NURS FPX 9010 Assessment 2 Project Proposal

Project Proposal

The increasing transitions to adult patients with improperly managed Type 2 diabetes in the practice setting have demonstrated that there are still significant gaps in understanding regarding the patterns of daily insulin administration that directly affect the process of glycemic control and that are likely to result in reduced adherence to insulin administration and suboptimal self-management practices. Even though the nursing staff offer standard diabetes education and medication counseling when they meet with the patients, the short and sporadic character of such encounters has failed to lead to long-term changes in the glycemic outcome. It was shown that ADA-compliant diabetes technology interventions, especially combining FDA-approved smart insulin pens with dose-logging and prompts to notify nurses about missed insulin doses to structured, nurse-managed clinical management frameworks, can result in better insulin uptake, improved medication safety, and meaningful declines in HbA1c (Galindo et al., 2021). The American Diabetes Association (ADA) Standards of Care in Diabetes underline the implementation of insulin delivery technologies in the context of defined clinical workflows and team-based models of care, optimizing glycemic regulation and patient interaction. The PICOT question the project will use is as follows: Among patients with diabetes using insulin (P), the deployment of ADA-linguistic insulin pen clinical management toolkit (I), versus the existing practice (C), how do the patient’s HbA1c values improve (O) within 12 weeks (T)? Based on the given recommendations, the proposal is a comprehensive solution to implement and test an ADA-based Smart Insulin Pen Clinical Management Toolkit at the practice site to empower nursing routines, standardize insulin management procedures, and ensure patient glycemic outcomes.

Practice Problem

Acuity of type 2 diabetes is a major problem in outpatient primary care clinics. The clinic has a culturally diverse population of approximately 5,000 adult patients each year, with an almost 40-percent population reported to be at high risk compared to Type 2 diabetes. The review of patient outcomes in the recent past showed that there have been numerous visits to the emergency department due to hyperglycemia (Nurse Manager, personal communication, October 10, 2025). Adult patients with type 2 diabetes have poor self-management of type 2 diabetes and poor follow-up at the project site, leading to high levels of fasting glucose, 145 mg/dL, indicating poor glycemic control. The American Diabetes Association (2023) recommends under 100mg/dL as a normal factor of fasting glucose levels; thus, the existing site averages of 145 mg/dL are not an ideal self-management behavior affecting the attainment of good glycemic control in comparison with recommended levels. Within the six months, the clinic treated around 450 adult patients with Type 2 diabetes, and the average fasting glucose levels have been around 145mg/dl, much higher than the desired target of less than 100mg/dl recommended by the ADA (Executive nurse, personal communication, October 10, 2025). The continuity in high-level glycemic control in a large number of patients also indicates that glycemic control and management at the site is weak, and therefore should be reinforced. The Smart Insulin Pen Clinical Management Toolkit (ADA-aligned) that was introduced by the nursing faculty will lead to a greater level of adherence to insulin injections and self-management behaviors, which are going to enhance the level of HbA1c and overall glycemic control in 12 weeks.

Impact on Individuals and Stakeholders

The impact of ineffective self-management of diabetes spreads to various spheres of patient welfare, and insufficient screening of patients at risk only makes the process of diagnosis and treatment even later. According to Lamptey et al. (2022), no direct correlation was observed between the poorer outcomes that were caused by poor self-management, but structured DSME programs literally ameliorated glycemic control. To the healthcare staff and administrators, the workflow inefficiency and poor performance on the important quality indicators are the result of the uneven application of the evidence-based model. Asmat et al. (2024) disclosed that patient-centered self-management intervention has a positive effect on glycemic control. Nevertheless, there is still a gap between what is practiced currently at the project site, which is not yet based on the evidence-based approaches that contribute to improved patient outcomes. Measures that are available now in the clinic indicate that there is a need to consistently utilize an evidence-based model in strengthening self-management behaviors that result in better glycemic control.

Recognizing Potential Areas for Improvement or Additional Knowledge

The existing measures and practices in the location need to be refined to make self-management practices more effective among individuals with Type 2 diabetes. The plans need to be incorporated into the current workflow through your training of staff and having compliance regularly reviewed. Research on the long-term feasibility of protocol-based diabetes management should be conducted in the future (Lamptey et al., 2022). The correspondence of the project with CITI standards supports the ethical management of data, patient confidentiality, and compliance with institutional quality improvement standards. The improvements made to the aspects will strengthen the implementation fidelity and improve the self-management outcomes of adult patients with Type 2 diabetes. The practice issue represents a broken system based on inconsistent technology-enabled insulin management adoption, the absence of standardized nurse-led follow-up, and inconsistency in the nursing documentation concerning insulin administration and adherence follow-up. The issue was detected in terms of EHR audits, communication with the executive nurses, and trend analysis proving the plants with the constantly high HbA1c levels despite regular clinical care. The concern identified is supported by national data. The Centers for Disease Control and Prevention (2024) indicates that over 37 million Americans have diabetes, and almost half of them do not meet recommended glycemic levels, often because they do not track insulin adherence measures and use diabetes management technologies less frequently. On the same note, the American Diabetes Association (2023) also indicated that there were substantial gaps in the adoption of FDA-approved insulin delivery technologies into routine outpatient care. The disparity indicates a significant requirement for organized, nurse-centered clinical management designs that integrate smart insulin pen technology to aid adherence checks, enhance glycemic results, and diminish diabetes-related issues and hospitalizations.

Project Site

The project location is an outpatient primary care clinic in a suburban area of New Jersey. The clinic is a part of a community-based health network and focuses on convenient, patient-centered care among adults and the elderly. Services cover routine medical checkups, health education, and lab tests. The unit upholds a team-based care model that incorporates medical, nursing, and administrative personnel into an activity of sustaining continuity of care. The average number of patients attended each week in the clinic is 15-20, though about 40 percent of patients deal with Type 2 diabetes or similar metabolic disorders (Executive nurse, personal communication, October 10, 2025). The facility comprises three well-equipped examination rooms, a small laboratory to perform point-of-care testing, and an area with patient education that will be used as a counseling area. The interprofessional team includes a physician, nurse practitioners, registered nurses, a medical assistant, as well as part-time diabetes educator. The electronic health records (EHR) implementation at the clinic helps to make decisions based on data and undertake continuous quality improvement (QI) efforts.

Potential Implications of the Project Site for the Project

The primary care setting is a perfect place where an evidence-based model can be implemented. The aim of the project (improving the level of fasting glucose in adults with Type 2 diabetes) fits well into the clinic’s focus, which is on prevention and chronic disease management. The benefit of the nurse-led practice model is that nurses are able to apply their expertise in diabetes management, which can be successful (Baek et al., 2023). Access to sophisticated diagnostic means, though, can be limited by a tight budget, which means that utilizing the available resources must be efficient. The nurse-led one is easy to implement at a low cost and improves self-management. The selected project corresponds with the mission of the organization to provide access to patient-centered chronic disease management and enhances the ongoing quality improvement programs. The prior quality improvement interventions on the site were centered around the use of medication adherence and lifestyle counseling, but a standardized, technology-enabled insulin management system with minimal sustained gains on glycemic outcomes. This project will have a direct contribution to the strategic efforts of the clinic in the area of population health, achievement of diabetes-related quality measures, and decrease in the avoidable use of the emergency department by the clinic by implementing an ADA-aligned Smart Insulin Pen Clinical Management Toolkit.

Project Population

The population targeted by the project is the adult patients who are aged 18 years and above and have been diagnosed with Type 2 diabetes who are under primary care outpatient clinic and who are being provided with insulin therapy. This group of people has several similarities in population, such as the burden of chronic diseases, cultural diversity, and insulin self-management competence. The project population inclusion criteria are as follows: (a) a diagnosed Type 2 diabetes, (b) insulin therapy is used, (c) at least one clinic visit in the past six months, and (d) the electronic health record contains HbA1c data. People who are isolated in this case are those with Type 1 diabetes, gestational diabetes, severe cognitive impairment, or who cannot use or take part in smart insulin pen-based care processes. At least 30-50 patients are needed to identify any clinically significant movement in HbA1c during the 12 weeks of intervention. Since over 450 adult patients with Type 2 diabetes have been under care in the clinic for the last six months, the corresponding population is adequate to support the necessary recruitment and to supply continuous data which could be used in quality improvement assessment.

Evidence-Based Interventions

The conceptual intervention is evidence-based to enhance adherence to insulin and glycemic control in Type 2 diabetes insulin users. The project will mainly be implemented by the application of an ADA-conformant Smart Insulin Pen Clinical Management Toolkit, which requires FDA-approved smart insulin pens along with dose-logging and final dose-miss features to be integrated into normal nursing routines. The intervention transitions a known-only intervention to a data-driven, technology-enabled insulin control to enable nurses to proactively identify missed insulin doses, review injection patterns, and intervene to provide the necessary real-time support to achieve optimal glycemic control. The effectiveness of the smart insulin pen technology in terms of enhancing adherence and glycemic outcomes was supported by evidence. Galinda et al. (2021) found that among adults with uncontrolled Type 2 diabetes who received an insulin pen cap equipped with smart features, significant improvements in HbA1c and a reduction in insulin doses missed showed a statistically significant difference between the participants receiving an insulin pen cap with smart features and those receiving a standard insulin pen. Likewise, an extensive multinational cohort study by Danne et al. (2024) reported a high correlation between missed doses of basal and bolus insulin and worse glycemic outcomes, and increased consistency of interaction with smart insulin pens and better HbA1c and time-in-range results. Dose-logging and missed dose alerts can be effective tools to enhance compliance related to insulin and glycemic regulation.

Other real-life and cohort studies support the results. Pantanetti et al. (2025) found that there were great improvements in the mean glucose levels, length of time-in-range, and decrease in hyperglycemia in adults who switched standard insulin injections with a smart pen-based insulin delivery system. Likewise, in a 2025 study, published in Diabetes Research and Clinical Practice, adult patients taking connected insulin pens had superior adherence and significant improvement in HbA1c relative to those taking standard insulin pens (Chico et al., 2025). The organised adoption of the smart insulin pen technology improves glycemic control through the minimisation of missed insulin injections and facilitating regular administration of the insulin dose.

The Smart Insulin Pen Clinical Management Toolkit is supported by the national clinical guidelines in its implementation. The ADA Standards of Care in Diabetes, Technology Section, have unambiguously supported connected insulin pens to enhance adherence to insulin therapy in people receiving insulin therapy, promote medication safety, and help reduce HbA1c with the help of the structured model of care (ElSayed et al., 2024). The ADA recommendations include a focus on technology-based insulin management as the most effective in ensuring embedding these programs in the routine workflow and team-based care, involving nurse-led monitoring and follow-up systems.

Even though there are cases of small short-term HbA1c changes, other gains enhance the value of interventions. HbA1c changes, as presented by Jackson et al. (2023), did not vary significantly in a small cross-over pilot, yet the results of smart insulin pen users showed a decrease in diabetes-related distress and enhanced levels of involvement with insulin management, which served as evidence of the psychosocial and adherence-related benefits. The advantages of engagement and adherence contribute to the long-term behavioral change and long-term glycemic control. Empirical evidence on the usefulness of an ADA-suited Smart Insulin Pen Clinical Management Toolkit to the nursing process is quite impressive, as presented in the literature. Standardization of insulin dose review, missed dose protocol, and outcome monitoring practice fills crucial gaps in practice at the project site and provides a scalable, evidence-based intervention to decrease HbA1c, increase insulin compliance, and decrease the risk of complications related to diabetes in adults with Type 2 diabetes.

Implementation plan for Interventions

Step-by-Step Process for Implementing the Intervention

The Smart Insulin Pen Clinical Management Toolkit will be a staged, chronological procedure that will create a sense of fidelity, uniformity, and reproducibility of the clinical environments. The introduction will start with the introduction of a specific staff training session where nursing employees, nurse practitioners, medical assistants, and the diabetes educator will be provided with a detailed description of the smart insulin pen system, the guidelines in the use of the ADA technology, the integration of workflow, and the standard procedure of the EHR documentation (ElSayed et al., 2024; ADA, 2025). The pre-implementation phase will provide essential knowledge of all members of staff on the nature of operational processes and the clinical protocols relating to the intervention that will be essential in sustaining fidelity to the intervention (Chico et al., 2025). The identification of eligible adults with Type 2 diabetes under insulin use will be conducted by utilizing weekly electronic health record (EHR) reports with the use of the diagnosis codes and recent measures of HbA1c or fasting glucose. Reporting will be done by medical assistants, and eligibility checked by the project head with pre-established inclusion and exclusion criteria.

Following patient enrollment, individualized onboarding including smart insulin pen setup, dose-logging education, and education on responding to missed-dose notifications will be given. Nurses will receive and discuss insulin intake data once a week and make necessary changes in terms of dosing programs or self-management. The HbA1c and glucose values will be monitored monthly to assess favorable adherence, trends and make improvements in care delivery through iterative processes. It has been shown that nurse-led smart insulin pen interventions—structured and incorporating post-discharge follow-ups—are effective in enhancing adherence and HbA1c levels and facilitate in the maintenance of glycemic control (Galindo et al., 2021; Danne et al., 2024; Pantanetti et al., 2025). The entire patient experience, insulin dose measurements, alerts of missed dosing, and compliance measurement will be recorded in a standard EHR template. Frequent review meetings and stakeholder huddles will evaluate compliance with the workflow, detect barriers in the processes and adapt the strategies depending on the formative data and ensure further optimization of clinical processes and patient outcomes.

Learner Role and Scholarly Leadership

The learner, as the academic project leader, will supervise all of the operations and clinical elements of the Smart Insulin Pen Clinical Management Toolkit intervention to keep them in compliance with evidence-based standards and in line with project objectives. The learner will also organize personnel education about the use of smart insulin pens, competency checking of using devices, and reviewing the data, ensuring that the process of patient identification is performed in the same way, and that the process of insulin dose monitoring and alert are used to work with the help of the standardized procedures. Other actions of the directive encompass ethical supervision in line with the CITI training, ensuring that documentation is accurate, upholding data integrity and performing weekly workflow compliance audits. It has been demonstrated that leadership of a project that presupposes active control, checking competency, and staying in touch, greatly enhances adherence to evidence-based intervention and makes technology-facilitated insulin management programs more effective (Ernawati et al., 2021). The learner will further assess the feedback of the staff, monitor emerging challenges and spearhead continuous quality checks to facilitate the fidelity of the procedures. In proactive leadership, good communication and well-structured oversight, the learner makes sure that every step of the project is completed in time and the data is based on actual clinical process in relation to the smart insulin pen use.

Preceptor Partnership and Oversight Support

In the evaluation plan, it will be concerned on the effectiveness of the use of ADA-paralleled Smart Insulin Pen Clinical Management Toolkit in enhancing insulin adherence and glycemic control in adults with Type 2 diabetes. HbA1c is the main outcome measure and the changes will be monitored within the 12-week period of intervention in standardized lab data, which will be recorded in EHR. Secondary outcome measures are the amount of missed insulin injections, frequency of dose-logging compliance and time-in-range measures based on smart pen data. Monitoring and following documentation by nurses will report process measures, such as staff compliance with workflow protocols, dose review accuracy, and compliance with promised alerts (missed doses). The week will be used to collect data based on insulin adherence variables and the month will be used to collect data based on HbA1c so that the trends are detected early and then modifications can be made accordingly. All the interactions with patients, smart pen data, and adherence feedback will be captured through standardized templates of EHR. Regular evaluation sessions will be used to check compliance among staff, workflow issues, and the adherence of interventions, to make sure the ADA Standards of Care regarding diabetes technology is followed (ElSayed et al., 2024). The anticipated results would be statistically as well as clinically significant reductions in HbA1c at the endpoint (after 12 weeks), reduced rate of insulin doselttipsiness/misses, increased patient compliance with insulin administration, and higher levels of nurse monitoring and follow-up compliance. It has been shown that smart insulin pens with dose-logging and missed-dose-alarm capabilities which are implemented in a structured manner can enhance adherence, decrease glycemic variability, and sustain glycemic control (Galinda et al., 2021; Danne et al., 2024; Pantanetti et al., 2025; Chico et al., 202 Process assessment will also gauge competency and workflow interaction of the staff so that nurses will adhere to the standardized protocols in the process of dose review, patient education and follow-up injections of the missed doses. It is expected that positive results in these areas will be used to further implement the concept of smart insulin pen-based management as the standard of care in the clinic which can serve as a model of duplication in the context of glycemic results improvement in adults with Type 2 diabetes.

Stakeholder Engagement and Participation

The success of the smart insulin pen clinical management toolkit intervention will largely depend on stakeholder engagement. Insiders comprise nurses, nurse practitioners, physicians, medical assistants, diabetes educator, clinic administrators and quality improvement staff. Determined people will be involved in onboarding patients to smart insulin pens, patient identification, scheduling, recording data on doses and adherence, monitoring missed-dose notices, and facilitating administration logistics. Internal stakeholders will be required to adhere to new workflow, undergo training, and standardized documentation protocols to directly be affected by changes in visit structure, a greater focus on technologies-enabled insulin management, and additional duties regarding dose review and follow-up. Structured, technology-based insulin interventions that involve active participation of internal stakeholders in the process have been proven to increase the implementation fidelity, staff commitment to standardized procedures, and patient-centered outcomes of chronic disease management (Silva et al., 2022). Examples of external stakeholders are adult patients, who have smart insulin pens, family members, who are part of insulin self-management support, and community-based partners, who help provide larger resources on diabetes. Stakeholders identified will be influenced by interventions in the communication format, education about equipment utilization, and access to systematic adherence support plans and participation and satisfaction will be crucial indicators of intervention acceptability and sustainability. Inclusion of the external stakeholders such as patients, families, and community partners into the technology-enabled insulin management programs have been linked with increased adherence, increased satisfaction, and sustainability of intervention outcomes (Ernawati et al., 2021; Asmat et al., 2024). As part of the evaluation plan, patient satisfaction and perceived usefulness of the toolkit of smart insulin pen will be monitored.

Interprofessional Team Roles and Responsibilities

The interprofessional team embracing the smart insulin pen clinical management toolkit intervention has well-established roles to make it efficient and well coordinated. Patients will be onboarded to smart insulin pens, dose-logging data will be reviewed, missed-dose alerts will be responded to, adherence coaching will be given and all encounters will be documented (utilizing standardized EHR templates). Clinical oversight will be obtained by nurse practitioners and physicians with the aim to ensure that the interpretation of smart pen data and the unique treatment plan are in accordance, as well as to respond to medical problems found due to dose monitoring. Medical assistants will oversee EHR-facilitated patient identification, set up smart pen onboarding and follow-up, patient adherence tracking, and data collection processes. The use of technology-enabled insulin management program with external stakeholders (patients, families, and community partners) has been linked to better adherence, increased satisfaction, and continued intervention effects (Ricci et al., 2023). The diabetes educator will offer specialized counseling to complicated cases and aid nursing staff to encourage patient involvement in using smart pens. The quality improvement coordinator will help manage data, ensure the reliability of outcome measures, and track compliance with improvement processes. The clinic administrator will be in charge of the availability of resources, coordinate the logistics of scheduling, facilitate the work of communication systems, and assist in adjusting the workflow. The use of interprofessional roles including diabetes educators, quality improvement coordinators and administrators has proven to boost the effectiveness of the programs, patient outcomes and maintain uniform adherence to evidence-based practices of managing diabetes through the use of technology (Ernawati et al., 2021). The project also promotes a coordinated implementation and the reduction of redundancy as well as the exploitation of collective expertise needed to produce the desired improvements in insulin adherence and in glycemic results by engaging the interprofessional team in well defined activities.

Data Collection, Analysis, and Desirable Outcomes

Desired Outcomes

The future project goals will be quantifiable changes in adherence to insulin and glycemic control amongst adult Type 2 diabetic patients. The main outcome of the project is to decrease the poor glycemic control which is shown by the reduction of mean of HbA1c and fasting glucose near to ADA target (<130 mg/dL fasting glucose) in 12 weeks of the project through the improved adherence to the prescribed insulin regimens. The secondary outcomes will be a higher guest insulin administration, a low amount of missed insulin doses and unnecessary specialist services referrals. Insulin adherence and dose documentation will be tracked weekly via the EHR, and adherence data will be analyzed to understand adherence trends and compliance to smart pen monitoring workflows by staff. Before and after intervention measurements will be able to give impartial facts of goal improvement. The effectiveness of intervention ADA-aligned smart insulin pen at the practice site will be directly measured with the help of selected toolkit measures. Mean HbA1c, fasting glucose, frequency of missed doses, and data consistency rates will be considered as quantitative indicators and compared between baseline and 12-week data point. Nursing staff feedback and patient satisfaction survey will be considered as qualitative indicators to assess the feasibility, usability, and sustainability of an intervention (Ricci et al., 2023). Together, these actions will give proof of the project success in supporting the creation of evidence-based and technology-oriented studies of insulin management and the quality of the diabetes care.

Measurement of Outcomes

Point of care fasting blood glucose measured at baseline (within 2 weeks of beginning the intervention) and monthly after that will be used as a measure of clinical outcomes, although the 12-week outcome will be noted as the main outcome of post-intervention. Where there is secondary clinical evidence (where HbA1c measures were ordered within the 3-month span around the time of the intervention), these data will be included as secondary clinical evidence, but fasting glucose will be the main operational outcome because it is regularly available at the clinic. The data of insulin dose-logging on smart insulin pens will be used to monitor insulin adherence and frequency of missed doses weekly. Validated scales will be used to assess self-management of insulin administration and self-efficacy (self-efficacy and the summary of diabetes self-care activities (SDSCA)) to measure adherence behaviors (glucose monitoring, injection regularity, medication adherence) and a scale of self-efficacy to measure perceived capacity to manage insulin therapy at baseline and after 12 weeks. To assess adherence behavior and perceived competency, validated questionnaires like the SDSCA, diabetes self-efficacy scales have been proven to be reliable in predicting the quality of glycemic control in patients with Type 2 diabetes (Ibrahim et al., 2025; Romadlon et al., 2024). Structured logs will be used to assess the achievements of process measures like completion of smart insulin pen onboarding, nurse-led dose review, and adherence follow-up, and the compliance with documentation will be assessed by weekly audits of the standardized smart pen EHR template. The use of the smart insulin pen toolkit will be assessed in terms of patient satisfaction and perceived usefulness, using a short validated survey at the end of the program, to give information on feasibility, engagement, and acceptability of the intervention.

Evaluation Criteria to Ensure the Planned Change Occurred

In measuring success, both clinical and process thresholds will be used in the project. The main clinical measure of success will be statistically and clinically significant decrease in the mean fasting glucose at baseline to 12 weeks with a target mean in the group less than 130 mg/dl; a measure of success will be calculated by the p-values alongside effects size and confidence intervals. Secondary success criteria are: a completion of smart insulin pen onboarding and monitoring protocols by at least 70% of enrolled patients, a compliance with the weekly dose review and missed-dose follow-up protocols by the nursing staff, and compliance with documentation by at least 80% based on the weekly audit in the standardized smart pen EHR template. It is also expected that there will be significant improvements in mean SDSCA scores of insulin adherence and diabetes self-efficacy measured at baseline to 12 weeks. It is expected that patient satisfaction means will register within the upper tertial on the survey scale, which points to the acceptability of the smart insulin pen toolkit. Setting clear and quantifiable clinical and process goals, including fasting glucose reductions, higher adherence rates, and higher self-management scores, are aligned with the evidence that shows that structuring, technology-mediated insulin interventions with specific targets yield quantifiable results in glycemic regulation and patient engagement (Galindo et al., 2021; Danne et al., 2024; Pantanetti et To address sustainability issues, a decrease in the number of diabetes-related ED visits or emergency referrals in comparison to the previous 12-week baseline will be documented, but such information is preliminary data during the implementation process that is short (12 weeks).

Measurement Tools and Psychometric Properties

The most significant measurement tools are: (1) point-of-care fasting blood glucose and HbA1c (clinical laboratory measurements promoted by ADA standards), (2) the summary of diabetes self-care activities (SDSCA) to measure self-management behaviors, (3) a reliable measures of diabetes self-efficacy scale, and (4) a short patient satisfaction instrument that was valid in outpatient education settings. The SDSCA has been extensively applicable in diabetes QI and studies and has shown reasonable reliability and construct validity in a variety of outpatient groups (Ibrahim et al., 2025; Ricci et al., 2023). Self-efficacy versions have shown high internal consistency (Cronbach’s alpha values were generally in the acceptable to good range), and sensitivity to change following education intervention (Chowdhury et al., 2024; Ibrahim et al., 2025). Clinical glucose measures are routine, fasting plasma glucose and HbA1c have validity and reliability as a measure of checking glycemic control (ADA, 2023). In case any of the instruments to be used in the survey is proprietary or not publicly displayed, the project lead will require instrument owners to grant permission, and will record the permission before use. The final report will mention instruments and the psychometric properties and will be included in the evidence matrix that explains why the instruments were chosen.

Data Analysis Plan

Different data cleaning and descriptive statistics will be used to start the analysis by describing the sample (means, standard deviations, medians, interquartile ranges of continuous data; counts, percentages of categorical data). The statistical tool to be used to analyze the clinical outcome (fasting glucose) will be to compare baseline and 12-week means using paired statistical tests, i.e., a paired t-test should the differences be closer to normal distribution and the Wilcoxon signed-rank test should the results not meet the normality criterion. The project will provide reports in the form of mean difference, standard deviation, 95 percent confidence bands, p-values, and an effect size (Cohen d when using parametric tests or an acceptable nonparametric effect size otherwise). Paired comparisons of pre and post insulin adherence and self-efficacy measurements will be undertaken in the same way, using dose logging data of smart insulin pens, and validated self efficacy measures. Simple proportions will be used to analyze process measures (onboarding completion, dose review completion, missed-dose follow-up completion, documentation compliance measurement and responsibility) and present as percentages with 95% confidence levels. Visual change over time as well as special-cause variation detection during implementation will be done using trend and run-chart techniques frequent in quality improvement (e.g., weekly run charts and control-chart annotations).

Applying descriptive and paired statistical tests, process monitoring instruments like run charts, is consistent with the best practice in quality improvement research and, in fact, has demonstrated the ability to represent both clinical and operational outcomes in technology-enabled insulin interventions (Knight et al., 2022). Subgroup analyses (eg. based on baseline level of glucose, frequency of missed doses, adherence to smart pen review procedures) will be performed with t-tests or MannWhitney comparisons to investigate different effects, assuming that the sample size and data quality allow it. It is proposed to pay increased attention to the estimation of the effect, confidence interval, and the practical significance instead of level exclusively on the null-hypothesis significance testing, based on the anticipated sample size (3050, in particular).

Handling Missing Data, Statistical Assumptions, and Practical Considerations

All missing data will be reduced by proactive scheduling, reminders, and various types of follow-ups (phone, in-person). In case of missing data, the project shall provide the degree and patterns of missingness, and shall carry out available-case analysis as primary analyses; the simple sensitivity analysis (e.g., last observation carried forward or multiple imputation) can be used in case of the nontrivial missing data and they are unmet. Normality tests will be evaluated both graphically and statistically; nonparametric tests will be conducted when the normality is not observed by the tests. The interpretation of statistical significance will be combined with clinical relevance and effect sizes with roles of informing practical conclusions to the clinic. Evidence-based proactive follow-up planning and proper statistical management of missing data are advocated measures of sustaining data integrity and presence of trustworthy interpretation of intervention outcomes in clinical quality improvement studies (Romadlon et al., 2024; Ibrahim et al., 2025). All data analyses will be conducted with the assistance of the usual statistical packages available in the academic/practicum environment (say SPSS, R or any other like these), and an analysis log will be kept to ensure the ability to reproduce.

Data Management, Confidentiality, and Ethical Considerations

All information retrieved both in the EHR and questionnaires will be de-identified and stored in encrypted password-protected drives in line with HIPAA and other organizational policies. Studies indicate that adherence to data encryption procedures, secure data storage, and de-id procedures will lower the chances of unauthorized access to a considerable degree and ensures compliance with the HIPAA privacy regulations (Ricci et al., 2023). Access to identifiable linkage files by approved project team members only on need basis due to scheduling or follow up purposes will be made available separately and they will be destroyed once the project closes in accordance with the institutional policy. The minimum required identifiers will be included in data collection forms as well as the EHR Intervention template and will be used to analyze data with the help of the study IDs. The learner will guarantee the adherence to CITI training and any site-specific human subjects or QI governance procedures; where applicable the project lead will aim to have the IRB status or exemption as per the institutional regulation. Reporting of results will be done on a collective basis to safeguard the confidentiality and will be provided to the stakeholders both in monthly review meetings and in a final project report.

Conceptual Model

Overview

Plan-do-study-act (PDSA) model is a fundamental quality improvement model enabling the teams to test the effect of changes in actual clinical environment by the use of quick and repetitive cycles. The model starts with the phase of plan, whereby the aim of the improvement is established, forecasts provided and plans on data collection are outlined. The implementation of the intervention is done on a small scale during the do stage. The study phase entails an analysis of the collected information and evaluation of results as compared to what is expected in the planning phase. Lastly, follows the act phase that helps to decide whether an intervention should be adopted, adapted, or abandoned according to the findings (Bechtold and Kome, 2025). The model is in cyclical form, which allows continuous refinements and enables teams to quickly respond to barriers or workflow issues or unforeseen factors. PDSA cycle is largely known to be flexible, practical and capable of supporting evidence based and incremental change in healthcare delivery.

PDSA Model Incorporated Into the Project

All the steps of implementation of the clinical management toolkit of the smart insulin pen will be organized in accordance with the PDSA framework. During the Plan stage, the project team will make final changes to the workflow, develop outcome goals (alleviating to mean fasting glucose below 130mg/dL and improving insulin adherence), create patient onboarding resources regarding the smart insulin pens, and educate the staff on how to use the device, review dose-logging capabilities, handle missed doses, and develop standardized procedures to use EHRs The Do phase will be characterized by the initiation of the toolkit whereby eligible patients will be identified by EHR reports, and the nurses will provide the standardized process of smart pen onboarding, track dose- logging and receive missed-dose notifications, and record all encounters in the structured EHR template.

During the Study phase, fasting glucose, as well as HbA1c where available, insulin adherence, the proportion of missed doses, and documentation compliance will be checked biweekly to see whether early trends represent improvement. Deviations, barriers, or workflow inefficiencies will be investigated by the project lead and preceptor and their findings compared with the baseline targets. The data demonstrates that the PDSA cycle contributes to a higher level of intervention fidelity and has been shown to hasten quality improvement by allowing teams to test the changes in small and small steps and make changes to the processes in accordance to the real-time performance information (Turner et al., 2022). Lastly during the Act, changes that are required like change in schedule, review of dose administration, support documentation or patient follow-ups procedures will be implemented prior to completion of the subsequent cycle. The iterative method will make the smart insulin pen intervention increasingly effective, patient-focused, and clinic-operating.

Connection of the PDSA Model to the Project Goals and PICOT Question

The PICOT question of the project would be whether the use of ADA aligned true clinical management toolkit of the smart insulin pen in adult patients having uncontrolled Type 2 diabetes in order to reduce the levels of fasting blood glucose and the levels of insulin adherence within 12 weeks is possible. The PDSA model directly underpins the goal as it presents a means through which to implement and improve the intervention of smart insulin pen in a systematic step-by-step fashion. Every model cycle gives the team the opportunity to test the measurement of PICOT-approach results, such as fasting glucose, HbA1c when needed, missed-dose frequency, and adherence to dose evaluation measures, gauge progress toward glycemic improvement, and change workflows to optimize clinical advantage. Since the PICOT question focuses on glycemic improvement and insulin adherence as a span of a specified time, the continuous measurement and feedback made in the PDSA approach will guarantee stability between the intervention and the expected results. The model also supports the project objective of enhancing staff commitment to standardised workflows of using smart pens by inculcating continuous monitoring, dose appraisals, and real-time analyses in the implementation plan (Bechtold and Kome, 2025). Combined, the PICOT framework along with the PDSA methodology form the closely interconnected framework which can offer credible changes in the practice and influence the quantifiable and lasting changes in insulin management, patient interaction, and glycemic outcomes.

How the Model Will Guide the Project

The PDSA model will direct the project, influencing the interpretation of decisions in the implementation process and ways of improvement of data that will be taken. The model offers a systematic approach to testing change (that is, a revision of smart insulin pen dose review processes, a change in the way missed doses are followed up or documentation processes are refined) prior to becoming widespread, minimizing risk and enhancing sustainability. The plan phase provides clarity on the roles, expected outcomes, and data measures in the team, such as fasting glucose, HbA1c, when available, insulin adherence, and the frequency of missed doses. The do phase is used to guarantee the same intervention, the smart insulin pen intervention is applied by trained nursing staff. The iterative process and clinical data reviewing at the study stage will be used to uncover gap, workflow inefficiencies or unintended consequences. The act will inform the implementation of progress and the introduction of a culture of constant learning and cooperation with uniform smart pen protocols. The formal but versatile guidance is needed in the primary care environment as workflow variation and patient complexity may affect the results of quality improvement (Danne et al., 2024). The project can be implemented within a dynamic primary care setting to enhance the nurse-led insulin management, patient engagement, and glycemic outcomes on a lasting basis by grounding the intervention in the data-driven framework of modifying the process of drug administration through the iterative approach.

Literature Supporting PDSA Use in Similar Projects

PDSA model has been extensively reported in the chronic disease management and care improvement initiatives within diabetes care. Research shows that smart insulin pen interventions with the guidance of PDSA raise the levels of glycemic control, insulin adherence, and clinical workflow performance (Jackson et al., 2023). As an illustration, Pullyblank et al. (2024) showed that PDSA distribution of iterative cycles enhanced patient self-efficiency to handle insulin and increased adherence by the staff to the smart pen monitoring methods. ERP EHR templates have been refined using the model and enhanced accuracy in documenting dose-logs, follow-up of any missed dose, and standardization of chronic disease care processes with outpatient settings (Carr et al., 2023). The results justify choosing the PDSA as the best model to implement the process of iterative testing, data alignment and ongoing assessment in the project of smart insulin pen clinical management in the same toolkit.

Methodology, Budget, and Ethical Considerations

Project Assumptions and Methodological Approach

The project designs its methodology based on a quality improvement (QI) design, which prioritizes a systematic implementation of interventions, continuous evaluation, and refinement of the smart insulin pen clinical management toolkit intervention. The major hypothesis of the project is that, under standardized nurse-led conditions, the introduction of smart insulin pens with dose-recording and missing dose notification when incorporated into integrated clinical processes will result in improved fasting glucose, increased insulin adherence, and overall, improve the glycemic control. The assumption is supported by current literature that has shown the effectiveness of technology-enabled insulin management in primary care. It has been shown that patients with well-informed self-management behaviors, dose adherence, and significant improvements in glycemic outcomes have a high likelihood of using smart insulin pumps with the help of structured nursing supervision (Galindo et al., 2021; Danne et al., 2024; Pantanetti et al., 2025). The other assumption is that the staff will attend necessary training, follow standardized dose review and documentation procedures, and be faithful to the toolkit workflows. The pre-post QI research design adopted in the project considers PDSA framework, which enables the smart insulin pen intervention to be tested, evaluated and altered over time through the structured iterative cycles.

Human Subjects Protection

Though the initiative is a QI project and not a human subjects research, ethics are important. The intervention of participation in the smart insulin pen clinical management toolkit is viewed as a part of the usual clinical care and no experimental procedures are presented. Nevertheless, patient data gathered to assess outcomes, such as fasting glucose, HbA1c, dose-logging, and missed-dose warnings will be de-identified before analysis to safeguard the privacy of patients. Only authorized nursing staff and clinicians, who will be involved in the onboarding of devices, dose review, and documentation will be authorized to access identifiable patient data. The project will otherwise comply with the requirements of the organizational IRB/QI oversight and the learner will comply with all the institutional requirements of ethical conduct in line with CITI training and HIPAA regulation.

Project Limitations and Mitigation Strategies

The project can have a number of constraints that can influence its delivery and effectiveness. The variability of staff workload can be listed as one of the restrictions that can decrease the chance of continuous smart insulin pen onboarding, dose verification, and records. The concerns will be lessened because smart pen workflow will be incorporated into the current appointment schedules, and the project lead will work with the preceptor to have staffing cover at the time of high clinic traffic. The other restriction is the possibility of uneven engagement with the patients, especially those with transportation, employment, or socioeconomic obstacles. A missed follow-up monitoring and review session will be minimized by use of reminder calls, flexible scheduling, and brief follow-up via telephone or portal to track dosages. Findings indicate the introduction of flexible scheduling, reminders, and remote follow-up tactics contribute to the enhancement of patient engagement and adhesion to insulin regimens to a significant extent, especially in populations with socioeconomic or logistic limitations (Ricci et al., 2023). The third weakness is the brief project time frame that might not enable long term measurement of glycemic control and compliance. To overcome this, fasting glucose and smart pen conformity data will be followed up on monthly, and early trend data will be prioritized to be interpreted. There is also an issue of data accuracy and variability in documentation. To address these concerns, employees will be systematically trained on smart pen workflows, the project leader will conduct weekly dose-log audits, missed-dose alerts, and EHR documentation audits to make sure that standardized fields are filled out uniformly and properly. Lastly, due to small sample sizes (characteristic of QI projects), the small sample sizes could be a constraint to generalizability. Nonetheless, descriptive statistics, measures of the process and adherence can anyway enable meaningful assessment of trends and practical influence on insulin management and glycemic results.

Project Budget and Resource Allocation

Though this plan is a low cost QI project, there are multiple costs, as well as resource factors, involved with the implementation. The primary budget items are time on training the staff on the smart insulin pen clinical management toolkit, project meetings, review of documentation, and onboarding and dose review of patients. The estimated time required to train one staff member will be about 2-3 hours, which can be provided as part of the current professional development hours. More personnel will be required to identify patients, schedule now and follow-ups regarding missed dosements, and attend monthly project meetings. Very few material materials will be needed with copies of toolkit guides, SMART goal work sheets, dose tracking log, and session attendance forms being the list of the necessary materials. The expenses are supposed to lie under the normal patients education and technology supportive budget of the clinic. EHRs might need to modify to include standardized smart pen documentation fields, which might need around 1-2 hours of IT staff assistance. Internal IT labor should be pre-budgeted, but it should be included in the project budget. The learner will also not need to spend money, but the time spent by the project head, such as staff coordination, data monitoring and analysis is a non-monetary organisational expense. The identified budget elements in the form of staff time and IT support assist in transparency and proper long-term organizational planning of smart insulin pen intervention sustainability.

HIPAA Compliance and Data Security Plan

Protections of patient confidentiality and data security are going to be observed stringently during the project. The full scope of identifiable data such as patient names, date of birth, medical record numbers will also not be exported to be analyzed as it will stay in the secure EHR. None of the data will be typed into the project data spreadsheet, except some de-identified data (i.e., fasting glucose values, attendance, self-management scores). The spreadsheet will be placed on an encrypted, password-protected, organization-issued laptop, which the learner and preceptor can access. No data will be stored on personal networks or on cloud services other than those that are within the safe network of the organization. Any tangible copies, like sign-in sheets or printed education logs, will be locked in cabinets at the clinical site and shredded when data processing is done. Role-based access control will be used to restrict electronic access to EHR, and employees will discontinue the last session to avoid unauthorized access. The compliance with the established data safety and confidentiality measures, such as de-identification, encrypted storage, and limited access, is consistent with the requirements of HIPAA and proven to decrease the risk of data breaches and safeguard patient privacy in clinical quality improvement initiatives (Ibrahim et al., 2024). The transmission of any data will be done only in secure and HIPAA compliant channels that have been approved by the organization. The measures that are identified make sure that the requirements of HIPAA are fully covered and compatible with the best practices of health information protection in the context of QI initiatives.

Project Timeline

The smart insulin pen clinical management toolkit will be implemented based on an organized 8-10 week process that is planned to make sure that the staff is trained systematically, patients are onboarded, reviewed on the use of the dose, data is gathered and the process is further evaluated. The first two weeks will be devoted to project orientation, concluding the project procedures, and involving the inner stakeholders with the introduction meeting, where the roles, duties, and expectations will be presented. The prep phase is timely to have all the resources, materials, and systems ready, such as EHR documentation fields and the equipment to use a smart pen, before active implementation starts. Week 3-4 will be spent on training the personnel in detail on working with tools kits, the functionality of smart pens approved by the FDA, dose-logging, management of missed-doses, and the introduction of new workflows into the routine care. Pre-training assessment will be carried out to determine the level of knowledge and willingness of the staff to adopt the smart pen intervention. Technology-based interventions have the potential to enhance staff skills and competence, adherence to the evidence-based protocols, and engagement of patients in insulin self-management after structured training and orienting programs (Galondo et al., 2021; ADA, 2025). In weeks 5-6, the potential patients will be selected via EHR reports and contacted to finalize the first smart pen onboarding sessions. Nursing staff will initiate provision of standardized device education such as operation, dose recording, explanation of missing dose notifications as well as SMART goal-setting to enhance compliance. The learner will manage the logistics of sessions, compliance with the toolkit procedures, and keep track of preliminary data recording. Weeks 7-8 (possibly till week 10, depending on the extension) will focus on further patient follow-up, dose logs, strengthening of adherence habits, and adjustments between the staff feedback and real-time data. Patient engagement, missed-dose patterns, and preliminary changes in fasting glucose levels will be measured weekly with the help of huddles and reviews of EHR. The learner will summarise data, and prepare progress reports to the preceptor and clinic leadership. The last week of the implementation process will be dedicated to evaluation and dissemination, which will involve post-intervention outcome analysis, administration of qualitative feedback surveys among the staff and patients and the final report. Barriers, sustainability-based lessons learned, and recommendations will be reported. This is a 8-10 week phase process to provide a steady assessment, response, and repeat modifications that assure the smart insulin pen intervention implementation is executed in a stable manner and project objectives and the PICOT question stay on track.

Practicum Hours Plan of Action

Table 1

DNP 1,000-Hour Practicum Plan of Action

Conclusion

The proposed project describes a well-organized, evidence-based intervention designed to enhance the self-management of diabetes and the level of glycemic control by introducing an ADA-oriented Smart Insulin Pen Clinical Management Toolkit. The QI plan will involve a well-articulated implementation plan, stringent program of data gathering, analysis, and application of the PDSA model to drive continuous improvements during the 810 weeks of the project. Engagement of interprofessional team members, internal/external stakeholders and effective cooperation with the preceptor guarantee organizational correspondence, staffing involvement, and patient-based care. The approach will focus on ethical concerns, data protection of patients, HIPAA laws, and a feasible budget to fund the feasibility of operations. The preparedness to be executed is shown in the work plan (weekly) and helps to prepare the nursing practice to be more structured the review of insulin doses is standardized, the use of adherence is checked, and clinical follow-up is established in the structured toolkit approach. The proposal offers a logical and practical structure towards realizing tangible changes in insulin self-management, decreases in fasting glucose, and increase in patient interaction, and strong advanced nursing leadership and quality improvement capabilities.