NURS FPX 9040 Assessment 1 Manuscript with Abstract

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Abstract

A considerable gap in the outpatient primary care setting exists in glycemic control in adults with type 2 diabetes, and this non deal control is mostly attributable to lack of follow-up, insufficient patient education, and inadequate medication management. The percentage of patients with HbA1c >9% (42%) at the project site was higher than the national average of 22% of U.S. adults with diabetes (Adjei et al., 2025; APRN, personal communication, November 2025). The PICOT question that guided the research was: For the diabetes nurse who cares for diabetes adults (P), what is the effect of using the ADA diabetes follow-up protocol (I) versus current practice (C) on glycemic control (O) over 8 weeks (T)? The quality improvement project deployed a structured follow-up protocol for eight weeks, in an outpatient primary care environment, which was designed to be ADA compliant.

The interdisciplinary implementation team comprised nursing professionals and health care providers who were educated and trained in structured learning sessions about diabetes management and the use of EHRs. In bi-weekly follow-up visits, adult patients with type 2 diabetes were involved. Evaluation focused on HbA1c levels, visit frequency, and adherence monitoring through tools in the EHR. There was a clinically meaningful mean change in HbA1C of 1.52 percentage points (9.95% to 8.22%), which is more than the success criterion of 0.5%. Adherence to follow-up was good, with 89.2% of visits completed.

The HbA1c goal of <7% was not reached by 10% of the people within 8 weeks. The results of this structured ADA follow-up protocol were shown to be clinically beneficial for glycemic control, which proves the PICOT hypothesis. Results indicate that nurse-driven, protocol-based care has a positive impact on diabetes care. There may be a need for longer intervention time for optimal target achievement, however. The project helps to sustainably integrate more standardized follow-up protocols to improve chronic disease outcomes in primary care.

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

The failure to provide standardized and protocoled pathways for follow-up is a significant gap in practice that is present across outpatient primary care settings, which also has the potential for missed opportunities for education, non-standardized medication review, and preventable complications amongst adult patients with type 2 diabetes mellitus. The project site had 42% of adult patients with hemoglobin A1c levels > 9%, and only 36% with levels < 7%, which are far from national targets, where 38% of U.S. adults with diabetes have hemoglobin A1c levels < 7% (Adjei et al., 2025; APRN, personal communication, November 2025).

Implementation gaps remain in follow-up, staff competency, and structured patient education of nurse-led diabetes care throughout primary care settings despite the established clinical practice guidelines of the American Diabetes Association. The PICOT question for this project is: In the care of the adult patient with diabetes (P), does the use of the ADA diabetes follow-up protocol (I) improve glycemic control (O) over 8 weeks (T) compared to the use of current practice (C)? A systematic follow-up routine with structure for a procedure that is compatible with the ADA, along with staff competence building and patient education on self-management, will result in clinically significant improvements in glycemic outcome and move the field of chronic disease management towards evidence-based practice in the outpatient primary care setting.

Practice Problem

Chronic disease management in outpatient primary care should be a systematic, evidence-based approach that has been shown to close the gap between the glycemic control of adults with type 2 diabetes and the desired health system benchmarks. Based on the site-level data from the outpatient primary care clinic, 42% of all the adult patients had HbA1c levels above 9%, while 36% had levels below 7% (APRN, personal communication, November 2025). The national performance data for the adult population with diabetes is also very poor – almost one in every five (22%) adult diabetes patients with a history of diabetes are not well controlled, and nearly half (45%) of all adult diabetes patients worldwide have never reached an HbA1C below 7% – which is a significant gap when compared to established benchmarks from health systems (Adjei et al., 2025; Dinavari et al., 2023).

The poor metabolic control of 1 in 4 adults in the U.S. and Europe is reflected by a hemoglobin A1c value of more than 9% (Gomes et al., 2022). In adults attending an outpatient diabetes clinic, low glycemic control is largely attributed to behavioral and demographic risk factors, and the need for early identification of those at greater risk for poor glycemic control and for employing structured clinical intervention to improve glycemic control is emphasized (Karmakar et al., 2025). The quantitative data gathered from this site provides a measurable basis to improve the quality of the site being used for a targeted intervention at the practicum site.

A thorough assessment of existing workflow and process flows, staffing patterns,s and care coordination efforts in the clinical setting is needed to fully determine the causal factors associated with poor glycemic control. Challenges with the scheduling of the EHR, insufficient structured follow-up, and inconsistent delivery of education were identified as common flaws in core processes that were found to impact suboptimal glycemic outcomes during the audit of charts and documentation at the project site (APRN, personal communication, November 2025).

The absence of a protocolized follow-up plan resulted in inconsistent and ad hoc scheduling, inconsistent use of the EHR reminders, and no multidisciplinary coordination, which affected timely adjustment of medications and the provision of tailored education for patients who were most likely to develop complications (APRN, personal communication, November 2025). Follow-up visit completion rates and the EHR documentation audit also revealed systemic problems in scheduling visits and proactively contacting patients (APRN, personal communication, November 2025).

Previous educational interventions were delivered through monthly general sessions, and some were followed by occasional telehealth support, but they were inconsistent in their delivery and/or failed to have clear evaluation tools, causing inconsistent quality of the education delivered and incomplete understanding of the content by the patients (Dailah, 2024). As a result, the need for a protocolized follow-up pathway was confirmed as the most modifiable determinant identified through the comprehensive needs assessment of the identified practice gap.

If “all stakeholders” are involved in chronic disease management, significant attention will need to be paid to how each of these stakeholders will be affected by, to warrant timely and systemic responses to help them improve quality. Poorly controlled diabetes has been linked to increased rates of hospitalization, utilization of health services, and burden of long-term complications like heart disease, neuropathy, and preventable hospitalization, with nursing staff, adults with diabetes, and organizational leaders being primary stakeholders affected by the continued glycemic disparities.

The timely implementation of effective evidence-based interventions was not clinically justifiable: for structured nurse-led interventions, reductions in HbA1C levels were shown to be approximately 0.4 to 0.9 percentage points across all outpatient primary care settings, thus demonstrating strong evidence for the impact of structured nurse-led interventions (Sun et al., 2025). There is a national report of a lack of glycemic control that needs to be addressed immediately with standardized methods at the project site, especially for vulnerable and low-income patients (Centers for Disease Control and Prevention, 2024). Therefore, consistent with the mission of the site, to provide accessible, evidence-informed primary care, it was both a clinical need and an organizational strategic priority to address this identified practice gap.

Project Site

The foundation of implementing structured chronic disease management interventions is diverse outpatient primary care clinics in urban areas. One such example was the outpatient primary care clinic in New York City that was the project site. The clinic population is diverse, with adults from a variety of cultural and socio-economic backgrounds. Around 60% of the clinic’s patients suffer from long-term diseases like diabetes and hypertension (APRN, personal communication, November 2025). The clinic’s infrastructure includes six examination rooms, two private rooms for counselling, and telehealth workstations with capabilities for virtual business and patient remote monitoring.

There are six healthcare professionals (nurse practitioners, medical assistants, a care coordinator, and a health educator) and several office staff who coordinate patient care and work-related demands associated with patient care. The clinic’s vision is to help people be healthy by offering primary care and preventive health services that are accessible to the community and based on evidence. Therefore, the clinic is a suitable venue for a diabetes-related quality improvement initiative.

Learning about the specific context of the practice site will allow the reader to appreciate the timing and appropriateness of a quality improvement project to address a practice issue. The clinic focuses primarily on health education, ongoing care, and chronic disease management. Opportunity to leverage a diabetes follow-up process using a structured process (APRN, personal communication, November 2025), with a focus on health education, continuity of care, and management of chronic conditions, without significant additional organizational changes needed.

The clinic implemented electronic health records, facilitating improved patient data management, appointments,s and monitoring of outcomes. A standardized protocol was already in place to support educating patients and providing medication reinforcement; thus, the protocol would augment current protocols and not burden staff. There was a gap in practice, and the leadership agreed the project was important as it would have both potential clinical and potential financial implications. Leadership understood that glycemic stabilization would be a catalyst for moving this organization’s performance metrics for quality and would meet value-based care and patient satisfaction requirements. The project was aligned with the strategic priorities of the organization, thus establishing an ideal position for the quality improvement intervention at the practicum site.

The members of the team in the practicum site methodically reviewed the way diabetes is managed before the project to understand how the flawed process has led to poor glycemic control outcomes at the site. The most common way the nursing staff provided diabetes care and education was by frequent provider visits, but neither of these two ways of providing diabetes care had a corresponding structured or standardized follow-up process. There was no standard follow-up process, and translation of diabetes education and communication about self-management measures between nurses and patients was inconsistent.

The following process flaws had a significant impact: ad hoc scheduling and rescheduling, untimely use of EHR reminders, lack of multispecialty coordination, and inadequate review of patient follow-up data that could have led to timely medication changes and targeted patient education for those who were at greatest risk. Patients’ glycemic outcomes and adherence to recommended self-management behaviors have been consistently found to be worse in unstructured diabetes care processes in outpatient settings (Heise et al., 2022).

In addition, benchmarking and routine use of a follow-up protocol and incorporating it into EHRs has been found to decrease missed visits, delays in timely interventions, and quality gaps in diabetes management (Wang et al., 2025). The completion of an evidence-based needs assessment (baseline data extraction, staff interviews, chart auditing, and EHR auditing data) confirmed the need for an intervention to improve diabetes follow-up at the clinic. The process failures highlight the critical need for the implementation of a diabetes follow-up program based on a protocol at the practicum site.

Project Population

Defining the target population is essential for effective targeting of interventions for quality improvement and for the expectation of obtaining meaningful and measurable results. For the project, the project population was defined as a population of only nursing staff who provide care for patients with type 2 diabetes in the outpatient primary care clinic, as the intervention was intended to increase nursing staff competency levels of implementing the standardized ADA diabetes follow-up protocol (APRN, personal communication, November 2025).

The nursing education, clinical experience, and professional background varied among the nursing personnel involved in the project, which made the approach to diabetes management and patient education different. A minimum of 8-10 nursing staff members was needed to gain meaningful progress on competency levels and follow-up the registered diabetes protocol. Whole-staff competency mapping carried out before the design of the quality improvement intervention informed the targeting, development, and implementation of a competency-based and achievable intervention to ensure quality improvement.

The example described characteristics of the nursing staff as a basis for preparing for the implementation of a standardized diabetes follow-up intervention. The majority of nursing staff involved in the project were either registered nurses (RN) or nurse practitioners (NP) who are currently licensed to practice in the state, and directly cared for adult patients with type 2 diabetes as part of a nurse-directed, multidisciplinary team that includes education, self-management sup, port and chronic disease follow-up as core duties (APRN, personal communication, November 2025).

The nursing staff had a diverse level of confidence, knowledge,e and practice of established diabetes management protocols before the intervention, with a pre-intervention competency level of 59% demonstrating a need for an integrated structured diabetes education program. The multi-disciplinary nursing team included three nurse practitioners, two medical assistants, one care coordinator, and one health educator and took part in the structured competency development program. The common characteristics of the professional staff members created a good foundation for the development of a quality improvement program for the follow-up protocol intervention for the ADA.

The criteria for the inclusion and exclusion of the nursing staff members in the project led to a population focus which enabled the project to include any contribution to glycemic outcomes that was in line with a desired improvement of the population. The inclusion criteria for the project focused on nursing staff who provide care to adults who have a type 2 diabetes diagnosis; engaging in patient education regarding diabetes, provide medication management for diabetes, and/or providing diabetes-related follow-up as part of normal, routine clinical functions at the clinic (APRN, personal communication, November 2025).

All nursing staff at the site have to engage in all of the above roles and have to be actively working in the project site during the entire eight weeks of the implementation period and actively working in clinical provider roles directly related to the follow-up protocol goals of the ADA. The project excluded the following nursing staff: Nursing staff who were employed in administrative positions (not engaged in direct patient care), Nursing staff in support positions (not engaged in providing direct patient cand nursingursing staff who held temporary and/or short-term employment positions (not providing adequate direct patient care). The project’s inclusion criteria, as well as the exclusion criteria for the project, greatly enhanced the internal validity of the project and allowed for the results of the structured intervention to accurately reflect the impact of the structured intervention on the nursing population included in the project.

Evidenced-Based Interventions

To achieve greater and more sustained glucose improvements than single-component interventions, effective quality improvement efforts have to package more than one intervention component. Literature affirmed that a combination of approaches would ensure fidelity and outcomes while being scalable, culturally tailored, integrated with EHRs, and measured iteratively. The project put into practice the recommended diabetes follow-up protocol from the ADA more consistently to support diabetes care processes during the 8-week implementation period. Diabetes-specific education sessions focused on diabetes pathophysiology and effective use of EHR tools to monitor outcomes, boost patient engagement, and improve adherence were conducted for healthcare providers (Fracso et al., 2022).

The educational programme included simulation sessions, case scenario sessions, and peer mentoring sessions to reinforce the real-life application of evidence-based diabetes management techniques (American Diabetes Association, 2024). Pupils’ competency was assessed using teaching observations, a performance checklist, and knowledge tests to ensure that they are able to use validated patient education resources and apply a standard process for follow-up procedures confidently. Continuous staff education was fundamental to the sustainability of the initiative, and was important in achieving shared ownership, standardization of clinical practice and a culture of continuous improvement (Dailah, 2024). To explore barriers, evaluate training impact and share best practice amongst the nursing participants, regular refresher sessions, peer discussions and feedback cycles were incorporated.

The HbA1c parameters were chosen with the understanding that there was evidence of significant reduction in HbA1c in quasi-experimental outpatient settings (Kerari et al., 2024). The patient population’s health literacy and resource differences were significant and will influence the applicability of the ADA guidance, but the design of the intervention was iterative and similar to the ADA-structured 8-week intervention design (American Diabetes Association, 2024). The systematic transfer of the ADA standards to clinic processes created the structure to attain the measurable improvements in glycemic control over the entirety of the implementation.

A multidisciplinary team-based approach to care was adopted to ensure clinical responsibilities are shared fairly among the clinicians, care coordinators, and health educators. The clinical rationale for interprofessional role distribution was supported by the consistent decrease in hospitalizations and increase in adherence in population-level diabetes care in team-based models (ElSayed et al., 2022). The clinical team was complemented with competency-oriented team training, which enhanced coordination and fidelity to implementation of all roles within the clinic for the delivery of the interventions (Samardzic et al., 2020).

Multidisciplinary interventions consistently led to greater system-level changes compared to single-provider education interventions (ElSayed et al., 2022; Samardzic et al., 2020). But the level of resources required and staffing limitations meant that there were only limited options for scaling up in smaller clinics without strategic reallocation plans. Structural aspects of the intervention design that enabled the consistent and equitable delivery of the intervention across the project site, therefore, included multidisciplinary team-based care.

Patient-centered self-management programs were singled out as key interventions to enhance self-efficacy and glycemic control outcomes for the entire patient population enrolled. In a multicenter randomized trial, Asmat et al. (2024) found that intensive patient-centered teaching resulted in substantial decreases in HbA1c and improvements in self-care practices. A phenomenological study was carried out by Fracso et al. (2022) that provided a description of empowerment mechanisms of peer support and personalized goal setting among vulnerable participants.

Two systematic reviews found significant effect sizes but also noted variations in program delivery and measurement techniques between the studies included (Asmat et al., 2024; Fracso et al., 2022; Huang et al., 2024). Because the program was implemented across a wide range of patients at the project site, customized curricula and fidelity monitoring were introduced to ensure that the program would be most effective for the different patient populations. Patient-centered self-management education was a key process through which nurse-led visits led to improvements in glycemic control and long-term behaviour change.

Implementing telehealth follow-ups and automated electronic health record (EHR) reminders were implemented to help enhance accessibility and adherence among those who may have transportation issues or limited mobility. Ezeamii’s (2024) analysis identified improvements in the use of telemedicine in appointment attendance and remote monitoring aspects in the national telemedicine implementation. However, there were some moderating factors to the effectiveness of telehealth that were unevenly distributed by socioeconomic status, such as disparities in digital access and in health literacy.

The short-term glycemic results for using telehealth, in combination with a structured follow-up program, were comparable to face-to-face visits (Ezeamii, 2024; ElSayed et al., 2022). The HbA1c tracking system was put in place using EHRs to coordinate follow-ups, remind about missed appointments, and to aggregate HbA1c results from the project site. The overall findings by Okemah et al. (2023) indicate that web-based tools were associated with better documentation accuracy and eased the process of outcome monitoring within provider teams.

Comparative results indicated that EHR prompts made protocolized visits more effective than passive reminders (Okemah et al., 2023; ElSayed et al., 2022). Training investments, reorganization of workflow, and periodic audits were needed to ensure the quality and utility of the data during the intervention period. An important aspect of EHR integration was the ability to monitor in a scalable way and to tightly couple the monitoring with the outcome goals of the project that were measurement-based.

Education interventions were delivered in a culturally responsive manner to address language barriers and culturally specific self-management beliefs among those enrolled in the program. Wadi et al. (2021) found better outcomes of HbA1c with interventions that included culturally appropriate food management and family engagement techniques. Goetz and Schork (2020) highlighted the concepts of personalized medicine to improve relevance in both rural and urban environments. Culturally targeted education led to more long-term behavior changes among a variety of populations when compared to generic education methods.

Training on the use of diabetes education protocols and to reinforce teaching skills was given by simulation training to staff. With the use of web-based faculty training modules, Okemah et al. (2023) have shown knowledge gains as well as improvements in patient education performance. Comparative studies indicated that the amount of practical skill that was retained in the didactic sessions was lower than in simulated tasks with hands-on experience (Bisbey et al., 2021; Dailah, 2024). Therefore, the focus of the project was on the use of the simulation, on the observed demonstration, and on the competency checklist for sustainable staff competence during the implementation period.

Patient-centered behavioral goal setting and motivational interviewing techniques were integrated into each follow-up visit to facilitate patient-centered behavior change and to help patients maintain lifestyle changes (Huang et al., 2024). Use of culturally responsive education and behavioral strategies in the structured follow-up protocol guaranteed relevance, equity, and consistency of intervention delivery to the varied self-management needs of enrolled patients.

Peer mentoring and group support sessions were added as a means to take advantage of common experiences and social reinforcement to help maintain engagement in self-management. Fracso et al. (2022) reported qualitative results for an improvement in confidence, self-efficacy, and problem-solving abilities as a result of having regular, structured interactions between group members. Individual interventions showed a greater rate of knowledge improvement, and group interventions showed greater sustained behavior change and long-term peer accountability in comparative studies. Data reviews and adaptations were included biweekly across the project to maintain fidelity and expedite learning (Lin et al., 2022).

However, the costs of the device, concerns about data security, and patient engagement with the device have restricted the widespread use of the device in smaller practice settings. The targeted rollout and the embedding of the system into the EHR systems ensured that the system was most useful for motivated patients and minimized implementation resource requirements throughout implementation. Peer mentoring, group support, and iterative data review were used strategically and cohesively to ensure the intervention was responsive, socially reinforced, and supported the maintenance of patient engagement during its complete eight-week implementation.

Role of the Project Lead

Quality improvement projects will require both systematic and logical designs, as well as scholarly and decisive leadership at every step of the process that connects the clinical knowledge/experience, interprofessional teamwork, and systems thinking components. The DNP student took on the leadership role in designing a standard ADA diabetes follow-up protocol, creating educational materials to help facilitate the implementation, setting up EHR dashboards to support the protocol, and ensuring that all logistical aspects were taken care of during the eight-week implementation period (APRN, personal communication, November 2025). The project lead conducted a baseline needs assessment that gathered pre-intervention HbA1c results from EHRs for the patients, staff competency scores, and follow-up completion rates to provide clear baseline measures to be used as benchmarks.

The project lead needed to regularly communicate with each of the organizational stakeholders, interprofessional team members, and academic mentors throughout the implementation of the project to maintain fidelity with the implementation process and the scholarly rigor of the project. To ensure that the workflow changes that occurred during each implementation cycle were based on data and transparent, the plan-do-study-act (PDSA) framework was implemented. Ongoing communication with the site preceptor, DNP faculty mentor, and the clinic leadership (APRN, personal communication, November 2025) occurred through structured meetings, virtual consultations, and written progress reports documenting the completion of implementation tasks and/or adaptive modifications.

Ethical compliance was maintained throughout the project, and strict steps were taken to ensure that all participants in the project knew what they were getting into and that the data they shared was de-identified to ensure their Health Insurance Portability and Accountability Act (HIPAA) compliance. The scholars’ rigor of the project lead, clinical resources, nd collaborative leadership through the entire implementation process illustrated the essential contribution that the APRN can make to achieving sustainable quality improvement outcomes within the nursing profession.

Roles of Other Team Members

Effectiveness of QI programs in outpatient primary care depends on defining interprofessional team roles and equitably distributing responsibilities across team members and improving the provision of coordinated care services by all elements of the intervention. The preceptor from the clinical site was the clinical supervisor and APRN, directly supervised implementation of the protocol, and was the main liaison with the organization’s leadership throughout the entire eight weeks of the clinical project (APRN, personal communication, November 2025). At each biweekly visit, nurse practitioners conducted clinical evaluations and interviewed the patient alone to deliver education and counseling and helped the patient meet ADA-recommended follow-up targets.

In general, there is a clear association between role clarity in a quality improvement team and increases in shared accountability and fidelity to the delivery of evidence-based interventions (Hempel et al., 2022). The coordinator for care had no role in scheduling, telehealth logistics, reminder activation in the EHR, or attendance to maintain follow-up rates that exceed benchmarks. The health educator culturally adapted patient education materials to a collection of patients who were enrolled in the program and had different language and health literacy needs. Consistency, accountability, and alignment to the project’s evidence-based objectives were achieved with each team member knowing and learning a clear role to play throughout the project’s implementation.

Each member of a quality improvement team needs to have a unique and complementary role to play in implementing the project in order to ensure implementation fidelity and scholarly rigor throughout the entire project. Medical assistants collected patient information, including vital signs, created educational resources, facilitated communication with patients, and recorded clinical information gathered from every other week visit to the EHR. All nurses attended all educational sessions, and standardized elements of the ADA follow-up protocol were followed during visits with patients, with all nurses filling out the fidelity checklist for each patient visit.

Interprofessional working and formal communication between professions are recognised as being crucial to the ongoing success of quality improvement work in primary care (Dellafiore et al., 2025). When everyone in the team is responsible for the same, shared responsibility increases compliance with the protocol of implementation and helps to identify that there are any obstacles to implementation promptly (Grant et al., 2024). During the entire implementation process, the DNP Faculty Mentor was available to the DNP Student for academic consultation, reviewing the reports kept by the DNP Student. The interdisciplinary team members met with the stakeholders every other week to keep the project team communicating, transparent, and working cooperatively.

Literature Synthesis

The starting point for a thorough and systematic approach to literature search is to identify high-quality, relevant evidence that directly answers the PICOT question that is the focus of the quality improvement project. PICOT: When the PICOT question is formulated, it is: For patients with diabetes (P) in the nursing care setting, what is the impact of implementing an ADA diabetes follow-up protocol (I) compared to current practice (C) on glycemic control (O) over 8 weeks (T)? The problem was addressed comprehensively by performing multiple database searches, namely: PubMed/MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, Web of Science, Scopus, andProQuest Dissertationss and Theses. Relevant peer-reviewed research, clinical practice guidelines, and doctoral projects on nurse-led diabetes management and the implementation of the ADA guidelines in an outpatient primary care setting were captured in the databases.

Medical Subject Headings (MeSH) terms used included “diabetes mellitus,” “type 2 diabetes,” “glycemic control,” “HbA1c,” “nurse-led interventions,” “ADA guidelines,” “diabetes follow-up,” “self-management education,” and “primary care. Combination of the Boolean operators were applied: (“type 2 diabetes” OR “diabetes mellitus”) AND (“nurse-led” OR “nursing intervention” OR “diabetes self-management education”) AND (“ADA guidelines” OR “clinical practice guideline” OR “follow-up protocol”) AND (“glycemic control” OR “HbA1c”). A good search strategy must be well designed and applied, and the evidence retrieved must be representative, reproducible, and directly relevant to the clinical problem being investigated.

The first searches of the databases produced a total of 362 records from the databases accessed. Following the removal of 54 redundant articles, 308 distinct articles were screened for title and abstract, using pre-established inclusion and exclusion criteria. Peer-reviewed English-language publications from January 2021 to February 2026 that included adult populations, nurse-led interventions or structured follow-up protocols, and quantifiable glycemic outcomes (HbA1c) were included. Pediatric patientss, inpatient-onlyacute care interventions, non-clinical commentary and editorials, and studies with no measurable HbA1c or glycemic control were excluded.

Manual reference list searching was used to retrieve a further 11 sources relevant to the topic from systematic reviews and clinical position statements and from publications from the American Diabetes Association Standards of Care publications. Gray literature searches included professional standards published by the diabetes associations, government publications, and doctoral dissertations that compared nurse-led models of diabetes care in outpatient settings. Clear and logical screening criteria increase the credibility and academic rigour of the evidence synthesis.

Following a full-text appraisal, 20 sources were selected for synthesis and creation of the evidence table, after subsequent in-depth review of their relevance to the PICOT focus, methodological rigour, and measurable glycemic endpoints. Each study included in the final analysis was assessed for methodological quality and clinical applicability by systematically using the strength of Recommendation Taxonomy (SORT) framework; this is a method developed by Duke University (2023). This framework focused on outcomes that were patient-oriented, including reduction of HbA1c, prevention of complications, and avoiding hospitalisation.

There were seven studies with SORT Level A (high-quality randomized controlled trials, systematic reviews, and meta-analyses). Ten studies were rated as Level B, having been well-designed comparative effectiveness studies, quasi-experimental studies, or cohort investigations. Three studies were given Level C classifications, with clinical practice guidelines and quality improvement projects, and narrative reviews. The quality of the evidence used to support diabetes follow-up interventions is consistent with the preponderance of moderate-to-high quality evidence to support structured diabetes follow-up by nurses in a variety of outpatient settings in accordance with the ADA clinical practice standards.

Analysis of Evidence

A thorough review of the 20 studies retained found consistent and convergent evidence that nurse-led implementation of diabetes follow-up protocols that are compliant with ADA is an effective strategy for improving glycemic control, self-efficacy, and self-management behaviors among adult patients with type 2 diabetes. Effect sizes from investigations ranged from small to very large. Comparative analyses showed HbA1c reductions from 0.25% to 1.69% with nurse-led interventions compared with comparators of usual care (Asmat et al., 2024; Chen et al., 2025; Koo et al., 2024), indicating meaningful metabolic improvements. As evidence, structured diabetes self-management education and support (DSMES) programs yielded pooled standardized mean differences of -0.468 (95% confidence interval [CI]: -0.658 to -0.279).

The mean differences ranged from -0.59 (95% C: I -0.85 to -0.34) across a variety of clinical populations and delivery settings (Yimer et al., 2025; Chen et al., 2025). The technology-enhanced delivery modalities (telehealth consultation, structured telephone coaching and peer-supported instant messaging) were shown to be clinically equivalent to a face-to-face follow-up. The modalities significantly enhanced patient access, participation,n and compliance with self-monitoring procedures. Results from a variety of study designs and geographic environments increase confidence in the clinical applicability of nurse-led interventions for diabetes follow-up.

Across the literature retained, evidence gaps were found for limited data on protocols for the optimal frequency of follow-up and lack of longitudinal outcome data beyond twelve months. Several ongoing challenges to regular adherence to ADA guidelines were also found, such as providers lacking knowledge, disconnect of workflows, and lack of institutional accountability mechanisms. Interrelated themes that emerged from the analytic synthesis were: adherence to the ADA guidelines and standards of clinical practice; nurse-led interventions and competency development of staff; diabetes self-management education and support interventions; and technology-based diabetes care and remote follow-up protocols.

Themes capture different aspects of the evidence base but are together a reinforcement of the need for a multi-faceted approach to achieve clinically meaningful and organizationally sustainable improvement in glycemic control. The findings of the identified evidence gaps further support the scholarly value and relevance of undertaking a structured and protocol-driven quality improvement initiative in an outpatient primary care environment. A thematic organization of findings allows for a systematic review of the interplay of different but interrelated components of an intervention to address the complexity of outpatient diabetes care.

Theme 1: ADA Guideline Adherence and Clinical Practice Standards

Implementing effective glycemic control in the outpatient primary care setting requires adherence to clinical practice guidelines, versus delivery of care that is inconsistent or fragmented, which creates a more organized and reliable care delivery system. ElSayed et al (2022) found that high compliance levels (89.8%) were strongly correlated with a significantly greater proportion of adults achieving target HbA1c levels, whereas low compliance levels were strongly correlated with persistently poor metabolic outcomes in the study population. Similarly, Tiwari and Aw (2024) found that key factors affecting regular guideline adherence, including provider lack of knowledge and inefficiencies in workflow, further exacerbate the gap.

Overall, the results indicate that factors both at the system level and at the provider level act as barriers to the successful implementation of the ADA guidelines; in contrast, protocol-driven nursing interventions are well suited to the gaps found. Adequate follow-up can be integrated into the nursing workflow in a systematic way, thereby improving the ability to measure and consistently apply published guidelines to guide patient outcomes.

Adopting ADA-compliant practices for nursing care will translate the recommendations that were based on evidence to clinically relevant glycemic burden reductions. Compared to standard care, Abukhalil et al. (2024) demonstrated that the use of ADA-guided follow-up pathways in a patient-centered medical home led to a mean HbA1c decrease of 0.74% (p < .01) and an improvement in the proportion of guideline-concordant antihyperglycemic prescriptions.

Likewise, with a more impressive effect, Chen et al. (2025) showed a 1.02% drop in HbA1c levels at 12 weeks (p < .001), which was achieved through structured follow-up to the ADA guidelines combined with nurse-led medication review. Comprehensively and in comparison with unstructured interventions, these studies suggest that structured nurse-led follow-up leads to more standardized and clinically meaningful glycemia reduction in a primary care outpatient environment.

But to ensure optimal glycemic control, systems of reinforcement, accountability, and ongoing monitoring are essential along with guidelines. Structured reinforcement interventions, which are more likely to yield consistent results, are more effective than interventions that do not include reinforcement, even though interventions that do include reinforcement tend to be more effective but are more likely to yield heterogeneous results (Sun et al., 2025). In addition, ElSayed et al. (2022) showed that only 23% of the adult population reached target HbA1c, blood pressure, and lipid levels at the same time, highlighting that diabetes management is complex; by comparison, adherence to single components does not cover this complexity.

Nevertheless, Tiwari and Aw (2024) found that provider-level knowledge gaps persist, even in the presence of revised guidelines, whereas the data showed that the lack of access does not guarantee adequate use in practice. Similarly, Abukhalil et al. (2024) found low uptake of preventive screening and poor pharmacotherapy care despite the expectations of full care. Thus, for effective and lasting improvements in glycemic control, ADA standards need to be part of a nurse-led, accountable system that incorporates structured education, ongoing monitoring, and follow-up to diabetes care, providing a more comprehensive and effective approach to diabetes.

Theme 2: Nurse-Led Interventions and Staff Competency Development

Nurse-led care is aquality-basedd initiative, supported by evidence, which empowers patients to remain engaged in their care and to coordinate it with other health care providers. The models highlight continuous interaction and a focus on the patient, as compared with traditional physician-centered approaches. Dailah (2024) found that nurse-led diabetes education programs were effective in enhancing patient knowledge, self-management skills, psychological factors, and HbA1C levels through ongoing engagement and encouragement. This is in contrast to models that have limited follow-up and do not achieve such continuous improvements.

This study was continued by Jiang et al. (2024), who found statistically significant increases (p < .001) in knowledge about diabetes, anxiety, depression, and self-care activities after six months for patients receiving follow-up from a nurse compared to those receiving routine care (2024). In contrast, multifaceted educational programs to improve nursing skills were shown to achieve uniform improvements in HbA1c, blood pressure, and lipid parameters when nurses’ roles are clearly defined, and systematic education programs are conducted (Aldahmashi et al., 2024). In such settings that empower the nurse and hold the nurse accountable, nurse-led interventions demonstrate consistent and multidimensional benefits to patient outcomes, especially compared to less structured care settings.

Staff competency development and the consistent provision of patient-centred diabetes care in the outpatient setting are well connected by the provision of a mechanistic link. Compared to low-education resource settings, Aldahmashi et al. (2024) reported that targeted education greatly boosted nurse confidence in implementing ADA protocols, thus promoting adherence to glycemic monitoring guidelines and the provision of good patient education. More recently, Abukhalil et al. (2024) demonstrated the systemic benefits of competency integration through their findings that follow-up in the team-based primary care setting based on the ADA protocol resulted in a mean HbA1c reduction of 0.74% and had beneficial effects on prescribing concordance and care coordination. Like fragmented care delivery, the results also note the need for coordinated, skill-based approaches.

Dailah (2024) revealed that only about 22% of hospitals have diabetes inpatient specialist nurses, where diabetes is a growing need for specialized diabetes care, but there are gaps in knowledge. This is confirmed by the findings of Jiang et al. (2024), who found that the nurse-led care plus structured education and multiple engagement strategies resulted in significantly improved outcomes, even when the nurse-led care only was supplemented with additional physical activity support in the control group. In comparison, the data suggest that investing in nursing development has a more consistent and potent effect on glycemic outcomes than discrete interventions.

Further improving the effectiveness of nurse-led diabetes management interventions are interprofessional working and clearly defined nursing roles, which extend coordination beyond primary care systems. Compared with individual or multi-disciplinary care, collaborative care allows for multidimensional care management. Anguish and depression scores were lower and glycemic control was better in nurse-led programs with structured educational and multimodal engagement strategies than in less integrated programs that address clinical measures only, as shown by Jiang et al. (2024).

Four critical nursing responsibilities were identified by Aldahmashi et al. (2024) that all worked toward better guideline adherence and better patient safety: education, collaborative practice, program design, and documentation review. In line with this, Abukhalil et al. (2024) found that nursing-led post-visit follow-up care in patient-centered medical home approaches had a more comprehensive systemic impact than did traditional follow-up care, such as improved prescribing practices and better care coordination. Also, Dailah (2024) noted that nurses, given their regular and direct patient contact, can offer more education and motivation than many other health care providers. In general, when nursing roles are embedded in an interprofessional team with a clear interprofessional working model, outcomes of diabetes management are better and more likely to be sustainable than can be achieved by working with individuals in single-discipline teams.

Theme 3: Diabetes Self-Management Education and Support Interventions

Follow-up by nurses to implement clinical recommendations into long-term physiological and behavioral change is best done through structured diabetes self-management education and support (DSMES) programs. DSMES offers a more systematic and patient-oriented approach to behavior change as compared to unstructured or routine care models. In a multi-center randomized controlled trial, Asmat et al. (2024) showed that patients who participated in a patient-centered self-management intervention experienced a significant mean HbA1c reduction of 0.25% (p = .03), and a substantial increase in self-efficacy and self-care behaviors, while routine care may not be enough to achieve such behavioral changes.

The mediation analysis also validated that behavioral changes were the most important factors in achieving glycemic outcomes. This was confirmed by a systematic review and meta-analysis of 19 trials that evaluated the effect of DSMES on HbA1c, with the findings demonstrating a statistically significant reduction in HbA1c with DSMES, as compared to structured DSMES programs, which consistently resulted in better glycemic control than routine care (Yimer et al., 2025). In general, patient-centred education programmes that include personal counselling and reinforcement have more reliable and measurable outcomes than standard care models.

The length, intensity, and organization of DSMES programs are important factors to consider for lasting patient outcomes. One-time or short-term education interventions do not have the same lasting effect as longer-term interventions. A systematic review and meta-analysis conducted by Fracso et al (2024) included 34 studies with 7,603 participants and revealed that interventions with durations of 6–12 months demonstrated significantly better improvements in quality of life, self-efficacy, nd sustained decreases in depressive symptoms. Likewise, but more emphatically, Fracso et al. (2022) gave qualitative evidence that participation in a chronic disease self-management program for a sustained period of time changed patients’ motivation, sense of community, and commitment to self-improvement, which are typically not outcomes of a brief intervention.

By adding bi-weekly telephone coaching to the nurse-led follow-up, Chen et al. (2025) extended the findings, showing that the combination of the two was a more effective intervention for enhancing self-efficacy and increasing the frequency of blood glucose monitoring than was nurse-led follow-up alone, and that it was more effective at activating behavioral pathways to physiological benefit. Thus, DSMES programs designed to engage patients for extended periods of time, support through structured reinforcement, and ensure continuity of care are more effective in improving long-term results than short and fragmented interventions.

Content that is culturally responsive and contextually based further enhances the effectiveness of DSMES programs. Culturally adapted programs yield more equitable and impactful outcomes, as opposed to generic, one-size-fits-all programs. There was significant variation in effectiveness across studies, with differences suggested to be due to the cultural adaptation, teacher training, and fit with patient health literacy; comparatively, programs tailored to specific populations showed stronger outcomes (Yimer et al. 2025). Sun et al. (2025) noted that the effectiveness of the modules is lower if they are not culturally adapted, whereas the ones that include culturally specific elements like community health beliefs, medication timing, and dietary habits are more effective. As mentioned by Asmat et al. (2024), culturally adapted nurse-led interventions yield sustained improvements, accounting for a substantial portion of outcome variance via self-efficacy. Overall, culturally responsive content, structured reinforcement, and extended follow-up, when integrated, are more effective and equitable in glycemic control than non-tailored interventions in a variety of populations.

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

Using technology-based channels to provide services opens up more convenient and scalable options for nurse-led diabetes follow-up care. Technology-based models have greater reach than traditional in-person models without sacrificing clinical effectiveness. In a systematic review and longitudinal meta-analysis of 13 studies that included 2,294 patients, a fixed mean HbA1c reduction of -0.59 (95% CI -0.85 to -0.34, p < .00001) was reported in relation to nurse-led telephone interventions, compared to optimized protocols with 16 contacts of 20–25 minutes, which achieved an even greater reduction of -1.23 (p < .001).

The results diverge from those of less structured, or less frequent, contact models, indicating the need for repeated and formalized interactions. Koo et al. (2024) confirmed the findings from a 24-month cohort study that demonstrated sustained HbA1c improvement with a remote self-care program that used telephonic nursing and smartphone technology, with an average HbA1C level of 7.33% to 7.62%. Considering the long-term view, technology-supported nurse-led follow-up shows long-term consistent engagement with patients and clinically meaningful glycemic control compared to conventional care.

Longitudinal studies also corroborate the short- and long-term effectiveness of technology-enhanced nurse-led models. The models have lasting effects, unlike shorter programs based on trials that tend to produce short-term results. Ezeamii (2024) found that nurse-led telemedicine significantly improved chronic disease outcomes as compared to face-to-face visits, while also increasing access and patient satisfaction by overcoming geographic and transportation barriers. Kamal et al. (2023) found that 12 months of interprofessional engagement significantly improved glycemia, weight, and waist circumference, but qualitative results indicated that patients need more time to make lasting behavioral changes when increased awareness is present. Sun et al. (2025) highlighted the importance of leveraging digital tools like automated reminders, virtual consultations, and message structuring to improve engagement and accessibility, as opposed to conventional care approaches. Thus, when used with a structured protocol, technology-enhanced care offers a more flexible and scalable approach to achieving sustained glycemic control as compared to standard follow-up.

Although the results of technology-enhanced follow-up models are consistently positive, there are barriers that need to be overcome in order to provide equitable access and effectiveness. While there are ideal scenarios for implementation, in the real world, problems arise with digital literacy, access to devices, and socioeconomic differences. Such restrictions could undermine the benefits of telemedicine, especially for marginalized groups, while people with greater digital access and expertise gain more benefits from telemedicine care, Ezeamii (2024) pointed out. The authors of Graue et al. (2023) acknowledged that this time period may not be long enough for empowerment-based interventions to trigger measurable changes in behavior, whereas longer and more adaptive engagement models have been found to generate changes.

The heterogeneity was found to be high (I² = 87%) across different studies, and this may be attributed to the differences in the protocol designs, patient characteristics, and outcome measures, making it difficult to compare the effectiveness of these studies. Sun et al. (2025) also cautioned that a single uniform digital intervention might not be as effective in delivering benefits across different populations as would be a contextually specific intervention that takes into account patient-specific needs and engagement. In conclusion, in order to achieve an equitable and effective approach, technology-based diabetes care needs to tackle inequities in access, where possible, standardize protocols, and ensure high-quality nursing oversight in comparison to poorly integrated and/or fragmented models.

Synthesis of Findings

A comprehensive conclusion was drawn when evaluating evidence within each of the categories, as structured nurse-administered diabetes follow-up interventions for outpatient primary care can be based on clinically actionable evidence. All twenty studies that fulfilled inclusion criteria consistently showed an overall positive direction (improvement) in HbA1c outcomes in people with diabetes across all types of delivery model, geography, and study design examined. The impacts covered a broad range of effect sizes, from very small (short-term-only effects from RCTs with reductions in HbA1c of 0.25%) to clinically significant (large structured longitudinal diabetes programs with effective effects of > 1.5% reduction in HbA1c) (Asmat et al., 2024; Koo et al., 2024).

A single intervention bundle (ADA adherence, nurse-led competency, patient-centered education, and technology-enhanced follow-up) will yield better, more sustainable HbA1C outcomes than any of the interventions alone (ElSayed et al., 2022; Sun et al., 2025). Hence, a multifaceted, all-encompassing approach to managing diabetes in the outpatient environment is required to achieve clinically important, sustainable glycemic outcomes in outpatient environments.

Along with evidence synthesis that established the relevance for the proposed quality improvement project, review of the existing literature led to the identification that there were plenty of existing gaps that still require quality improvement in the area. In the early stages, evidence synthesis methodology evolved from simple guideline following to meta-analytic synthesis of evidence with no longitudinal literature studies more than twelve (12) months in length, limited standardization of follow-up frequency and/or data acquisition protocols, limited cost-effectiveness analysis, and limited attention to culture-specific needs for access to technology-enhancing service delivery models.

Thus, there is a need for several implementation studies of contextually relevant interventions, which should have been methodologically evaluated by rigorous and thorough examination, to further examine the outcomes in various outpatient care settings (American Diabetes Association, 2024). Evidence gap closure will contribute to the body of literature and help to meet practical objectives related to nurse-led, sustainable chronic disease management.

Implementation Plan for the Intervention

A coherent, systematic and sequential plan needs to be developed and carefully carried out to achieve fidelity, replicability and uniformity across all project phases when implementing a structured quality improvement intervention. The implementation timeline included an eight-week process with a phased implementation process, including weeks one and two, when baseline HbA1c data, rates of follow-up completion for patients, and the nursing staff’s competency scores (using competency checklists) were extracted from the electronic health record (EHR) system and provided as the foundation for measurable pre-implementation benchmarks. The baseline assessment of data is common in quality improvement frameworks for the purpose of measuring the effectiveness of the intervention and identifying significant clinical change over time (Lighterness et al., 2024).

Pre-intervention benchmarks are essential to the project team to understand what needs to improve to meet the project’s goals, what they can reasonably expect to achieve, and what metrics should be used to track progress toward the organization’s goals (Willmington et al., 2022). For nursing participants, the focus for weeks three and four was on completing structured staff education, which included instructional sessions on: Diabetes Pathophysiology; ADA Guidelines for Diabetes Management; Principles of Medication Reconciliation; and Documentation into EHRs through simulation and case-based learning; in addition to peer mentoring workshops.

All nursing participants completed the competency checklists and knowledge assessments before and after the completion of the nursing education sessions to ensure that each nursing staff member had a competency level of 80% or higher before implementing the patient-facing portion of the intervention. The sequential delivery of the instruction and training ensured accountability, consistency, and quantifiable fidelity across the eight weeks of implementation.

Ongoing monitoring was needed to ensure fidelity of implementation, and the PDSA approach was used for iterative changes through structured interprofessional collaboration for the remaining weeks. Structured biweekly patient follow-up visits were provided in Weeks 5 and 6; continuous patient telehealth sessions were provided for patients who were challenged with transportation; and mid-point competency assessments of nursing care delivery with subsequent adaptive changes in educational delivery strategies were provided when necessary due to lack of protocol compliance or patient engagement.

The evidence is considerable that use of real-time performance monitoring during a quality improvement initiative can help identify implementation barriers early in the initiative and help to correct performance in response (Lighterness et al., 2024). In primary care settings and in managing chronic disease, particularly diabetes, there is often a system of structured interprofessional collaboration and communication in place for sustaining quality improvement (Sze et al., 2025). Process and outcome data from the EHR-based tracking systems were actively managed and monitored throughout weeks 7 and 8 to schedule repeat visits, to flag overdue patient visits, to centralize HbA1c data, and provide performance dashboards that enabled real-time monitoring at the practicum site of process indicators and outcomes.

Through structured checklist review, fidelity of the processes was verified, and through a comprehensive outcome analysis process, all baseline and post-intervention patient-related outcome data (glycemic, competency, and behavioral domains) were thoroughly reviewed in week eight. Since this intervention was planned using the structure, iteration, and eight-week time frame, it was responsive to evidence-based practice and was able to yield clinical improvements in the area of glycemic control for the practicum site.

Conceptual Model

Quality improvement frameworks offer the essential building blocks to launch, evaluate, and refine evidence-based interventions using systems and cycles of learning/adjustments. The PDSA model was selected to guide the project from its long history of success with chronic disease management (BARR & Brannan, 2024). The PDSA is based on the theory of quality improvement developed by W.E. Deming and is about learning/refining in a process way in the context of complex systems. The use of QI frameworks that involve repeated cycles of evaluation is consistently shown to be effective with chronic diseases (Endalamaw et al., 2024).

In the ‘plan’ phase, the team identified poor glycemic control as the key focus for adult patients, identified measurable outcome targets, and developed a structured ADA diabetes follow-up protocol and competency for staff. The ‘do’ phase involved simulation-based staff training, patient follow-up visits every 2 weeks (including telehealth) and activation of the EHR dashboards throughout the intervention. The evidence-based, iterative nature of PDSA led to decisions about implementation being made based on measurable evidence and will directly help lead to a more sustainable level of glycemic control through the standardisation of the nurse-led protocols.

The PDSA phases helped with the evaluative and adaptive aspect of the PDSA model to keep the intervention’s fidelity/quality and improve learning throughout the implementation period of 8 weeks. Formative data collected weekly in the ‘study’ phase included HbA1C trends, staff competency scores, follow-up visit completion rates, and EHR data documentation errors to assess progress toward goal thresholds and to identify any barriers being encountered and plan adaptive strategies. The PDSA model’s iterative progression allows healthcare teams to adapt to the challenges that arise during implementation and allows for the use of measured evidence to change the original protocol (Abuzied et al., 2023).

Within structured nurse-led diabetes management programmes, PDSA cycles have been implemented successfully, leading to reductions of the mean HbA1c level of 0.5%-1.0% where systematic testing of workflows was undertaken and protocols were continuously improved; this is congruent with the current project (Konnyu, 2023). The ‘act’ phase involved using insights from formative analyses to improve the delivery of adult education content, making systematic changes to workflow scheduling processes, and improving the telehealth outreach to patients with reduced engagement—a process that will become embedded in the routine clinic workflow after implementation. The flexibility, measurable processes, and looped feedback of the PDSA process continue to make PDSA the obvious project quality improvement model and the ideal model for effective and repeatable implementation and maintenance of improved outpatient glycemic management.

Data Collection and Analysis

For quality improvement efforts to yield evidence-based, interpretable, and clinically meaningful results, the selection of the appropriate design and the use of rigorous data collectionprocedures ares both critical. To obtain baseline and follow-up data for all 20 adult type 2 diabetes patients and 8 nursing staff members at the facility, the project’s design was a pre-post evaluation. The pre-post design is among the most widespread and accepted designs used in evaluating the effectiveness of a structured intervention in a real-world setting in a quality improvement context and has the advantage of being pragmatic and feasible to compare results of the same group of participants across defined periods of time (Klaic et al., 2022). Outpatient chronic disease management studies with pre-post designs report adequate sensitivity to find clinically meaningful changes in patient outcomes in a regular fashion (Lee et al., 2022).

To ensure that all measures were compared with a known, measurable standard, baseline assessments of the facility’s EHR system included assessments of HbA1C levels, attendance at follow-up visits, and competency testing for the nursing staff. Before the start of the project, the project was approved by the Institutional Review Board, and all HIPAA-related concerns regarding participant confidentiality and coding of names for use in data collection and analysis were addressed. Outcome evidence was gained using established quality improvement research methods and based upon a credible, comparable, and clinically interpretable pre-post design and standardized baseline data extraction for the project.

 Valid and consistent instruments of record and appropriate measures or metrics are critical to credible and dependable evidence of clinical and non-clinical operations quality improvement. The primary outcome measure was the average HbA1C level at baseline and at week 8, using a point-of-care laboratory test that was integrated into the clinic’s electronic health record system. The clinical significance of HbA1C reduction from baseline after a structured follow-up protocol recommended by the American Diabetes Association was defined as a 0.5 percentage point or greater reduction (Tiwari & Aw, 2024).

Measurement instruments should be considered to have high content validity and measurement reliability, both before and after the project, for outcomes to be used as a valid basis to determine the effectiveness of a structured intervention. Validated and reliable outcome measures played a vital role in the quality improvement entity’s evidence base for making clinical decisions, modifying protocols, and planning sustainability (Gabriela et al., 2025). The secondary outcome measures were as follows: Diabetes management competency test scores of the nursing staff (pre- and post-training) using a validated instrument. The percentage of follow-up visits that are completed (as reflected in scheduling audit logs within the electronic health record (EHR) system).

Structured behavior checklists to evaluate insulin adherence and frequency of blood glucose monitoring; patient engagement in diabetes self-management. Before the implementation of all measurement instruments, an expert panel was asked to evaluate them for content validity and guidelines for using the same data collection procedures at each of the measurement time points throughout the 8-week project to ensure that the outcomes collected would be reliable and valid. A comprehensive selection of primary and secondary outcome measures across the glycemic, competency, and behavior domains will give a complete feel to the intervention.

Ethical Considerations

For the quality improvement projects, ethical principles need to be carefully considered to not only protect participants and maintain confidentiality of data, but also to ensure institutional compliance at each step of the way (i.e., during planning, implementing, and evaluating). An IRB evaluation of the project was performed before implementation, which resulted in the determination that the quality improvement project was not “human subjects research. As such, the IRB determined that the project was not fully IRB-reviewed because the research was to improve practice and not to assess generalizable knowledge (APRN personal communication, November 2025).

Quality improvement projects in health care institutions are often not considered human subjects research when they target existing care processes, use retrospectively collected clinical data, and use evidence-based practices. Just checking institutional review requirements and federal ethics guidelines is not enough to fulfill the ethical responsibilities of conducting a nurse-led quality improvement project.

Furthermore, ethical compliance involves compliance with the guidelines for IRB review of all data collection methods and procedures, recruitment/consent processes, and outcome reporting processes; thus, all collaborative institutional training initiative (CITI) certification requirements must be met before the project leader’s ability to conduct quality research that meets ethical standards of practice for conducting research in the clinical environment (APRN, personal communication, November 2025).

During the implementation of the project (8 weeks), the IRB determination, which was accompanied by the completion of all necessary CITI certifications, served as the ethical structure and regulation of all activities related to data collection, analysis, and reporting. The project’s ethical standards of practice in implementation helped to establish trust among the participants, institutional integrity, and scholarly credibility during each phase of implementation and outcome data measurement.

Conducting a quality improvement project ethically is one of the most important responsibilities in each of the stages of implementing a project, and protecting the confidentiality of the patient information and securing the storage space of all the project documents and information is part of this responsibility. All identifiers attached to patient data collected in the course of the QI project were replaced with unique coded identifiers before any process of data extraction, analysis, or reporting activities took place so that no individual patient could be identified by the documents created, the results of the data analysis, or the dissemination of materials developed during the 8-week implementation phase of the project.

All individually identifiable health information (IIHI) collected as part of a health care quality improvement project must be de-identified, secure, and accessible only to authorized personnel, according to the HIPAA requirements (CDC, 2024). The de-identification of IIHI in quality improvement projects is an essential ethical safeguard to support individual privacy rights, as well as ensure compliance with federal regulations for protecting confidential data (Lulamba et al., 2025). During the 8 weeks of implementation, all electronic data and competency assessment records were kept on password-protected, encrypted devices (only accessible to the project lead, site preceptor, and designated project personnel), and all hard copy data were kept in locked cabinets with restricted access to the clinic (APRN, personal communication, November 2025).

Weekly checks were carried out to ensure compliance with all de-identification processes; any deviations from compliance with the established procedures, as noted during the weekly check, were corrected on the spot to ensure data integrity and compliance with institutional requirements. The project adhered to all data security and de-identification procedures, and robust application of those procedures confirmed that the project had the highest ethical standards, and that there was credible evidence in support of sustainable quality improvement in outpatient diabetes management.

Project Results

When presenting project results, the clinical importance and organizational effect of the quality improvement intervention (QI) should be clearly communicated to all stakeholders in an organized, evidence-based manner. The primary outcome results indicated a clinically significant mean reduction in HbA1c of 1.52 percentage points after 8 weeks (9.95% at baseline to a mean of 8.22% at the end of the intervention, compared to a threshold of 0.5 percentage points for a successful intervention set before the start of the QI intervention). 89.2% of scheduled follow-up visits were completed during the 8-week implementation of the QI intervention, signifying that patients were engaged in the structured ADA diabetes follow-up process.

In addition, patients and nursing staff having finished the bi-weekly follow-up visit schedule confirm the feasibility of the current operations to accommodate the bi-weekly visit schedule. While there was much improvement in the glycemic measures, just 10% of the patients enrolled in the study at the end of the 8-week intervention period, and there were undoubtedly many other factors that contributed to reaching the full targets, including an intervention period longer than the 8 weeks that was the duration of the practicum.

In general, the findings of the primary outcome support that the project site nurse-led follow-up protocol using a standardized, ADA-compliant approach led to clinically and dimensionally meaningful improvements in glycemic control in adult patients with type 2 diabetes. The secondary outcome results also support the overall and multi-faceted effect of the structured intervention, in all three of the domains of nursing staff competency, patient self-management engagement, and nursing staff delivery fidelity over the 8-week structured intervention. At the end of the structured training, the nursing staff competency scores went up dramatically from a mean pre-training score of 59.0% to a mean post-training score of 85.4%, with seven of the eight nursing staff achieving the minimum competency score of 80% needed for independent protocol delivery (APRN, personal communication, November 2025).

The self-management engagement scores averaged 7.4 on a scale of 10 at 8 weeks; 70% of patients were taking 100% of their medication as prescribed, and 65% of patients monitored their blood glucose routinely every day during the 8-week structured intervention period. An unexpected finding of the study was Transportation barriers, as 67% of scheduled visits to the clinic were completed by patients, which negatively affected the glycemic trajectory of some enrolled patients and underscored the clinical importance of implementing an integrated telehealth approach as an equitable and alternative method for providing long-term outcomes to the structured diabetes follow-up. Overall, the findings of the secondary outcome results indicated change in a uniform and consistent manner across the clinical, operations, and behavioral domains, supporting that the diabetes follow-up protocol was structured and ADA compliant, and that there was dimensional and meaningful change at the project site. The results of the project are presented in the appendix.

Project Outcomes

Evaluating progress toward the project’s objectives provides information on the value of the program as a whole for clinical practice and as an evidence-based intervention. The primary outcome of the projecta, decrease in HbA1c, was met, with a decrease of 1.52 percentage points (from baseline) and a large margin of success in achieving the required decrease that was set at 0.5 percentage points. The clinical significance of the 8-week implementation of the structured ADA diabetes follow-up protocol was fully manifested, as there were sustained and clinically significant reductions relative to baseline in glycemic measures after the first 8 weeks of implementation.

The results of the QI project demonstrated a similar reduction in HbA1c compared to previous studies that focused on similar patient populations in nurse-led (protocol-driven) diabetes follow-up care, which showed a range of HbA1c reductions from 0.25% to 1.69% across similar outpatient primary care organizations (Asmat et al., 2024; Koo et al., 2024), and was larger than expected in the literature on diabetes QI (Asmat et al., 2024; Koo et al., 2024). Results from nurse-driven self-management education indicated almost all nurse competency scores andpatients’s self-care behavior were improved when delivered in a structured nurse follow-up process that is protocol-driven (Dailah, 2024).

In addition to achieving the primary outcome of improving nursing staff competency, there was also a significant and measurable T-test difference (p < .01) in the number of participants (7 out of 8) who achieved a minimum of 80% upon completion of the training, and while achieving an HbA1c < 7% for 70% of all patients enrolled in the pilot program was not achieved in the eight-week timeframe, it is assumed that with ongoing implementation for a longer duration than the practicum period, final HbA1c target attainment (< 7%) for all enrolled patients will occur.

There were also several unintended findings such as patients experiencing transportation barriers that affected the ability to attend all planned in-person visits (67% completion of in-person scheduled visits), which limited data on the patients and mentioned earlier, indicated an urgent need for the implementation of telehealth for follow-up with patients so there is an equitable and accessible way to deliver continued nurse-led follow-up care to patients who may have experienced barriers to visiting the healthcare organization in person.

The strengths, limitations, opportunities, and barriers assessment of a quality improvement project also offers an evaluative lens on the internal validity and external applicability of a quality improvement project in similar clinical settings. The main benefits of the project were high staff competency improvements, high compliance with the follow-up system (89.2%), accurate EHR documentation and interprofessional clinical team collaboration, and the introduction of the nationally recognised ADA clinical practice guidelines.

These elements added to the credibility of the intervention design. QIPs with high fidelity to intervention protocols (i.e., following protocols as described) and systematic competency development and EHR monitoring yielded a more consistent, valid, and generalizable outcome, thus supporting methodological strengths of the present QIP (Endalamaw et al., 2024); while those with no systematic accountability structures did not. Multi-disciplinary structured quality improvement initiatives resulting in a validated follow-up protocol and EHR-based monitoring continuously yield positive outcomes (Ebbers et al., 2023). The challenges faced with the quality improvement project were that the implementation time was 8 weeks for the project, which made it difficult to assess the sustainability of the HbA1c improvement.

Furthermore, the number of participants on the nursing staff was small (n = 8), reducing the power, and only one clinic site was included, further reducing the generalizability of the results across multiple clinical settings. During implementation, opportunities for expanding the standardized ADA follow-up protocol were identified for other chronic disease populations seen at the outpatient clinic, using peer-supported digital messaging to further engage patients between clinic visits, and disseminating the project findings from peer-reviewed publications to build the evidence base.

Sustaining change happens post-project, intentionally planned for by the organization, documented in an organizational agreement to sustain the changes, and systematically integrated into everyday clinical practice and practice accountability. The clinic will implement the structured ADA diabetes follow-up protocol into its routine nursing workflow procedures to support the protocol. The EHR dashboards, automated appointment reminders, and fidelity checklists will continue to be part of the permanent operations infrastructure to ensure adherence to the protocol in the future (APRN, personal communication, November 2025).

Structured outpatient interventions must be monitored, adjusted, and followed for at least one year after implementation to ensure that the change in practice is sustained in the organization’s clinical routine and culture (Jahed et al., 2025). Key components of successful protocols are best captured through formal policy adoption for greatest long-term sustainability in quality improvement efforts for chronic disease management (Endalamaw et al., 2024). New roles being created for outcome sustainability will involve a Diabetes Protocol Coordinator to track EHR dashboard metrics and to schedule periodic quarterly competency checks on nursing personnel (APRN, personal communication, November 2025). The outcomes of the quality improvement project will be disseminated through internal project reports, conference presentations, and peer-reviewed journal articles, further reinforcing the organization’s commitment to the standardized diabetes follow-up model, and supporting future replication in similar outpatient primary care environments that care for a diverse adult population.

Recommendations

Results of Quality Improvement efforts based on evidence will yield additional understanding that would not only be relevant to its implementation, but also to future research and practice in nursing. There are several recommendations for future practice, including the time frame of the intervention, which was only 8 weeks long, for future research to determine the long-term sustainability of HbA1c levels following the 8-week practicum. Furthermore, the protocol should be expanded to other chronic disease populations in the same outpatient environment, thereby increasing organizational impact and allocation of resources.

Future studies should include replication studies in other centers to assess the effectiveness of the protocol in larger and more diverse nursing populations. Another area that calls for additional research is cost-effectiveness analyses, which involve determining the number of fewer hospitalizations that result from a standardized follow-up. Adopting digital messaging tools that are supported by peers will enhance patient engagement and self-management assistance between appointments (Nagra et al, 2024). Culturally Responsive Curriculum Development and Digital Equity research will assist in determining underserved populations’ digital access gaps. One of the most important ways to achieve glycemic equity and improve the quality of outpatient primary care to a diverse adult population will be through the continuation of well-supported, structured nurse-led diabetes follow-up programs.

Summary

Key findings from a QI project are a vital way to reinforce the clinical significance, organizational relevance, and scholarly value of the implemented clinical intervention. Patients’ HbA1c levels decreased by 1.52% at the end of the 8-week ADA diabetes follow-up protocol, as nursing staff competency scores rose from 59.0% to 85.4%, and adherence rates rose to 89.2% at the end of the protocol. Thus, the introduction of the ADA protocol into clinical practice led to overall clinically significant, measurable improvements in glycemic control, productivity of nursing, and follow-up adherence. Implementation has progressed the clinic’s organizational mission of offering patient-centered, evidence-based, and accessible primary care by implementing a standardized diabetes follow-up process, enhancing interprofessional coordination, and establishing EHR-integrated monitoring processes as a routine workflow in the clinic.

The project results aligned with the clinic’s strategic priorities related to value-based care delivery, quality in the care of people with chronic diseases, and health equity goals for a population of people from various urban communities being served by the practicum site. Finally, the nurse-led protocol developed using the ADA can and should be replicated, expanded to other similar outpatient primary care clinics, and will help ensure continued glycemic improvement in similar clinics/ambulatory care settings. Finally, interprofessional working in an organizational framework to support evidence-based QI has significant and sustainable clinical outcomes that are relevant to the organization’s mission, as well as to national standards for excellence in chronic disease management.