NURS FPX 9040 Assessment 1 DNP Project Proposal and PICOT Question Development

Table of Contents

Improving Glycemic Control in Adult Patients with Type 2 Diabetes Through Implementation of a Structured ADA Diabetes Follow-Up Protocol in an Outpatient Primary Care Setting. 5

Practice Problem.. 5

Project Site. 8

Project Population. 10

Evidenced-Based Interventions. 12

Role of the Project Lead. 16

Roles of Other Team Members. 17

Literature Synthesis. 18

Analysis of Evidence. 20

Theme 1: ADA Guideline Adherence and Clinical Practice Standards. 22

Theme 2: Nurse-Led Interventions and Staff Competency Development 24

Theme 3: Diabetes Self-Management Education and Support Interventions. 26

Theme 4: Technology-Enhanced Diabetes Care and Remote Follow-Up Protocols. 28

Synthesis of Findings. 30

Implementation Plan for the Intervention. 31

Conceptual Model 33

Data Collection and Analysis. 35

Ethical Considerations. 37

Project Results. 39

Project Outcomes. 40

Recommendations. 43

Summary. 44

Appendix A.. 58

Demographic Characteristics and Baseline HbA1c (N = 20) 58

Appendix B.. 60

HbA1c Outcomes Across Measurement Time Points (N = 20) 60

Appendix C.. 62

Follow-Up Adherence and Visit Completion Data (N = 20) 62

Appendix D.. 64

Nursing Staff Competency Assessment Results (N = 8) 64

Appendix E.. 65

Self-Management Behavior Checklist — Week 8 (N = 20) 65

Appendix F. 67

Summary Statistics: Project Implementation Outcomes. 67

Improving Glycemic Control in Adult Patients with Type 2 Diabetes Through Implementation of a Structured ADA Diabetes Follow-Up Protocol in an Outpatient Primary Care Setting

High levels of glycemic control in adults with T2DM are a critical practice gap in the outpatient primary care setting that creates missed opportunities for patient education, medication reviews, and prevents complications. Only 36% of the adult patients at the project site had an A1c level under 7% (the target guideline) compared with 42% having an A1c level over 9%; this is significantly worse than the national averages for adults with diabetes (30% with poor glycemic control and less than 20% with optimal control). Although the American Diabetes Association (ADA) has guidelines on its follow-up program for nurses and staff competency as well as structured patient education, there are some unmet implementation needs throughout primary care settings. The PICOT question for the project is: With the diabetes follow-up protocol developed by the ADA (I), as compared to current practices (C), how will it affect glycemic control (O) over 8 weeks (T) for nursing staff caring for an adult patient with diabetes? A follow-up protocol that is structured and has been adjusted to meet the needs of ADA, along with competency building among staff and education for patients about their self-management for chronic diseases, will yield clinically relevant improvements in glycemic control and improve the evidence-based aspects of chronic disease care within the outpatient primary care setting.

Practice Problem   

Chronic disease management (CDM) in OP-PC should be systematic and based on evidence, and it is important to tackle the chronic, persistent gap in glycemic control of adults with type 2 diabetes and health system benchmarks. Hemoglobin A1c levels were collected at the site, and 42% of adult patients had a value greater than 9 (APRN), and only 36% had a value less than 7 (APRN). The national-level site performance data is in line with global data, where almost one-fifth of adults with diabetes have sub-optimal glycemic control, and almost a quarter of adults with diabetes in the world have not attained HbA1c <7% (Adjei et al., 2025; Dinavari et al., 2023). In the U.S. and Europe, 25% of adults have a hemoglobin A1c level > 9%, which means that they have very poor metabolic control.

Two sets of factors—behavioural and demographic—are the main causes of poor glycemic control in adults attending outpatient diabetes clinics, indicating that early identification of those at risk of poor glycemic control and use of structured clinical intervention to enhance glycemic control are important. The information gathered from the site is quantitative data, which can provide a baseline from which quality improvement strategies can be measured at the practicum site. A thorough assessment of the current workflow, process flows, staffing, and care coordination programs in the clinical setting is needed to comprehensively determine causal factors that contribute to poor glycemic control. The project site audit found that key challenges to the process that were found to be consistent across sites were poor scheduling, infrequent structured follow-up, and variability in the education provided that led to sub-optimal glycemic outcomes. The absence of a standardized,

protocolized follow-up pathway resulted in inconsistent processes for scheduling follow-up appointments, the inconsistent use of EHR reminders, and the lack of coordination among the various disciplines for timely medication adjustments and tailored education for those at highest risk of complications. A data completeness check of follow-up visits and EHR audits of documentation completed also identified process failures systemically in scheduling visits and proactively communicating with patients. Previous generalized diabetes education courses and individualized diabetes check-in calls over the phone were sporadic and had no systematic evaluation system, which resulted in uneven teaching quality and a lack of patients’ understanding of the material taught. The absence of a follow-up pathway that is protocolized, therefore, was confirmed as the main modifiable factor that led to the identified practice gap through the comprehensive needs assessment.

Any interventions needed or planned to focus on quality improvement efforts for chronic diseases will have to pay close attention to the magnitude of the impact for each of the various stakeholder groups affected by the intervention to merit timely and systematic intervention. A poor glycemic control environment unfavorably impacts the following primary stakeholders: nursing staff, adults with diabetes, and organizational leaders, and there are known increased hospitalizations, use of health care systems, and burden of preventable diabetes complications such as heart disease, neuropathy, etc. Evidence of reduction in HbA1c levels between approximately 0.4 and 0.9 percentile points for all types of outpatient primary care settings for structured nurse-led interventions is sufficient to justify the clinical timeliness of reducing the use of these types of interventions, which were shown to be highly effective in self-management at decreasing HbA1c levels (Sun et al., 2025). Therefore, addressing the practice gap was both a need and an organisational strategic priority in keeping with the mission of the site for the provision of accessible, evidence-based primary care

Project Site

Structured interventions for chronic disease management are being implemented in primary care clinics that include various types of services, are located in urban settings, and do not provide inpatient care. One example is the primary care clinic in NYC that was the focus of the project and was in the outpatient setting. The clinic serves a variety of adults with a diverse ethnic/cultural and socioeconomic patient population. Seeing as about 60% of patients at the clinic have chronic diseases like diabetes and hypertension (APRN, personal communication, November 2025), it is clear that there is a significant burden of these diseases in the clinic. Clinics will have 6 examination rooms, 2 private rooms for counseling, and a virtual business and patient remote monitoring function enabled via telehealth platforms in workstations.

There are six Healthcare Professionals (HPs): nurse practitioners, medical assistants, a care coordinator, and a health educator who are responsible for handling patient care and patient care-related workload. There are a number of office staff, along with six HPs (nurse practitioners, medical assistants, a care coordinator, and a health educator), responsible for handling patient care and healthcare-related workload. The purpose of the clinic is to promote the health of the community by offering primary care services that are accessible, evidence-based, and good for preventing health issues.

As a result, the clinic is a suitable location for a structured quality improvement project for diabetes. Reading the setting in which a practice site will take place will allow the reader to appreciate the need for a quality improvement project at the right time and in the right place as a response to a clinical problem identified. The health education, health care continuity, and chronic disease management are all important topics in the clinic. Having a structured process in place for diabetes follow-up and focus on health teaching, continuity of care, and diabetes management of chronic conditions provides an opportunity to leverage existing processes with no major restructuring of organizations. The clinic employed electronic health records (EHRs), enabling the organization to document patient progress, provide scheduling, and maintain more detailed patient records. There was already a system in place for staff to educate about the medication and provide reinforcement of the medication, and the standardized system would simply support the current system, but not be an additional burden. The fact that there was a gap in practice was acknowledged by the leadership, and a decision was made to prioritise the project as it had both potential clinical and potential financial impacts. Leadership realised that by stabilising their glycemic levels, the organisation would progress in meeting the quality and value-based care indicators and also against patient satisfaction criteria. The connection between the project and the current strategic plans of the organizations validated that the site they selected for the practicum project was a well-suited site for the quality improvement intervention.

In order to gain insight into the diabetes management process and how it had been problematic, leading to poor glycemic control results at the practicum site, a thorough literature search was conducted on the diabetes management process prior to the project. Most of the nursing staff’s diabetes care and education activities were through regular staff visits to the patients and general, provider-centred verbal counselling, but there was no equivalent formal, structured process linked to the two ways of providing diabetes care. An unstructured follow-up process resulted in different diabetes education being offered and poor communication of diabetes self-management strategies from the nurse to the patient. Notable issues with the process included the following: ad hoc scheduling and rescheduling; prompt use of EHR reminders; lack of multispecialty coordination; and the not-so-prompt review of patient follow-up data, which could have been used to timely adjust medications and provide targeted patient education to those at highest risk. Patients’ diabetes outcomes and adherence to recommended self-management behaviours have been found to be poorer in unstructured outpatient diabetes care settings compared to structured ones. Additionally, a standardized approach to a follow-up protocol and embedding it into EHRs has been found to decrease missed visits, delays to timely interventions, and lack of optimal diabetes management quality. The completion of a needs assessment (including data extraction from baseline data and staff interviews as well as chart auditing and auditing of data in the EHR) confirmed the need for an evidence-based diabetes follow-up protocol intervention for the clinic. Process failures are used to stress the importance of a diabetes follow-up program, based on a protocol, at the practicum site.

Project Population

Defining the project’s population is extremely important, as it will help ensure that quality improvement interventions are effectively targeted and have meaningful and measurable impacts. In the project, the project population consisted of only nurses who provide care for patients with T2DM in the outpatient primary care clinic; the intervention was aimed at raising the competency level of the nurses to implement the standardized diabetes follow-up protocol of the ADA.

 The education, clinical rotations, and previous experiences of the nursing team that participated in the project varied in terms of clinical experience and educational levels; hence, the approach to diabetes management and provision of diabetes education was not the same. At least 8-10 members of nursing staff were needed to ensure the competency of the team and the implementation of the standardized diabetes follow-up protocol to document meaningful progress in competency levels and follow-up of the standardized protocol. The nursing staff was profiled in detail prior to designing the QI intervention, which served as a framework to target, develop, and implement a competency-based feasible intervention to address QI.

The example laid out the environmental context of implementing the standardized diabetes follow-up intervention by highlighting common attributes among the nursing employees. The multi-disciplinary team of nurse practitioners included three, medical assistants two, a care coordinator one, and a health educator one who participated in the structured nurse practitioner competency development program. The common professional traits among the nursing staff served as a good foundation to create a quality improvement program on the intervention (ADA follow-up protocol).

Carefully defining inclusion and exclusion criteria for the nursing staff involved in the project enabled the project to keep the population focused, thereby making sure any advancement towards glycemic improvements was consistent with the improvement goals. The inclusion criteria for the project were nurses who work with adults with a diagnosis of type 2 diabetes, as these nurses play a key role in educating patients about diabetes, giving medication for diabetes, and/or following up for diabetes as part of their normal, routine, clinical duties in the clinic.

 The nursing staff will also carry out all of the above roles as well as actively work at the project site throughout the eight weeks of the project implementation phase and be actively and/or clinically involved in provider responsibilities related to the project’s ADA follow-up protocol goals. The nursing staff involved in administrative (not direct patient care) positions, nursing staff involved in support (not direct patient care) positions, or nursing staff who provided temporary and/or short-term employment (not providing adequate direct patient care) positions were not included in the project.

 The inclusion criteria, along with the exclusion criteria for the project, increased the internal validity of the project and ensured the results of the structured intervention would accurately represent the effect of the structured intervention on the nursing population targeted for the project

Evidenced-Based Interventions   

Successful quality improvement efforts need to include several intervention strategies to yield greater and more sustainable efforts in glycemic control than the individual components. Combined approaches that supported fidelity and outcomes while being scalable/culturally adapted/integrated with EHRs, and measured in an iterative manner, were well supported in the literature. The project used the diabetes follow-up protocol recommended by the ADA to help create a more consistent diabetes care process during an eight-week implementation. Healthcare professionals attended training sessions, where they learned about the pathophysiology of diabetes mellitus and how to effectively use EHR to monitor health outcomes, improve patient adherence and engagement, and improve health outcomes. (Fracso et al., 2022)

 The education plan included simulation sessions, case-based learning lessons, and peer mentoring sessions to ensure the diabetes management strategies discussed would be applied in the real world (American Diabetes Association, 2024). Continuous staff training was a key component of the implementation of continuous quality improvement, to support shared responsibility, consistency of clinical practice, and to develop a culture of constant improvement. To understand the barriers and how the training was impacting the participants, regular refresher sessions, peer discussion, and feedback cycles were put in place and incorporated to assist in exchanging good practices.

Evidence showing the effect of biweekly schedules in reducing HbA1c was used to determine the length of follow-up schedules. The ADA guidance was mostly about team-based, iterative care, which directly translated to the project’s eight-week intervention, which was structured. However, some differences in how it was implemented were necessary and required local adaptation of the guidance in terms of addressing health literacy and resource differences of the patient population. The systematic implementation of the ADA standards in the clinics, including in clinic workflows, served as the structure to enable achieving the measurable glycemic improvements over the entire duration of the implementation process. Managed and facilitated by a multidisciplinary team of health educators, care coordinators, and clinicians with the goal of distributing clinical care equally among the team members. The models that involved collaborative role-sharing between members of the same team led to similar reductions in hospitalization and improved adherence, supporting the clinical rationale for collaborative role-sharing between members of the same team in population-level diabetes care. The competency-oriented team training was complementary to the clinical team, leading to better coordination and fidelity of implementation of the different roles of intervention delivery in the clinic. Multidisciplinary approaches always resulted in a greater number of system-level changes, compared with single-provider educational interventions alone, across the different studies.

 However, smaller clinics may have a limited extent of scalability because of resource intensity and staffing issues if they do not have plans for reallocation of resources. Structural aspects of the intervention design were, therefore, multidisciplinary team-based care whereby all members of the team were provided with a consistent and equitable protocol delivery for the project site. Enrolled patient population effects of better patient-centered glycemic control and patient-centered outcomes in the context of self-management were highlighted as core patient-centered intervention(s) that would positively impact study findings. Asmat ran a multicenter randomized trial study, which found that HbA1C was significantly lowered and self-care behaviors improved when consistent, patient-centered education was provided. Fracso undertook a phenomenological study that outlined empowerment mechanisms of peer support and individually determined goals for the vulnerable participants. Telehealth follow-up was implemented, and automated EHR reminders were used to boost the availability and compliance of patients lacking transportation and mobility. Ezeamii’s analysis recorded the enhancements in national telemedicine implementation in the improvement of attendance rates of appointments and remote monitoring. However, digital access inequities and different health literacies have affected the impact of telehealth in different ways across socioeconomic status. Accurate short-term glycemic results were achieved with the use of telehealth to support structured follow-up programs with similar results as in-person visits. The tracking systems were based on EHRs to help schedule follow-up visits as well as identify overdue visits, and to make it possible to have a central repository of HbA1c results at the project site. Investment in training, redesign of work processes, and periodic audits were necessary for implementation to ensure the data quality and utility of the data during the intervention. EHR integration facilitated easy scaling of monitoring and was directly integrated with the outcome goals of the project, which focused on measuring outcomes. Interventions tailored for the language barrier and culturally specific patient over- and self-managing beliefs were offered to participants when they were enrolled. However, Wadi et al. (2021) found that interventions that included culturally appropriate changes to diet and approaches to engage family led to better results in reducing HbA1c levels. Goetz and Schork (2020) highlighted the concepts of personalized medicine to improve the applications of practice with an aim of being relevant both in rural and urban areas. Culturally targeted education was more effective in terms of longer-lasting behavior change across a broad range of populations as compared to generic approaches to education. Staff were given training through simulation to help further enhance both their skill in teaching and implementing diabetes education protocols. With web-based faculty training modules, Okemah et al. (2023) have shown that knowledge and efficiency in patient education were gained. Indicative of the effect of the didactic sessions, smaller learning retention was found in practical skills when compared to simulated learning through practical experiences (in comparative studies). Therefore, the project focused on simulation, observation of demonstrations, and competency checklists to ensure the staff’s competency and sustainability during the implementation period. Each follow-up appointment included behavioral goal setting and motivational interviewing to help patients make behavioral changes and maintain lifestyle changes. Culturally responsive approaches to education and behavior were incorporated into the structured follow-up protocol, which allowed intervention delivery to remain relevant, equitable, and responsive to the myriad of patients enrolled’s self-management needs.The use of peer mentoring and group support sessions was used to build on common experiences and social supports to maintain engagement in self-management.

 Qualitative results from Fracso indicated that there was a growing sense of confidence, problem-solving, and self-efficacy as a result of the consistent and structured group interactions. To maintain fidelity and expedite learning, an in-depth review of the data was conducted every two weeks, with adaptive change made throughout the project (Lin et al., 2022). Selections of patients who were motivated and the ability to implement it using the EHRs ensured that it was as useful as possible for as few resources as possible throughout the implementation process. The peer mentoring, group support, and iterative data review allowed for the intervention to be responsive, socially reinforced, and to maintain engagement with the patient throughout the entire implementation of the intervention over 8 weeks.

Role of the Project Lead

An effective quality improvement project requires scholarly and decisive leadership through systematic and logical designs, which are woven together to connect clinical knowledge/experience, interprofessional teamwork, and systems thinking throughout the process of implementing the project. The DNP student was responsible for creating a uniform ADA diabetes follow-up protocol, creating educational materials to guide the process of the follow-up, configuring the EHRs to support the protocol, and coordinating all of the follow-up’s logistics over an 8-week time span (APRN personal communication, November 2025). To effectively lead the evidence-based project, the project lead needed to frequently communicate with the organizational stakeholders, interprofessional team members, and academic mentors during the project implementation to maintain fidelity to the implementation process and to ensure the scholarly rigor of the project.

 The plan-do-study-act (PDSA) model helped make sure that the changes in the workflow during the implementation cycle were data-driven and transparent, and that iterative refinements for each implementation cycle adhered to subsequent cycles of the model (Abuzied et al. 2023). Ethical issues were addressed throughout the project, including CITI training and certification, IRB approval coordination, Health Insurance Portability and Accountability Act (HIPAA) de-identification of data, and consistent use of procedures to ensure informed participation in the project from all those involved. The scholarly rigor of the project lead, clinical expertise, and collaborative leadership during the entire process of implementation highlighted a very important role APRNs will play in securing sustainable outcomes of quality improvement in nursing practice.

Roles of Other Team Members

 For QI programs to be successful in an outpatient primary care setting, building clarity of the roles of interprofessional team members and assigning fair responsibilities for each to their team members is important, as is improving the provision of coordinated health services by all program elements. The preceptor of the site served as the clinical supervisor and APRN for this site; directly supervised implementation of the protocol; and was the key liaison between the DNP student and the organization’s leadership during the entire 8 weeks of the project. At each biweekly visit, nurse practitioners were able to reach the patient’s ADA-recommended follow-up standards, as they conducted a clinical assessment, educated, and counseled each patient individually. Being clear about roles on a quality improvement team is always shown to increase shared responsibility and fidelity to implementing evidence-based intervention. The care manager/coordinator is responsible for scheduling, logistics for telehealth, EHR activation of reminders, and attendance tracking in order to maintain high follow-up rates that meet goals. To deliver patient education materials, the health educator used culturally adapted materials for people who were enrolled in the program to address a variety of language and health literacy needs. All members of the team had rehearsed a clear role to ensure consistency and accountability with the project-specific evidence-based goals throughout its implementation. Given the need for implementation fidelity as well as scholarly rigor throughout the entire project, each individual on the team needs to have a different and complementary role in implementing the project. Medical assistants took down vital signs (VS) from patients, set up educational information, communicated effectively with patients, and documented information gathered during the patient’s biweekly appointments in the EHR. All educational sessions attended by nurses utilized standardized parts of the ADA follow-up protocol during patient visits, and nurses completed a fidelity checklist for each patient visit. While the value of interprofessional working and formal communication between those working in primary care to improve services is widely recognised, for quality improvement projects, this is particularly important for the ongoing success of a project in a primary care setting. Throughout each of the roles of the team, shared responsibility helps to ensure that the protocol of implementing the intervention is followed and helps identify if there are things that are holding the intervention process back early. During each step of implementation, the DNP student’s faculty mentor assisted with providing academic consultation in the review of the DNP student’s reports. Throughout the project, the interdisciplinary team members met the stakeholders every two weeks to allow for continued communication, transparency, and problem-solving among the members of the project team.

Literature Synthesis

ADA guidelines,” “diabetes follow up,” “self-management education,” and “primary care.” Combinations of words were made structured with the use of boolean operators: (“type 2 diabetes” OR “diabetes mellitus”) AND (“nurse-led” OR “nursing intervention” OR “diabetes self-management education”) AND (“glycemic control” OR “HbA1c”) AND (“ADA guidelines” OR “clinical practice guideline” OR “follow-up protocol”) AND (“nursing intervention” OR “follow-up protocol”). A properly designed and executed search strategy should result in a representative search of evidence that can be replicated and directly related to the clinical problem being addressed.

After initial searches of databases, a total of 362 records were found in all the databases accessed. The 308 articles included in the analysis after removing 54 duplicate articles were screened for title and abstract according to the following predefined inclusion and exclusion criteria. All publications were required to be peer-reviewed and published in English, involve an adult population, include any nurse-led intervention or established protocol for follow-up, and include measurable glycemic outcomes such as HbA1C levels.   

Each study that was retained was systematically assessed to determine the level of methodological quality and the clinical relevance by using the strength of recommendation taxonomy (SORT) framework. The framework focused on patient-centered measures like decreases in HbA1c, complications, and hospitalization avoidance. There are seven studies that were classified as SORT Level A for their high-quality randomized controlled trials, systematic reviews, and meta-analyses. Ten studies were included in the Level B category, and they had well-designed comparative effectiveness research, quasi-experimental or cohort investigations. Three studies were awarded Level C Clinical Practice Guidelines, Quality Improvement Projects, and Narrative Review. The distribution of the ratings of evidence quality showed that most of the evidence for structured nurse-led diabetes follow-up interventions, consistent with ADA clinical practice guidelines, was found in a variety of outpatient settings and had a moderate-to-high level of evidence.

Analysis of Evidence

The 20 studies that were retained provided consistent and convergent evidence for nurse-led implementation of ADA-aligned diabetes follow-up as an effective intervention to improve glycemic control, self-efficacy, and self-management behaviors in adult patients with type 2 diabetes  (T2D). The size of the effects found in the different investigations varied from small to generally large. Comparative studies of the nurse-led interventions showed that they achieved reductions in HbA1c of 0.25% to 1.69%, as compared to usual care comparator studies. Evidence shows that structured diabetes self-management education and support programs resulted. The mean differences of telephone-based nurse follow-up protocols were -0.59 (95% CI -0.85 to -0.34) for various clinical samples across a range of delivery settings. Six technology-enhanced follow-up delivery modalities were found to be clinically equivalent to traditional, in-person follow-up: via a telehealth consultation, via structured telephone coaching, and via peer-supported IM. The modalities significantly enhanced the patients’ access to, engagement with, and adherence to the self-monitoring procedures. The results of the different kinds of studies and their geographical location boost confidence in the clinical applicability of nurse-led diabetes follow-up interventions.

The literature reviewed was limited in some ways, with some identified gaps as follows: few data were available on the optimal follow-up frequency protocol and, in most cases, not enough long-term outcome data beyond 12 months were analyzed. There are also factors that prevented adherence to the ADA guidelines consistently, such as a lack of understanding about the guidelines among providers, a lack of cohesive workflows, and provisions for institutional accountability. Evidence gaps identified in this study further validate the scholarly contribution and utility of the structured and protocol-based quality improvement (QI) effort in an outpatient primary care setting. A thematic organization of findings allows for systematic review of the effectiveness of the different but interrelated components of intervention to contribute to the complexity of outpatient diabetes management.

Theme 1: ADA Guideline Adherence and Clinical Practice Standards

Achieving good glycemic control for outpatients in primary care depends on adherence to clinical practice guidelines: better care delivery is more organized and reliable, compared to fragmented and inconsistent care delivery. ElSayed found a significantly higher proportion of adults reporting to have target HbA1c levels when compliance was above 89.8%, compared with persistently poor metabolic outcomes in those who didn’t meet the target level at all, whose compliance rates were < 40% and > 89.8%. On a comparative basis, Tiwari and Aw identified some significant challenges to routinely delivering guidelines that were not being followed, which included inefficiencies along the workflow, provider knowledge, etc. Overall, the results indicate that there are problems at the system level as well as the provider level in implementing the ADA guidelines, compared to the nursing-driven protocols that are uniquely able to address some of these gaps. If follow-up is structured into a more consistent and systematic nursing protocol, appropriately translating published guidelines to measurable and consistent patient outcomes can be substantially enhanced.

Routes to reduce glycemic burdens to the level recommended by evidence will be implemented into nursing activities and become clinically meaningful. Abukhalil demonstrated significant improvements in achieving a 0.74% mean HbA1c reduction (p < .01) and the percentage of patients with a guideline-concordant antihyperglycemic prescription when compared to usual care within a patient-centered medical home. Likewise, and with greater significance, at twelve weeks Chen showed a reduction in HbA1c of 1.02% (p < .001), showing how effective structured follow-up visits in adherence to ADA guidelines and nurse-led medication review are. Combined and compared to non-structured interventions, these studies suggest that nurse-led, structured follow-up can facilitate more stable and clinically meaningful glycemia reductions to take place in an outpatient primary care environment.

However, systems of reinforcement, accountability, and frequent monitoring, in addition to following guidelines, are necessary in order to obtain optimal glycemic control. While interventions that aim for the adoption of guidelines have heterogeneous results, structured reinforcement interventions have more standardized results as compared to those that do not include structured reinforcement. Comparatively, adherence to one component cannot compensate for diabetes management, which has multiple components, as the authors of this study, ElSayed (), also showed that only 23% of adults had target blood pressure and blood lipids, and were nonsmokers. In contrast to provider-level knowledge gaps reported by Tiwari and Aw, the data point towards the fact that it is not sufficient to simply have access; knowledge gaps need to be addressed in order to see effective application in practice. Similarly, Abukhalil observed a lack of preventive screening or pharmacotherapy, whereas there was an expectation for full care. In order for glycemic improvement to be sustained, ADA standards should be a part of a nurse-led, accountable process that incorporates the use of a structured education program, ongoing monitoring, and follow-up of the individual on a personal level that is more comprehensive in nature and thus more effective in diabetes care.

Theme 2: Nurse-Led Interventions and Staff Competency Development

It is an evidence-supported approach for ensuring sustained continuity in patients’ engagement with care and effective interprofessional working, to enhance the management of their glycemic control. The models emphasize continuous interaction and support in a patient-centered fashion as compared with the traditional way of physician-centered interaction. The Importance of Nurse-Managed Diabetes Education Programs (Dailahstudyn) confirmed that diabetes education programs under the nurse’s management provided the patients with improvements in terms of knowledge, self-help skills, psychological factors, and glycated hemoglobin test (HbA1C).

These improvements have been achieved by the use of knowledge durabilities and motivational support provided to the patients during the educational process. On the other hand, the models that have limited follow-up don’t see such continuous improvement. After six months, patients who were followed by a nurse had significantly better knowledge, anxiety, depression, and self-care activities compared to patients who were followed with routine care (p < .001), stated Jiang. Comparatively, the multifaceted education strategies to improve nursing competencies yielded improved levels of HbA1c, blood pressure, and lipid levels in a consistent fashion when the role of the nurse and the education the nurse received were clearly defined and systematic. When nurse-led interventions are implemented within a setting that supports nurses’ autonomy and accountability, they lead to consistently and multidimensionally better outcomes for patients, especially when compared to less structured care settings.

Staff competencies are developed to offer good support in providing consistent diabetes care with a focus on the patient in the outpatient environment. Based on comparison with the low training opportunities settings, the targeted education significantly increased the nurse confidence in applying the ADA protocol, which in turn resulted in better adherence to the guidelines of glycemic monitoring, and higher quality nurse education of patients. Subsequent to this, the Abukhalil study demonstrated the system-wide benefits of competency integration with the finding that follow-up with ADA protocol in team-based primary care resulted in an average of 0.74% decrease in HbA1c levels, along with better prescribing concordance and care coordination. Likewise, however, a coordinated, skillful mode of care delivery was found to be crucial, as contrasted to fragmented care delivery.

By strengthening interprofessional interactions and having well-defined nursing roles, nurse-led diabetes management interventions can improve the effectiveness of the interventions across the primary care system. Collaborative care models allow for more comprehensive care as compared to isolated care or care models focused on a single discipline. Using structured educational and multimodal engagement strategies in nurse-led projects was shown by Jiang et al. to have been successful in decreasing anxiety and depression and enhancing glycemic control, compared to less integrated nurse-led projects that emphasize only clinical indicators. Secondly, nurses’ daily interaction with patients was found to give doctors an opportunity to provide continuous education and motivation. Dailah’s study showed that nurses can do a much better job. Overall, interprofessional working of nursing roles in structured teams results in better and more sustainable diabetes management outcomes than single-discipline working, which is not possible to achieve without the nurse working within an interprofessional team.

Theme 3: Diabetes Self-Management Education and Support Interventions

Structured diabetes self-management education and support (DSMES) programs are the key way that nurse-led follow-up is achieved in the translation of clinical recommendations to physiological and behavioral changes. The systematic and patient-centered approach of DSMES offers a more structured and systematic approach to behavior change than unstructured or routine approaches. A multi-center randomized controlled trial showed that the mean decrease in HbA1c was 0.25% (p = .03), and there was significant improvement in self-efficacy and self-care in the intervention group, compared to the routine care group, which may not be intense enough to effect the behavioral shift.

Mediation analysis also demonstrated that behavioral improvements were the most important factors in glycemia. Structured DSMES programs also generally showed a greater effect on glycemic control than routine care through a systematic review and meta-analysis of the 19 trials (Yimer ), demonstrating a statistically significant association of DSMES with HbA1c. When it comes to overall results, patient-centred education programmes with some individual counselling and reinforcement show greater reliability and measurability of improvement than do standard care programmes.

The key factors of the length, intensity, and consistency of DSMES programs are crucial for long-term patient outcomes. If an educational program lasts for a longer time period, there are more meaningful results and a longer-lasting impact than in a one- or two-day program. In a systematic review and meta-analysis of 34 studies with 7,603 participants, Fracso concluded that interventions that focus on improving quality of life and self-efficacy and reducing depressive symptoms consistently are more effective with interventions lasting over six months. Similarly, although more compelling, Fracso demonstrated qualitatively that chronic disease self-management (CDSM) programs moved patients’ motivations, community feelings, and commitment toward the benefits of self-management – benefits that are generally not obtained from brief interventions. Furthermore, Chen showed that the bi-weekly telephone coaching in conjunction with the nurse-led follow-up led to greater self-efficacy and frequency of blood glucose monitoring than either nurse-led follow-up or no follow-up, and that it was more effective in triggering behavioral pathways that result in the physiological improvements. Hence, programs that promote continuous connections with healthcare, reinforcement, and continuity in the process of diabetes management are more effective in providing lasting results than shorter and more fragmented interventions.

Educational content that is culturally responsive and contextually appropriate further supports the effectiveness of DSMES programs. Culturally adapted programs achieve a more equitable and effective result as compared to generic, one-size-fits-all programs. There was significant heterogeneity among the studies reported by Yimer, which identified differences because of the cultural adaptation of programs, educator preparation, and the level of program comprehension by patients’ health literacy. Programs that were tailored were more effective than those that weren’t, whereas programs that were tailored to patients in specific populations showed greater effectiveness. Sun stated that modules that are not culturally adapted are less effective than those that do include aspects of the community culture, such as the dietary habits, time of taking medicines, and health beliefs surrounding medicines. Asmat also confirmed that culturally adapted nurse-led interventions lead to lasting improvements, which are mediated by self-efficacy, which explained a considerable variance of the outcome. Culturally responsive content, structured reinforcement, and a longer follow-up period led to a greater degree of effectiveness and equity in glycemic control as compared to interventions that were not tailored.

Theme 4: Technology-Enhanced Diabetes Care and Remote Follow-Up Protocols

Using technology-driven approaches to provide services offers greater access and scalability for diabetes follow-up by nurses. Technology-based methods enable easier access to more people while maintaining clinical effectiveness, compared to traditional in-person methods. In a systematic review and longitudinal meta-analysis of 13 studies (2,294 patients), nurse-led telephone interventions reduced mean HbA1c levels by a fixed amount of -0.59 (95% CI -0.85 to -0.34, p < .00001); optimized protocols (16 contacts of 20–25 minutes at biweekly intervals) reduced mean levels to -1.23 (p < .001).

While less structured and purposeful forms of contact are found in less frequent or less consistent studies, the results of the more regular and consistent models emphasize the need for regular and standard contact. By conducting a 24-month cohort study, Koo’s study confirmed that HbA1c levels remained significantly decreased over an extended period of time, with an average level between 7.33% and 7.62% HbA1c achieved through a remote self-care program, involving a telephonic nurse with the support of a smartphone. In sum, technology-based nurse-led follow-up has shown a sustained level of engagement with patients and clinically relevant patient outcomes in glycemic control, compared to traditional follow-up.

Digital tools, including the use of automated reminders, virtual consultations, and structured messaging, were cited as ways to improve engagement and access when compared to more traditional care delivery models that may be hindered by time and place. In conclusion, technology-enhanced care equates to a more flexible and scalable pathway that can achieve more durable glycemic control as compared to standard follow-up approaches, if these are used in a structured manner.

Although the results have been consistently good, obstacles to the use of technology-enhanced follow-up models need to be overcome in order to make them effective and available to everyone. While it is possible to implement this as an ideal, there are problems of low digital literacy, lack of devices, and socioeconomic differences in the real world. But Ezeamiistudy noted that these restrictions could have a negative impact on the utilization of telemedicine, especially for vulnerable populations, while those with more digital access and skills are likely to benefit more from telemedicine care. In contrast, Graue said, a 12-month window is too short to see behavior change happen with an empowerment-based intervention, as longer and more adaptive engagement windows do. The degree of heterogeneity was high (I² = 87%) across the studies, making direct comparisons of the effectiveness difficult based on the different protocol designs, patient characteristics, and measures of efficacy. In addition, a second study by the University of Colorado, Boulder, indicated that digital interventions might not be equally effective across various populations compared to interventions with a more context-based approach that take into account patient engagement levels and/or needs. In this context, to deliver diabetes care equitably and effectively, disparities need to be addressed, where possible, through the standardization of protocols and through ensuring that access to technology-enhanced diabetes care is high.

Synthesis of Findings

Looking at the evidence across the categories, an overall comprehensive conclusion was that it is possible to take evidence-based decisions for the creation of structured nurse-administered diabetes follow-up interventions for outpatient primary care where the evidence is clinically actionable. All studies included in the analysis cited a positive overall trend (improvement) in HbA1c results for people with diabetes in all types of delivery models, geographic locations, and study designs examined. This encompasses a large spectrum of effect sizes, from small to modest reductions of -0.25% in HbA1c with short-term RCTs, to perhaps clinically meaningful reductions of >-1.5% in effective HbA1c with large structured diabetes programs over a longer period of time. Adherence to ADA guidelines, nurse-led competency development, patient-centered education, and technology-enhanced follow-up will help to achieve improved and more sustainable levels of HbA1c than any of the individual elements alone.

On top of these, evidence synthesis confirmed that the area is relevant to the proposed quality improvement project, and a review of the existing research revealed a number of gaps. At first, evidence synthesis methodology evolved from simply following the guideline steps to meta-analysis; no longitudinal research existed that was longer than twelve (12) months; few studies explored variation in follow-up frequency or technology-enhanced service delivery; there was little analysis of cost-effectiveness; and culture-specific issues around access to technology-enhanced service delivery models received little attention. For this reason, a series of implementation studies should be conducted to further research the results in the context of multiple outpatient clinics and studies, which should be subject to rigorous evaluation to assess their methodological quality in the context of methodological quality assessment. Evidence gap closure will enhance knowledge and help to meet practical aims and outcomes of sustainable, nurse-led, chronic disease management.

Implementation Plan for the Intervention

The fidelity, replicability, and uniformity of a structured quality improvement intervention necessitate a sequential plan that is coherent, systematic, and carefully planned and implemented throughout all phases of the project. The implementation process took place over 8 weeks and was implemented via a phased implementation process: Weeks one and two involved gathering baseline HbA1c data, follow-up completion rates for patients, and the competency score provided by nurses (based on competency checklists) from the electronic health record (EHR) system to create measurable pre-implementation benchmarks. Rigorous baseline data collection is a key component of the quality improvement frameworks and is essential to assess the effectiveness of the intervention and to demonstrate a clinically significant difference over time. Using accurate pre-intervention benchmarks helps project teams recognize areas of weakness in achieving the project’s goals, establish realistic goals, and establish measures for progress towards the organization’s goals.

The training covered two weeks of structured staff education, including the following: simulation and case-based learning training sessions for nursing participants on Diabetes Pathophysiology, the updated ADA Diabetes Management guidelines, the principles of medication reconciliation, and documenting into EHRs; and peer mentoring sessions for the 20 participants. The training included two weeks of structured staff education, which included the following: simulation and case-based training for the 18 nurses on the following topics: Diabetes Pathophysiology, updated ADA Diabetes Management guidelines, principles of medication reconciliation, and documenting into EHRs; and peer mentoring sessions for the 20 participants. All nursing participants completed competency checklists at baseline and post-education, as well as knowledge assessments at baseline and after completing the education sessions, to confirm that they possessed the necessary competency level (at 80% or more) before delivering the patient-centered component of the intervention. Phased instructional and training structure ensured accountability, consistency, and fidelity for the entire 8-week implementation of each of the components in the intervention.

Structured interprofessional collaboration was used to implement the PDSA methodology to achieve the fidelity needed for the remaining weeks. Structured bi-weekly patient follow-up visits were provided in weeks 5 and 6, as were follow-up visits via telehealth for patients who struggled with transportation, and competency assessments at the midpoint of the program to make adaptive changes to the educational delivery strategies where necessary if patient engagement and/or protocol compliance were found to be lacking. There is significant evidence that using real-time performance monitoring during quality improvement efforts helps identify obstacles to implementation early in the effort and helps make sure performance gets corrected in response to the information. Practicing interprofessional collaboration and communication is a frequent feature of maintaining quality improvement in the primary care setting and chronic disease management – particularly for diabetes.

Throughout weeks 7 and 8, the EHR-based tracking systems were actively managed, monitored, and used to schedule follow-up visits, identify overdue patient visits, centralize HbA1c data, and develop performance dashboards that could be used to monitor process indicators and outcomes in real time at the practicum site. In week eight, follow-up activities were completed for all patients, and the fidelity of the processes was confirmed by means of structured checklist reviews, while a comprehensive outcome analysis process ensured that a thorough review of all patient-related outcome data (glycemic, competency, and behavioral domains) was performed before and after the intervention. The iterative and 8-week implementation plan ensured that the intervention was clinically relevant and responsive to evidence-based practice in order to provide clinical improvements for the practicum site in glycemic control.

Conceptual Mode

The frameworks for quality improvement offer the groundwork for implementing, evaluating, and adapting EBI to be the best it can be, through iterative systems and iterative cycles of

learning/adjustments. A chronic disease management model called PDSA was selected to guide the project, due to its previous success with chronic disease management. The PDSA comes from the theory of quality improvement developed by W.E Deming and is about iterative learning/ refining based on the process of a complex system. Effective frameworks for quality improvement involve repeated cycles of continuous evaluation of chronic diseases and lead to measurable results. During the ‘plan’ phase, the team identified that the main focus would be poor glycemic control in adult patients, developed measurable outcome targets, and developed a staff competency based Diabetes follow-up protocol and staff development program based on the ADA. The ‘do’ phase got the intervention going, with simulation training with staff, weekly patient follow-up visits (including Tele Health), and activation of EHR dashboards in all intervention phases. PDSA’s approach is both evidence-based and iterative, which will ensure that the evidence related to measurement data will be the basis for all implementation decisions, and that the overall goal of achieving a higher and more sustainable level of glycemic control will be reached by the standardization of the nurse-led protocols.

The evaluative and adaptive part of the PDSA model was offered on the PDSA phases above to ensure fidelity/quality of the intervention and enhance learning throughout the 8-week implementation. During the ‘study’ period, monthly reviews were done using formative data (HbA1C trend, staff competency scores, follow-up visit completion, and errors in the EHR) to get a sense of progress toward targets and build adaptive strategies for any challenges identified with the formative data. The iterative approach of the PDSA model allows healthcare teams to adapt, respond, and adjust to the challenges that they encounter during implementation and to change the original protocol based on evidence measurement. The findings from structured nurse-led diabetes management programmes that led to the successful implementation of PDSA cycles showed mean HbA1c level reductions of 0.5%-1.0% due to systematic testing of workflows and iterative modifications of the protocols (compared to the current project). The ‘act’ phase involved improvements to the content delivery for adult education lessons, to the scheduling processes within the clinic, and to the telehealth outreach to patients engaging in decreased levels, based on lessons learned during formative analyses, and will put successful methods into practice as part of the routine clinic workflow following implementation. Because the PDSA is so adaptable, has measurable processes, and has continuous feedback mechanisms, making PDSA the obvious quality improvement methodology for this project, it is also very obvious that it will work well as the methodology to recreate, measure, and sustain improvements in outpatient glycemic management.

Data Collection and Analysis

Choosing the appropriate design and having quality data collection procedures are essential to obtaining meaningful, clinically relevant, and interpretable outcomes from quality improvement efforts. The project was designed as a pre/post evaluation to be able to obtain baseline and follow-up data from all 20 adult type 2 diabetes patients and 8 nursing staff members at the facility. Structured intervention can be evaluated by a pre-post design, which presents a pragmatic and feasible evaluation method to compare the results of the same group of participants over defined time periods and is one of the most common and accepted methods that have been used. The pre-post design is a common study design of quality improvement projects in outpatient chronic disease management, and the results of these projects are consistently sensitive enough to detect clinically meaningful improvement in patient outcomes. To compare all the post-intervention measures with a specific and measurable baseline, baseline measurements of the facility’s electronic health record (EHR) system were obtained for the nursing staff competence tests and completion of follow-up visits before the intervention started. Prior to start, this project was approved by the IRB, and any coding of participants’ names (and compliance with the HIPAA guidelines regarding participant confidentiality) for the purposes of data collection and analysis was adhered to. Outcome evidence for the project was obtained through baseline data extraction that was standardized and based on established quality improvement methodologies and a strong pre-post design.

 The first step toward evidence of quality improvement (both clinical and non-clinical) that is credible and dependable is to establish appropriate metrics and use valid/cconsistent instruments of record. The primary outcome measure was the mean baseline and week 8 HbA1C level obtained via point-of-care lab tests embedded in the clinic’s electronic record system. A significant difference in a patient’s HbA1C level was defined as a change of at least 0.5 percentage points from the baseline HbA1C level as a result of the follow-up protocol recommended by the American Diabetes Association. To assess the effectiveness of a structured intervention, both pre-project and post-project quality improvement studies should use instruments that have been established to have high content validity and measurement reliability for the outcomes. Validation and reliability of the outcome measurement instruments were critical to the quality improvement entity’s evidence base upon which clinical decision making, protocol revisions, and planning for sustainability would be based. The secondary outcome measures were: Competence test scores of the nursing staff (Using a validated competency assessment instrument for diabetes management pre- and post-training). The proportion of patients who complete follow-up visits (scheduling audit logs in the EHR system). Structured behavior checklists to evaluate insulin adherence, frequency of blood glucose monitoring, and patients’ participation in self-management of diabetes. The entire measurement tool was assessed by an expert panel prior to implementation to ensure content validity, and guidelines were provided to ensure identical data collection procedures at each measurement time for the 8 weeks of the project to ensure that the outcomes collected would be reliable and valid outcomes. The wide variety of primary and secondary glycemic, competency, and behavior measures will give a full dimensional picture of the intervention.

Ethical Considerations

For the quality improvement projects, ethical principles need to be carefully considered to not only protect participants and maintain the confidentiality of data, but also to ensure institutional compliance at each step of the way (i.e., during planning, implementing, and evaluating). An IRB study of the project was carried out before the project was implemented, and the project was found not to be “human subjects research”. Based on this, the IRB agreed that the project was not subject to full IRB review, as it was aimed at enhancing the practice, rather than assessing the generalizability of knowledge. When choosing to conduct a quality improvement project in a health care institution, one may wonder if such work is human subjects research. Quality improvement projects in health care institutions are often thought of as non-human subjects research because they involve a focus on improving existing care delivery, the use of retrospective clinical data, and the use of evidence-based practices. Just checking fulfillment of accepted institutional review standards and federal ethics regulations is not enough to satisfy ethical duties in the performance of a nurse-led quality improvement project.

Furthermore, ethical compliance of all methods and procedures that are followed in the collection of all data from the project must be adhered to as outlined in the guidelines for IRB review, with all Collaborative Institutional Training Initiative (CITI) certification requirements met, prior to being permitted to conduct quality research (in keeping with the ethical standards of practice in the clinical setting). During the project (8 weeks), all activities regarding data collection, analysis, and reports were based on the IRB determination and the completion of all required CITI certifications in order to ensure the activities were conducted in an ethical manner. Working within the framework of defined ethical guidelines for the practice of the project helped to develop the trust, integrity of the institution, and credibility of the scholars at every stage of project implementation and evaluation of the outcome data.

Confidentiality of all patient information and space for storing all information and documentation related to the project are some of the more significant ethical concerns that must be addressed throughout a project. To ensure that no individual patient could be identified from the documents, results, or sharing of materials created during the 8-week implementation period of the project, all identifiers that were collected during the course of the project for the purpose of the quality improvement project were replaced with coded identifiers prior to any data extraction, analysis, or reporting activities. According to the HIPAA rules, all individually identifiable health information (IIHI) gathered as part of a quality improvement project in a health care facility should be de-identified, securely kept, and only accessible to authorized personnel. De-identification of IIHI in quality improvement projects is a critical ethical protection that will help uphold individual privacy rights and comply with federal regulations for the protection of confidential data. During the 8-week implementation period, all electronic data and competency assessment records were kept on password-protected and/or encrypted devices, which were only accessible to the clinic preceptor, the project lead, and designated project staff, and all hard copy data were stored in locked data cabinets with restricted access during implementation. Conformity to each de-identification process was checked weekly, and any failure to comply with data integrity and established compliance processes identified during the check was corrected immediately, as necessary. Properly executed, all data security and de-identification processes confirmed that the project was conducted with the highest ethical standards and gave credible evidence for a shift towards sustainable quality improvement in the management of diabetes in the outpatient sector.

Project Results

The primary outcome showed a clinically meaningful mean reduction of 1.52 percentage points over an eight-week period of treatment, or a change from a baseline level of 9.95% to an average post-intervention level of 8.22% (which is well below the post-intervention success threshold of 8.75%), a value significantly higher than the success threshold of 0.5 percentage points before implementation of the QI intervention. The patients fully participated in the structured ADA diabetes follow-up protocol, with 89.2% of scheduled follow-up visits completed during the eight-week period of the QI intervention.

Also, the fact that patients and nursing staff completed the bi-weekly follow-up visit schedule demonstrates the existing operations’ capacity to accommodate the bi-weekly visit schedule. Few patients (10%) reached an HbA1C level of less than 7% at the conclusion of the intervention period, although there was significant glycemic improvement, and many other aspects of reaching complete targets were likely to have contributed, such as a longer intervention period outside of the practicum. Overall, the primary outcome finding showed great promising improvement in glycemic control for adult patients with type 2 diabetes at the project site following the implementation of a standardized, ADA-compliant nurse-follow-up protocol that had a clinically and dimensionally significant impact. Secondary outcome results also confirm the wide and multi-dimensional effects of the structured intervention across five domains of nursing staff competency, patient self-management engagement, and nursing staff delivery fidelity, and across an eight-week period of the structured intervention. After the structured training program, the mean competency of nursing staff jumped from 59.0% at the beginning of the training to 85.4% at the end of the training, reaching the threshold of 80% or more for independent protocol delivery for seven of the eight nursing staff members.

Self-management engagement scores were 7.4 out of 10 at 8 weeks, 70% of patients in the intervention group took medication 100% of the time during the structured 8 weeks, and 65% of patients did routine blood glucose monitoring throughout the intervention period. The transportation barriers were also noted as an unexpected outcome of the study, with 67% of the scheduled visits to the clinic completed, which adversely affected the glycemic trajectory of some patients enrolled in the study and the clinical importance of integrating a structured diabetes follow-up protocol while providing an equitable and alternative means to provide durable outcomes for some patients. Finally, the secondary outcome results showed results in all areas of the clinic, operations, and behavioral dimensions with similar and consistent gains, and confirmed that the structured, ADA-compliant diabetes follow-up protocol led to both dimensional and meaningful changes in the project site. The results of the projects are presented in the appendix.

Project Outcomes

Evaluating the success of the project provides data regarding the value of the overall project for promoting clinical practice and its use as an evidence-based intervention. The most important goal of the project, to reduce HbA1c, was achieved, resulting in a reduction of 1.52 percentage points (from baseline) and exceeding the stated successful threshold (0.5 percentage points) by a wide margin. Implementation of the structured ADA diabetes follow-up protocol was fully clinically significant, as improvements in glycemic measures at 8 weeks following implementation were consistent and clinically significant when compared to baseline.

 In previous studies that involved similar patient populations but were split into two groups (one receiving nurse-led [protocol-driven] diabetes follow-up care and the other receiving standard care), similar reductions in HbA1c (0.25% to 1.69%) across similar outpatient primary care organizations have been found: Not only are the results from the QI project consistent with the results of similar studies, but the effect size is not significantly weaker than that seen in the QI studies (. < 0.2%). Results of the program of nurse-driven SME indicated virtually all improvement in the nurse competency scores and patient self-care behavior in a nurse follow-up program with structure and protocol. Additionally, there was a significant measurable difference (p < .01) with a T-test when determining: number of participants that reached a minimum of 80% at the end of the training; and although the final target of < 7% for HbA1c was not met in 70% of all patients during the eight week period, it is assumed that with continued implementation of the programme over a longer period of time than the post training practicum, this final target will be achieved.

Additionally, a few unexpected results emerged, including the lack of data on patients (an 80% completion rate of in-person scheduled visits to patients), indicating a need for an accessible and equitable method to provide nurse-led follow-up care to those who may have faced transportation barriers to making in-person visits to the healthcare organization. The strengths, limits, opportunities, and barriers (S-L-O-B) analysis of a quality improvement project can also be used as an evaluative frame for internal validity, as well as external applicability to other similar clinical contexts.

 The main strengths in the project included increased competency of staff (35%), good compliance with the follow-up system (89.2%), the accuracy of EHR documentation, and interprofessional collaboration of the clinical team, in addition to adherence with the follow-up system and documentation of the ADA clinical practice guidelines. The elements combined to lend the intervention design credibility. The methodological strengths of the current project are robustly supported by quality improvement projects that show high fidelity to intervention protocols (i.e., following the procedures as outlined) and have systematic accountability structures, such as competency development and EHR monitoring, as well as demonstrating a much more reliable and generalizable outcome. Multi-disciplinary structured quality improvement efforts employ well-documented follow-up protocols and are monitored through EHRs and, therefore, on an ongoing basis, yield positive outcomes. A quality improvement project was limited by only having implemented the project for 8 weeks, making it difficult to assess the sustainability of the HbA1c improvement.

Furthermore, limited statistical power due to the small number of participants (8) on the nursing staff, and limited generalizability of results across multiple clinical settings, due to the fact that one clinic site was used. Findings made both at the time of implementation and later on involve expanding the standardized ADA follow-up to other chronic disease populations treated at the outpatient clinic, creating the opportunity to use peer-supported digital messages to improve patient engagement between visits, and disseminating project findings through peer-reviewed publications to contribute to the evidence base.

Supporting practice change after the end of the quality improvement project is the result of deliberate organizational planning, documentation of organizational commitment to sustaining the practice change, and embedding practices of the successful intervention systematically into the flow of clinical practices and professional accountability systems. The clinic will embed the structured ADA diabetes follow-up system in the nursing work of routine procedures in order to continue the follow-up system. The EHR dashboards, automated appointment reminders, and fidelity checklists will continue to operate as a permanent operational infrastructure to assist with ongoing fidelity to the protocol. Structured interventions to enhance glycemic control need to be continuously monitored, adjusted, and implemented post-intervention for at least one year after intervention to ensure that changes in practice have become integrated into the organization’s culture and clinical practice.

Formal adoption of the key elements of a successful protocol (institutionalization of the elements) is a key component of the greatest long-term sustainability for any quality improvement program in chronic disease management. New positions created to help sustain the outcomes will include the Diabetes Protocol Coordinator position, which will track the data from the EHR dashboard and make repeated competency re-assessment of the nursing staff a quarterly task. Reporting the outcomes of the quality improvement project to internal organizational reports, conference presentations, and peer-reviewed journals will further solidify the organization’s commitment to the standardized diabetes follow-up model and inform future attempts to replicate such a model in similar outpatient primary care real-world health care settings serving a diverse adult population.

Recommendations

Results from the quality improvement efforts based on evidence will yield new insights that will not only be relevant to implementation but also to future nursing research and nursing practice. It is recommended that in the future, the intervention be carried out for a larger period of time, such as 12 months, to see if the HbA1c levels will last after the 8-week period of the practicum. The protocol should also be expanded to other chronic disease populations for the same outpatient population to further increase the impact and allocation of resources. Multi-center replication studies for assessing the effectiveness of the protocol with a larger and more heterogeneous sample of nurses should be conducted in the future. Another key area of further research is the cost-effectiveness analyses of reduced hospitalisation rates, calculated based on a standardised follow-up.

With a digital messaging platform that uses patients as its backbone, the integration will enhance patient engagement and the support of patient self-management between visits. Culturally responsive curriculum development research and digital equity research will be helpful to find gaps in technology access in underserved populations. Ongoing maintenance of nurse-led diabetes follow-up programs will be one of the most important ways of promoting glycemic equity and improving the quality of outpatient primary care services to a wide array of adults.

Summary

One of the more significant ways to “reaffirm” the clinical importance, clinical relevance, and scholarly contribution of the intervention that was introduced into clinical practice from a QI project is to provide a summary of the most important takeaways. The ADA diabetes follow-up protocol, which was implemented over 8 weeks, yielded a clinically significant reduction of HbA1C level (1.52%), competence scores of nursing staff from 59.0% to 85.4%, and an 89.2% adherence rate at follow-up. As such, its application of the ADA protocol in clinical practice resulted in the development of a broad-based, quantifiable set of changes and benefits in glycemic control, nursing productivity, and follow-up. Implementation has progressed the clinic’s organizational mission in three ways: a diabetes follow-up process was standardized, interprofessional collaboration was enhanced, and monitoring processes were integrated into the EHR as a routine workflow in the clinic. The project results identified as successful aligned with the clinic’s strategic goals related to: Value-Based Care Delivery, Quality of Chronic Disease Management, and Health Equity Goals for patients in a variety of urban communities served by the practicum site. Finally, the nurse-led protocol inspired by the ADA can be replicated, expanded to other similar ambulatory primary care practices, and will help maintain sustainable glycemic improvements in other similar clinics/ ambulatory care settings. Finally, inter-professional working within an organisation can lead to evidence-based QI that has tangible and long-term clinical outcomes that go beyond the organisation’s mission, but are aligned with national benchmarks for excellence in chronic disease management.