IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO Implementation of Diabetes Tracking Applications into the Chronic Care Model in the Program of All-Inclusive Care for the Elderly (PACE): A Quality Improvement Effort Jessica A. Bates & Tobias R. Bepler College of Nursing, Michigan State University NUR 997 Doctor of Nursing Practice Project III Dr. Patrick Crane & Dr. Elizabeth Hengstebeck April 20, 2023 IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 1 Table of Contents Abstract............................................................................................................................................4 Introduction......................................................................................................................................6 Background/Significance.....................................................................................................6 Problem Statement/Clinical Question..................................................................................8 Description of Clinical Site .................................................................................................8 Key Stakeholders ..............................................................................................................10 Quality Improvement Model .............................................................................................10 Review of Literature .....................................................................................................................11 Literature Inquiry Method .................................................................................................11 Review of Literature and Synthesis Table ........................................................................12 Self-education to Manage T2DM ......................................................................................12 Self-education to Improve Quality of Life ........................................................................13 Use of Applications for T2DM Self-education .................................................................13 Methods..........................................................................................................................................14 Clinical Site Methodology of Project ................................................................................14 Ethical considerations/Protection of Human Rights .........................................................15 Cause/effect Analysis ........................................................................................................15 Intervention and Data Collection.......................................................................................16 Measurement Instruments and Tools.................................................................................16 Implementation/ Plan.........................................................................................................17 Project budget ....................................................................................................................17 Analysis..........................................................................................................................................18 IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 2 Limitations and Community Partner Takeaways...........................................................................20 Sustainability Plan .........................................................................................................................21 Discussion/Implications for Nursing .............................................................................................22 Conclusion ....................................................................................................................................22 References......................................................................................................................................24 Appencies.......................................................................................................................................28 Appendix A (Stakeholder Analysis Matrix) ......................................................................28 Appendix B (SWOT Analysis) ..........................................................................................31 Appendix C (Chronic Care Model) ...................................................................................32 Appendix D (Literature Inquiry)........................................................................................33 Appendix E (PRISMA Table) ...........................................................................................34 Appendix F (Literature Review)........................................................................................35 Appendix G (Literature Synthesis Table) ..........................................................................43 Appendix H (Pre/Post Survey) ..........................................................................................44 Appendix I (Fishbone Diagram) ........................................................................................46 Appendix J (Data Collection Tool) ...................................................................................47 Appendix K (GANTT Chart).............................................................................................48 Appendix L (HbA1c levels Pre/Post Intervention) ...........................................................49 Appendix M (HbA1c Pre/Post Intervention Paired T-test)................................................51 Appendix N (Question 1 Survey Results) .........................................................................52 Appendix O (Question 1 Paired T-test) .............................................................................54 Appendix P (Question 2 and 3 Survey Results) ................................................................55 Appendix Q (Question 4 Survey Results) .........................................................................56 IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 3 Appendix R (Question 4 Paired T-test) .............................................................................58 Appendix S (Question 5 Survey Results)..........................................................................59 Appendix T (Question 5 Paired T-test) ..............................................................................61 Appendix U (Question 6 Survey Result) ...........................................................................62 Appendix V (Question 6 Paired T-test)..............................................................................64 IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 4 Abstract Background: Those with type 2 diabetes are at a higher risk of debilitating consequences such as impaired vision, nephropathy, and decreased quality in life, resulting in premature death. The cost of diabetes care is also at least 3.2 times greater than the average per capita health care expenditure, rising to 9.4 times in the presence of complications. Review of Literature: Articles chosen from PubMed and CINAHL databases using key terms Type 2 diabetes mellitus, mobile applications, chronic care, the program of all-inclusive care for the elderly, diabetes management, quality improvement, and quality of life. Of the 214 articles, 10 met the criteria for review. Purpose: This paper aims to improve Type 2 Diabetes Mellitus (T2DM) for PACE participants by lowering their hemoglobin A1c to reduce their risk of morbidity and mortality while improving their quality of life using the Chronic Care Model. Methods: 30 Alcatel Joy Tablets supplied to PACE participants with a diagnosis of T2DM loaded with an application to provide education on the management of T2DM, 12 consented to participate in the practice change. Participants attended an educational session on device functionality and expectation of use. Data extraction of baseline A1Cs collected. Follow-up with participants will occur monthly, either by phone or when present in the office. Pre/post-survey responses will conclude at the end of the project in Dec 2022. Implementation Plan/Procedure: In September 2022, participants were provided the Alcatel Joy Tablets and began learning about T2DM and managing the disease by taking steps to lower their hemoglobin A1c. In December 2022, hemoglobin A1c data and pre/post-test survey results analysis consisted of calculations using a two-paired T-test to determine the success of project implementation and outcomes. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 5 Implications/results/ Conclusion: Reducing HbA1c’s through technology grounded in the Chronic Care Model at PACE location will be successfully implemented. Although multifactorial, data analysis of pre/post HbA1c levels obtained during the Sept-Dec months showed statistically significant results in favor of improved outcomes. The HbA1c average using the mean of pre-initiation was 7.9%. HbA1c's post-project was 6.9%, a reduction of 1.0%, with an HbA1c goal of 7%. A two-sample T-test calculation with an alpha of 0.05 resulted in a p-value of 0.0495. Improving quality of life (QoL) through management of T2DM's survey results was overall neutral, with little improvements in participants' knowledge and understanding of tablet devices, mobile applications, and perceived quality of life. Improvements are likely the result of the collective impact of the intervention, such as new medications, dietary changes, and exercise habits during the intervention period, which is consistent with Wagner's Chronic Care Model. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 6 Chronic illness is an issue that has been pervasive in the United States healthcare system for several decades. While chronic illness affects those of all ages, it disproportionately affects the elderly population, with 85% diagnosed with a chronic condition (National Institute on Aging, 2017). Type 2 Diabetes Mellitus (T2DM) is one of the most significant chronic illnesses in the United States, culminating in various negative impacts on the health and well-being of older adults, primarily when not managed adequately. The lack of proper tracking and management of T2DM leads to increased hospitalization rates due to exacerbations of chronic diseases and reduced quality of life (QOL) among those affected (Raghupathi & Raghupathi, 2018). The Program for All-Inclusive Care of the Elderly (PACE) practices within the Chronic Care Model to maintain its participants' current level of health. Since PACE participants live at home and manage their diabetes independently, there is potential for inadequate chronic disease management, which may lead to increased hospitalizations and adverse health outcomes. With 44% (80/181) of PACE participants diagnosed with type T2DM, we aim to improve or maintain QOL within this population by utilizing diabetes management technology on Alcatel Joy Tab 2 devices. Alcatel Joy Tab 2 is an 8-inch tablet android device that allows 9 hours of video/ screen time or 25 days of stand-by on one battery charge (Metro, 2022). T-Mobile® provides unlimited 4G internet to the devices for participants to engage in the application to learn about T2DM diagnosis and how to manage symptoms. Applying the devices provided to participants with T2DM-specific education and interventions will improve QoL within the PACE population in an urban city in Michigan. Background/ Significance IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 7 T2DM is a severe public health concern that considerably impacts QOL and creates an economic burden. In 2018, approximately 415 million people will develop diabetes, with 90% having T2DM (Chaterjee et al., 2017). By 2060, both types of diabetes will affect more than 60.6 million American adults (Smith et al., 2021). Increased consumption of unhealthy diets and sedentary lifestyles have resulted in elevated Body Mass Index (BMI) and higher fasting plasma glucose, contributing to an increased prevalence of T2DM (Khan et al., 2019). Older age also contributes to the risk of T2DM and is a significant concern for the elderly growing population (Khan et al., 2019). Those with type 2 diabetes are at a higher risk of debilitating consequences such as impaired vision, nephropathy, and decreased quality in life, resulting in premature death(Smith et al., 2021). The perception of a person's QOL can be affected by disease burden of T2DM due to overall diagnosis of diabetes causing distress, daily medication adherence, and insulin use (Zurita-Cruz et al., 2018). The cost of diabetes care is also at least 3.2 times greater than the average per capita health care expenditure, rising to 9.4 times in the presence of complications (Khan et al., 2020). The total estimated cost of diagnosis for all diabetes in 2017 was $327 billion, including $237 billion in direct medical costs and $90 billion in lost productivity (CDC, 2022). Nonpharmacological approaches to managing blood glucose levels are essential to diabetes care. Per Gonzalez et al., (2021) diabetes education and support improved self-management knowledge and skill. According to Smith et al., (2021) self-management and understanding diabetes education is associated with better health outcomes and reduced health costs. Pairing diabetes education with mobile application technology can also assist in providing diabetes education that is convenient and cost-effective for PACE participants. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 8 Problem Statement/ Clinical Question PACE's priority is to maintain its participants' independence within the home. Implementing technology to improve education and provide tracking blood sugar may increase adherence. With a recent grant, 30 Alcatel Joy Tab 2 devices were given to PACE to use for its participants diagnosed with T2DM. Devices were pre-loaded with the Glucose Buddy Diabetes Tracker mobile app for those with a history of T2DM. Participants who met the criteria had no cost of data usage through their T-mobile® partner. We aim to evaluate if implementing diabetes management applications within the PACE population will improve patients' perceived level of health and well-being, while lowering hemoglobin A1c (HbA1c) levels, from September to December of 2022. PICO statements intend to gather evidence with research to answer a clinical question to promote proof of reliable resources for changes in practice (Melnyk & Fineout-Overholt, 2019). Clinical questions guided the quality improvement project using P for participants, I for the planned intervention, C to compare current practice, O for outcomes expected and T for the time frame of intervention. The following statement guided the examination of articles: For (P) Pace participants with T2DM do (I) mobile applications with diabetes self-management education (C) compared to standard T2DM education provided within the office setting (O) reduce A1C levels (T) within three months; from Sept- Dec 2022. Description of Clinical Cite PACE is a community-based model caring for elderly adults 55 years and older, accounting for more than 50,000 participants across 31 states in the US (Gonzalez, 2021). They are dual-enrolled in Medicare and Medicaid. They are also considered a high-risk population due to multiple comorbidities, lower socioeconomic status, and risk for hospitalizations using a IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 9 capped financing model (Arku et al., 2022). According to Boersma et al., (2020)76.9% of adults 65 and older who are dual enrolled have two or more chronic conditions. PACE provides a multidisciplinary team approach to managing participants' chronic health conditions allowing them to live in the community and within their homes (Arku et al., 2022). This PACE location has 181 participants; 51 have a T2DM diagnosis. While it is difficult to identify a causative nature of hospitalizations or deaths due to the multiple chronic conditions, the diagnosis of T2DM is related to poorer health outcomes. The current T2DM education during medical visits is provided verbally from provider to participant. There are currently two physicians, three nurse practitioners, four nurses, five dietary/aides, transportation staff, social workers, dieticians, two pharmacy technicians, physical and occupational therapists, and 20 patient rooms to provide medical care. The day center is located in the east wing and can allow 70 people to participate in activities planned twice weekly. Activities include bingo, and art/crafts, with lunch provided through meals on wheels. Two showers are handicap accessible for participants unable or who do not have access to bathe regularly. A therapy gym with various pieces of equipment is necessary for occupational and physical rehabilitation. Medical information is limited to PACE providers and does not interface with other local electronic medical records (EMR), and allows communication with the interdisciplinary team within PACE. Unfortunately, it does not provide portal access to participants access to their medical charts or update them on current diagnoses or visit summaries from each visit encounter. Patient-specific data extraction occurred through interdisciplinary notes created for each patient, including providers, nursing staff, physical therapists, support staff, case management, and transportation. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 10 Key Stakeholders A stakeholder analysis assessed the organizational system and stakeholder interests in practice change (Appendix A). The analysis identifies needs or unforeseen barriers hindering the proposed change and their involvement. Many stakeholders play a significant role in the proposed intervention of using mobile applications to provide education and management of T2DM to PACE participants. These stakeholders include the medical director, provider including MD and APRNs, nursing support staff, transportation team, participants, information technology (IT), insurance companies, T-Mobile®, grant partners and participants. Key stakeholders that will strongly influence the intervention and support will be the medical director, providers, participants, insurance companies, and grant partners. These individuals will play a crucial role in initiating the first steps of this change and communicating with other stakeholders about the intervention and its importance. The intervention comes with cost, time, and education using applications. Resistance with medical directors, providers, participants, insurance, and grant partners during the intervention can affect future funding or reimbursement opportunities. A SWOT analysis provides valuable insight when delimiting the project's scope and strategies to control positive and negative factors affecting success (Harris et al., 2020). It identifies (see Appendix B) strengths, weaknesses, opportunities, and threats during the implementation of the proposed project. It is essential to assess and provide discussion during the initial 1:1 visit when providing the education and expectations of the project to limit barriers. Quality Improvement Model The model utilized for application in this project was Wagner’s Chronic Care Model. The Chronic Care Model outlines six critical elements aimed to improve outcomes in those with IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 11 chronic conditions. This model also effectively shows the relationship between the community, the healthcare system, patients, and providers of care (see Appendix C). This model was designed to focus on self education and tracking to promote better health and to strengthen communication within healthcare organizations in individuals with T2DM (Baptisma et al, 2016). Patients with chronic conditions who are informed and activated have more productive interactions with health care teams and are associated with better health outcomes (Wagner, 1998). An additional benefit in utilizing the Chronic Care Model is its emphasis on information tracking systems which is theorized to allow for better feedback to healthcare providers on patients performance and ability to manage their respective chronic illnesses’. The projected outcomes on the implementation of the Chronic Care Model follows two basic principles with a symbiotic relationship. As chronic healthcare conditions are better managed through improved care systems, not only will patients continue with longer, healthier lives with improved quality of life (Wagner, 1998). But this improved health leads to a decrease in healthcare burden and overall costs to continually treat chronic conditions indefinetly. However, the implementation of this model on a large scale is difficult to quantify as it requires a large scale and comprehensive system change. Review of Literature Literature Inquiry Method The literature review focused on the Cumulative Index to Nursing, Allied Health Literature (CINAHL) and PubMed of the U.S. National Library of Medicine National Institutes of Health databases. Keywords, limitations, and the number of each search criterion results are within Appendix D. Key terms such as “Diabetes type 2” and increased healthcare costs,” “ IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 12 diabetes type 2,” and “decreased quality of life,” diabetes type 2” and “applications or apps,” “self-education or learning,” “type 2 diabetes and “healthcare costs and “mobile apps, “type 2 diabetes and “quality of life” and “mobile apps” were considered. Exclusion criteria comprised articles older than five years old, articles missing technology or self-educational learning methods. The PRISMA diagram details the thorough search of evidence collected with the number of results obtained (Appendix E). After evaluation of the stated criteria for exclusion, ten articles remained. Review of Literature and Synthesis Table The literature review (Appendix F) identified commonalities between the research and the common themes presented in the studies. After examining each selected article, commonly identified themes are labeled within a synthesis table (Appendix G). The themes selected are using self-education to manage T2DM, self-education to improve quality of life, use of applications for self-management T2DM, and use of applications to improve quality of life. The themes are essential to discuss among healthcare professionals and assist with investigating the presented clinical question. Self-education to Manage T2DM Self-management is essential to managing one's blood glucose levels and is associated with improved outcomes, reduced health care costs, and decreased HbA1c measurements (Smith et al., 2021; Nkhoma et al., 2021). Diabetic management applications include similar features, including opportunities for patient education to understand better and track the progress and severity of their T2DM (Nkhoma et al., 2021; Yap et al., 2021). Understanding a complex diagnosis such as T2DM can cause patients to feel overwhelmed or distressed; through education IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 13 and management through technology, diabetic distress may be reduced with a coinciding improvement in self-efficacy (Yap et al., 2021; Nkhoma et al., 2021). Self-education to Improve Quality of Life Lifestyle changes and treatment are essential in preventing or significantly delaying complications of T2DM while improving QOL (Hilmarsdootir, 2021; Yap et al., 2021). Providing diabetes education programs can assist in ways to reduce HbA1c and lower lifestyle risks, such as weight loss, to manage diabetic symptoms and complications. According to clinical practice guidelines, people with diabetes should participate in self-management education focusing on self-care and empowerment (Hilmarsdootir, 2021). T2DM is also a chronic condition that can affect mood and self-esteem, generating frustration and symptoms of depression (Zurita-Cruz, 2018). Self-led education and diabetes management through mobile applications have shown reductions in HbA1c levels but also improved health-related QOL (Nkhoma et al., 2021; Sunil Kumar et al., 2020). Use of Applications for T2DM Self-education Digital education can offer a way to reduce T2DM with minimal burden on our healthcare organizations by creating early aid among those living with T2DM (Lavikainen et a., 2022; Yap et al., 2021; Nkhoma et al., 2021). Applications can assist with self-management, including a healthy diet, weight loss, increased physical activity, and regular blood glucose monitoring (Hilmarsdottir et al., 2021; Tsunemi et al., 2021). They can increase the effectiveness of diabetes care without increasing the frequency of outpatient visits, which would be positive for the patient's health and save healthcare resources (Hilmarsdottir et al., 2021; Nkhoma et al., 2021). The use of digital health in T2DM management also has the potential to lower healthcare IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 14 costs over extended periods of 10-20 year interventions compared to standard management techniques (Gilmer et al., 2019). Self-care and management of chronic conditions can be challenging to understand. According to the World Health Organization (WHO), education provides the bases and foundation for the treatment of diabetes, and key objectives include raising awareness of individuals' attitudes and behaviors to promote self-care (Ghoreishi et al., 2019). By using daily tracking and monitoring, individuals become active participants in their care and develop a better understanding and knowledge base related to their T2DM (Lavikainen et al., 2022). Methods Clinical Site Methodology of Project Thirty participants received an Actel Joy 2 Tablet with the application “Glucose Buddy Diabetes Tracker” pre-downloaded onto the device. Before application use, the participants completed a pre-survey detailing their current skill level with tablet devices and their current knowledge of T2DM. A group presentation along with one-on-one instruction on device and application functionality occurred during September 2022. A project description guideline and expectations of daily use take home handout was provided to each participant. Participants completed a pre/post-survey that included questions on prior technology use, knowledge of diabetes A1C levels and current QOL rating are provided (Appendix H). Daily participation of minimally 5 minutes or 1 article per day will focus on knowledge of HbA1c levels, effects of T2DM and self- management. Medical staff were also provided instruction on project expectations to reinforce the importance of use during all interactions at PACE. The team process may uncover barriers to use or problems with the application prior to the end of the project. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 15 Participants have been chosen by the PACE medical director, including patients with T2DM and active with PACE who are willing to enroll in the site program. The usual care of diabetes education provided at PACE currently includes consultation with dietitians and verbal education during office visits. Ethical Considerations/ Protection of Human rights Federal Policy for protecting human subjects requires universities and other institutions to seek approval from the International Review Board (IRB) to protect the human rights of the participants who enroll in the clinical site project (Harris et al., 2020). Before implementing the proposed project, the IRB at Michigan State University reviewed the outlined proposal application of form HRP-512 and provided consent to proceed with implementation in September 2022. Data collection included assessing the electronic medical record containing comorbid conditions, social and economic factors, access compliance, barriers, and interventions necessary to improve health and quality of life. The information collected did not contain identifiable data to protect the individual's identity and privacy. Cause/effect Analysis A fishbone diagram is a comprehensive view of essential components of the clinical problem. Contributing factors assessed include socioeconomic status, comorbidities, barriers to implementation such as lack of device experience, perceived health status, and genetic components located within Appendix I. The assessment will guide team members when difficulties arise during the course of the practice improvement project (Moran, Burson, & Conrad, 2020). IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 16 Intervention and Data Collection T2DM is a patient-specific chronic condition with varying levels of disease progression. Our intervention focuses on quality improvement of diabetic care using diabetes tracking applications on the Alcatel Joy Tab 2. Over three months, beginning in September 2022, participants were asked to track health information via Glucose Buddy Diabetes Tracker mobile application, pre-downloaded onto their device with five minutes or one article daily minimal use required for participation. Of the 30 identified participants, 12 consented to participate. Data collection occurred over 12 weeks. The PACE support staff will continually monitor the interventions to ensure proper use and application adherence. All data collected will be compiled and stored anonymously via a password-protected shared drive between both DNP students and the medical director located within Appendix J. Measurement Instruments and Tools Data collection will occur via PACE TruChart Electronic Health Record (EHR) system. EHR screening included deidentified general and demographic information such as age, race, gender, and comorbid conditions. Completion of a pre/post-survey questionnaire occurred with all participants in writing with the help of PACE staff. The survey questions utilized a five-point Likert scale and examined patient satisfaction, knowledge, and HrQOL. Other means of data collection will occur through Glucose Buddy Diabetes Tracker that allows participants to measure, track data such as weight, blood pressure, blood sugar, HbA1c, and carbohydrate intake. Three primary measurements defined the quality improvement effort. Health data will be measured to see changes in participants' objective health data recorded before and after implementation to assess changes in weight, and HbA1c measurements. Pre- and IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 17 post-questionnaires using 5-point Likert scales measured participant satisfaction, perceived health, QOL, and current knowledge of T2DM A1C goals. Analysis of the pre/post surveys included a paired T-test comparing before implementation and after responses. Success of the project will be determined by participants' response. Clinical significance will be measured using the responses, EHR values of HbA1c, and glucose levels to compare results. The self-created survey determines each participant's perceived quality of life and the understanding of T2DM as a chronic condition which is the main goal of the practice improvement project. Implementation Plan Scheduled tasks were formatted using a Gantt chart located in Appendix K. A Gantt chart focuses the project to remain on schedule by ensuring task completion within a reasonable timeframe. The details include project activity, the person responsible for the task, the start and end dates, and expected completion date. Duties included IT verification/ download of the application onto tablets, participant pretest, education with training staff/ participants on the use of technology, obtaining baseline HbA1c's, touching base every two weeks with participants to identify any barriers, meeting with the PACE medical director monthly, obtaining after implementation HbA1c's and completion of the pre/post-test. The project team completed a stakeholder analysis and SWOT matrix to help ensure the project's success and to decrease barriers and limitations early in the project process. Project Budget The Alcatel Joy tablets were purchased using grant funding awarded to PACE. The amount purchased tablets for PACE to use at their discretion. T-mobile® provided the paid IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 18 internet use for each tablet at no cost to the participant or PACE. No other cost is associated with the project other than time for education, implementation, and analysis. Analysis HbA1c target levels can vary by each person's age and the complexity of medical conditions. According to the American Diabetic Association (ADA), an HbA1c above 6.5% indicates a diagnosis of T2DM (2023a). An HbA1c goal for many nonpregnant adults of less than 7% (53 mmol/mol) without significant hypoglycemia is appropriate; Grade A (ADA, 2023b). It is essential to determine the process used to test the samples to ensure reliability. According to the ADA, point-of-care measurements are unreliable compared to venous samples (ADA, 2023b). The data collected for this analysis used venous samples processed by an outside laboratory. Data collection included HbA1c venous levels pre/post-intervention and pre/post-intervention survey responses. The HbA1c average using the mean of pre-initiation was 7.9%. HbA1c's post-project was 6.9%, a reduction of 1.0%, and the HbA1c goal of 7% and below is the desired outcome (see Appendix L). A statistical two-sample T-test calculation assessed the significance of HbA1c samples. The alpha level used was 0.05. The p-value for pre and post-HbA1c was 0.0495 (see Appendix M). This value is statistically significant, validating reliable results. The survey consisted of seven questions, and one was open-ended. The responses included 1 (very poor), 2 (poor), 3 (neutral), 4 (good), and 5 (excellent). Question 1 stated: What is your current experience with tablets and app use with technology? The question response ranges from 1 (very poor) to 5 (excellent). Participants who scored 3 (fair) to 1 (very poor) were closely monitored monthly for reinforcement of education and technology use to increase IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 19 compliance. Data analysis of Pre/post-intervention scores included using the mean and two sample T-tests. The mean pre-implantation score is 3.08; the post is 3.0, which indicates a neutral response with current technology use (see Appendix N). The alpha significance level is 0.05, with a p-value of 0.43 (see Appendix O). Although the score is not statistically significant, the scores slightly decreased. Potential causes include functionality differences between current devices and application use. Evaluating satisfaction is essential for future improvement projects with the community partner. Questions 2 and 3 described satisfaction with the application glucose buddy and the Actel Joy tablet. The post-question mean score is 2.8 meaning poor to neutral for the application, while the tablet score is 3.5 (Appendix P), implying neutral to good feedback. Question 4 asks the participant to evaluate their perception of health status and its effects on their quality of life. How would you describe your current quality of life? The pre-survey median response is 3.67; the post-survey is 3.91 (Appendix Q). The two-sample T-test for alpha is 0.05; the p-value is 0.23 (Appendix R). The response is not statistically significant, with a mean improvement of 0.24. However, the overall increase in quality of life can substantially impact emotional health and is necessary to assess (Hilmarsdottrr et al., 2021). Question 5 explores how happy participants were with their current health; designed to gain further insights into participants' QoL based on emotional health. The pre-survey and post-survey responses were 3.083 and 3.833 (Appendix S), respectively, with a mean improvement of 0.8 with a p-value of 0.022, suggesting a statistically significant increase in participants' happiness with their current health (Appendix T). The chronic care model emphasizes patient self-management of disease to proactively improve patient-provider interactions and overall health outcomes. Question 6 evaluates IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 20 participants' perceived self-management and control of their T2DM. Respectively pre-survey and post-survey mean results were 3.0 and 3.75, a 0.75 mean increase (Appendix U). A two-sample T-test revealed a p-value of 0.047, a statistically significant finding in the rise in T2DM self-management (see Appendix V). Of the twelve responses, only one participant reported a post-survey decline. The final survey question focused on understanding the extent of personal knowledge gained by determining participants' understanding of their HgA1c goals. If participants answered 'yes,' they were expected to write their HgA1c goal as a percentage. 75% (9/12) of participants needed to learn what their HgA1c goal was. Post-survey results yielded the same level of understanding, with the same 75% (9/12) participants' responding 'no.' Limitations and Community Partner Takeaways Limitations in this quality improvement effort were extensive. These multifaceted limitations included participant-specific limits and constraints within the organization and third-party funding bodies. Fallout was high during the early implementation of this project, with 60% (18/30) electing to not participate in implementation as explained previously; thus limiting the sample size of participants observed to 12. The tablets utilized in this quality improvement effort were accessible due to a grant from a T-mobile® partnership. This donation of tablets also included the addition of unlimited free 4G internet access for the tablets once set up by the community partner. This access was delayed during the implementation, meaning participants could not access the "Glucose Buddy Diabetes Tracker" in their homes or public as initially intended. A decrease in the utilization of diabetic self-management and tracking likely occurred. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 21 Battery life on the selected tablets was an issue and barrier to participants. While education on tablet use was extensive, including a demonstration of charging, some participants believed their device no longer functioned once the battery died even after multiple one-on-one learning sessions. Overall acceptance and perceived self-efficacy regarding using tablets and mobile applications remained low due to prior beliefs and failures with different technology exposures in the past among participants despite motivational efforts. Acceptance and willingness of various factors considering a significant number of participants in this effort are dually eligible for Medicare and Medicaid. Other motivationally limiting factors not explored may have included language and literacy barriers, the highest level of education completed, and previous professional experience. Sustainability Plan The sustainability of this project is set to follow the outline of the chronic care model and a continuous process of improvements among both participants and providers (Wagner, 1998). Participants were able to continue use of their tablets and applications for T2DM management after the implementation was completed. The goal for this project's sustainability would be to see an overall plateau of HgA1C and a gradual increase in patient self-efficacy and knowledge of their T2DM. Prior to implementation, all staff at this site were given educational material on the intervention and goals of the project. The hope of educating staff was to provide a point of contact for patients to continue the interventions to improve long term health outcomes. Per Medical directors request, participants are permitted to keep tablets for continued use. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 22 Discussion/Implications for Nursing The positive impact on both HgA1c and patient perceptions on quality of life are promising which warrants further investigation in future practice to improve population health by improving self-efficacy among patients. The implications for this project has an array of potential long term benefits. Overtime, we believe that acceptance and understanding of these technologies will only grow as the younger population ages. If this intervention was applied to a younger adult population with more access and understanding of technologies, we may have seen different results. Further inquiries may be beneficial among populations with chronic health conditions who have an initially higher aptitude for technology use and application. By utilizing and understanding these technologies as healthcare providers we can be of benefit for patients utilizing interventions such as the ones observed in this project. One gap that would impede potential future inquiries on this topic would be the cost of implementation on a larger scale as future costs would likely be placed on the patients opening the door to socioeconomic concerns of implementation. This issue was negated in this project due to grant funded tablets and free applications. As more people now have access to smart devices, this could counteract future costs if further investigated and may prove to be a low-cost implementation for chronic care management. Conclusion Prevalence of T2DM has continued to increase without signs of remission (Smith et al., 2021). The overwhelming impact of T2DM compounds its harm as a chronic illness with an array of potential negative comorbidities if not addressed or adequately controlled at both the primary and secondary levels of healthcare (Zurita-Cruz et al., 2018). Older adults are IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 23 disproportionately affected by chronic illnesses like T2DM (National Institute on Aging, 2017). Incorporating technology into chronic disease with self management in the future may enhance provider to patient communication, improve QOL, and compliance with use of the chronic care model. This project aimed to utilize Alcatel Joy Tab with the "Glucose Buddy Diabetes Tracker" pre-downloaded to promote participant self-management and tracking of their T2DM by utilizing technology to motivate and promote participants' self-efficacy to drive improvements in T2DM management and quality of life, respectively. HgA1c data and pre and post-surveys were analyzed to determine the effectiveness of interventions on diabetes self-management and overall quality of life among participants (see Appendix H and Appendix L). Twelve participants participated in the quality improvement effort. Survey results were overall neutral, with little improvements in participants' knowledge and understanding of tablet devices, mobile applications, and perceived quality of life. An increase in participants' emotions toward their health with observed A1C improvements can increase perceived ability and confidence to manage T2DM. HgA1c was used as a measurement to understand potential improvements in participants' self-lead management in their diabetic care as outlined in the chronic care model. A decrease in HbA1c's observed after intervention from an overall group mean HbA1c pre-intervention of 7.91 to 6.99 post-intervention. It is essential to note that the reduction in HbA1c is multi-faceted. Improvements are likely the result of the collective impact of the intervention, such as new medications, dietary changes, and exercise habits during the intervention period, which is consistent with the chronic care model (Wagner, 1998). IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 24 References American Diabetes Association (ADA,a). Classification and diagnosis of diabetes: Standards of care in diabetes. Diabetes Care. 46(1). S19-S40. https://doi.org/10.2337/dc23-S002 American Diabetes Association ( ADA,b). Glycemic targets: Standards of care in diabetes. Diabetes Care. 46(1). S97-S110. https://doi.org/10.2337/dc23-S006 Arku, D., Felix, M., Warholak, T., Axon, D.R. (2022). Program of all-inclusive care for the elderly (pace) versus other programs: A scoping review of health outcomes. Geriatrics. 7(31). https://doi.org/10.3390/geriatrics7020031 Baptista, D.R., Wiens, A., Pontarolo, R., Regis, L., Reis, W. C., Correr, C.R. (2016). The chronic care model for type 2 diabetes; A systematic review. Diabetol Metab Syndr, 8(7), https://doi.org/10.1186/s13098-015-0119-z Boersma, P., Black, L. I., & Ward, B. W. (2020). Prevalence of multiple chronic conditions among US Adults, 2018. Preventing chronic disease, 17, E106. https://doi.org/10.5888/pcd17.200130 Center for Disease Control and Prevention (CDC). (2022). By the numbers diabetes in america. Retrieved from: https://www.cdc.gov/diabetes/health-equity/diabetes-by-the-numbers.html Chatterjee, S., Khunti, K., Davis, M. (2017). Type 2 diabetes. Lancet. 389, 2239-2251. https://doi.org/10.1016/S0140-6736(17)30058-2 Goreishi, M.S., Vahedian-Shahroodi, M., Jafari, A., Tehranid, H. (2019). Self-care behaviors in patients with type 2 diabetes; Education intervention based on social cognitive theory. Diabetes Metab Syndr. 13, 2049-2056. https://doi.org/10.1016/j.dsx.2019.04.045 IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 25 Gilmer, T., Burgos, J. L., Anzaldo-Campos, M. C., & Vargas-Ojeda, A. (2019). Cost-Effectiveness of a technology-enhanced diabetes care management program in mexico. Value in health regional issues, 20, 41–46. https://doi.org/10.1016/j.vhri.2018.12.006 Gonzalez, L. (2021). Will for-profit keep up the pace with the united states? The future of the program of all-inclusive care for the elderly and implications for other programs serving medically vulnerable populations. Int J Health Serv. 51(2), 195-202. https://doi.org/10.1177/0020731420963946 Harris , J.L., Roussel, L., Dearman, C., Thomas, P.L. (2020). Project planning and management: A guide for nurses and interprofessional teams. (3rd ed). Burlington, MA. Jones & Bartlett Learning. Hilmarsdottir, E., Siguroardottir, A.K., Arnardottir, R.H. (2021). A digital lifestyle program in outpatient treatment of type 2 diabetes: A randomized control study. JDST. 15(5). 1134-1141. https://doi.org/10.1177/1932296820942286 Khan, M.B., Hashim, M.J., King, J.K., Govender, R.D. (2020). Epidemiology of type 2 diabetes- Global burden of disease and forecasted trends. Epidemiol. Glob. Health. 10(1). https://doi.org/10.2991/jegh.k.191028.001 Lavikainen, P., Mattila, E., Absetz, P., Harjumaa, M., Lindstrom, J., Jarvela-Reijonen, E., Aittola, K., Mannikko, R., Tiles-Tirkkonen, T., Lintu, N., Lakka, T., Van- Gils, M., Pihlajamaki, J., & Martikainen, J. (2022). Digitally supported lifestyle intervention to prevent type 2 diabetes through healthy habits: Secondary analysis of long-term user engagement trajectories in a randomized control trial. J Med Internet Res. 24(2). https://doi.org.10.2196/31530 IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 26 Melnyk, B.M., & Fineout-Overholt, E., (2019). Evidence-based practice in nursing and healthcare. (4th ed.) Philadelphia, PA: Walters Kluwer. Metro By TMobile. (2022). Retrieved from: Tablet Computers with Wi-Fi & Cellular | Metro by T-Mobile Moran, K., Burson, R. & Conrad, D. (2020). The doctor of nursing practice project: A framework for sucess (3rd ed.) Burlington, MA. Jones & Bartlett Learning. National Institute on Aging (2017) Supporting Older Patients with Chronic Conditions. https://www.nia.nih.gov/health/supporting-older-patients-chronic-conditions Nkhoma, D. E., Soko, C. J., Bowrin, P., Manga, Y. B., Greenfield, D., Househ, M., Li Jack, Y. C., & Iqbal, U. (2021). Digital interventions self-management education for type 1 and 2 diabetes: A systematic review and meta-analysis. Computer methods and programs in biomedicine, 210, 106370. https://doi.org/10.1016/j.cmpb.2021.106370 Raghupathi, W., & Raghupathi, V. (2018). An empirical study of chronic diseases in the united states: A visual analytics approach. International journal of environmental research and public health, 15(3), 431. https://doi.org/10.3390/ijerph15030431 Smith, M.L., Zhong, L., Lee, S., Towne, S.D., Ory, M.G. (2021). Effectiveness and economic impact of a diabetes education program among adults with type 2 diabetes in south texas. BMC Public Health. 21(1646). https://doi.org/10.1186/s12889-021-11632-9 Sunil Kumar, D., Prakash, B., Subhash Chandra, B. J., Kadkol, P. S., Arun, V., & Thomas, J. J. (2020). An android smartphone-based randomized intervention improves the quality of life in patients with type 2 diabetes in Mysore, Karnataka, India. Diabetes & metabolic syndrome, 14(5), 1327–1332. https://doi.org/10.1016/j.dsx.2020.07.025 IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 27 Tsunemi, A., Sato, J., Sugimoto, S., Iwagaki, Y., Enomoto, M., Someya, Y., Kiya, M., Matsuhashi, E., Wakabayashi, Y., Funayama, T., Mita, T., Uchida, T., Miyatsuka, T., Azuma, K., Shimizu, T., Kanazawa, A., Satoh, H., & Watada, H. (2021). A Pilot Study of Intervention With a Mobile Application Visualizing the Macronutrient Content for Type 2 Diabetes at a Japanese Center. Journal of clinical medicine research, 13(8), 425–433. https://doi.org/10.14740/jocmr4558 Wagner E, H. Chronic disease management: What will it take to improve care for chronic illness? Effective Clinical Practice. 1998;1(1):2-4. Yap, J. M., Tantono, N., Wu, V. X., & Klainin-Yobas, P. (2021). Effectiveness of technology-based psychosocial interventions on diabetes distress and health-relevant outcomes among type 2 diabetes mellitus: A systematic review and meta-analysis. Journal of telemedicine and telecare, 1357633X211058329. Advance online publication. https://doi.org/10.1177/1357633X211058329 Zurita-Cruz, J. N., Manuel-Apolinar, L., Arellano-Flores, M. L., Gutierrez-Gonzalez, A., Najera-Ahumada, A. G., & Cisneros-González, N. (2018). Health and quality of life outcomes impairment of quality of life in type 2 diabetes mellitus: a cross-sectional study. Health and quality of life outcomes, 16(1), 94. https://doi.org/10.1186/s12955-018-0906-y IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 28 Appendix A Stakeholder Analysis Matrix Stakeholder Contact Impact Relationship How What is important How can the How can Strategy for person (How to the much to the stake stakeholder the engaging the Phone, much intervention: influenc holder contribute to the stakeholder stakeholder email does How is the e do intervention reject the interventi stakeholder they intervention on affect affected by have them it over the low, interven med, or tion, high) low med or high PACE 517-319- High Medical High Participants Can report By not Meeting her Medical 0700 director/ improved back success approving monthly Director quality of life or failures, the with provider and decreased provide proposed updates hospitalizations alternative interventio with the approaches to n intervention caring for Answer Pace questions participants PACE NP’s 517-319- High NP/ High Improved Can oversee Not Meeting 0700 provider education patients use of offering monthly delivery system device and interventio with to participants, recommend n to updates decreasing options or participant with the hospitalization changes to or refusing intervention rates, improving improve to answer quality of life sucess participate questions Nursing 517-319-0 Med RN, MA Med/ Will help aid in Support staff Potential Monthly support staff 700 High providing see patients in for adding communicat diabetic home more additional ion with education and frequently and workload support management in may help with if patient staff to home while technological tracking is discuss working with issues that not correct issues, their patients may arise. or if barriers, education and is not compliance. utilized. Answering questions. Transportati 517 Low Minimum Low Decreased Minimal Unknown Devices do on -319-0700 hospitalizations contribution not require and wifi and can coordination of be used care may lessen during transportation transport IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 29 burden Participants High Self care High Self Highest level Non Observation management of of complianc of their own contribution. es or not application chronic Primary role utilizing use and data condition and in tracking, education being health managing, and of tracked. understanding manageme Perceived theirT2DM. nt tools level of through health and tracking wellness applicatio with ns intervention IT 517-319- Med Support Low Assuring Allowing May be Minimize 0700 applications and application perceived workload devices work permission as added burden correctly and and the ability workload early. participants can to add outside if Utilizing accessT2DM applications of problems easy to use management tablet devices arise applications applications on tablet from anywhere. devices for the participants. Insurance High Hospitaliza High Reduce health Support the Refusing ability to companies tions result care costs education by to generalize in high associated with approval of reimburse results of healthcare increased education for visits intervention cost; lower hospitaliztions reimbursemen educating to use for health care t patients on future use costs by use of with decreasing device and participants hospitalizat education with ions chronic diseases T-Mobile® Low More use Low Increasing Provide Provide Ability to of customers with quality wifi low generalize participants use of devices without quality intervention more data that require wifi internet internet for future used, interruptions with many use with increased interruptio wifi and customers ns devices to with wifi help use manage chronic dx in the future, invitation to presentation in April 2023 IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 30 Grant High Future Low Grant funds are Providing Not Invitation to partner grant used more grant provide presentation funding, appropriately funding in the future in April future future grant 2023 projects funding in the future Table A1. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 31 Appendix B SWOT Analysis Strengths Weaknesses ● Tablets received as a grant from ● Technology may not be fully understood by T-mobile® making it no cost to the participants in selected population participants ● Sensory deficits may impact application ● Tablets do not require wifi in order to and tablet use operate ● Requires participants to read. Literacy of ● Health tracking data is readily available participants is not known at this time. and graphed to share with patient and provider Opportunities Threats ● Improve patient self efficacy in ● Selection bias of patients receiving devices management of T2DM that may be more apt to use devices based ● Wide scale implementation of health data on functional status tracking in home ● Fragility of tablet devices if dropped, lost, ● Improved provider understanding of stolen, or otherwise incapable of use by patients chronic illness management participants. Table B1. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 32 Appendix C Figure C1. Chronic Care Model flow sheet IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 33 Appendix D Literature Inquiry DataBase Keywords Limitations Number of Results PubMed “ Diabetes type 2” Within 1 year 62 and increased healthcare costs” PubMed “ type 2 diabetes” From 2019-2022 (3 77 and “ decreased years), with quality of life” systematic reviews and RTC CINAHL “ Diabetes type 2” Within the last 5 32 and “applications or years apps” and “self education or learning” PubMed (type 2 diabetes) Within past 5 years 11 AND (healthcare costs) AND (mobile apps) PubMed (type 2 diabetes) Within past 5 years 33 AND (Quality of life) AND (mobile apps) Table C1. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 34 Appendix E Prisma Table Figure D1. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 35 Appendix F Literature Review Citation Design/level of Sample Intervention Measurable Findings Strengths/limitations/ implications evidence/ variables/ purpose instruments Batch et al, Longitudinal n=201 Download an Pre/post Hgb A1C, Not statistically Limitations: 2021 Level: III participan application of after all 12 levels significant with Small amount of participants, short duration ts a self guided were completed reduction of HbA1c of study, lasting 3 months mobile app participants were and how many for diabetes sent a follow up levels were education survey. The primary completed within using outcome was change the app, Diabetes Strengths: intervention of design, which is Time2Focus in HbA1C, secondary self efficacy based on behavior change theory and focuses by outcomes included showed a large and on increasing self efficacy and problem completing medication significant increase solving skills, limited resources needed for 12 levels of adherence, self-care during app users for study, collection of data in new ways education activities, self completers, reporting of physical Severity of illness activities, diabetes perceptions showed self efficacy illness a small but perceptions, diabetes significant decrease distress scale, and for users who users engagement completed the with and rating the levels. The net app promoter score was 62.5, indicating that those who completed the levels rated it highly and recommended it to others IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 36 Citation Design/level of Sample Intervention Measurable Findings Strengths/limitations/ implications evidence/ variables/ purpose instruments Gilmer et Randomized n= 301 3 arm Cost of intervention PD-TE arms had a Limitations: Younger population not as Clinical Trial patients randomized and quality of life significantly higher generalizable to PACE population. al., 2019 Level: I with control with -adjusted life years. cost of initiation Technology enhancements included a T2DM Project Dulce Measurements were and management. glucometer device. Limited cost wireless to improve A1c, All 3 arms showed effectiveness at 5-10 years with PD-TE arms. diabetes care blood pressure and improvement in management lipids. Clinical staff cost-effectiveness (PD), and had access to diabetic for diabetes Strengths: Study design. Use of medication Project Dulce tracking information. management. PD and blood sugar reminder systems. Strong with Analyzed cost of and PD-TE arms cost analysis. technology interventions against have better long enhancement cost of diabetic term cost (PD-TE) complications. effectiveness. All including arms have mobile improved estimated application life years Hilmarsdottr Randomized N=30 Participants Every 6 months One difference was Limitation: Small amount of participants, r et al, 2021 Control Trial were variables tested were a significant short study, no follow up after the Level: II randomly body weight, HbA1c difference in A1C, intervention, not enough staff in clinic to assigned to an levels and lipids as a decrease in support the study due to illness intervention well as disease specific or control questionnaires about distress and anxiety group after distress related in symptoms was Strength: the randomization and age and toT2DM, health noted in the stratification of the participants according to gender related quality of life, intervention group, age and gender and results reported stratification. depression and no differences were according to the intervention to treat. In addition to anxiety Statistics noted in the control the standard included group of care, comparisons between intervention both groups group participants used a IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 37 Citation Design/level of Sample Intervention Measurable Findings Strengths/limitations/ implications evidence/ variables/ purpose instruments smartphone application to access a lifestyle program (SidekickHea lth) through which they received personalized recommendat ions and education on healthy lifestyles. Lavikainen Randomized N=1022 Objective: Groups DIGI and Adhering to the Limitations: et al, 2022 Control Trial: investigate DIGI + accessed intervention daily More women than men in the study also Level: I healthy BitHabit for 12 successfully calculated how much the person participated habits, months. Intervention improved diets, and in monthly instead of weekly to show BitHabit and goal to encourage lost weight over the adherence. in T2DM RF. people to develop course of a year. It was noted in the study, the sensitivity of An RTC healthier choices to Intermittent use of detecting any types of changes within the risk evaluating the improve T2DM 2-3 times per week factor is not known. improvement using self only showed mild application by determination theory. improvements itself or BitHabit offered comparing those Strengths: partnered thirteen areas of who did not Large sample size, had a 1 year F/U with an in improvement from participate or quit. Initial application participation was nearly person group diet, exercise, and Every day users 100% for using the application. with healthier sleeping showed the greatest These results reduced bias in selection of education in habits. Other areas benefit from the participants. comparison included ways how intervention. Older with current mood affects adults were IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 38 Citation Design/level of Sample Intervention Measurable Findings Strengths/limitations/ implications evidence/ variables/ purpose instruments practice. lifestyle, how to deal associated with Participants with stressful increased were situations limiting engagement. randomly smoking and alcohol allocated into intake. a digital The DIGI+ group intervention Attended six group DIGI, a coaching sessions. group BMI and waist combining measurements. At the digital next office visit lab intervention values such as blood and face to sugar and first face measurements DIGI+GROU repeated 12 months P or control later. group Nkhoma et Meta-Analysis N= 39 None (DSMES) improving DSMES improved Limitations: HrQoL was not found to have a Level: I Studies A1C, diabetes A1C, diabetic statistically significant improvement at 6 or al., 2021 included education, and knowledge with 12 month follow-ups. with 6861 (HrQoL) of Type 1 & T2DM. No participan 2 DM in 10 years significant changes Strengths: Study design. Large sample size ts in HrQoL. and number of studies included IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 39 Citation Design/level of Sample Intervention Measurable Findings Strengths/limitations/ implications evidence/ variables/ purpose instruments Smith et al, longitudinal level n=5,907 Interactive A1C, and expected The largest HbA1c Limitations: the high attrition rate was a 2021 III participan workshop health savings cost. drop 3 m F/U; P significant finding, which prohibited ts taught in A series of <0.001 adj change obtaining HbA1c measures over time for all Prognostic study Spanish and independent sample -0.926, at 6 months: participants with baseline data and may have investigating the English, test and linear mixed P <0.001 adj introduced bias. Attribution rates at 12 month outcome of collecting model regression change -0.870, 12 follow up were higher among younger disease, over data at 5 time analysis was used to months, P 0.001 adj participants, uninsured, or medicaid insured time. The primary points; identify changes over change: -.731 and those who drank alcohol and smoked. outcome variable baseline time of interest was 3,6,9,12 Cost savings: using Cost savings were extrapolated based on 2 HbA1c and the Gilmer prior studies of cost savings from reduction estimated health approach: was an of A1C. cost savings were est after 3 years, care costs savings estimated cost location South Texas associated with savings if f/u every HbA1c reductions 12 months for 3 Strengths: Large population sample, 5 years, est savings follow up points, and measuring more than 1 would be 1501 per variable: HbA1c and health care costs. Study person. is 1 year old. Sunil Kumar Randomized field N= 300 Intervention Pre and post test Improved quality of Limitations: Fixed sample size. trial patients group results were life with mobile app Non-scientific calculation of sample size et al., 2020 Level: II age 18-65 received the reviewed for the intervention with = android quality of life using type 2 smartphone the same WHO Strengths: Randomized study. Use of pre diabetes app Diaguru QOL BREF and post test quality of life questionnaires over a Questionnaire at the year end of six months IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 40 Citation Design/level of Sample Intervention Measurable Findings Strengths/limitations/ implications evidence/ variables/ purpose instruments Tsunemi et Pilot Study 18 Single arm HbA1c was the Improvement of Limitations: Study design and small sample Level: III patients pilot study primary short term HbA1c size in Japan, may have different dietary al., 2021 T2DM using the measurement. and BMI that were intake compared to eating habits in the Calomeal Secondary measures statistically United States. mobile app were bodyweight, significant. DTSQ over the lipids, and quality of and PAID improved course of 3 life scores. The but were not Strengths: Use of mobile applications with months DTSQ and PAID statistically clear outcomes. Older population utilized self administered to significant at dietary management and tracking of T2DM. evaluate patient QOL P=0.1063 and at the beginning and P=0.1361 end of the study respectively. Yap et al., Meta-Analysis 18 None Technology-based TBPIs reduced Limitations: Multiple studies reviewed had Level: I randomiz psychosocial diabetic distress, small sample sizes. Studies reviewed related 2021 ed interventions (TBPIs) and Hgb A1C. to HrQoL and depression were related to one controlled and diabetes distress, Improved patient study specifically. trials patient self efficacy, self efficacy included HrQoL, Hgb A1C No significant change in HrQoL Strengths: High level of evidence with study design. Large sample size and number of studies included IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 41 Citation Design/level of Sample Intervention Measurable Findings Strengths/limitations/ implications evidence/ variables/ purpose instruments Zurita-Cruz Cross sectional n=1,394 Patients were The following Identified factors: Limitations: more women in the study, and et al, 2018 study level IV participan classified into variables related to in physical the results should not be generalized to both ts 3 groups quality of life were function: increased genders as environmental factors may have according to studied: age, sex, age and depression been influenced by biological sex, Second their HRQol occupation, marital were statistically they did not address the influences of genetic scores, those status, years of significant factors. stratification. Third they did not address the with scores T2DM2 evolution, The emotional role, possible participation of educational level 0-50, 51-75, comorbidities, and mental health and and or socioeconomic status in the triad 76-100 presence of body pain include: quality of life-emotional distress of T2DM2. depression (Beck depressive Depressive Depression symptoms, duration Strength: Large number of participants, symptoms Inventory). Perceived of months of study occurred 3 years ago were defined QOLwas measured T2DM2, and as having a with a health-related number of score of less quality of life scale comorbid or = to 14 (HRQol) scale and a conditions were 36-short item also significant Short-Form Survey (SF-36), the Shapiro-Wilk test was applied to determine the distribution of the quantitative variables also the chi test was used along with Shapiro-Wilk used for comparisons among the groups. Table E1. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 42 Appendix G Literature Synthesis Table Study Self- Self- education to Use of apps for self education for Application use and cost education, improve quality of life management of T2DM analysis manage T2DM Lavikainen et al, 2022, X Hilmarsdottir et al, 2021 X Batch et al, 2021 X Smith et al, 2021 X Zurita-Cruz et al, 2018 X Gilmer et al., 2019 X Nkhoma et al., 2021 X Sunil Kumar et al., 2020 X X Tsunemi et al., 2021 X X Yap et al., 2021 X X Table F1. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 43 Appendix H Pre/post Survey Participant Statement of approval: This is a quality improvement project being done to help us evaluate diabetic care and education using mobile apps at PACE. We are asking you to complete a survey before and following the use of diabetic tracking applications for a 3 month period. The project team is going to evaluate health data collected through the mobile applications. The data collected will be anonymous. Participation in this survey is voluntary and you may refuse to answer any question. You may withdraw or stop participating at any time without consequence. By completing the survey, you are indicating your voluntary agreement to participate. Please answer the following prompts: What is your current level of experience with tablets and app use with technology? 1 2 3 4 5 Very Poor Poor Fair Good Excellent Please rate your satisfaction with tracking information on the Glucose Buddy Diabetes Tracker application. 1 2 3 4 5 Very Poor Poor Fair Good Excellent How would you describe your ability to use the Actel Joy tablet? 1 2 3 4 5 Very Poor Poor Fair Good Excellent How would you describe your current quality of life? 1 2 3 4 5 Very Poor Poor Fair Good Excellent IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 44 How happy are you with your current health? 1 2 3 4 5 Very Unhappy Unhappy Neutral Happy Very Happy I feel I have better management of my type 2 diabetes. 1 2 3 4 5 Strongly Disagree Neutral Agree Strongly Disagree Agree I know what my HbA1c goal is? Yes NO goal_____________ Figure G1. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 45 Appendix I Fish Bone Diagram Figure H1. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 46 Appendix J Data Collection Tool Appendix J GANTT Chart Figure I.1 IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 47 Appendix K GANTT Chart Task 1: IT adding apps on tablets DNP Students Task 2: provide pre test to participants DNP Students Task 3: educate each participant on use and functionality of DNP Students the application/ use Task 4 : Obtain HbA1c levels in charts for September to mark DNP Students for baseline Task 5: review expectations with participants and staff in DNP Students relation to QI project and goals Task 6: follow up with participants monthly to identify barriers NPs, Nursing Staff, DNP Students or implementation procedures that require fixing Task 7: Update Medical director monthly on implementation DNP Students process to quickly resolve and conflicts Task 8 Gather HbA1c results in December if applicable DNP Students Task 9: Review with each participant the process, complete DNP Students post assessment in December Table J1. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 48 Appendix L HbA1c levels Pre/Post Intervention N Pre-HbA1c Post-HbA1c Age 1 10.5 6.7 74 2 10.4 8.6 78 3 10.3 6.6 74 4 8.2 8.6 75 5 7.7 7.6 55 6 7.6 6.7 66 7 7.3 6.6 66 8 7.2 6 55 9 6.9 6.7 66 10 6.7 6.6 76 11 5.5 7 77 12 5.6 6.2 78 mean 94.9/12= 83.9/12= 840/12= AVG/Mean 7.91 6.99 70 Table K1. Average and Mean HbA1c pre and post project implementation. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 49 Figure K1. Graphical representation of HbA1c results pre and post intervention. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 50 Appendix M HbA1c Pre/Post Intervention Paired T-test Pre-HbA1c Post-HbA1c Mean 7.90833 6.99167 Variance 2.68447 0.71538 Observations 12 12 Pooled variance 1.69992 Hypothesized 0 Mean diff df 22 T Stat 1.72216 P(T<=t) one tail 0.04954 T-critical one tail 1.71714 P(T<=t) two tail 0.09907 T-critical one tail 2.07387 Table L1. Paired T-test results of HbA1c’s pre and post intervention. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 51 Appendix N Question 1 Survey Results N Pre-survey Post-survey 1 3 4 2 4 2 3 3 2 4 1 1 5 1 3 6 3 5 7 3 3 8 2 2 9 5 3 10 3 5 11 5 2 12 4 4 37/12= 36/12= AVG/ 3.08 3.0 Mean Table M1. Question 1: What is your current level of experience with tablets and app use with technology? IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 52 Figure M1. Graphical representation of question 1 pre and post survey responses. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 53 Appendix O Question 1 Paired T-test Pre-survey Post-survey Mean 3.08333 3 Variance 1.7197 1.63636 Observations 12 12 Pooled variance 1.67803 Hypothesized 0 Mean diff df 22 T Stat 0.15758 P(T<=t) one tail 0.43811 T-critical one tail 1.71714 P(T<=t) two tail 0.87623 T-critical one tail 2.07387 Table N1. Paired T-test results of question 1: What is your current level of experience with tablets and app use with technology? IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 54 Appendix P Question 2 and 3 Survey Results Glucose Buddy Actel Joy Tablet N Post-survey N Post-survey 1 3 1 5 2 2 2 3 3 3 3 3 4 1 4 1 5 3 5 3 6 5 6 5 7 4 7 3 8 1 8 2 9 4 9 5 10 1 10 3 11 3 11 2 12 4 12 4 34/12= 39/12 AVG/Mean 2.8 3.5 Table O1. Question 2 and 3 Responses with AVG/Mean: Please rate your satisfaction with tracking information with Glucose Buddy and Actel Joy Tablet (Respectively). Note: these questions were not included as part of the pre-survey as participants had no prior knowledge of the tablet devices or mobile application. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 55 Appendix Q Question 4 Survey Results N Pre-survey Post-survey 1 3 4 2 4 5 3 3 3 4 3 5 5 3 3 6 5 5 7 4 4 8 3 3 9 3 3 10 4 4 11 5 5 12 4 3 44/12= 47/12= AVG/Mean 3.67 3.91 Table P1. Question 4 responses with AVG/Mean: How would you describe your current quality of life? IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 56 Figure P1. Graphical representation of question 4 responses. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 57 Appendix R Question 4 Paired T-test Pre-survey Post-survey Mean 3.66667 3.91667 Variance 0.60606 0.81061 Observations 12 12 Pooled variance 0.70833 Hypothesized 0 Mean diff df 22 T Stat -0.72761 P(T<=t) 0.23726 one tail T-critical 1.71714 one tail P(T<=t) 0.47453 two tail T-critical 2.07387 one tail Table Q1. Paired T-test results of question 4: How would you describe your current quality of life? IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 58 Appendix S Question 5 Survey Results N Pre-survey Post-survey 1 3 4 2 4 4 3 2 3 4 2 5 5 3 3 6 5 5 7 3 4 8 3 3 9 2 3 10 4 4 11 3 5 12 3 3 AVG/ 37/12=3.08 46/12= 3.83 Mean Table R1. Question 5 responses with AVG/Mean: How happy are you with your current health? IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 59 Figure R1. Graphical representation of question 5 responses IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 60 Appendix T Question 5 Paired T-test Pre-survey Post-survey Mean 3.08333 3.83333 Variance 0.81061 0.69697 Observations 12 12 Pooled variance 0.75379 Hypothesized 0 Mean diff df 22 T Stat -2.11598 P(T<=t) 0.02295 one tail T-critical 1.71714 one tail P(T<=t) 0.0459 two tail T-critical 2.07387 one tail Table S1. Paired T-test results of question 5: How happy are you with your current health? IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 61 Appendix U Question 6 Survey Result N Pre-survey Post-survey 1 3 4 2 1 4 3 2 3 4 3 4 5 1 2 6 5 5 7 3 4 8 3 3 9 4 4 10 4 4 11 3 5 12 4 3 36/12= 45/12= AVG/ 3 3.75 Mean Table T1. Question 6 responses with AVG/Mean: I feel I have better management of my type 2 diabetes. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 62 Figure T1. Graphical representation of question 6 responses. IMPLEMENTATION OF DIABETES TRACKING APPLICATIONS INTO 63 Appendix V Question 6 Paired T-test Pre-survey Post-survey Mean 3 3.75 Variance 1.45455 0.75 Observations 12 12 Pooled variance 1.10227 Hypothesized 0 Mean diff df 22 T Stat -1.74982 P(T<=t) 0.047 one tail T-critical 1.71714 one tail P(T<=t) 0.09409 two tail T-critical 2.07387 one tail Table U1. Paired T-test results of question 6: I feel I have better management of my type 2 diabetes.