NURS FPX 9030 Assessment 2 Data and Data Analysis

NURS FPX 9030 Assessment 2 Data and Data Analysis

NURS FPX 9030 Assessment 2
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    Data and Data Analysis

    Student Name

    Capella University

    NURS-FPX9030

    Professor Name

    Submission Date

    Introduction

    DM continues to be among the most common chronic diseases that are dealt with in the primary care facilities, and one of the diseases that still poses a major challenge in attaining optimum glycemic control. The results on diabetes were significantly lower than recommended levels. At the project site, 42 per cent of the patients reported that their A1C was over 9 per cent, and 36 per cent stated that their A1C was only lower than 7 per cent. These results were higher than country-wide results of low glycemic control and pointed out some important performance gaps in managing diabetes (Adjei et al., 2025).

    Lack of a formalized follow-up procedure meant unequal education of the patients, lack of follow-up, and lowering of clinical outcome. To overcome the challenges, 8 weeks-long Quality Improvement (QI) program was undertaken based on an American Diabetes Association (ADA) diabetes follow-up program. The project was guided by the PICOT question in that the introduction of the ADA diabetes follow-up protocol into nursing personnel working with adult patients with diabetes would increase their level of glycemic control compared to current practices in the 8-week period. The program measured the glycemic outcomes, competence of the nursing staff, compliance with follow-up, and self-management practices of patients.

    Project Design and Data Collection

    The project used a pre-post design with the aim of assessing the success of the ADA diabetes follow-up protocol with an adult patient population of 20 and a nurse population of 8. Before the implementation, IRB approval was received, HIPAA compliance was determined, and participant confidentiality was ensured by using coded identifiers. The pre-post design was chosen due to its ability to offer a suitable model to evaluate the changes induced by the structured interventions in the real-life setting of healthcare practice and is prevalent in Quality Improvement programs (Mitchell et al., 2025).

    In the process of data collection, standards were applied to data collection across the 8-week implementation period to strive to ascertain reliability and validity as guaranteed. Various sources of information, such as EMR records, competency assessments, follow-up adherence documentation, and self-management evaluation tools of patients, were used. Content validation of all instruments was done via expert reviews, and all of the instruments were uniformly used by all of the participants to aid in valid measurements of clinical and operational outcomes. Validated measurement tools to produce a dependable source of clinical outcomes data and facilitate sound evidence-based decision-making in healthcare quality improvement initiatives are paramount (Kaplan et al., 2021).

    Data Analysis

    The effectiveness of the ADA diabetes follow-up protocol was evaluated by the conduct of both descriptive and inferential statistical tests of the quantitative measures of the outcomes of activities. The follow-up adherence rates, nursing staff scores on competency, and patient self-management outcomes were summarized by using descriptive statistics.

    To assess the glycemic control changes, t-tests were done to evaluate the differences between the baseline values and the Week 8 HbA1C of participants. In this way, this method allowed the project team to exclude the possibility of randomly observed changes and conclude that the changes could be a reflection of significant clinical improvement (Mangory et al., 2021).

    Repeated pre- and post-implementation measurements enhanced statistical sensitivity and minimized the effect of the variability of an individual; pre-post comparisons are more useful in assessing the outcomes of interventions (Chicco et al., 2025). Data to complete all analyses were obtained in de-identified extracts of the EMR and standardized assessment instruments and presented in table format as summaries to be easier to interpret and assess.

    Project Results

    The use of the ADA diabetes follow-up plan led to significant changes in all the project outcomes. Glycemic control increased greatly over the course of the intervention, with the mean HbA1c at Week 8 of intervention being 8.22, which was a significant change given the baseline was 9.95 and a mean difference of 1.52 percentage points. There was high engagement of the patients in the structured follow-up process, based on an overall state of 89.2% in the completion rate of 89.2%.

    PCA training showed significant competency improvement in diabetes management in the nursing staff after the training of the protocols. Before the implementation, the overall competency averages were 59.0 per cent, but post-training was an improvement of 85.4 per cent, and 87.5 per cent finalized the set competency standard of 80 per cent or above. These results showed that the protocol was adopted successfully and that there was an increase in the clinical readiness of the personnel involved.

    The behavioral changes of self-management of patients also increased within the project period. Overall, these results indicated positive clinical, operational performance, and treatment behavioral results.

    Project Outcomes

    The results showed that the use of the ADA diabetes follow-up protocol was an effective way to answer the project PICOT question and provided clinically significant changes in glycemic control. The change in the mean HbA1c of -1.52 percentage points was much more than the preset standard of success of -0.5 percentage points. Though the proportion of respondents who were able to reach the target HbA1c value of less than 7 percent in the 8 weeks of intervention was low (10 percent), the general effect of the intervention pointed to the possibility that even greater gains will be achieved due to the intervention when implemented over a longer period of time.

    Various lessons were learnt in the implementation of the project. There were also issues with transportation that led to missing appointments and influenced the possibility of some participants to take scheduled follow-up visits, which led to the lower provision of follow-ups among some participants. These obstacles notwithstanding, the competency of the staff, a high adherence to follow-up, and steady documentation of EHR facilitated a successful project implementation. The main weakness of the initiative was that the intervention period was relatively short, and it might not be able to extrapolate the results to other populations and long-term results of managing diabetes.

    Moreover, the monitoring and the subsequent follow-up should be continued during a specific period to determine the possibility of continually maintaining the results in the glycemic control (Jahed et al., 2025).

    Conclusion

    The 8-week program of the ADA diabetes follow-up protocol proved to have great advantages in glycemic control, nursing staff competencies, adherence to follow-ups, and self-management behaviours of the patients with Type 2 Diabetes Mellitus who were provided with care under a nurse-led primary care setting.

    Despite the inability to achieve the best glycemic values during the intervention period, the significant decrease in the values of HbA1c, as well as the positive change in the measures of operation and behavior, indicated the efficiency of evidence-based standardized practices of follow-up. The project contributes to the sporadic application of ADA-oriented follow-up procedures as a long-term approach to effective diabetes control outcomes and to improve the quality of chronic disease treatment in hospital practice.

    Next Assessment: NURS FPX 9030 Assessment 3

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      References for
      NURS FPX9030 Assessment 2

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        Below are references for NURS FPX9030 Assessment 2:

        Adjei, S. K., Adjei, P., & Nkrumah, P. A. (2025). Poor glycemic control and its predictors among type 2 diabetes patients: Insights from a single‐center retrospective study in Ghana. Health Science Reports8(3), 8–12. https://doi.org/10.1002/hsr2.70558

        A simple guide to the use of Student’s t-test, Mann-Whitney U test, Chi-squared test, and Kruskal-Wallis test in biostatistics. BioData Mining18(1), e56. https://doi.org/10.1186/s13040-025-00465-6

        A scoping review of continuous quality improvement in the healthcare system: Conceptualization, models and tools, barriers and facilitators, and impact. BioMed Central Health Services Research24(1), e487. https://doi.org/10.1186/s12913-024-10828-0

        Mangory, K. Y., Ali, L. Y., Rø, K. I., & Tyssen, R. (2021). Effect of burnout among physicians on observed adverse patient outcomes: a literature review. BMC Health Services Research, 21(1). https://doi.org/10.1186/s12913-021-06371-x

        Mitchell, S., Schmitz, F. M., Janusz Janczukowicz, Buzzi, A.-L., Haas, N., Hitzblech, T., Wagenfuehr, J., Idris Guessous, & Guttormsen, S. (2025). Does Education Design Matter? Evaluating an Evidence-Based Continuing Education Intervention on Genomic Testing for Primary Care; a Pre-Test Post-Test Study. Journal of CME, 14(1). https://doi.org/10.1080/28338073.2025.2526234

        Jahed, S. A., Nikoosokhan, A., Moravej, H., Sarkheil, P., Malek, M., Esteghamati, A., Hosseinpanah, F., & Sedaghat, S. (2025). The use of continuous glucose monitoring in outpatient diabetes care: Iranian expert consensus statement. Diabetes Research and Clinical Practice230, e112961. https://doi.org/10.1016/j.diabres.2025.112961

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