues associated with medication adherence. In addition, supportive types of relationships can be established to effectively strengthen the patient’s ability to adhere to his/her prescribed medication regimen.
The two theories (i.e., the attachment theory and the SCT) are associated with improved health-related adherence and enhanced clinical results. Through education and support, medication adherence can improve. The attachment theory and the SCT will be used during this project to aid in improving medication adherence among patients. Patients often need to be educated, by a trusted medical provider, about the benefits of medication adherence. Therefore, through using the MAP resources, which encourage patient-provider conversation and discussion, special interventions can occur, thereby improving medication adherence. Healthcare providers, of the selected project site, will encourage patients to make behavioral changes and will offer support/rationale for these changes, thereby likely improving medication adherence.
Review of the Literature
Medication adherence is a major healthcare challenge that impacts a patient’s quality of life. Researchers are constantly exploring ways to minimize medication non-adherence and continue to develop evidence-based strategies to improve medication adherence among patients. Medication non-adherence is a critical issue that deserves a higher level of attention. Understanding medication adherence-related barriers, addressing those barriers, and inspiring patients to change their actions/beliefs is an important step in improving health among patients.
At the selected project site, healthcare workers, who work directly with diabetic patients, believe it is critical to ensure medication adherence. Patients present with unique health-related challenges, thereby reinforcing the importance of minimizing health-related threats. Lacking medication adherence can mean the difference between life and death (Rathish et al., 2019). Adherence to antiretroviral therapy is considered a predictor of effective clinical outcomes among diabetic patients, which is one of the reasons why medication adherence is essential.
Medication adherence. The term medication adherence refers to the art of taking medication as prescribed by a patient’s healthcare practitioners (Ahmed et al., 2018). Healthcare practitioners must ensure that the prescriptions that are provided to patients are suitable to the patient’s unique condition(s). Ahmed et al. (2018) stated that the quality of healthcare can be influenced by the ability of the body to respond to treatment. It is important to conduct physical assessments of patients so high-quality care is offered.
While medication adherence is important, there is a plethora of literature available that expresses the prevalence of medication non-adherence among patients. Various factors continue to impact medication adherence, which includes, but are not limited to, fear, costs, misunderstanding, too many medications, lack of symptoms, mistrust, worry, and depression (American Medical Association [AMA], 2020). To prevent medication non-adherence, providers can seek to understand the needs of patients and provide them with resources that can aid in overcoming non-adherence.
Enhancing medication adherence. To handle the issue of medication adherence among the diabetic patients who have had an issue with adherence to medication needs to come up with a variety of strategies that have been attained from scholarly reviews as well as journals for purposes of well researched data on the concept. Appropriate types of medications are usually considered to be the identified cornerstone regarding the prevention as well as disease treatment yet according to numerous research carried out, there is solely about half of the individual patients who adhere to the instructions of their prescribed medication (Bosworth, 2015). This usually causes a common as well as costly public health-associated challenge especially for the healthcare system in the US.
Since the aspect and issue of inappropriate as well as inefficient medication adherence are considered to be a complex change with a variety of contributing causes, there is no universal solution (Rodriguez-Saldana, 2019). The following theme breaks down into three subcategories that form the basis of the sub-themes associated with this theme. The sub-themes are used to offer a comprehensive analysis of all the vital types of interventions that are considered to be effective in enhancing medication adherence among diabetic patients but are also considered to be potentially scalable, that is they are easy to implement in any given scenario and population (Bosworth, 2015). Key traits that make these interventions effective are discussed throughout the DPI. The information offered under each sub-theme is vital to explain, as it can result in enhanced medication adherence through the implementation of documented and cost-effective solutions.
Strengthening the Relationships with Patients
Patients usually consider their healthcare providers (HCPs) as the most dependable source of data regarding their health condition and treatment. Patients are highly likely to effectively follow the treatment plan when they are involved in having a good relationship with their HCP due to the confidence and trust that has been built over time. Relationship building in healthcare is considered to be a vital aspect in the day to day lives of healthcare practitioners due to the nature of their job, which necessitates that they maintain long-term relationships with their patients for enhanced medication and treatment outcomes (Heston, 2018).
Trust is critical to developing, specifically since patients can experience improve health-related outcomes when they value relationships with their HCPs. Patients who have trust in their HCP often believe that their provider has a high level of competence and truly cares about their health-related outcomes (Heston, 2018). Mistrust develops when the patients attain unrealistic, inconsiderate, or insensitive advice from their HCPs, as well as feel some kind of emotional distance from them.
Importance of Adhering to Medication Regimen
Literacy is the ability to read and understand the different information that is provided to a person. Researchers have and continue to explore the impact of low literacy rates on patient compliance with medication regimens and other health-related advice (Glanz, Rimer, & Viswanath, 2015). An estimated 35% of American adults are considered to possess basic or below basic health literacy. Lacking literacy rates are a global concern and impact an individual’s ability to comprehend and read what is indicated on prescribed medicines or treatment sheets. Health literacy has been considered to be a vital aspect in receiving any kind of service. Health literacy helps diabetic patients comprehend the details of their care or seek further clarification if they do not understand the information (Glanz et al., 2015).
Given inadequate literacy rates, among members of the general population, world practitioners continue to create unique strategies that can be used to reduce lacking health adherence among patients with diabetes. Improved literacy is a theme that should be of the utmost priority, specifically since it creates the foundation for long-term sustained profitability. Furthermore, as patients can understand the importance of medication compliance, adherence to medication regimens improves (Glanz et al., 2015).
Using universally implemented and published resources that can improve medication adherence is important. Tools and resources can be utilized by HCPs to identify patients who are not taking their prescribed medications. Prescriptions need to be taken seriously for exceptional results and for the continued well-being of patients who have critical illnesses like diabetes.
The use of simple language by HCPs, as well as by medication manufacturers, can encourage providers to meet patients where they are and utilize teach-back techniques to ensure a patient’s understanding of his/her prescribed medication regimen. Teach-back methods have been utilized to enhance medication adherence among many types of non-adhering patients. Most of the time people opt to not take their medication as they cannot read all the instructions written on the medicine and are afraid that they will die, especially in the cases that they mistake those drugs for poison or some drug that may look like a famous poison causing death. This is a key issue that has left most of the people victims of non-adherence (National Academies of Sciences, Engineering, and Medicine, 2018).
Reading instructions and making a patient understand what is written on a medicine bottle or package should never be taken for granted as it is key for determining how patients will effectively or ineffectively adhere to the given drugs for treatment and disease control purposes. For the medical practitioner to be aware and sure that what they have explained to the patients has been delivered safely and appropriately, there is the need for a verification test. The patients as well as their identified support individuals need to be asked to explain in their own words stating what they have understood from everything the practitioner has told them regarding their health, along with drug management and intake. This teaching back method is vital in offering additional data on the key topic of interest; thus it should be used often.
Concerns associated with the issues of side effects can be challenges to medication regimen adherence, especially when the given advantages associated with taking the medication are not properly comprehended. To minimize the potential concerns that are associated with the side effects of drugs, since this can be identified as one of the reasons why patients may opt to not adhere to medications in fear that they will experience the side effects and be greatly inconvenienced, there is the need for HCPs to offer the relevant data regarding the common types of side effects when they are in the prescription process.
There have been issues of people and patients dying or experiencing very negative and disturbing side effects when it comes to them taking the medication prescribed by their doctors. These cases have always been used as examples to explain the reason why people have been reluctant to take medications for prolonged periods. When an individual has a critical illness, it is not uncommon that he/she needs to take the prescribed medication for a long period, as this can result in improved medication efficiency. Lacking understanding of medication-related details has caused patients to withdraw from their prescribed medication regimen, which is due to lacking knowledge and prolonged side effect issues that are associated with their medication (Institute of Medicine [IOM], 2016). For example, when offering metformin, to enable adherence to the drug there is a need to inform patients that are suffering from diarrhea during their time of prescription to anticipate that the loose bowel issues will be over in about a week if the drug is continued. It is also vital to offer brief explanations about medication side effects and benefits due to time limitations. If a patient cannot have additional time with his/her provider, then other members of the health care team should aid in answering their questions and provide additional education. Education can be in the form of printed handouts, websites, or a teaching module that should be readily available for use with the identified patient.
In summary, among Americans, the level of medication illiteracy is assumed to be high. This significantly contributes to the difficulties faced by patients when they are required to follow instructions. There is a need for practitioners to take time and educate patients on the right measures to take. Educated patients will have a better understanding of the actions to take, which can positively impact their health-related outcomes.
Tools/Support Strategies for Improving Self-Efficacy and Medication Adherence
Using tools and instruments that are considered effective and appropriate is vital in supporting adherence in different ways and in achieving self-efficacy among the various patients. Positive family and social support are considered to be vital aspects associated with adherence to the issue of diabetes management (Rodríguez-Saldana, 2019). The engagement of family members can enhance self-care activities for patients suffering from diabetes, including eating effective and healthy foods, keeping fit, monitoring blood glucose, and adhering to medication.
A web-based portal is an innovative resource that can be used to assist patients. This web-based portal can improve medication reconciliation processes among patients and providers. The web-based portal can help patients with various regimens navigate challenges. Furthermore, this medication information, available through the portal can help individuals understand medication requirements, as the portal often helps to clarify and verify inaccuracies. The web portal aims to enhance medication adherence and prevent the improved use of the medication (Forman & Shahidullah, 2018).
When patients can verify information in their electronic medical records to ensure proper medication adherence, this can enhance patient well-being. The EMR provides an accurate list of a patient’s medications and provides detailed medication information (e.g., type of drug, what the drug is used to treat, frequency of drug use, etc.). Also, the use of screening tests is vital in understanding how well patients are taking their drugs. If there is no consistency in medication-taking then motivation aspects should be utilized to enhance adherence (Eskola, Waisanen, Viik, & Hyttinen, 2018).
In summary, the simultaneous utilization of tools and instruments plays an essential role in upholding medication adherence. Having a supportive and positive-minded family also plays an essential role in supporting the self-efficacy of the patients. Innovation should be incorporated in searching for medications. This will be advantageous because of the contemporary rapid advancement in technology.
Diabetes Care Concepts
When dealing with patients who are reluctant to take their medications, various care concepts must be understood. Through improving one’s literacy, knowledge about the medication, and offering patient-specific details, enhanced outcomes can occur. Improved medication adherence can result in enhanced patient outcomes, thereby reinforcing positive long-term health-related outcomes. The following themes noted below, provided comprehensive knowledge, as well as in-depth illustrations, about the distinct components associated with clinical control for patients who have been diagnosed with diabetes. The review offers effective clinical practice guidelines, which must be considered, to enhance population health. It is important to note that to ensure identified optimal outcomes (discussed below), individualized patient care is critical.
Patient-Centeredness. Patient-centeredness entails ensuring that all the identified interventions described in the first theme are focused on the individual patient who is being helped to effectively adhere to the given medication during home care settings. Patients who have been diagnosed with various critical illnesses and have been asked to go home for home-based care have been associated with poor adherence to the medications they are given when they are discharged from the hospital (Steinberg & Miller, 2015).
Practice recommendations, whether they are focused on evidence or expert opinion, are intended to offer the desired guidance on an overall approach to care (da Costa, van Mil, & Alvarez-Risco, 2018). The science, as well as the art associated with medicine, usually come together when the identified clinician is experiencing or has experienced some sort of situation whereby, they have to make treatment recommendations for any patient who would be considered to not have effectively met the eligibility criteria for the studies on which the given guidelines were based.
Diabetes Across the Life Span. An increment in the identified proportion associated with patients that suffer from diabetes is usually considered to be mostly adults (Balogh, Miller, & Ball, 2015). For the less salutary reasons, the identified incidences associated with type II diabetes are considered to be highly increasing in the creating in the children as well as the young adults. Patients that possess type II diabetes as well as those that have type I diabetes are considered to have good lives even in their older age, which is regarded as a stage of life whereby there is minimal evidence from the identified clinical traits to be used in the guidance of therapy (Bonney, 2016). All these toes of demographic alterations are usually involved in highlighting another key challenge to high-quality diabetic patient care. In this case, the identified need is usually considered to be the enhancement of the coordination between clinical teams as well as patients in the effective transitioning via the dysfunction phases enticed in life span (Corcora & Roberts, 2015).
Advocacy for Individuals with Diabetes. Advocacy is a vital aspect in healthcare since it addresses the needs of the patient who need the utmost help and care, thereby allowing them to go back to their previous health state (D’Onofrio, Sancarlo, & Greco, 2018). Advocacy is an aspect that can be referred to as active support, as well as engagement, that aims to effectively develop a cause as well as a policy (Mollaoglu, 2018). Furthermore, advocacy is usually needed to enhance the lives of individuals suffering from diabetes. The various issues that diabetic patients experience, such as obesity, physical inactivity, and societal challenges reinforce the need for advocacy (Firstenberg & Stanislaw, 2017).
Summary
The existence of chronic illnesses such as diabetes requires studying affected persons to limit negative events. The proposed intervention techniques should be studied to limit the occurrence of diabetes-related issues like frequent urination, fatigue, and thirst. The issues affect an individual’s capability to function in life. Optimal adherence to prescribed medications can be entailed in the decrement of complications, also enhancing clinical outcomes and saving healthcare-associated costs.
The DPI project has been constructed using careful techniques that promote the development of patient initiatives. The purpose of the project is to ensure that diabetic patient care techniques get applied to enhance the validity of treatment proposals. There are practical solutions to limiting the effects of diabetes, which require careful adherence (Nunes, 2015).
Medication adherence is considered to be the largest challenge that healthcare workers, as well as their patients, are facing in their daily lives. It is often considered to be a critical issue that deserves a higher level of attention. Inspiration along with the act of supporting patients to take their identified medications as prescribed can be a great issue, however, it is considered to possess the capability to possess the highest effect on their identified long term associated health as the well as on the economic well-being regarding the healthcare system of the nation.
Two theories will be used to guide this direct practice improvement project, which includes: the attachment theory and the SCT. The identified theories point to the possibility of solving the problem of poor medication taking behaviors through the use of attachment and social learning. The theories reveal that medication taking is learned and can be enhanced through the use of cognitive behavior change.
The empirical review points to the complications caused by lack of medication adherence in diabetes patients. It also highlights possible ways in which health care providers can help patients better adhere to medication through strategies such as advocacy and patient-centeredness. Overall, medication adherence is important to the treatment and effective management of diabetes in patients, and health care providers can play a vital role in ensuring that diabetes patients learn the importance of adherence.
Chapter 3: Methodology
Medication adherence is a critical aspect in minimizing the impact of negative patient-related outcomes among those with chronic illnesses. According to Ahmed et al. (2018), medication adherence, for the purpose of this practice improvement project, refers to the extent to which a home-based care patient can correctly take his/her medication in the absence of health practitioners. Medication adherence requires the patient to adhere and comply with all the medical instructions given (Bellou et al., 2018). Ahmed et al. (2018) noted that diabetes impacts one in ten Americans. Furthermore, the prevalence of diabetes continues to rise and is projected to increase each year by 0.3% by 2030 (Lin et al., 2018). There are two types of diabetes that plague a large proportion of Americans: type I diabetes, which is insulin-dependent, and type II diabetes, which is glucose related (Bellou et al., 2018). There are ways to curtail the onset of type II diabetes; however, once individuals are diagnosed with diabetes, there is no cure (Bellou et al., 2018).
This chapter’s purpose aims to determine if the implementation of the MAP resources, which will be delivered by home healthcare nursing staff members, will impact medication adherence.
The chapter is organized into sections. Chapter 3 details information about the methodology that will be used during this project. Information about the project’s design, selection of the sample, instrumentation, validity, and reliability are presented. Additionally, data collection procedures, data analysis procedures, ethical considerations, and limitations are included in this chapter.
Statement of the Problem
It is not known if or to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List, will impact medication adherence among type II diabetic home healthcare patients, ages 35 to 64 of a home healthcare organization located in urban Texas over a period of four weeks. At the selected project site, which is a home healthcare organization located in urban Texas, the stakeholders have cited that medication adherence among diabetic patients is lacking. In fact, according to data obtained from the site’s EHR, home healthcare providers have documented that 10% of diabetic home healthcare patients are not adhering to their medication regimen. At the project site, failure to adhere to the prescribed medication regimen has resulted in the limited capability to deal with diabetes related issues. Various researchers have noted the implications associated with lacking adherence to medication regimens, specifically among diabetic patients, thereby reinforcing the need for this practice improvement project (Ahmed et al., 2018).
Clinical Question
Prior studies have demonstrated that medication adherence among home-based care patients is lacking. Researchers have explained that medication non-adherence is often due to a variety of factors, which include lack of knowledge, trust, fear, and inadequate monitoring. Wolff-Baker and Ordona (2019) noted that there is usually nobody to remind patients to take medication the right way. Furthermore, many patients do not understand the importance of medication adherence, which is another issue that healthcare providers can aid patients in overcoming. The clinical question that will guide this direct practice improvement project is:
Q1: Does using the MAP resources improve medication adherence among home health diabetic patients?
Many researchers have explored ways to improve medication adherence among patients. To enhance medication adherence among home healthcare diabetic patients, a quantitative, quasi-experimental design approach will be utilized. Specifically, the PI will utilize the MAP Toolkit and Training Guide resources, which include: (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List.
The PI will evaluate how the use of the newly implemented MAP protocol contributes to medication adherence among patients over four weeks. Using the project site’s EHR, pre-project data will be analyzed from April 1, 2021 to April 30, 2021. The purpose of examining this pre-implementation project data is to determine if or to what degree the implementation of Medication Adherence Project resources may enhance medication adherence. Medication adherence among type II diabetic home healthcare patients, ages 35 to 64, will be explored by comparing pre-project implementation data to post-project implementation data. Currently, nursing staff members, of the selected project site, assess medication adherence by conducting interviews.
Unfortunately, the method of assessing medication adherence differs among nursing staff members. Furthermore, no tools or resources that are highly cited and/or evidence-based are utilized to assess medication adherence. Since there is no site-specific patient protocol developed or utilized to encourage medication adherence among patients, this project is necessary to ensure process standardization and to ensure that any patient-specific medication adherence barriers are properly addressed.
Medication adherence, which is the dependent variable explored in this project, will be measured using data attained through the project site’s EHR. The MAP resources, which serve as the independent variables explored in this project, include (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List.
Table 1
Characteristics of Variables
| Variable | Variable Type | Level of Measurement |
| MAP Resources | Independent | Nominal |
| Medication Adherence | Dependent | Nominal |
Project Methodology
A quantitative methodology is appropriate for this project because of the clinical question being answered. According to Fain (2017), this research methodology focuses on objective measurements and analyzes the data collected through statistical, numerical, or mathematical analyses. Quantitative methodology also uses computational techniques to manipulate pre-existing statistical data. Usually, it is applied to test if certain theories and assumptions are true or false. According to Zaccagnini and Pechacek (2019), the two important foundational aspects of projects that use quantitative methodology are that they build on results and evidence from past research and that they usually form the basis for future research.
Specifically, the PI plans to analyze the impact of the change initiative pre-and post-project implementation, in which data from the project site’s EHR will be obtained. The project site data, about medication adherence, is quantifiable and objective data that is related to the clinical question and PICO question being explored during this project. To assess the impact of the intervention, numerical data will be analyzed using statistical analyses.
A quantitative methodology is the preferred methodology to utilize for this project, as compared to a qualitative methodology because compliance with medication adherence will be analyzed. If the PI wanted to learn more about common themes or issues impacting medication non-adherence, then a qualitative methodology, using interviews or focus groups, may have been utilized. Qualitative methods do not allow for numerical data to be compared. For this project, numerical data will be collected pre-and post-project implementation. All numerical results will be analyzed using statistical methods to explore the impact of the MAP resources. Based upon the data results, project-related conclusions will be made.
Project Design
This quality improvement project will use a quasi-experimental design as the principal evaluation method (Handley, Lyles, McCulloch, & Cattamanchi, 2018). The purpose of a quasi-experimental design is to compare data pre-and post-project implementation to explore the impact of a specific intervention. For this project, the impact of MAP resources as compared to current practice at the project site will be assessed. The PI will determine if the implementation of the intervention improved medication adherence among diabetic patients.
Since this project aims are to compare current practice versus the implementation of this project on enhancing medication adherence, numerical data will be collected and analyzed. Demographic data will also be collected during this project, which will be extracted from the project site’s EHR. Specifically, information about the gender and age of each participant will be attained. At the project site, there are 100 patients of which 30 have been diagnosed with type II diabetes. Using a G*power analysis, helps to determine the sample size for the study, which will help with the probability of detecting a “true” effect of comparing two different diets, A and B, for diabetic patients. Therefore, a minimum sample of 20 participants will involve in this project to ensure constancy of program design, implementation, and evaluation. It is important to note that although 30 of the patients, at the project site, have been diagnosed with type II diabetes, not all potential participants will meet the eligibility criteria. As previously noted, type II diabetes home healthcare patients must be between the ages of 35 to 64 and must not have any cognitive issues that would impair them from partaking in this project.
Pre-project implementation data and post-project implementation data, which will be reported in the EHR, by nursing staff members of the selected project site, will be analyzed. SPSS version 25 will be utilized to determine the impact of the intervention in improving medication adherence among patients. Given the benefits of the MAP resources, in enhancing medication adherence, it is the hope of the PI that medication adherence will be improved at the selected project site.
Population and Sample Selection
The term population reflects that main group of focus that possesses similar characteristics or traits. Therefore, the population for this project is type II diabetes patients who receive care through home healthcare organizations. Since the PI cannot incorporate the involvement of all type II diabetes patients who receive care through home healthcare organizations, throughout the world, the PI is therefore relying on a select sample. A sample refers to a subset of the population. The sample is type II diabetes patients of a home healthcare organization that is located in urban Texas.
The PI will use a non-probability sampling technique to carry out this project. Specifically, a convenience sample will be used because of ease of access to this particular group of individuals. The purpose of convenience sampling is to obtain information about the population of interest through accessing individuals who are easy to reach. Home healthcare patients, of the selected project site, will comprise the project’s sample.
Individuals who are eligible to participate in this project must meet the following criteria: (1) have a type II diabetes diagnosis, (2) be between the ages of 35 to 64, (3) be cognitively capable of engaging in this project (i.e., no mental impairments), and (4) be a home healthcare patient of the selected project site. According to a Texas Medicaid and Texas Diabetes Council report (2020), which provides the most up-to-date information about hospital claims from diabetes patients in 2019, 82,708 outpatient hospital claims were made by diabetes patients. Furthermore, 193,551 professional claims were made by Medicaid clients in 2019 (Texas Diabetes Council, 2020). The information reported by the Texas Diabetes Council (2020) is significant because it reinforces the prevalence of diabetes in the state of Texas where this project is to be carried out.
According to a study by the United Health Foundation (2019), the prevalence of diabetes among residents of Texas continues to increase. In the United States, according to the CDC (2019), approximately 10.7% of adult females have diabetes. In the state of Texas, 11.5% of females have diabetes. Furthermore, the prevalence of diabetes among U.S. males is 11.4%, while the prevalence of diabetes among Texan males is 13.0% (CDC, 2019). These findings reinforce the higher prevalence of diabetes among Texas residents.
At the selected project site, which provides home healthcare to 100 individuals, approximately 30% have a type II diabetes diagnosis. Of those individuals with a type II diabetes diagnosis 66% likely meet the inclusion criteria for participating in this project. As noted above, to determine the estimated sample size needed to encourage statistical significance, a power analysis was conducted. Based upon the effect size, the sample size, and the variability, it was determined that the ideal sample size for this project is 20, this relates to the G*power participants.
Sources of Data
The tools utilized in this project, which are from Starr and Sacks’s (2010) MAP Toolkit and Training Guide resources, include: (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List. The first MAP tool that will be utilized is the Questions to Ask Poster. The Questions to Ask Poster is a tool that encourages patients to ask providers about their medication(s). The Questions to Ask Poster will be presented by home health nursing staff members and will be reviewed with type II diabetes patients. Home health nursing staff members will address all of the six questions on this poster, which include: (1) “Why do I need to take this medicine?,” (2) “Is there a less expensive medicine that would work as well?,” (3) “What are the side-effects and how can I deal with them?,” (4) “Can I stop taking any of my other medicines?,” (5) “Is it okay to take my medicine with over-the-counter drugs, herbs, or vitamins?,” and (6) “How can I remember to take my medicine?”
When barriers associated with medication adherence are addressed, in terms of knowledge, expenses, side effects, etc., patients typically feel more empowered. Furthermore, according to Starr and Sacks (2010), it is not uncommon for patients to feel surprised that they can ask these questions. The researchers noted that the Questions to Ask Poster aided individuals in feeling empowered, provided them with a list of questions that they normally would not ask, gave patients an idea of how to ask certain questions and what questions would be meaningful to them, and provided patient relief (Staff & Sack, 2010).
After discussing information and addressing all of the questions on the Questions to Ask Poster, the Adherence Assessment Pad will be given to all patients. The Adherence Assessment Pad explores answers to the following question, “What gets in the way of taking your medicine(s)?” The questions on the Adherence Assessment Pad include: (1) Makes me feel sick, (2) I cannot remember, (3) Too many pills, (4) Costs, (5) Nothing, and (6) Other. Nursing staff members will be asked to assume that individuals are not properly taking their medication. Through making this assumption, nurses can gain stronger insight into barriers that impact patients. For example, if cost-related concerns were denoted by the patient, then the nurse would likely go back to the patient’s primary care provider (PCP) and discuss why costs are impacting medication adherence. The process of exploring individual concerns with the patient’s care team can result in collaboration and enhanced patient-related outcomes.
It is important to note that if individuals cannot remember to take their medication, appropriate resources will be provided. According to Starr and Sacks (2010), “The question encourages truthful discourse, validates a positive response” (p. 16). Through encouraging truthfulness, individuals will feel empowered to express their concerns, which will allow for resources to be offered as appropriate based upon the patient’s concerns.
The final tool that will be utilized is the My Medications List. The My Medications List details information, in chart form, which will be discussed by the nursing staff member and patients. The purpose of the My Medications List is to encourage medication adherence among patients. The nursing staff provider and patients will discuss all of the categories in the chart, which include: (1) Name and Doses of My Medicine, (2) This Medication is for My Diabetes, (3) When Do I Take and How Much [options include: morning, noon, evening, and bedtime], and (4) I Will Remember to Take My Medicine _____ [note: the blank will be filled in]. It can be time-consuming to fill out this list, but it’s important to note that likely, once the patient and the provider work on the list together, patients will buy into the chart requirements and, therefore, improve their medication adherence. After filling out this chart, unless modifications are needed, subsequent visits will not require the chart to be filled out again.
In addition to the aforementioned instruments that will be utilized, it is important to note that information from the project site’s EHR will be collected. As mentioned above, pre-and post-project implementation data will be collected and analyze to determine the impact of the MAP intervention. Specifically, the PI will examine medication adherence rates from April 1, 2021 to April 30, 2021 to determine adherence rates before the project was implemented and four weeks after the project’s implementation.
Validity
There are various types of validity which include face validity, content validity, criterion validity, and discriminant validity. In terms of the MAP toolkit, the resources that are utilized, at face value, explore the topic of interest. For example, the researchers noted the instrument had strong validity in terms of attaining detailed feedback from participants regarding their lacking adherence to their prescribed medication regimen. The statements that were asked of participants, using the MAP resources, had good face validity and seek to encourage adherence to one’s medication regimen.
It is important to note that from 2007 to 2009, the MAP project was developed and included a group of professionals from the Fund for Public Health in New York and the New York City Department of Public Health and Mental Hygiene. The professionals developed and implemented a training course and toolkit, based upon years of experience. Professionals who were involved in this effort included physicians, pharmacists, nurses, medical assistance, nutritionist, social workers, and health workers (Starr & Sacks, 2010). In addition to making improvements from 2008 to 2010, when the study was published, about ways to strengthen the toolkit’s content, expert guidance and support were offered from key stakeholders who are knowledgeable in their field. Based upon expert feedback, modifications to the MAP toolkit were made (Starr & Sacks, 2010). The recommendation set forth, in terms of toolkit improvements, are aligned with best practices noted by the CDC and other healthcare governing bodies.
Reliability
The reliability of the instrument refers to its consistency of a measure. Often times three different types of consistency are explored, which include inter-rater reliability, internal consistency, and test-retest reliability. For the purpose of the MAP toolkit, inter-rater reliability was confirmed (Starr & Sacks, 2010). Observers noted the same benefits associated with utilizing the instrument, which was aligned with the findings in the literature about the processes associated with collecting information concerning medication adherence.
Over time, researchers have utilized the MAP toolkit and noted its benefits. In fact, in a study published by Harrell (2017), which was conducted over 90 days, weekly medication adherence rates were assessed. Before the implementation of the study, Harrell (2017) cited that 78% of patients did not adhere to their prescribed medication regimen. After the three-month implementation of this project, 56% of patients (those who originally cited lacking adherence rates) noted improved medication adherence, thereby reinforcing the benefits of this toolkit.
Data Collection Procedures
After obtaining approval from Grand Canyon University’s Institutional Review Board, the PI will reach out to the administrator and the Director of Nursing at the project site who will assist in scheduling a time for the educational training sessions to take place. Ideally, these training sessions will be offered twice, so nursing staff members who work on weekends will be able to participate. Once ideal times are determined, two face-to-face training sessions will be conducted. During these training sessions, the PI will provide information about current medication adherence rates at the selected project site and will compare these rates to the national average. Then, the PI will explain details about the MAP resources. The PI will use a PowerPoint presentation to conduct this training, which will be provided to participants. In addition to providing participants with the PowerPoint slides, the PI will also insert all relevant MAP resource information into a binder. All training participants, upon the completion of the training, will have a binder to take with them.
The PI will also work with the Information Technology Department, at the project site, to ensure that the three MAP resources, which will be utilized during this project, are input into the site’s EHR. Over four weeks, nursing staff members, who engaged in the educational training session, will be required to utilize the MAP resources. As noted above, the MAP resources, at first, will take a bit longer to complete, specifically since the following resources need to be explored during Week 1: (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List. Furthermore, since providers will be educating individuals about their medication adherence (i.e., using the Questions to Ask Poster) and will be exploring barriers associated with medication adherence (i.e., using an Adherence Assessment Pad), this initial phase, during Week 1, will be time-consuming. In subsequent weeks (Weeks 2-4), unless a huge revision is made to one’s My Medications List, then the process of examining medication adherence and answer questions will take no longer than ten minutes.
Each week, nursing staff members will record medication adherence information in the patient’s EHR. If the patient expresses that he/she has not adhered to the medication regiment, during the previous week, lacking adherence information will be recorded in the system. Upon the completion of the four-week project, all information, input by nursing staff members into the EHR, will be assessed. The PI will compare pre-project implementation medication adherence rates to post-project implementation medication adherence rates. In addition to exploring medication adherence rates after the implementation of this project, pre-project implementation adherence rates will be explored over four weeks from April 1, 2021 to April 30, 2021.
Once pre-project implementation data and post-project implementation data are obtained, the results will be statistically analyzed. The PI will work with a statistician, who will assist in the data analysis process. Data will be compared analyze using various statistical techniques. For more about data analysis procedures, explore the heading below.
Data Analysis Procedures
For this project, data will be analyzed to explore if medication adherence improved among type II diabetic patients after the implementation of the MAP resources. The collected data, pre-and post-project implementation, will be inserted into a Microsoft Excel document, which will be provided to the PI by ___who____. Once information is inserted into the Microsoft Excel spreadsheet, missing data, if applicable, will be coded or excluded, depending on the recommendation set forth by the PI’s statistician. The Microsoft Excel spreadsheet will then be imported into SPSS version 28.
For this project, data will be analyzed to explore if medication adherence improved among type II diabetic patients after the implementation of the MAP resources. The collected data, pre-and post-project implementation, will be inserted into a Microsoft Excel document, which will be provided to the PI by the secretary. Once information is inserted into the Microsoft Excel spreadsheet, missing data, if applicable, will be coded or excluded, depending on the recommendation set forth by the PI’s statistician. The Microsoft Excel spreadsheet will then be imported into SPSS version 28.
To explore the impact of the MAP resources on improving medication adherence, a t-test will be used. For this project, data will be provided in written format, as well as in tables and figures. It is important to note that descriptive statistics will be used to measure central tendency and standard deviations across the variable groups. T-test will be used to compare the means between the two groups. The two groups that will be explored in this project are the pre-project implementation group and the post-project implementation group. It is important to note that demographic data will also be explored to determine if certain demographic variables impact medication adherence rates. A p-value of 0.05 will be used to determine statistical significance.
Potential Bias and Mitigation
There is a number of sources of potential bias that may exist throughout this project. While biases are present in most projects, it is important to formulate a proactive solution about how to mitigate biases. One potential source of bias is recall bias, which references what happens when a person self-reports information. Sometimes, self-reporting surveys are inaccurate, as patients do not feel comfortable reporting the truth or forget valuable details.
For the purpose of this project, diabetic patients will be required to respond to MAP resources, which address information about medication adherence. Based on the patient’s memory, the information may or may not be accurate. To improve the accuracy of the data obtained, the nursing staff members will encourage patients to fill out documents (as appropriate) daily and to determine a set time to report information in these documents.
Ethical Considerations
An authorization letter has been obtained from the project site (Appendix B). The project has also been submitted to the project site for Institutional Review Board (IRB) exemption approval (Appendix B). The project will be submitted to Grand Canyon University’s IRB for review (Appendix B).
Before this project is conducted, the PI will attain permission from the project site’s IRB and GCU’s IRB. Once permission is obtained, the project will begin. There are two groups of project participants who will engage in this project. The first group of participants is home healthcare nurses of the selected project site. Considering the support by the project site, for this initiative, all nursing staff members will be asked to implement the newly implemented processes when interacting with eligible participants. Therefore, participation among nursing staff members is not voluntary as this is a sitewide effort, which is supported by organizational stakeholders. The other group involved in this project includes patient participants. Nursing staff members will provide patient participants with information about all aspects of the project.
Three MAP resources will be used during this project. The purpose of using these three resources is to provide patient-specific training and details about medication adherence. All attained data will be gathered by nursing staff members, whether in written or verbal then transcribed form, and will be entered into the patient’s EHR. Considering that the EHR is only available to individuals of the selected project site, who have an account and password, no unique identifiers will be used. Paper-based questionnaire information and verbal notes, from patient-provider interactions, will be input into the EHR by the end of the provider’s shift.
Data will be extracted from the EHR, after the four-week project timeline, by the PI. It is important to note that the data files, which will be presented to the PI pre-and post-project implementation, will not include any patient identifiers. For example, only relevant project-related data will be attained, which is related to the patient’s age, race, and gender. Furthermore, data regarding medication adherence among type II patients will be obtained. The data files, which will be sent to the PI via email, will be encrypted. Furthermore, the data files will only be accessible to the PI using her work computer. Aggregate data will only be shared, as needed, with individuals who are directly impacted by the project’s implementation (e.g., organizational stakeholders and nursing staff members).
All project-related data will be maintained by the PI for a period of three years, which is aligned with the requirements set forth by GCU’s IRB. After the three-year timeframe is over, the PI will dispose of project-related data. The PI’s work computer will be scrubbed of these data files.
Limitations
There are several limitations to this project, which must be explored. First, it is important to note that the project’s timeframe is short. Due to this four-week timeframe, it might be difficult to assess the true impact of the intervention. The second limitation is that the sample size set for this research project is also relatively small. In March of 2021, the home healthcare system serviced approximately 100 patients of which 30 were diagnosed with type II diabetes. While the sample size as relevant to the project site’s patient population is large, given the overall sample size (n = 30), it may be difficult to generalize the results of this project.
It is important to note the only patients who will engage in this project are those who have been diagnosed with type II diabetes and are between the ages of 34 to 65, thereby further limiting the project’s sample. While there is much merit in utilizing the MAP tools, the overarching effectiveness of this tool might be difficult to determine given eligibility requirements
This project is also limited by the data collection technique that will be used. For example, since a lot of the data gathered is self-reported, patients may overinflate information about medication adherence. If incorrect information is provided by patients the project’s overall results will be impacted (Brown, Kaiser, & Allison, 2018).
Delimitations
The study had the following Delimitations:
- Due to convenience and university policies, there will be a small sample size of 20 participants. The consequence is that, it might negatively influence the transferability of study findings because of limited participants (Hesse et al., 2019). To minimize the impact of the small sample size I will attempt to reach saturation when no new topics are arising in new interviews.
- The participants that will be included in this study were healthcare providers at the project site. As a result, this study did not involve healthcare providers from other parts of the city. The consequence is that it might not be transferable. To minimize this the participants, their work environment will be described to allow readers to assess if the findings transfer to their context.
Summary
Medication adherence among patients with diabetes remains a crucial determiner of their well-being. The purpose of this quantitative quasi-experimental project is to determine if or to what degree the implementation of MAP resources, which include (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List impact MA among type II diabetic home healthcare patients, ages 35 to 64, at a home healthcare organization located in urban Texas over four weeks. The project’s design will explore the impact of the MAP resources on improving medication adherence among type II patients. As noted above, the validity and reliability of the MAP resources have been established.
Medication adherence rates will be collected before the implementation of the intervention and after the implementation of the intervention. An analysis of the two sets of data will be used to determine the impact of the independent variables on the dependent variable. The data gathered will be compiled in an Excel spreadsheet and transferred to SPSS for analysis.
To ensure that ethical research standards are upheld, the PI will comply with the standards set forth by GCU’s IRB. Participant anonymity and privacy will be maintained. This project is limited by several factors, which include a small sample size, the short project timeframe, and the use of self-reporting data regarding medication adherence.
In Chapter 4, project results will be presented. Information in Chapter 4 will be presented in a written and visual format. Chapter 5 will provide project-related recommendations based upon the data analyzed and will offer details about limitations.
References
Ahmed, I., Ahmad, N. S., Ali, S., Ali, S., George, A., Danish, H. S., … Darzi, A. (2018). Medication adherence apps: Review and content analysis. JMIR mHealth and uHealth, 6(3), e62. Retrieved from https://mhealth.jmir.org/2018/3/e62/
American Medication Association. (2020, December 2). 8 reasons patients don’t take their medications. Retrieved from https://www.ama-assn.org/delivering-care/patient-support-advocacy/8-reasons-patients-dont-take-their-medications
America’s Health Rankings. (2020). Diabetes. Retrieved from https://www.americashealthrankings.org/explore/annual/measure/Diabetes/state/TX
Balogh, E. P., Miller, B. T. M., & Ball, J. R. (2015). Improving diagnosis in health care. Retrieved from https://www.worldcat.org/title/improving-diagnosis-in-health-care/oclc/1001623571
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
Bellou, V., Belbasis, L., Tzoulaki, I., & Evangelou, E. (2018). Risk factors for type 2 diabetes mellitus: An exposure-wide umbrella review of meta-analyses. PLoS ONE, 13(3). doi:10.1371/journal.pone.0194127
Bowlby, J. (1958). The nature of the childs tie to his mother. International Journal of Psychoanalysis, 39, 350-371.
Bonney, W. (2016). Mobile health technologies – Theories and applications. Retrieved from https://www.worldcat.org/title/mobile-health-technologies-theories-and-applications/oclc/965915046
Bosworth, H. B. (2015). Enhancing medication adherence: The public health dilemma. Philadelphia, PA: Springer Healthcare.
Bretherton, I. (1992). The origins of attachment theory: John Bowlby and Mary Ainsworth. Development Psychology, 28(5), 759-775.
Brown, A. W., Kaiser, K. A., & Allison, D. B. (2018). Issues with data and analyses: Errors, underlying themes, and potential solutions. Proceedings of the National Academy of Sciences of the United States of America, 115(11), 2563-2570. https://doi.org/10.1073/pnas.1708279115
Brown, M. T., & Bussell, J. K. (2011). Medication adherence: WHO Cares? Mayo Clinic Proceedings, 86(4), 304-314. Retrieved from https://doi.org/10.4065/mcp.2010.0575
Bryant, B. (2018, December 12). Home care remains seniors’ preference, but alternatives gaining steam. Home Health Care News. Retrieved from https://homehealthcarenews.com/2018/12/home-care-remains-seniors-preference-but-alternatives-gaining-steam/
Bussell, J. K., Cha, E. S., Grant, Y. E., Schwartz, D. D., & Young, L. A. (2017). Ways health care providers can promote better medication adherence. Clinical Diabetes, 35(3), 171-177.
Camacho, G., Kalichman, S., & Katner, H. (2019). Anticipated HIV-related stigma and HIV treatment adherence: The indirect effect of medication concerns. AIDS and Behavior, 24, 185-191.
Centers for Disease Control and Prevention. (2020). National diabetes statistics report, 2020. Retrieved from https://www.cdc.gov/diabetes/library/features/diabetes-stat-report.html#:~:text=34.2%20million%20Americans%E2%80%94just%20over,1%20in%203%E2%80%94have%20prediabetes.
Choi, D., Choi, H., & Shon, D. (2019). Future changes to smart home based on AAL healthcare service. Journal of Asian Architecture and Building Engineering, 18(3), 190-199.
Choo, P. W., Rand, C. S., Inui, T. S., Lee, M. L., Canning, C., & Platt, R. (2001). A cohort study of possible risk factors for over-reporting of antihypertensive adherence. BMC Cardiovascular Disorders, 1(6).
Corcoran, K., & Roberts, A. R. (2015). Social workers’ desk reference (3rd ed.). England: Oxford University Press.
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Newbury Park, CA: SAGE Publications, Inc.
da Costa, F. A., van Mil, J. W. F., & Alvarez-Risco, A. (2018). The pharmacist guide to implementing pharmaceutical care. Switzerland: Springer International Publishing.
D’Onofrio, G., Sancarlo, D., & Greco, A. (2018). Gerontology. London, England: InTech Open Limited.
Eskola, H., Waisanen, O., Viik, J., & Hyttinen, J. (2018). EMBEC & NBC 2017: Joint Conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC), Tampere, Finland, June 2017. Singapore: Springer International Publishing.
Fain, J. A. (2020). Reading, understanding, and applying nursing research (5th ed.). Philadelphia, PA: FA Davis Co.
Firstenberg, M., & Stanislaw, P. S. (2017). Vignettes in patient safety – Volume 1. London, England: InTech Open.
Forman, S. G., & Shahidullah, J. (2018). Handbook of pediatric behavioral healthcare: An interdisciplinary collaborative approach. Switzerland: Springer International Publishing.
Francis, H. M., Osborne-Crowley, K., & McDonald, S. (2017). Validity and reliability of a questionnaire to assess social skills in traumatic brain injury: A preliminary study. Brain Injury, 31(3), 336-343.
Glanz, K., Rimer, B. K., & Viswanath, K. (2015). Health behavior: Theory, research, and practice (5th ed.). San Francisco, CA: Jossey-Bass.
Hadler, A., Sutton, S., & Osterberg, L. (2020). The Wiley Handbook of healthcare treatment engagement: Theory, research, and clinical practice. Hoboken, NJ: John Wiley & Sons, Inc.
Hamrahian, S. M. (2020). Medication non-adherence: A major cause of resistant hypertension. Current Cariology Reports, 22. Retrieved from https://link.springer.com/article/10.1007/s11886-020-01400-3
Handley, M. A., Lyles, C. R., McCulloch, C., & Cattamanchi, A. (2018). Selecting and improving quasi-experimental designs in effectiveness and implementation research. Annual Review of Public Health, 39, 5-25. Retrieved from https://www.annualreviews.org/doi/abs/10.1146/annurev-publhealth-040617-014128
Heath, S. (2018). How health coaching improves medication adherence, chronic care. Patient Access Care News. Retrieved from https://patientengagementhit.com/news/how-health-coaching-improves-medication-adherence-chronic-care
Heston, T. F. (2018). Ehealth: Making health care smarter. London, England: InTech Open Limited.
Holecki, T., Romaniuk, P., Woźniak-Holecka, J., Szromek, A. R., & Syrkiewicz-Świtała, M. (2018). Mapping health needs to support health system management in Poland. Frontiers in Public Health, 6, 82. https://doi.org/10.3389/fpubh.2018.00082
Holly, R. (2020, January 6). The top home health trends of 2020. Home Health Care News. Retrieved from https://homehealthcarenews.com/2020/01/the-top-home-health-trends-of-2020%EF%BB%BF/
Hunter, J., & Maunder, R. (2016). Improving patient treatment with attachment theory: A guide for primary care practitioners and specialists. Switzerland: Springer International Publishing.
Institute of Medicine (U.S.). (2016). A framework for educating health professionals to address the social determinants of health. Washington, DC: The National Academies Press.
Jajarmi, A., Ghanbari, B., & Baleanu, D. (2019). A new and efficient numerical method for the fractional modeling and optimal control of diabetes and tuberculosis co-existence. Chaos, 29(9).
Kleinsinger, F. (2018). The unmet challenge of medication nonadherence. The Permante Journal, 22, 18-33.
Kvarnström, K., Airaksinen, M., & Liira, H. (2017). Barriers and facilitators to medication adherence: A qualitative study with general practitioners. BMJ Open, 8(1). doi:10.1136/ bmjopen-2016-015332
Leedy, P., & Ormrod, J. (2013). Practical research: Planning and design (11th ed.). Upper Saddle River, NJ: Pearson/Merrill Prentice Hall.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Newbury Park, CA: SAGE Publications, Inc.
Lin, J., Thompson, T. J., Cheng, Y. J., Zhuo, X., Zang, P., Gregg, E., & Rolka, D. R. (2018). Projection of the future diabetes burden in the United States through 2060. Population Health Metrics, 16(9). https://doi.org/10.1186/s12963-018-0166-4
Liu, M., & Butler, L. M. (2016). Patient communication for pharmacy: A case-study approach on theory and practice (1st ed.). Burlington, MA: Jones & Bartlett Learning.
Misquitta, C. (2020, December 11). Three challenges in medication adherence that can be overcome by pharmacists. Pharmacy Times. Retrieved from https://www.pharmacytimes.com/view/three-challenges-in-medication-adherence-that-can-be-overcome-by-pharmacists
Mollaoglu, M. (2018). Caregiving and home care. London, England: InTech Open Limited.
National Academies of Sciences, Engineering, and Medicine (U.S.). Committee on National Health Care Utilization and Adults with Diabetes. (2018). Health-care utilization as a proxy in disability determination. Washington, DC: The National Academies Press.
Nunes, K. (2015). Major topics in type 1 diabetes. London, England: InTech Open Limited.
Ong, S. E., Koh, J. J. K., Toh, S. A. E., Chia, K. S., Balabanova, D., McKee, M., … Legido-Quigley, H. (2018). Assessing the influence of health systems on Type 2 Diabetes Mellitus awareness, treatment, adherence, and control: A systematic review. PLoS One, 13(3). https://doi.org/10.1371/journal.pone.0195086
Polonsky, W. H., & Henry, R. R. (2016). Poor medication adherence in type 2 diabetes: recognizing the scope of the problem and its key contributors. Patient Preference and Adherence, 10, 1299-1307. https://doi.org/10.2147/PPA.S106821
Price, P. C., Jhangiani, R., Chiang, I. C. A., Leighton, D. C., & Cuttler, C. (2017). Research methods in psychology (3rd ed.). Open Book Publishing. Retrieved from https://opentext.wsu.edu/carriecuttler/
Raoufi, A. M., Tang, X., Jing, Z., Zang, X., Xu, Q., & Zhou, C. (2018). Blood glucose monitoring and diabetic patients: A cross-sectional study in Shandong, China. Diabetes Therapy, 9, 2055-2066.
Rathish, D., Hemachandra, R., Premadasa, T., Ramanake, S., Rasangika, C., Roshiban, R., & Jayasumana, C. (2019). Comparison of medication adherence between type 2 diabetes mellitus patients who pay for their medications and those who receive it free: A rural Asian experience. Journal of Health, Population, and Nutrition, 38(1), 4.
Rodríguez-Saldana, J. (2019). The diabetes textbook: Clinical principles, patient management and public health issues. Switzerland: Springer International Publishing.
Schweizer, M. L., Braun, B. I., & Milstone, A. M. (2016). Research methods in healthcare epidemiology and antimicrobial stewardship – Quasi-experimental designs. Infection Control and Hospital Epidemiology, 37(10), 1135-1140. https://doi.org/10.1017/ice.2016.117
Sharma, S. K., Ravi, K., Sanjay, K., & Bishnoi, R. (2020). Prevalence of primary non-adherence with insulin and barriers to insulin initiation in patients with type 2 diabetes mellitus – An exploratory study in a tertiary care teaching public hospital. European Endocrinology, 16(2), 143-147.
Singletary, M. (2019). For seniors hoping to age in place, the cost of in-home care just got a lot more expensive. Washington Post. Retrieved from https://www.washingtonpost.com/business/personal-finance/for-seniors-hoping-to-age-in-place-the-cost-of-in-home-care-just-got-a-lot-more-expensive/2019/10/29/7f9b63a4-fa4c-11e9-8190-6be4deb56e01_story.html
Starr, B., & Sacks, R. (2010). Improving outcomes for patients with chronic diseases: The Medication Adherence Project (MAP). NYC Health. Retrieved from https://www.hfproviders.org/documents/root/pdf_9a3a46fa03.pdf
Steinberg, M. P., & Miller, W. R. (2015). Motivational interviewing in diabetes care (3rd ed.). New York, NY: Guilford Press.
Szanton, S. L., Leff, B., Wolff, J. L., Roberts, L., & Gitlin, L. A. (2016). Home-based care program reduces disability and promotes aging in place. Health Affairs, 35(9).
Tedla, Y. G., & Bautista, L. E. (2017). Factors associated with false-positive self-reported adherence to antihypertensive drugs. Journal of Human Hypertension, 31(5), 320-326.
Texas Health and Human Services. (2017). Texas Medicaid and Texas Diabetes Council Coordination. Retrieved from https://hhs.texas.gov/reports/2018/09/texas-medicaid-texas-diabetes-council-coordination
Verloo, H., Chiolero, A., Kiszio, B., Kampel, T., & Santschi, V. (2017). Nurse interventions to improve medication adherence among discharged older adults: A systematic review. Age and Aging, 46(5), 747-754.
Voortman, T., Kiefte-de Jong, J., Ikram, M. A., Stricker, B. H., van Rooij, F. J. A., Lahousse, L., … Schoufour, J. D. (2017). Adherence to the 2015 Dutch dietary guidelines and risk of non-communicable diseases and mortality in the Rotterdam Study. European Journal of Epidemiology, 32(11), 993-1005. https://doi.org/10.1007/s10654-017-0295-2
Watson, R. (2015). Quantitative research. Nursing Standard, 29(31) 44-48.
Wolff-Baker, D., & Ordona, R. B. (2019). The expanding role of nurse practitioners in home-based primary care: Opportunities and challenges. Journal of Gerontological Nursing, 45(6), 9-14. doi:10.3928/00989134-20190422-01
Wong, Z. S., Siy, B., Lopes, K. S., & Georgiou, A. (2020). Improving patients’ medication adherence and outcomes in nonhospital settings through eHealth: Systematic review of randomized controlled trials. Journal of Medical Internet Research, 22(8). doi:10.2196/17015.
Wood, B. (2012, April 23). Medication adherence: The real problem when treating chronic conditions. U.S. Pharmacist. Retrieved from https://www.uspharmacist.com/article/medication-adherence-the-real-problem-when-treating-chronic-conditions
Zaccagnini, M., & Pechacek, J. M. (2019). The Doctor of Nursing practice essentials: A new model for advanced practice nursing (4th ed.). Burlington, MA: Jones & Bartlett Learning.
Appendix A
10 Strategic Points
| The 10 Strategic Points | |
| Broad Topic Area | 1. Broad Topic Area/Title of Project:
Improving Medication Adherence among Type II Diabetic Home Healthcare Patients
|
| Literature Review | 2. Literature Review:
a. Background of the Problem/Gap: ● Medication adherence is defined as how well patients in home-based care adhere to their medication regimen in the absence of health practitioners. ● Medication adherence incorporates total adherence and compliance with the medical instructions that patients are given. ● Proper medication adherence can significantly improve patient-related healthcare outcomes. ● In the United States, alone, the number of patients who have been diagnosed with type II diabetes cannot be accommodated by hospital settings (Brown & Bussell, 2018). Therefore, to prevent overflowing hospitals, home healthcare programs have been created. b. Theoretical Foundations (models and theories to be the foundation for the project): a. Attachment theory: In accordance with Hunter and Maunder (2016), there are two key reasons why the attachment theory is considered effective for the following DPI. First, the theory acts as a solid foundation for the enhanced comprehension regarding the identified development of ineffective coping techniques, as well as the underlying dynamics associated with the emotional difficulties of the person. Clinicians can help people who have attachment anxiety and fail to comprehend past experiences. Through the involvement of caregivers and/or significant others, individuals can help to reshape their coping patterns. b. Social cognitive theory: The social cognitive theory (SCT) is a critical theory that will be utilized during this DPI project. The SCT is utilized to explain the manner in which human behavior is associated with dynamic, reciprocal, and progressive types of interactions that exist between the person and his/her given surrounding (Bosworth, 2015). Therefore, the SCT is famous because it often proposes that identified behavior aspects are an outcome of the cognitive processes that individuals usually develop. Cognitive processes are developed through social knowledge acquisition. c. Review of Literature with Key Organizing Themes and sub-themes (Identify at least two themes, with three sub-themes per theme) a. Theme 1: Medication Adherence – To handle the issue of medication adherence among the diabetic patients who have had an issue with the adherence to medication needs, various strategic should be utilized. The primary focus of this review of literature is to ensure that drug adherence, though understanding why lacking adherence occurs, is improved upon. i. Drug Adherence: This is the art of sticking to the drug prescription as being presented by the doctors. There are many reasons why home care patients might fail to take drugs as prescribed. For instance, when there is no person to remind them of what is supposed to be taken and at what time (Brown & Bussell, 2018). Some patients go ahead of suffering conditions that make it difficult for them to progress in life. b. Theme 2: Enhancing Adherence through Understanding i. Patient-Centered Communication Approach: This approach will incorporate the interests and preferences of the patients. It will also serve to determine the possible barriers that patients might be facing related to their medication adherence (Voortman et al., 2017). To address components associated with the patient-centered approach, the following MAP resources will be used: Questions to Ask Poster and an Adherence Assessment Pad. ii. Chronic Care Models: It is important to understand that patients need care when they are dealing with a chronic illness. Therefore, to ensure that proper care resources are provided, the My Medications List will be used. c. Summary i. Prior studies: Prior studies have revealed that medical adherence among home healthcare-based patients is lacking and has been a smooth process. In fact, up to 14% of diabetic patients (nationally) do not adhere to their prescribed medication regimen; however, other sources note that this lacking adherence is much higher than 14%, thereby contributing an issue that must be addressed. ii. Quantitative application: The WHO reports numerical data about medication adherence among home healthcare patients. Furthermore, researchers have cited that medication adherence is often impacted by lacking literacy, poor understanding/knowledge about the importance of one’s medication, etc., thereby resulting in inflated adherence rates. iii. Significance: Using the MAP resources and providing patient-specific care, medical adherence among type II diabetes patients will likely improve, thereby resulting in enhanced health-related outcomes. |
| Problem Statement | 3. Problem Statement:
It is not known if or to what degree the implementation of the Medication Adherence Project (MAP) resources, which include (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List, will impact medication adherence among type II diabetic home healthcare patients, ages 35 to 64, of a home healthcare organization located in urban Texas over a period of four weeks.
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| Clinical/ PICOT Questions |
4. Clinical/PICOT Questions:
To what degree does the implementation of Medication Adherence Project resources, which include the Questions to Ask Pad, the Questions to Ask Poster, an Adherence Assessment Pad, and the My Medications List impact medication adherence among Type II diabetic home healthcare patients, ages 35 to 64, of a home healthcare organization located in urban Texas over a period of four weeks? The following clinical question will guide this quantitative project: Q1: Does using the MAP resources improve medication adherence among home health diabetic patients?
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| Sample | 5. Sample (and Location):
a. Location: The location of this project is in urban Texas. The project site provides a larger percentage of patients with healthcare services who reside in the urban area as compared to the rural area. b. At the selected project site, approximately 30 patients have been diagnosed with type II diabetes, though this census changes each month. Patients between the ages of 35 to 64, with no cognitive limitation, who speak English, will be invited to participate in this project. c. Inclusion Criteria i. 35 to 64 years of age ii. Type II diabetes diagnosis iii. English speakers iv. Cognitively abled d. Exclusion Criteria ▪ Younger than 35 and older than 64 years of age ▪ Not diagnosed with type II diabetes ▪ Non-English speakers ▪ Cognitively disabled/delayed
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| Define Variables | 6. Define Variables and Level of Measurement:
a. Intervention: Use of the MAP resources, by nursing staff members, which will be implemented upon the completion of an educational training session. Starr and Sacks’s (2010) MAP Toolkit and Training Guide resources, include: (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List. b. Outcome: Enhanced medication adherence. c. Variables: Medication adherence, which is the dependent variable explored in this project, will be measured using data attained through the project site’s EHR. The MAP resources, which serve as the independent variables explored in this project, include (1) the Questions to Ask Poster, (2) an Adherence Assessment Pad, and (3) the My Medications List.
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| Methodology and Design | Methodology and Design:
A quantitative methodology, which employs a quasi-experimental design, will be used to examine medication adherence rates pre-project implementation and post-project implementation. Statistical analyses will be used to compare pre-and post-project data. Demographic data will be collected because the prevalence of non-adherence is often high among certain groups (e.g., impacted by socioeconomic status, gender, age, etc.).
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| Purpose Statement | Purpose Statement:
The purpose of this quantitative quasi-experimental project is to determine if or to what degree the implementation of the MAP resources, which will be delivered by home healthcare nursing staff members, will impact medication adherence when compared to current practice among type II diabetic patients, ages 35 to 64, of a home healthcare setting in urban Texas.
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| Data Collection Approach | Data Collection Approach:
Each week, nursing staff members will record medication adherence information in the patient’s EHR. If the patient expresses that he/she has not adhered to the medication regiment, during the previous week, lacking adherence information will be recorded in the system. Upon the completion of the four-week project, all information, input by nursing staff members into the EHR, will be assessed. The PI will compare pre-project implementation medication adherence rates to post-project implementation medication adherence rates. In addition to exploring medication adherence rates after the implementation of this project, pre-project implementation adherence rates will be explored over four weeks from April 1, 2021 to April 30, 2021. Once pre-project implementation data and post-project implementation data are obtained, the results will be statistically analyzed. The PI will work with a statistician, who will assist in the data analysis process. Data will be compared analyze using various statistical techniques.
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| Data Analysis Approach | Data Analysis Approach:
The data will be collected using the project site’s EHR and will be presented to the PI by the secretary in a Microsoft Excel document. Data will be input into SPSS version 28 and analyzed using a t-test with a p-value of 0.05.
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| References
|
Bosworth, H. B. (2015). Enhancing medication adherence: The public health dilemma. Philadelphia, PA: Springer Healthcare.
Brown, M. T., & Bussell, J. K. (2011). Medication adherence: WHO Cares? Mayo Clinic Proceedings, 86(4), 304-314. Retrieved from https://doi.org/10.4065/mcp.2010.0575 Hunter, J., & Maunder, R. (2016). Improving patient treatment with attachment theory: A guide for primary care practitioners and specialists. Switzerland: Springer International Publishing. Starr, B., & Sacks, R. (2010). Improving outcomes for patients with chronic diseases: The Medication Adherence Project (MAP). NYC Health. Retrieved from https://www.hfproviders.org/documents/root/pdf_9a3a46fa03.pdf Voortman, T., Kiefte-de Jong, J., Ikram, M. A., Stricker, B. H., van Rooij, F. J. A., Lahousse, L., … Schoufour, J. D. (2017). Adherence to the 2015 Dutch dietary guidelines and risk of non-communicable diseases and mortality in the Rotterdam Study. European Journal of Epidemiology, 32(11), 993-1005. https://doi.org/10.1007/s10654-017-0295-2
|
Appendix B
Site Authorization Letter
Nations Pioneer
Health Services Inc.
11224 Southwest Freeway, Suite 240, Houston, Texas 77031
Phone: (281) 498-6203. Fax: (281) 498-6206
www.nationspioneer.com
Office of Academic Research
Grand Canyon University
College of Doctoral Studies
3300 W. Camelback Road
Phoenix, AZ 85017
Phone: 602-639-7804
Dear IRB Members,
After reviewing the proposed study, Improving Medication Adherence in Diabetic Patients in Home Health Care Settings, presented by Bola Odusola-Stephen, I have granted authorization for Bola Odusola-Stephen to conduct her quality improvement project at Nations Pioneer Health Services, Inc. and Pioneer School of Health, Houston, Texas.
I understand the purpose of this Quality Improvement Project is to determine if or to what degree the implementation of Medication Adherence Project resources (MAP) that include the Questions to Ask Pad, the Questions to Ask Poster, and the Adherence Assessment Pad impact medication adherence among Type II diabetic home healthcare patients, ages 35 to 64, in home healthcare in urban Texas
I have indicated to Bola Odusola-Stephen that the Nations Pioneer Health Services, Inc. and Pioneer School of Health, Houston, Texas will allow the following Direct Practice Improvement Project
- Provide staff an information session on the project and MAP project resources.
- Collect pre and post implementation medication adherence rates
The participants that will be in this Quality Improvement Project must meet the following criteria:
Registered nurses from single department that will participate in the informational session as well as diabetic patients ages 35-64 receiving home health services and are identified as having diabetes type II.
Bola Odusola-Stephen has agreed to provide a copy of the project results, in aggregate, to Nations Pioneer Health Services, Inc. and Pioneer School of Health
If the IRB has any concerns about the permission being granted by this letter, please contact me by (phone or email preference of site granting permission).
Sincerely,
________________________________________
Bamidele Jokodola MSNEd, RN (Administrator) Date
Office: (281) 498-6203 Cell: (281) 685-7280
Email: Daleyrn@sbcglobal.com
Bamidele Jokodola MSNEd, RN
Nations Pioneer Health Services, Inc.
Pioneer School of Health
Complete Answer:
