NURS FPX 9030 Assessment 4 Manuscript: Draft

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

It is important to understand that inadequate glycemic control in adult patients of type 2 diabetes mellitus (DM) is a critical practice gap in the outpatient primary care setting, and the lack of standardized, protocolized follow-up pathways equals loss of education, medication review, and/or preventable complications. Almost half (42%) of adult patients at the project site had a hemoglobin A1c level >9%, and only 36% had a level <7% compared with the national level of about 6% to 7% of adults with diabetes, reflecting poor glycemic control. Despite the American Diabetes Association (ADA) practice guidelines, there are gaps in the implementation of these guidelines in the form of nurse-led follow-up, staff competency, and structured patient education across all primary care settings. The PICOT question the project is focused on is: For nursing staff working with adult patients with diabetes (P), what is the impact of the diabetes follow-up protocol outlined in the ADA (I) as compared to the usual care provided by staff (C) on glycemic control (O) over eight weeks (T)? A structured ADA-aligned follow-up protocol, plus staff competency development and patient self-management education will offer clinically significant improvements in glycemic outcomes and take a step forward in evidence-based chronic disease management in outpatient primary care (Adjei et al., 2025; APRN, personal communication, November 2025).

Practice Problem

In outpatient primary care, a systematic, evidence-based approach is needed to manage chronic diseases and to raise standards of glycemic control of adults with type 2 diabetes, which are below those of established health system standards. Outpatient primary care clinic data at the site-level indicated that 42% of all adult patients had an APRN, and the APRN indicated that 36% of adult patients had an A1C level below 7 percent (APRN, personal communications, November 2025). The site performance data is well above standard health system benchmarks: for example, nearly 22% of all the nation’s adult population with diabetes has poor glycemic control, and nearly 45% of adults with diabetes have not achieved an HbA1c of less than 7% globally (Adjei et al., 2025; Dinavari et al., 2023). One out of four adults in the U.S. and Europe continues to have a hemoglobin A1c of greater than 9%, reflecting the very poor metabolic control of the individuals (NCD Risk Factor Collaboration (NCD-RisC), 2023). Poor glycemic control in adults seen at outpatient diabetes clinics is mostly attributed to both behavioral and demographic factors, and the need for identification of people at higher risk of poor glycemic control and structured clinical interventions to enhance glycemic control early in life. The quantitative data gathered from the site will provide a basis from which a measurable targeted quality improvement intervention can be implemented at the practicum site.

A comprehensive review of the current workflow and process flows, staffing, and care coordination practices in the clinical setting is necessary to identify causal factors that can lead to poor glycemic control. Key process failures reported to have a negative impact on glycemic outcomes identified during the project site chart audit and chart documentation of EHR included inconsistent scheduling, inadequate structured follow-up, and variations in education. The follow-up pathway was not standardised or protocolled, resulting in ad hoc follow-up scheduling, variable active use of EHR reminders, and no multidisciplinary coordination, with an impact of delayed medication adjustment and tailored education for those patients most likely to experience complications (APRN, personal communication, November 2025). Follow-up visit completion rates and EHR documentation audits also revealed variations in processes and systems, specifically in patient outreach and follow-up visit scheduling (APRN, personal communication, November 2025). In the past, general diabetes education sessions and periodic evaluations by telehealth were irregularly planned, with no clear evaluation process, resulting in inconsistent learning and teaching quality and incomplete patient understanding. However, the practice gap was confirmed to be due to the absence of a protocolised pathway for follow-up through a comprehensive needs assessment (Dailah, 2024).

All of these stakeholders who are impacted by chronic disease management will need to be taken into account to a significant degree to justify timely and systemic intervention to improve the quality of services they receive. Being poorly controlled diabetes has been proven to be associated with higher rates of hospitalization, use of health services, and long-term burden of complications, including heart disease, neuropathy, and preventable hospitalizations; the primary stakeholders affected by this glycemic disparity are nursing staff, adults with diabetes, and organizational leaders (Sun et al., 2025). For nurse-led structured interventions in all outpatient primary care settings, the potential for HbA1c reduction is between 0.4% and 0.9%, and a positive impact on adherence outcomes was well established; in most cases, the timely implementation of effective evidence-based interventions was clinically not justifiable. The Centers for Disease Control and Prevention (CDC, 2024) has reported a continuous gap in glycemic control at the national level, especially among vulnerable and low-income patients; therefore, there is an urgent need to take a prompt step to solve this problem with a standardized approach at the project site. Because of this, and consistent with the site’s mission to deliver accessible, evidence-based primary care, filling the identified practice gap would not only be clinically essential but also a site strategic priority.

Project Site

Structured chronic disease management interventions are delivered from a variety of outpatient primary care clinics to urban settings. An example of this is the primary care outpatient clinic in NYC on which the project was based. The clinic has a wide range of adult customers from a variety of cultural and socio-economic backgrounds. APRN (personal communication, November 2025) indicates that about 60% of the patients at the clinic suffer long-term illnesses like diabetes and hypertension. Clinics are equipped with six examination rooms, two private counselling spaces, and workstations with telehealth that allow for telemonitoring for patients and virtual business. There are six health care professionals (nurse practitioners, medical assistants, care coordinators, health educators, and others) and office staff who all work with patients and the workflow requirements involved in patient care. The Clinic’s vision is to promote health for the community through accessible, evidence-based primary care services and through its preventive health programs. So, the clinic is a suitable setting for a structured quality improvement project on diabetes.

To understand the organisational context of a practice-site, the reader will appreciate how the quality improvement Project is a timely and appropriate response to an identified clinical issue. The clinic’s focus is on health education, continuity of care, and management of chronic diseases. The heightened focus on health education, continuity of care, and chronic care management could allow the utilization of a clear model for the care of diabetes (APRN, personal communication, November 2025). The use of electronic health records facilitated improved patient documentation, scheduling, and tracking progress at the clinic. A standard protocol would allow staff to educate patients and provide medication reinforcement — and there was already a framework in place to do so, so it wouldn’t be an added burden. Leadership affirmed that there was a gap and decided that the project was important to be prioritized owing to the potential clinical and financial implications. Leadership knew that there would be opportunities to improve the organization’s quality performance measures and meet value-based care and patient satisfaction standards by achieving glycemic stabilization. The organization’s strategic priorities were identified prior to the project, and the alignment of the project with the organization’s strategic priorities ensured that the practicum site was well-positioned for the quality improvement intervention.

To gain insights as to how poor glycemic control at the practicum site she was assigned to was linked to the flawed process, a systematic review of how diabetes was managed prior to the start of the project was undertaken. The main way of the nursing staff providing diabetes care and education was through the regular provider visits and through general patient-centred verbal education; however, there was no corresponding standardised or structured follow-up procedure for the two ways of providing diabetes care. There were inconsistencies in diabetes education and poor communication between nurses and patients about self-management strategies due to a lack of structured follow-up. Ad hoc scheduling and rescheduling, untimely use of EHR reminders, lack of multispecialty coordination, and lack of reviewing patient follow-up data to facilitate timely medication changes and targeted patient education for patients at highest risk contributed to significant process flaws. Outpatient diabetes care has consistently been found to be associated with less optimal glycemic outcomes and less adherence to recommended self-care behaviors by individuals with diabetes(Heise et al., 2022). In addition, a follow-up protocol for diabetes care that is standardized and adopted would result in fewer missed visits, fewer delays in timely interventions, and more complete and improved quality of diabetes care (Wang et al., 2025). A needs assessment was conducted using baseline data extraction, staff interviews, chart auditing data, and EHR auditing data, which determined the need for an evidence-based, diabetes follow-up protocol intervention for the clinic. The process failures highlight the need for a diabetes follow-up program based on protocol at the practicum site.

Project Population

Clearly defining the project’s population is essential to successfully target the interventions and make a meaningful and measurable difference in improving quality. The project population was defined as only nursing staff who have patient contact with type 2 diabetes in the outpatient primary care clinic, since the project intervention was intended to raise the nursing staff’s competency levels of implementing the standardized diabetes follow-up protocol from the American Diabetes Association (ADA) (APRN, personal communication, November 2025). The project involved many nurses with varied educational levels, clinical experience, and professional experiences with no common approach to control diabetes and conduct patient education. At least 8-10 nursing staff members had to participate in the program to detect a meaningful improvement in competency and following of the standardized diabetes follow-up guideline. The detailed profile of the nursing staff was created before the design of the quality improvement intervention to provide a framework to target, develop, and implement a competency-based and feasible intervention to effect quality improvement.

The example described the context of the clinical and professional attributes of nursing staff and made it easier to anticipate how to prepare for implementing standardized diabetes follow-up intervention. Each member of the nursing staff team involved in the project was a registered nurse or nurse practitioner with a current license and actively engaged in direct patient care with adult patients with type 2 diabetes, where patient education, supporting patient self-management, and chronic disease follow-up are essential components of the role of a nurse (APRN, personal communication, November 2025). Before the intervention, the nursing staff demonstrated different levels of confidence, knowledge, and implementation of existing guidelines for the management of diabetes, and a pre-intervention score of 59% signified an urgent need for an integrated, structured educational programme. The multi-disciplinary nursing staff that underwent the structured competency development program consisted of three nurse practitioners, two medical assistants, one care coordinator, and one health educator. A common understanding of professional traits of the nursing staff gave a good foundation for a quality improvement program for the intervention of the ADA follow-up protocol.

By defining inclusion/exclusion criteria for the project nursing staff, the project was able to stay on target of having a population focus, and thus work toward the improvement goals that anything it could do to help glycemic outcomes would be in line with that. The inclusion criteria for the project aimed at the nursing staff members who work with adults with a diagnosis of type 2 diabetes, who are involved in patient education about the disease, manage medication, or provide follow-up care related to the disease as part of routine clinical functions in the clinic (APRN, personal communication, November 2025). The nursing staff will perform all the above functions as well as be actively employed at the project location for all 8 weeks of the intervention and be actively involved in clinical provider responsibilities pertinent to the ADA follow-up protocol objectives. Institutional staff members who were in an administrative role (not providing direct care to patients), nursing support staff (not providing direct care to patients), and institutional personnel with temporary and/or short-term staffing role (not providing adequate direct care to patients) were excluded from participation in the project. The internal validity of the project was enhanced by the inclusion criteria and exclusion criteria, which meant the results from the structured intervention would give an accurate representation of the effect of the structured intervention on the nursing population intended to participate in the project.

Evidenced-Based Interventions

Successful QI interventions involve using more than one component of the intervention to attain glycemic improvements that are more than those of the single-component QI interventions. The literature facilitated combined strategies with fidelity to the intervention and outcomes using scalability, cultural tailoring, EHR integration, and iterative measurement. Efforts were undertaken to improve the process of care to be offered to people with diabetes, as the process varied among the various providers during the eight weeks of the project, to make it more uniform, using the approach recommended by the ADA. Healthcare providers attended trainings to learn more about diabetes pathophysiology and how to utilize EHRs for tracking outcomes, patient engagement, and adherence (Fracso et al., 2022). The educational program consisted of two components: simulation exercises and the ADA educational case and peer-mentor workshops to reinforce the application of EBDDM practices (American Diabetes Association, 2024). Teaching observations, performance checklists, and knowledge assessments were used to assess competency to ensure participants could apply a standardised follow-up procedure and patient education resources, which had been previously validated. Staff continued to receive education to keep the momentum going, enabling the development of staff accountability, consistency in practice, and a culture of continual quality improvement (CQI) (Dailah, 2024). Feedback cycles, peer discussion, and regular refresher sessions have been interwoven to discuss what has worked well amongst the nursing participants and to check in whether training has had the desired effect and if there are any barriers. Biweekly follow-up schedules were selected as they showed to have an important impact on decreasing HbA1c levels in a quasi-experimental context in outpatient visits (Kerari et al., 2024). Variability between people with diabetes in literacy, resources available, and the model of iterative, team-based intervention needed adaptations to each project, and the structured intervention of eight weeks aligned with the guidance from the American Diabetes Association (2024). A systematic mapping of ADA standards to clinic workflows helped with measurable glycemic gains throughout the entire implementation process.

Due to the integration of delivering health promotion information by the health educator, care coordination, and multidisciplinary team (MDT) approaches were used to share clinical tasks among MDT members. Hospitalisations also decreased steadily in a population-based diabetes care under team-based models, with increases in engagement levels aligned with clinical reasoning of interprofessional role distribution (ElSayed et al., 2022). Along with the clinical team, competency-oriented team training contributed to improving coordination of the team’s intervention delivery roles in the clinic, and the fidelity of implementation (Samardzic et al., 2020). Comparative studies found that the multidisciplinary interventions resulted in greater changes to the systems as compared to the educational interventions by a single provider alone (ElSayed et al., 2022; Samardzic et al., 2020). However, with no strategic reallocation plans, smaller clinics were limited by the number of resources they had and the number of staff members who could work. Therefore, one of the main issues in the design of the intervention was the choice of a multidisciplinary team to provide the care in line with the uniform and fair protocol throughout the project site.

The critical role of patient-centred self-management programmes as key interventions for self-efficacy outcomes and for glycemic control outcomes at the patient level in all patients using these programmes was emphasised. A multicenter randomized trial by Asmat et al. (2024) showed that structured patient-centered education consistently reduced the levels of HbA1c and improved self-care behaviors. Fracso et al. (2022) conducted a phenomenological study, and found evidence for empowerment mechanisms surrounding peer support and setting one’s own targets by vulnerable individuals. Systematic reviews found meaningful effect sizes, but noted great differences in the program delivery and the measurement of the included studies (Asmat et al., 2024; Fracso et al., 2022; Huang et al., 2024). Further, the addition of tailored curricula and fidelity monitoring were included to maximize effectiveness of the intervention across the various populations of patients treated at the project site. The nurse led visits were underpinned by patient centred self-management education and subsequent behaviour change and quantitative glycaemic control improvement over time.

Telehealth follow-up and automated EHR reminders were used because access and compliance were issues for patients who were not mobile or had transport restrictions. At the national level, Ezeamii’s (2024) analysis highlighted that telemedicine interventions have been able to enhance the attendance of appointments and remote monitoring features. However, the effectiveness of telehealth was not evenly distributed among various socioeconomic groups because of inequalities in access to digital technologies, as well as inconsistent levels of health literacy. When extending the use of telehealth to the structured follow-up, similar short-term glycemic outcomes resulted (Ezeamii, 2024; ElSayed et al., 2022). The tracking system used in the EHR was implemented to help with follow-up scheduling, find any overdue visits, and to share information in one location at the project site. Okemah et al. (2023) found that web-based tools had a positive impact on documentation accuracy and enabled outcome monitoring to be done across providers’ teams. Comparative results showed that EHR prompts worked better to improve adherence to protocolized visits, compared to a passive EHR intervention with only the reminders component (Okemah et al., 2023; ElSayed et al., 2022). To implement it, investments in training were needed, as well as redesigning workflows and doing periodic audits to ensure the quality and utility of data during the course of the intervention. The introduction of EHR enabled the project to perform monitoring at scale, which met the thrust’s outcome goals.

To enable culturally-appropriate learning interventions to overcome language barriers and culturally specific self-management beliefs that were present in the patient population that participated in the study. Interventions that included cultural dietary preferences and how to engage the family reported more improvements in HbA1c levels (Wadi et al., 2021). There is emphasis on increasing the relevance to rural and urban practice settings in the sense of Goetz and Schork (2020) of personalizing medicine. Within the different populations, the culturally tailored education had longer-term impacts on behaviour change than the generic one. Staff were given simulation-based training to help strengthen their teaching skills and further implement the diabetes teaching procedures. Concentrating on patient education, Okemah et al. (2023) demonstrated knowledge gain and patient education performance after completing web modules, a form of training, for the faculty members. From the comparative studies, it was observed that didactic learning to retain the practical skills had a lesser impact as compared to simulated and practical learning (Bisbey et al., 2021; Dailah, 2024). Hence, the project has focused on simulation, demonstration, and competency checklists for maximisation of sustainable staff competency during the implementation process. To facilitate a patient-centered behaviour change and lifestyle changes, the follow-up involved the use of behavioural goal setting and motivational interviewing (Huang et al., 2024). Structured follow-up facilitated culturally responsive education and behavioral strategies, rendering culturally competent and equitable delivery of interventions to be culturally relevant and congruent with enrolled patients’ varied self-management needs.

Peer mentoring and group support sessions were also utilized to leverage the social reinforcement and experiences to maintain follow-through on self-management. Fracso et al. (2022) reported qualitative results of the boost in confidence, self-efficacy, and problem-solving with consistently structured group interactions. Individual interventions led to greater knowledge change, and group interventions led to greater sustained behaviour change and long-term peer accountability compared to other interventions. Biweekly data reviews and adaptive changes were integrated throughout the project to ensure fidelity and maximize learning. However, these factors have prevented the widespread application in smaller practices, due to the expense of devices, patient engagement variability, and concerns about patient data protection. While these trials are underway, integration with EHR systems could be optimized and enable outpatient use of a patient cohort that is motivated by participation in the program to reduce resource demand during the early stages of the programme rollout. A strategic approach to make the intervention socially reinforcing, responsive, and capable of involving patients for 8-weeks of implementation was provided through peer mentoring, group support, and repeatedly reviewing data.

• Role of the Project Lead

Successful quality improvement projects require systematic and logical designs, decision-making, and scholarly leadership that engage both clinical knowledge/experience and interprofessional teamwork and systems thinking throughout all phases of the quality improvement project. The DNP student was responsible for the design of a standardized ADA diabetes follow-up protocol, educational materials for the roll-out of the protocol, and setting up EHR dashboards to facilitate the protocol, and overseeing all the logistics of implementing the eight-week protocol (APRN, personal communication, November 2025). The project lead obtained baseline measures derived from the EHR of participating patients for hemoglobin A1c (HbA1c) data prior to the intervention, staff competency scores, and completion of follow-up to compare the effectiveness of the actions. To effectively lead the evidence-based project, regular communication between the project lead and the organizational stakeholders, interprofessional team members, and academic mentors was required throughout the implementation process to ensure fidelity with the evidence-based implementation process and maintain the scholarly rigor of the project. Iterative refinements for every implementation cycle were guided by the plan-do-study-act (PDSA) approach, making sure that changes in the workflow were data-driven and transparent throughout each implementation cycle (Talukder, 2025). Continued communication with the site preceptor, DNP faculty mentor, and clinic leadership (APRN, personal communication, November 2025) took place through structured meetings, virtual consultation throughout the implementation process, and a written progress report documenting implementation milestones and adaptive modifications. Ethical compliance was closely monitored and adhered to throughout the project; CITI training certification, IRB approval coordinating, de-identification of data records per HIPAA-compliant procedures, and informed participation from all participants were done consistently throughout the project. The scholarly rigour of the project lead, clinical expertise, and collaborative leadership throughout the implementation process were key and showcased the pivotal roles that APRNs will play to sustain quality improvement outcomes within the field of nursing practice.

• Roles of Other Team Members

Interprofessional team roles need to be clearly defined and responsibilities equally distributed between team members, while the quality of the care provided by each individual intervention component responsible for providing coordinated care also needs to be improved. Preceptor at the content location served as clinical supervisor and augmented the APRN functions, making decisions related to implementing the protocol as directed by the preceptor, and was the main liaison to the leadership of the organization during the entire eight weeks of the project (APRN, personal communication, November 2025). Nurse practitioners conducted clinical evaluation, educated and counseled individually with each patient, and supported the patient to achieve recommended ADA goals with each semi-monthly visit. Clear roles within quality enhancement teams are consistently found to positively affect shared accountability and strengthen fidelity in delivering evidence-based intervention (Hempel et al., 2022). Telehealth logistics needs a coordinator for care managed scheduling, EHR activation of reminders, and attendance in order to maintain telehealth follow-up rates higher than established benchmarks. The health educator offered patient education materials in a culturally adapted format to program enrollees with a variety of languages and health literacy requirements. Consistency, accountability, and harmonics were achieved by each team member in knowing and practicing a defined role that would contribute to both the evidence-based project objectives and all phases of implementation.

In order to sustain implementation fidelity and scholarly rigor throughout a quality improvement project, each of the team members participates in a different and complementary role for the project. Medical assistants recorded patients’ vital signs, created educational materials, facilitated communication with patients, and input clinical data from each biweekly encounter with the patient into the Electronic Health Record (EHR). All nurses attended all educational sessions, applied a fixed part of the ADA follow-up protocol when seeing patients, and filled in a fidelity checklist for each visit with the patient. It is known that collaboration between health care professionals and a formal communication system is essential for the ongoing success of quality improvement efforts in primary-care environments (Dellafiore et al., 2025). The shared accountability fosters following the protocol of the implementation and the prompt detection of any obstacles in the implementation process, irrespective of the roles different team members can play (Grant et al., 2024). As part of all phases of implementation, the DNP faculty mentor was available for academic consultation by reviewing the reports kept by the DNP student. The interdisciplinary team members met biweekly with the stakeholders with the aim of ensuring constant communication, transparency, and problem-solving within the project team.

Literature Synthesis

A well-designed and systematic search strategy for the literature is the key to identifying high-quality, relevant evidence that directly reflects the PICOT question that is used to guide the quality improvement project. Picot question: How will the practice of the ADA diabetes follow-up protocol (I), compared to current protocol practices (C), benefit glycemic control (O) for nursing staff caring for adult patients with diabetes (P) over 8 weeks (T)? A multi-database search was performed in PubMed/MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, Web of Science, Proquest Dissertations and Theses, and Scopus in order to answer the question in these databases. The databases that were chosen included peer-reviewed evidence, clinical practice guidelines, and pertinent doctoral projects related to nurse-led diabetes management and implementation of the ADA guidelines in outpatient primary care. The medical subject headings (MeSH) that were added were “diabetes mellitus,” “type 2 diabetes,” “glycemic control,” “HbA1c,” “nurse-led interventions,” “ADA guidelines,” “diabetes follow-up,” “self-management education” and “primary care. The following strategy was used to apply Boolean operators in creating structured combinations: (“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 search strategy must be systematic and well-developed to ensure that retrieved evidence is representative, reproducible, and directly related to the problem being addressed in the clinical problem.

A total of 362 records were obtained from initial database searches in all of the databases searched. 308 articles had unique titles and abstracts after removing 54 duplicate citations, which were then screened according to inclusion and exclusion criteria. Eligibility for inclusion was determined by being published in English in a peer-reviewed journal between January 2021 and February 2026, with a population of adults, a nurse-led intervention defined as a protocol or structure for intervention or follow-up, and a quantifiable glycemic outcome, such as HbA1c. Pediatric populations, interventions only in inpatient acute-care facilities, non-clinical commentary, editorials, and studies that did not provide measurable HbA1c data or glycemic data control were excluded. An additional 11 sources relevant to the topic that were not identified in the database searches were found by manual reference list searching of systematic reviews, clinical position statements, and publications of the ADA Standards of Care. Gray literature searches involved governmental publications, standards from the professional diabetes organizations, and doctoral dissertations examining nurse-led diabetes management models in outpatient settings. Transparent & systematic screening procedures enhance trust and rigor in the evidence synthesis.

Twenty sources were selected for synthesis and fact tables after an extensive full-text review for relevance to the PICOT focus, methodological rigor, and measurable glycemic endpoints. Duke University (2023) systematic approach for recommendations around the “strength of recommendation taxonomy” (SORT) framework was used to analyze the methodological soundness and clinical relevance of all retained studies. The framework emphasized outcomes focused on patients, including prevention of complications, lower HbA1c levels, and avoiding hospitalizations. Seven studies were classified as having SORT Level A from high-quality RCTs, SRs, and meta-analyses. Forty percent (10) of the studies were rated Level B, which were well-designed comparative effectiveness research, quasi-experimental studies, and cohort investigations. There were three studies eligible for Level C (clinical practice guidelines, quality improvement projects, and narrative reviews). Results of the distribution of evidence quality levels confirmed that the nurse-led diabetes follow-up interventions in the majority of outpatient settings are structured, and offer a preponderance of diabetes follow-up care that is moderate-to-high quality evidence in alignment with the American Diabetes Association clinical practices standards.

• Analysis of Evidence

Review of the full set of twenty retained studies indicated uniformity and consistent trends suggesting that nurse-led implementation of ADA-aligned diabetes follow-up was an effective approach to improving glycemic control, self-efficacy, and self-management behaviors of self and adult patients with type 2 diabetes. Effect sizes were found across the investigations, varying from modest to clinically significant. Eventually, in comparative analyses, HbA1c reductions were shown to range from 0.25% to 1.69% with all nurse interventions (Asmat et al., 2024; Chen et al., 2025; Koo et al., 2024). Using evidence, structured DSMEs had pool SMD of -0.468 (-0.658 to -0.279). Under various clinical contexts and delivery methods, differences in scores obtained from nurse telephone follow-up protocols ranged between -0.59 (95% CI -0.85 to -0.34) (Yimer et al., 2025) and -0.59 (95% CI -0.85 to -0.34) (Chen et al., 2025). There was clinical equivalence among technology-enhanced delivery modalities such as telehealth consultations, structured telephone coaching, and peer-supported instant messaging, and the traditional face-to-face follow-up. The modalities were found to have a significant impact on patients’ accessibility, patient engagement, and patient adherence with self-monitoring. The similarities between the results of the studies in the different types of designs and geographic locations increase the confidence in the clinical applicability of nurse-led diabetes follow-up interventions.

The evidence gaps that emerged from the retained literature were a lack of information on retention frequency protocols for optimal follow-up and the absence of longer term (>12 months) outcome data. Additional gaps in consistent application of the ADA guidelines were also mentioned, such as gaps in provider knowledge, fragmentation of the work flow and deficiency of institutional accountability mechanisms. The four themes that emerged from the analytic synthesis to order the findings were related to: adherence to the ADA guidelines and clinical practice standards, nurse-led interventions and staff competency development, the role of DSEBS interventions, and technology enhanced diabetes care and diabetes remote follow-up. Each one highlights a different part of the evidence-base and all dovetail into the broader ‘whole-organisational investment’ that is needed to achieve clinically relevant and organisationally sustainable glycemia benefits. The evidence gaps identified further support the academic and real-world importance of having a protocolized, structured quality improvement (QI) effort in an outpatient primary care clinic. Thematic organisation of findings can be used to look systematically at the individual, but related, components of the intervention in relation to how this handles the complexity of the outpatient diabetes management.

• Theme 1: ADA Guideline Adherence and Clinical Practice Standards

Development of ‘effective glycemic control of outpatients who accept primary care depends on the compliance which provides the framework of the organization of the healthcare structure. ElSayed et al. (2022) revealed a significant association between compliance rates 89.8% or higher and having more adults who achieved the desired level of HbA1c, as well as a strong correlation between low prescription accuracy of GLP-1 receptor agonists and SGLT2 inhibitors and poor metabolic outcomes in consistently low groups across the entire population studied. Tiwari and Aw (2024) found that many constraints exist that impact the ability to consistently implement guidelines for medication therapy and consistent monitoring, including inefficiencies of workflows and lack of provider knowledge. Taken as a whole, the studies indicated that some factors are found both on system and provider levels that prevent successful implementation of ADA guidelines, and that, protocol driven nursing interventions are particularly positioned to influence the factors. Systematically integrated follow-up can become more effective through a skilled application of ADA aligned follow-up in clinical nursing activities following a structured ADA aligned method.

New clinical guidelines based on ADA will translate in clinically relevant glycemic burden reduction within the nursing workflows. Utilizing the use of an ADA based follow-up pathway in the PCHM setting led to a mean change in HbA1c of -0.74% (p < .01) in patients who engaged in the pathways and to an increase in the proportion of patients with guideline appropriate antihyperglycemic prescriptions written for enrolled patients (Abukhalil et al., 2024). The findings were consistent with what was observed by Chen et al. (2025) which showed that after twelve weeks, structured adherence to ADA follow-up intervals and medication review visits by nurses led to a mean decrease of 1.02% in HbA1c (p < .001). Together, the studies indicate that consistent, clinical meaningful reductions in glycemia were seen in outpatient primary care when a structured nurse-led follow-up program that focused on ADA guideline adherence was implemented.

Guidelines alone are not enough to achieve best possible glycemic control, and other systems of reinforcement, accountability, monitoring and feedback are necessary. Implemented interventions with guidelines only show inconsistent results (Sun et al., 2025). Hence down-stream commitment from nurses and regular follow-up intervals are required, combined with the utilisation of protocols. At a population level, ElSayed et al. (2022) revealed only 23% of adults at the same time had target levels of HbA1c, blood pressure, and lipid levels, and were nonsmokers during the data collection period, which reflects that diabetes management comprises of various variables and adherence to guidelines on only one of these variables cannot resolve the other problem. Tiwari and Aw (2024) noted that there were knowledge gaps among providers on the updated diagnostic hierarchy and point-of-care testing requirements even though the updated guidelines were available and thus providers were not able to apply the guidelines to first line tests. In addition, Abukhalil et al. (2024) also revealed the low levels of adherence to preventive screening and the lack of adherence to guidelines for pharmacotherapy use in patients with diabetes; hence, the application of guidelines must take into account all clinical areas and not just diabetic pharmacotherapy. To ensure continued progress toward glycemic control, ADA standards should be integrated in an accountable care model with structured education, self-monitoring and follow-up, tailored to the individual needs of the patient, and led by the nurse along all aspects of diabetes care.

• Theme 2: Nurse Led Interventions and Staff competency development

Nurse-directed models of care are one evidence-based approach to enhance glycemic control through sustained interactions with patients and a coordinated, structured interprofessional care model. In addition, Dailah (2024) stated that the nurse-managed diabetes education program proved to affect people’s diabetes knowledge, as well as their behavior, psychological outcomes, and even their HbA1c level; educators and healthcare providers such as nurses can make a difference, as they have frequent contact with patients and educate them in a continuous manner. That’s where Jiang et al. (2024) took it further: They reported statistically significant improvements (p < .001) in diabetes knowledge, diabetes anxiety, depression, and self-care activities among the patients receiving nurse-led follow-up compared to patients receiving routine follow-up after six months of structured engagement. Multifaceted educational strategies targeting improvement of nursing competencies yielded a consistent reduction in HbA1c, blood pressure and lipid levels in the group of patients with clearly-defined scope of nursing responsibilities, and systematic education and training of their nurses (Lemoh et al., 2025). Hence, nurse-led interventions carry out consistent and multidimensional improvements in patient outcomes in practice projects which enable the nurse to exert autonomy and take clinical accountability for the quality of care.

Building staff skills creates a conduit between nursing practice, and the continuity of diabetes care to the patient in every health care setting. A recent study conducted by Aldahmashi et al. 2024, showed that targeted education led to an increase in the level of confidence of the nurses in implementing ADA protocols that can be reflected in the adherence rate to the glycemic monitoring protocol and patient education during the follow-up visit. A recent study by Abukhalil et al., (2024) demonstrated that integration of expertise led to the integration of competencies in the form of ADA protocol-based follow-up care in primary care, leading to better prescribing/medication use, better care coordination process and an average reduction in participants HbA1c of 0.74%. Having a nurse as one of the key players was positively mentioned as one of the factors contributed to better outcomes of care, related to advantage of the ADA. The study revealed a lack of knowledge and care through the absence of specialist diabetes nurses in inpatient wards in approximately 22% of the hospitals, thus highlighting the importance of building a strong outpatient nursing competence development to compensate for the lack of clinician/nurse support in inpatient wards (Dailah, 2024). Further evidence by Jiang et al. (2024) confirmed that care guided by nurses, which also involved structured education and several approaches to patient engagement, led to significantly better results; despite the fact that the control group received additional support on physical activity. Support for nursing development is directly associated with improved glycemic outcomes, from one outpatient setting to another, when supported and funded.

The availability of skills in co-ordinating interventions across the primary care system through the role of health visitors and midwives, combined with inter-professional working and well-defined nursing roles, enhances the clinical effect of nurse-led ways of working in diabetes. In one study, Jiang et al. (2024) showed that nurse-led interventions with structured educational intervention and multimodal engagement strategies lowered anxiety and depression scores as well as glycemic control and highlighted the multifaceted approaches of nurse-led interventions when using holistic, protocol-driven processes. Proper documentation review, collaborative practice, program design and education were all four proved to be the roles of the nurse that are essential in successful diabetes programs aimed at compliance with clinical practice guidelines and ultimately patient safety, as established by Aldahmashi et al. (2024). Abukhail et al. (2024) found that “reception” of [nursing-led post-visit follow-up] within patient-centered medical home (PCMH) models resulted in systemic improvements including improved prescribing practice and care coordination in the clinic. Dailah (2024) expressed that nurses are better equipped to deliver regular and persistent diabetes education, motivation and reinforcement compared to other health care providers because of frequency and quality of contact with patients through regular office visits. If nursing is embedded in and supporting structures developed interprofessional teams, the team as a whole generates quality products in diabetes management, which no other profession can attain on their own.

• Theme 3: Diabetes Self-Management Education and Support Interventions

Central enablers for implementing clinical recommendations and for achieving physiology and behaviour changes within the nurse-led follow up are structured diabetes self-management education and support programs. In a multi-center randomized controlled trial, Asmat et al. (2024) showed that patients randomized to the patient-centered self-management intervention had a significant mean HbA1c decrease of 0.25% (p = .03), large mean improvements in both self-efficacy (41.48, p < .0001) and self-care behaviours (18.56, p < .0001); inferior mediation analysis identified that the improvement in self-care behaviours was largely responsible for the reduction in glycemia. This corroborates the findings of systematic review and meta-analysis of 19 RCTs, which showed that structured DSMES has a statistically significant impact on glycemic improvement over and above routine-care (SMD = – 0.468, 95% CI – 0.658 – – 0.279, p < .001) (Yimer et al., 2025). Patient education programs, such as individualized counselling, that promote positive reinforcement for healthy behaviour change, have been shown to produce statistically significant improvements in the self-management of patients and improvements in clinical glycemic indicators time and time again.

Further factors – duration, intensity and structural consistency of DSMES programs – are key to achieving clinically important and lasting patient results. A systematic review and meta-analysis by Huang et al. (2021) of 34 studies with a number of 7,603 people found that self-management interventions of over 6 months had significantly greater impacts on quality of life, which included self-efficacy that was found to increase with each duration of intervention from 6 months onwards (95% CI 0.19 – 0.62, p < .001) with depressive symptoms reaching reductions consistently across intervention duration and reliably replicated across programs. In the same manner, Fracso et al. (2022) showed that, patients’ perspectives of motivation, a sense of community and a desire for self-improvement were changed and highlighted after their continued involvement in the Chronic Disease Self-Management Programme which was not achieved by merely having a short informative programme. The next step was to demonstrate that implementing bi-weekly TBC (telephone-based coaching) with pigai in the context of nurse-led FU (follow-up) care led to an increase in self-efficacy and frequency of BGM (behavior—blood glucose monitoring), which subsequently mediated the physiological improvements through the behavioral activation pathways (Chen et al., 2025). To achieve results outside the active intervention period it is important that the following design elements of DSMES are sustainable and meaningful in order to maintain contact and reinforcement and sustain the longevity of contact.

The content in the DSMEs has always been contextually appropriate and culturally responsive, and has enhanced the effectiveness of the programs and ensured glycemic outcomes are uniform across patient populations. There was high heterogeneity (I² = 85.5%) across the studies included, as noted by Yimer et al (2025), due to variations in cultural adaptability, the effectiveness of the educator as well as the health literacy of the target population in measuring the effectiveness of the DSMES program. Facing the community served, culturally-tailored modules that respect its eating habits, medication schedules, and community health-related beliefs are essential and integral to the efficacy of and success of the DSME modules rather than optional and contributing, as described by Sun et al. (2025). This was confirmed by Asmat et al. (2024), where these theoretically, culturally, and nurse-led interventions have a sustainable impact through a behavioural mediation model that accounts for 23.2% variance. Therefore, culturally appropriate content is tightly coupled and reinforcers and extra follow clues are carefully designed to be as impactful as possible at DSMES and glycemic improvements are equal across all patient populations.

• Theme 4: SOP for Technological solutions in diabetes management and remote management procedures.

Leveraging technology-based channels to provide services will also make nurse-led diabetes follow-up more accessible, and will prove more scalable to accommodate the increased demand for diabetes follow-up care features without impact on clinical result – as proven in the case of in-person based models. In a longitudinal meta-analysis systematic review including a total of 13 studies with 2294 patients, Chen et al. (2025) found that an ideal number of contacts is 16, each should be of 20 – 25 minutes and should be spaced half a month apart with the addition of the fixed mean HbA1c change attributable to nurse led telephone interventions, -0.59 (95% CI: -0.85 to -0.34, p < .00001) which resulted in a fixed mean HbA1c change of -1.23 (p < .001). With a remote home and self-care programme supported by nursing via the phone with the average level of HbA1c between 7.33% and 7.62% during follow-up, Koo et al. (2024) also observed the same results in a real-world longitudinal cohort study with 24 months of follow-up. These results corroborate the well-designed follow-up care protocols in the technology tools, involving the nurses regularly, and the engagement of patient with the nurse yielding clinically meaningful and sustainable glycaemic control outcomes.

Whereas cross-sectional evidence is conclusive that technology-driven nurse-led follow-up care models can lead to short-term decreases in HbA1c, longitudinal evidence reinforces the notion that their impact can extend to much longer follow-up periods than those of many of the shorter trials. Statistically significant differences in outcomes for chronic disease management also occurred when nurse-led interventions were delivered via telemedicine instead of in person, and statistically significant differences in access and patient satisfaction were found when the technologies were used to address geographical location and/or transportation barrier to regular follow-up visits associated with in-person follow-up interventions (Ezeamii 2024). From a qualitative perspective, Kamal et al., (2023) conclude that this study’s 12-month time frame is not long enough for the patients to act on the awareness and make it happen. Sun et al. (2025) reiterated the scalability of digital delivery of services to remote or resource-poor populations, and the key role of improved technologies in promoting health outcomes via engagement with patients, in the form of reminders, automated messages, and virtual visits that help overcome barriers to access. A structured follow-up care supplemented by technology can help achieve sustained glycemic control, by setting and monitoring the protocol parameters over the appropriate period of time carefully.

Even if good results are achieved, barriers are faced in the way of diabetes follow-up models and a proactive approach must be taken to ensure maximum possible scale-up and equitable and effective dissemination of the model across all patient groups. The digital literacy, access to technology and socioeconomic gaps remain a concern with a potential to affect the effectiveness of the utilization of telemedicine, which may lead to the exclusion of vulnerable groups or less benefits of telemedicine use, as highlighted by Ezeamii (2024). Rather than only measuring for 12 months as suggested by Graue et al. (2023), supporting the readiness of the individual to engage in behavior change, than a set of protocol requirements to endpoints, may be necessary. With regard to studies of telephone interventions, there was a high level of heterogeneity (I2 = 87%), with significant study-to-study differences in how the effectiveness of the protocol was defined, patient characteristics, and patient evaluation methods. However, as pointed out by Sun et al. (2025), remote care models should be adapted to the context, as not all of them are equally applied to patients’ healthcare due to the difference among different populations and patients’ willingness to use digital content. Equitable and effective technology enriched diabetes care inclusive should be considered in terms of the inequity linked to digital access, common protocols and consistent and quality oversight of nursing by different populations.

• Synthesis of Findings

An overall comprehensive conclusion was drawn in that designing structured nurse-administered diabetes follow-up interventions for outpatient primary care can be based on clinically actionable evidence when assessing evidence across the different categories. Twenty studies fulfilled the inclusion criteria and all studies showed an overall positive direction (improvement) in HbA1c outcomes for people with diabetes, regardless of the type of delivery model, geographic location, and type of study. Effect sizes varied from small to moderate improvements (0.25% reduction in HbA1c) in RCTs to large (clinically significant) improvements (>1.5% reduction in effective HbA1c) in large structured longitudinal diabetes programs (Asmat et al., 2024; Koo et al., 2024). HbA1c will be better and more sustainable when the single bundle of interventions is implemented vs any of the components alone, that is, adherence to ADA guidelines, nurse-led competency development, patient-centered education and technology enhanced follow-up (ElSayed et al., 2022; Sun et al., 2025). Thus, it is essential to develop and establish an all-inclusive, multifaceted outpatient diabetes care protocol to acquire clinically relevant and persistent glycemic target in an outpatient setting.

Evidence synthesis further confirmed its relevance to the proposed quality improvement project and examination of existing research highlighted there are significant research gaps that still require quality improvement in the field. First, evidence synthesis methodology progressed from adherence to guidelines to meta-analyses; no literature is available that is more than 12 months of evidence on HbA1c outcomes, the frequency and/or acquisition of “follow-up” were not well standardized, cost-effectiveness analyses were limited, and culture-specific needs regarding access to technology-enhanced service delivery models were not well described. To further evaluate outcomes across a variety of outpatient settings, multiple implementation studies that have undergone methodological quality assessment via rigorous evaluation and have contextually relevance are needed (American Diabetes Association, 2024). Evidence gap closure will contribute to building the literature and help to achieve tangible objectives around sustainable, nurse-led chronic disease management.

Implementation Plan

For a structured quality improvement intervention, a logical, organized, step-like plan should be designed and executed to guarantee fidelity, replicability and uniformity throughout all project stages. The implementation timeline involved a process of 8 weeks, with a phased implementation process: Week 1 and Week 2 to collect baseline HbA1c data, follow-up completion rates for patients and nursing staff’s competency scores (using competency checklists) from the electronic health record (EHR) system to establish and provide measurable pre-intervention benchmarks. In quality improvement frameworks, time-series data and the collection of rigorous baseline data is often highlighted as being crucial to evaluating the impact of the intervention and identifying the important clinical difference over time (Lighterness et al., 2024). Good pre-intervention baseline data helps project teams pinpoint gaps in performance to meet project goals, provides realistic performance targets, and defines a way to check progress toward the organization’s performance goals (Willmington et al., 2022). Structured staff education was completed in Weeks 3 and 4 with simulation and case-based learning, as well as peer mentoring workshops for the nursing participants on Diabetes Pathophysiology, the ADA guidelines for diabetes management, principles of medication reconciliation, and documenting into EHRs. All nursing participants completed competency checklists and knowledge assessments both before and after the completion of the education sessions to ensure competency of each nursing staff member was at or above 80% prior to offering the patient facing portion of the intervention. By implementing the program in a phased manner, the instructional and training components of each phase would have accountability, consistency and measurable fidelity across all eight weeks of implementation.

On-going monitoring and iterative changes were suggested as a way to ensure fidelity of implementation for the remaining weeks with the PDSA methodology, structured interprofessional collaboration. Structured biweekly patient follow-up visits were completed in weeks five and six and continuous telehealth visits were provided to those who were transportation challenged along with midpoint competency evaluation of the nursing staff and adaptive modification of the educational delivery strategies in weeks five and six when protocol compliance or patient engagement was determined to be lacking. There is strong evidence that real-time performance monitoring during quality improvement efforts can help identify barriers to implementing the intervention at the early stages of the effort and can be helpful in making data-driven performance corrections (Lighterness et al., 2024). In primary care and chronic disease management, particularly with regard to diabetes, there are generally structured arrangements for interprofessionally collaboration and communication for sustaining quality improvement (Sze et al., 2025). These EHR-based tracking systems were actively managed and monitored during weeks 7 and 8 to schedule follow-up visits, identify patients’ overdue visits, centralize HbA1c data, and develop performance dashboards to track process and outcome indicators in real time at the practicum site. During week eight, fidelity of processes and completion of follow-up patient activities were verified using checklist review of structured data and a comprehensive outcome analysis process was used to review all baseline and post intervention patient related outcome data (glycemic, competency and behavioral domains). Due to the structured nature, iterative design and eight week implementation, the intervention was responsive to evidence-based practice and able to achieve clinical changes in glycemic control for the practicum site.

Conceptual Model

Quality improvement frameworks create the foundations that enable information gathering, information analysis, and changes to evidence-based interventions via iterative cycles of learning/adjustments and iterative systems. Record of prior successful implementation of the PDSA model for chronic disease management (BARR & Brannan, 2024) was considered and presented as the rationale for how the project would be guided. The PDSA is an outcome of the W.E. Deming thought of quality improvement and the strategy is to improve the process over time through iterative learning/refining in the context of complex systems. Studies on measured effectiveness of quality improvement schemes with chronic diseases frequently reveal schemes that incorporate iterative cycles of evaluation. During the ‘plan’ phase, the team identified that the main focus would be improving poor glycemic control in 42% of our adult diabetics, identified outcome measures and developed a structured protocol for ADA diabetics follow-up and a staff development programme focusing on staff competency. The ‘do’ phase involved implementation of the intervention, with simulation based staff trainings, bi-weekly patient visits (including virtual using telehealth), and activation of EHR dashboards, for each phase of the intervention. Given PDSA’s evidence-based and iterative nature, all decisions about implementation were to be based on measurable data and would directly serve the overall goal of a more sustainable level of glycemic control via the standardization of the nurse-led processes.

The evaluative and adaptive aspects of the PDSA model was used to maintain fidelity/ quality of the intervention and to further enhance learning for the eight week implementation. The ‘study’ phase involved conducting bi-weekly analyses based on formative data (Progression Toward Goal parameters: HbA1c trends, practice staff competency scores, and follow-up visits completed; and errors in EHR documentation) to determine how well individuals were progressing to target percentages and to provide adaptive strategies for gaps in progress identified. The iterative nature of PDSA allows for flexibility when implementing the model and allows healthcare workers to modify their original protocol to be guided by measured evidence during their challenges as they work through the process (Abuzied et al., 2023). It is confirmed that PDSA cycles, when applied systematically in workflows, in structured nurse-led diabetes management programmes, yield improvements in mean HbA1c level between 0.5%-1.0% (Konnyu, 2023); compared to the current project. The ‘act’ stage involved applying the insights from the formative analyses to improve the implementation of adult education content, scheduling changes to workflows, and systematic changes to outreach processes in the telehealth setting – methods that, when successful, will be incorporated into the standard work of the clinic after implementation. The flexibility, step-by-step processes, and constant feedback within the PDSA framework further validates the overwhelming appropriateness of it as the guiding quality improvement methodology for the project and its capacity to recreate, measure and sustain outpatient glycemic management improvements.

Data Collection and Analysis

An appropriate design of the project, along with careful data collection processes, are essential to interpret and validate project results based on evidence. The design of this project was a prepost evaluation that would gather both baseline and follow-up data for all 20 adults with type 2 diabetes in this facility as well as 8 nursing staff. The pre-post design is one of the most common and accepted ways to evaluate how effective a structured intervention has been in a real-world healthcare quality improvement context by providing a pragmatic and feasible way to compare the results for the same group of participants across established time frames (Klaic et al., 2022). Outpatient chronic disease management programs with quality improvement designs employing pre/post designs emerged as having a preponderance of being sufficiently sensitive to demonstrate clinically meaningful changes in patient outcomes (Lee et al., 2022). The pre intervention measures, assessment of the HbA1C level, completion rate of clinic visits and competence levels of the nursing staff were all done through the facility’s electronic health record system; this was to allow a measurable outcome to be used when comparing post intervention measures. The Institutional Review Board approved the project before starting, and all HIPAA compliance procedures relative to participant confidentiality and coding of names for use in data collection and analysis were followed. This robust pre/ post design and established systems of baseline data extraction from standardized baseline tools were the foundation for deriving credible, comparable, and clinically interpretable evidence of project outcomes based on proven quality improvement research methodologies.

 Accurate and reliable clinical and non-clinical quality improvement data relies on identifying suitable metrics, and using valid/consistent measures of record. The main outcome measure was the mean HbA1c level at baseline and at week 8 using point-of-care laboratory testing that was integrated into the clinic’s electronic record system. The structured follow up as per the American Diabetes Association (Tiwari & Aw, 2024) was used to define clinically significant improvement in a patient’s HbA1C level as a reduction of 0.5 or more percentage points from the patient’s baseline HbA1C level. Both pre and post-project quality improvement studies need to employ measurement instruments that have been determined to possess high content validity and measurement reliability for outcomes to be a valid basis for determining the effectiveness of a structured intervention. For the quality improvement entity, the tools for outcome measures that were validated and reliable were crucial in supporting the evidence-based decision-making to improve protocols, and sustainability planning (Gabriela et al., 2025). Second outcome indicators were: If pre- and post-training diabetes management competency assessment instrument was used to assess the competence test scores of the nursing staff, they were included as the second outcome indicators. Follow-up visit completion, which is recorded in scheduling audit logs in the EHR system. To capture patient-reported adherence with insulin (using structured behaviour checklist) or checking blood glucose levels. An expert panel which assessed all measurement instruments for content validity prior to use, was established to ensure that outcomes collected at the various measurement time points would be reliable and valid outcomes, using the same data collection processes throughout the 8 week project. The broad range of outcome measures in each of the three developmental domains (glycemic, competency, and behavior) will give a holistic, multi-faceted picture of the intervention.

Ethical Considerations

Ethical issues must be seriously considered when designing quality improvement projects to not only safeguard participants and confidentiality of data, but to ensure institutional compliance throughout the course of the project (planning, implementation and evaluation). Before the project was implemented the project was assessed by the Institutional Review Board (IRB) and determined not to be “Human Subjects Research. The IRB determined that the project was more about improving practice and not to measure generalizable knowledge and did not require full IRB review (APRN, personal communication, November 2025). Quality improvement (QI) projects in health care institutions that involve improving the way care is delivered (as opposed to intervening with new care options), which rely on retrospective collection of clinical data, and which involve evidence-based practices are often believed to be not human subjects research. Compliance with existing institutional review procedures and federal ethics guidelines is not alone enough to fulfill ethical duties in the process of a nurse-led quality improvement project. In addition, ethical compliance requires that all data collection methods and procedures, recruitment/consent processes, and outcome reporting processes comply with the established guidelines for IRB review; therefore, all Collaborative Institutional Training Initiative (CITI) certification requirements must be met before the project leader is allowed to conduct quality research that meets the ethical standards of practice in the clinical setting (APRN, personal communication, November 2025). The IRB determination and completion of all necessary CITI certifications established the ethical guidelines for all aspects of data collection, analysis, and reporting which occurred as the project was implemented (8 weeks). Using the accepted ethical principles of professional practice while carrying out a project enabled the development of participant trust, institutional integrity and scholarly credibility in all aspects of the implementation and outcome data evaluation of the project.

One of the main ethics considerations for a quality improvement project is protection of the confidentiality of patient data and provision of safe storage space for all project-related documentation and data. All identities associated with patient data were coded to ensure that an individual patient wasn’t identifiable from documentation, outcomes, or dissemination of materials that were derived in the course of the quality improvement project before any data extraction, analysis, or reporting took place. CDC (2024) outlines in the HIPAA requirements that any individually identifiable health information (IIHI) collected as a part of a quality improvement project completed within the context of the health care organization’s business must be de-identified, secure, and made available only to authorized persons. 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). The electronic data and competency assessment records were kept in encrypted, password-protected devices only accessible to the project lead, site preceptor and project team members, and the hard copy data were kept in locked cabinets with controlled access to the clinic during the 8-week implementation period. (APRN, personal communication; November 2025). Compliance with all de-identification procedures was audited weekly, if non-conformance to procedures was identified during the audit, adjustments were made immediately to ensure the integrity of the data and adherence to institutional procedures for compliance. The data security and de-identification procedures were strictly followed and confirmed the highest ethical standards to provide credible evidence to support sustainable quality improvement in outpatient diabetes management with the project.

Project Results

It is crucial to convey the clinical importance and organisation impact of the quality improvement intervention (QI) in a clear, organised and evidence-based manner when presenting the results of the project to all concerned. The primary outcome demonstrated that there was a clinically relevant mean reduction in hemoglobin A1C (HbA1c) achieved over the course of eight weeks, with a mean baseline HbA1c of 9.95% compared to a mean HbA1c at 8.22% post QI intervention, which exceeds that success threshold set prior to implementing the QI intervention of hemoglobin A1C less than 0.5 percentage points. Of the 89.2% of follow-up visits that were completed, all were completed in the 8 weeks of implementation of the QI intervention, suggesting that patients were actively involved in the structured diabetes follow-up protocol offered by the ADA. Further, the percentage completion of bi-weekly follow-up visits by patients and nursing suggests that the existing operations are capable to support the bi-weekly visit schedule. Although girly ‘glycemic improvement’ was seen, only 10% of the enrolled patients obtained an HbA1c less than 7% at the end of the eight week intervention period, and a number of other interventions taking place outside of the practicum may have contributed to their full achievement of the targets. In general the findings on the primary outcome show that the undertaking of a standardised, ADA compliant, nurse led follow-up protocol, achieved clinically and dimensionally important improvement in glycemic control in the adult type 2 diabetes population at the project site. Results across the secondary outcomes further support the generalizability and multi-faceted influence of the structured intervention, as reflected in competency, engagement with patient self-management and delivery fidelity domains of the nursing staff during the 8-week period of the structured intervention. However, nursing staff competency scores following a structured training program were significantly higher, with the pre-training and post training scores being 59.0% and 85.4%, respectively, and 7 out of 8 nursing staff achieved a score equal to or greater than 80%, the minimum required for ability to independently deliver the protocol (APRN, personal communication, November 2025). By week 8, self-management engagement scores ranged from 0 to 10, with a mean score of 7.4; 70% of patients had 100 % adherence to the medication regimen; and 65% of patients regularly monitored blood glucose level each day during the 8 weeks structured intervention. The unintended finding of the study was transportation barriers accounting for 67% of scheduled visits to the clinic, having a negative impact on the glycemic trajectory of some patients enrolled and making it an equitable and alternative method of delivering durable outcomes, with the clinical value being incorporated into the structured diabetes follow-up protocol. Finally, the secondary outcome results showed that generalized and consistent change occurred in each of the clinical, operations and behavioral domains, indicating that there was practice-level dimensional and meaningful change as a result of participating in the structured, ADA compliant diabetes follow-up protocol at the project site. The results of the project are contained in the Appendix.

Project Outcomes

Evaluation of the usefulness of the project based on its objectives provides information on the value of the overall program to advance practice and use of it as an evidenced based intervention. Indeed, the most important goal of the project, to reduce HbA1c, was met and the extent to which this was achieved was well beyond the predetermined successful threshold of 0.5 percentage points, as the HbA1c score reduced by 1.52 percentage points (from the baseline score). The entire implementation of the structured ADA diabetes follow-up protocol, over 8-weeks, was able to fully establish clinical significance; with consistently and clinically significant improvements in glycemic measures, as compared to baseline in the initial 8-weeks post-implementation. Previous studies in similar patient populations involving nurse-led (protocol-driven) diabetes follow up care, showed similarisms in the reduction of HbA1c with values ranging from 0.25% to 1.69% across comparable outpatient diabetes care settings (Asmat et al., 2024; Koo et al., 2024) confirming not only the similarity with results reported in the QI project, but also that the results were found to be a larger effect-size than expected in the QI literature. The results of the nurse-driven self-management education programs showed that active follow-up within structure or protocol-driven (Dailah, 2024), nurse follow-up frameworks achieved high percentage levels of improved nurse competency scores and patient self-care behavior nearly in all cases. Although the final outcome (HbA1c < 7%) was not successfully met for 70% of all patients enrolled in the pilot program within eight weeks, it is assumed that, with continued implementation over a time frame larger than the practicum course, this outcome will be met. There also were unfortunately a few surprises including the non-non matrix, or in other words, patients who had barriers to attending all the planed in-person visits due to transportation (67% completed in-person scheduled visits) and as mentioned above an urgent need was felt for the inclusion of telehealth for follow up with patients.

Assessing strengths, limitations, opportunities and barriers of a quality improvement project also offers a frame of assessment for internal validity and external applicability to similar clinical settings. Some of the main assets of this project were: good competency level of the staff, good compliance with the follow-up system (89.2%), documentation of the EHR, collaboration of the clinical staff as a team of interprofessional professionals and application of the nationally recognized ADA clinical practice guidelines. The elements as a whole contributed to the credibility of the design of the intervention. Quality improvement projects that showed high fidelity of important procedures outlined (i.e., approaches to implement intervention) were also supported with systematic competency development, EHR monitoring that resulted in a much more reliable and generalizable outcome, which validates the methodological strength of the current project (Endalamaw et al., 2024). Multi-disciplinary structured quality improvement efforts utilize validated follow-up procedures and EHR based monitoring and are successful in delivering ongoing positive outcomes (Ebbers et al., 2023). The disadvantages of this quality improvement project were a study window of just 8 weeks, making it impossible to establish long-term effects of HbA1c reduction; a sample size of only 8 nurses in the clinic, restricting the statistical analysis of the results; and a single clinic site, limiting the transferability of the results to other clinical settings. Opportunities from implementation are: extending the standardized ADA follow-up protocol to other chronic disease populations encountered in the outpatient clinic; using peer-supported digital messaging as a means to boost engagement between patients and clinic during inter-visit times; and disseminating project results via peer-reviewed publications, which will expand the evidence base.

Sustaining practice change takes place after the quality improvement project is completed and involves intentional organizational planning, creation of an organizational commitment to practice change through a written plan, and the systematic incorporation of the successful components of the intervention into standard workflows and/or professional accountability systems. To maintain a structured ADA diabetes follow-up program, the clinic will add a structured diabetes follow-up program to the Routine Nursing Workflow Procedures. Operations infrastructure such as EHR dashboards, automated appointment reminders, and fidelity checklists will be kept as permanent systems to continue to support adherence to the protocol (APRN, personal communication, November 2025). Input and quality control of the glycemic control achieved after structured interventions in the outpatient setting should be continuous and maintained for at least 1 year after intervention to ensure that the practiced interventions have firmly been established in the organization’s culture and process (Jahed et al., 2025). Therefore, the adoption of key elements of successful chronic disease management protocols in policies is likely to result in long-term sustainability for the quality improvement process. To ensure outcome sustainability, enhancements will be made to the EHR dashboard metrics with creation of new roles, such as the Diabetes Protocol Coordinator responsible for scheduling ongoing assessment quarterly competency retraining for nursing staff (APRN, personal communication, November 2025). Spreading the results of the quality improvement project in the organization’s internal reports, at conferences, and peer-reviewed literature may further increase the organization’s dedication to the standard diabetes follow‐up model and future replication in similar outpatient primary care settings with a wide array of adult patients.

Recommendations

The findings resulting from evidence-based quality improvement projects offer important lessons that will be useful not only in implementation, but also to contribute to nursing research and practice in the future. Suggestions for future practices are to have a longer time span of the practicum (12 months) to determine the sustainability of a participant’s HbA1c level following the eight weeks. Furthermore, the protocol needs to be expanded to other chronic disease groups in the same outpatient setting, to further improve the organizational impact and improved resource allocation. Future studies should include multicenter replication studies to test the effectiveness of the protocol with larger and more diverse nursing populations. Another major area for which further research is needed is cost-effectiveness analyses, which estimate the rate reduction of the reduction in hospitalisation from standardised follow-up. Incorporation of peer supported digital messaging platforms will further improve patient engagement and delivery of self-management support between healthcare encounters (Nagra et al., 2024). Equity for technology access of marginalized communities will be identified through the research on culturally-responsible curriculum development (Martinez et al., 2023). One of the greatest opportunities to improve glycemic equity and continue to improve the quality of OPP services to a diverse adult population will be through ongoing support of structured nurse-led diabetes follow-up programs.

Summary

One crucial way of reaffirming the clinical importance, relevance to the organisation and scholarly contribution of the intervention implemented in clinical practice is through a summary of the most important take away things resulting from a QI project. After eight weeks of the ADA diabetes follow-up protocol, a clinically meaningful decrease in HbA1C of 1.52 percent was achieved, as well as an increase in competencies from the nursing staff, from 59.0 percent to 85.4 percent, and a follow-up adherence rate of 89.2 percent. Thus, application of the ADA protocol to the clinical practice was accompanied by a wide-ranging and quantifiable gain in the fields of glycemic control, productivity of nursing care and follow-up adherence. Implementation has enhanced clinic’s organizational mission to ensure evidence-based patient-centered, accessible primary care through a shared workflow process for diabetes follow up, interprofessional collaboration, and automated monitoring processes integrated into the EHRs as business as usual clinical care. The project results aligned with the clinic’s strategic goals related to value-based care delivery, quality chronic disease management and health equity for patients from various communities served by the practicum clinic. Finally, the nurse led implementation of the nurse-led protocol using the ADA can, and should be spread to other similar outpatient primary care practices and will help to sustain glycemic improvement in similar clinic/ ambulatory care settings. Finally, engage in interprofessional QI work to create QI initiatives based on evidence within your organization can translate to relevant and impactful clinical outcomes that are both sustainable and support the organization’s mission and, importantly, national standards of excellence for chronic disease management.