NURS FPX 9901 Assessment 2 Quality Performance Improvement (QI/PI)
NURS FPX 9901 Assessment 2 Quality Performance Improvement (QI/PI)
Name
Capella university
NURS-FPX 9901 Nursing Doctoral Project 1
Prof. Name
Date
Quality/Performance Improvement
Quality/Performance Improvement (QI/PI) represents a structured, methodical approach used in diverse sectors to refine the quality, effectiveness, and efficiency of services, processes, or outcomes. The core principle involves identifying opportunities for enhancement and systematically implementing changes. For this project, quality performance will focus on assessing staff education concerning nutritional modifications and telehealth interventions aimed at enhancing the diagnosis and management of Chronic Obstructive Pulmonary Disease (COPD). QI/PI frameworks are designed to foster ongoing improvements and attain higher standards of care (Agency for Healthcare Research and Quality [AHRQ], 2020).
Describing the Current Practice Needing Improvement
The primary issue addressed relates to the inpatient care provided to individuals diagnosed with COPD, a persistent respiratory disorder that adversely affects pulmonary function and overall quality of life (Konstantinidis et al., 2022). Effective symptom control, lung function optimization, and reducing hospital readmissions are essential components of care for these patients. A root cause analysis reveals significant shortcomings in current practices, such as inadequate knowledge of nutrition management, insufficient follow-up protocols, and ineffective identification of necessary care interventions for COPD patients. Additionally, limitations in emergency response services contribute to extended wait times and delayed interventions (Konstantinidis et al., 2022). This analysis underscores the need to enhance existing clinical practices to achieve improved patient outcomes.
A gap analysis further highlights critical deficiencies in current inpatient management strategies for COPD. To bridge this gap, the project proposes examining and implementing nutritional and telehealth interventions to enhance lung function outcomes and lower hospital readmission rates for COPD patients (Press et al., 2019; Wong et al., 2022).
A QI/PI Framework Supporting and Guiding the Project
To effectively structure and guide this quality improvement initiative, the Plan-Do-Study-Act (PDSA) model is recommended. This cyclical model offers a systematic framework for identifying problems, testing potential solutions, and measuring intervention effectiveness. Key components of the project—such as conducting literature reviews, developing protocols, and executing interventions—will align with the PDSA cycle. Continuous feedback from stakeholders and formative assessments will offer critical insights for refining the project and ensuring alignment with desired outcomes (Burkes et al., 2018; Ko et al., 2019).
How QI/PI Data Will Be Collected and Analyzed
The collection and analysis of QI/PI data are pivotal for determining the impact of implemented interventions. Data sources will include electronic medical records, patient satisfaction surveys, standardized clinical assessment tools, and telehealth usage reports. A comparative analysis will evaluate the effects of nutritional and telehealth interventions on patient lung function, hospitalization rates, and care quality. In addition, feedback from healthcare staff and patients will support ongoing formative assessments and identify areas requiring further improvement (Konstantinidis et al., 2022; Sculley et al., 2021).
Evaluation of Changes in Quality or Performance
The evaluation process will employ objective tools, such as the COPD Knowledge Questionnaire (CKQ) and spirometry assessments, to measure outcomes including patient knowledge, lung function values, and clinical care improvements. Quantitative measures, such as readmission rates and patient satisfaction scores, will be statistically analyzed to assess intervention effectiveness. Evaluation criteria will include indicators of efficiency, effectiveness, stakeholder involvement, and patient outcomes, ensuring alignment with project objectives and enabling comparison with baseline data (Robertson et al., 2021).
Conclusion
This quality improvement project highlights the value of implementing QI/PI initiatives in optimizing care for COPD patients. The findings demonstrate that targeted changes in staff education, nutritional management, and telehealth interventions can contribute to improved patient outcomes and reduced hospital readmissions. Ongoing monitoring and quality assessment will be essential to sustain these improvements and ensure continuous delivery of high-quality, evidence-based care to individuals affected by COPD.
References
Agency for Healthcare Research and Quality. (2020). Plan-Do-Study-Act (PDSA) directions and examples. www.ahrq.gov. https://www.ahrq.gov/health-literacy/improve/precautions/tool2b.html
Agency for Healthcare Research and Quality. (2020, January). Section 4: Ways to approach the quality improvement process (page 1 of 2) | Agency for Healthcare Research & Quality. ahrq.gov. https://www.ahrq.gov/cahps/quality-improvement/improvement-guide/4-approach-qi-process/index.html
NURS FPX 9901 Assessment 2 Quality Performance Improvement (QI/PI)
Backhouse, A., & Ogunlayi, F. (2020). Quality improvement into practice. BMJ, 368(1). https://doi.org/10.1136/bmj.m865
Berry, G., Shabana, K. M., & New England Journal of Entrepreneurship. (2020). Adding a strategic lens to feasibility analysis. New England Journal of Entrepreneurship, 23(2), 67–78. https://doi.org/10.1108/NEJE-08-2019-0036
Burkes, R. M., Mkorombindo, T., Chaddha, U., Bhatt, A., El-Kersh, K., Cavallazzi, R., & Kubiak, N. (2018). Impact of quality improvement on care of Chronic Obstructive Pulmonary Disease Patients in an Internal Medicine Resident Clinic. Healthcare, 6(3), 88. https://doi.org/10.3390/healthcare6030088
Calvillo-Arbizu, J., Román-Martínez, I., & Reina-Tosina, J. (2021). Internet of Things in Health: Requirements, issues, and Gaps. Computer Methods and Programs in Biomedicine, 208. https://doi.org/10.1016/j.cmpb.2021.106231
Furulund, E., Bemanian, M., Berggren, N., Madebo, T., Rivedal, S. H., Lid, T. G., & Fadnes, L. T. (2021). Effects of nutritional interventions in individuals with Chronic Obstructive Lung Disease: A Systematic review of randomized controlled trials. International Journal of Chronic Obstructive Pulmonary Disease, 16, 3145–3156. https://doi.org/10.2147/COPD.S323736
Haynes, J. (2018). Basic spirometry testing and interpretation for the primary care provider. Canadian Journal of Respiratory Therapy, 54(4), 92–98. https://doi.org/10.29390/cjrt-2018-017
NURS FPX 9901 Assessment 2 Quality Performance Improvement (QI/PI)
Ko, F. W. S., Chan, K. P., & Hui, D. S. C. (2019). Comprehensive care for Chronic Obstructive Pulmonary Disease. Journal of Thoracic Disease, 11(S17), S2181–S2191. https://doi.org/10.21037/jtd.2019.09.81
Konstantinidis, A., Kyriakopoulos, C., Ntritsos, G., Giannakeas, N., Gourgoulianis, K. I., Kostikas, K., & Gogali, A. (2022). The role of digital tools in the timely diagnosis and prevention of acute exacerbations of COPD: A comprehensive review of the literature. Diagnostics, 12(2). https://doi.org/10.3390/diagnostics12020269
Li, S.-A., Jeffs, L., Barwick, M., & Stevens, B. (2018). Organizational contextual features that influence the implementation of evidence-based practices across healthcare settings: A systematic integrative review. Systematic Reviews, 7(1), 1–19. https://doi.org/10.1186/s13643-018-0734-5
Press, V. G., Au, D. H., Bourbeau, J., Dransfield, M. T., Gershon, A. S., Krishnan, J. A., Mularski, R. A., Sciurba, F. C., Sullivan, J., & Feemster, L. C. (2019). Reducing Chronic Obstructive Pulmonary Disease hospital readmissions. An official American Thoracic Society workshop report. Annals of the American Thoracic Society, 16(2), 161–170. https://doi.org/10.1513/annalsats.201811-755ws
Robertson, N. M., Siddharthan, T., Pollard, S. L., Alupo, P., Flores-Flores, O., Rykiel, N. A., Romani, E. D., Ascencio-Días, I., Kirenga, B., Checkley, W., Hurst, J. R., Quaderi, S., & GECo Investigators. (2021). Development and validity assessment of a Chronic Obstructive Pulmonary Disease Knowledge Questionnaire in low- and middle-income countries. Annals of the American Thoracic Society, 18(8), 1298–1305. https://doi.org/10.1513/AnnalsATS.202007-884OC
Sculley, J. A., Musick, H., & Krishnan, J. A. (2021). Telehealth in Chronic Obstructive Pulmonary Disease: before, during, and after the Coronavirus Disease 2019 Pandemic. Current Opinion in Pulmonary Medicine, 28(2), 93–98. https://doi.org/10.1097/mcp.0000000000000851
Wang, C., Siff, J., Greco, P. J., Warren, E., Thornton, J. D., & Tarabichi, Y. (2022). The impact of an Electronic Health Record Intervention on spirometry completion in patients with Chronic Obstructive Pulmonary Disease. COPD: Journal of Chronic Obstructive Pulmonary Disease, 19(1), 142–148. https://doi.org/10.1080/15412555.2022.2049736
White, R. (2020). Implementation of a fall risk assessment tool in primary practice may decrease fall frequency in the ageing population. Doctoral Dissertations and Projects. https://digitalcommons.liberty.edu/doctoral/2768/
Wong, A. K. C., Bayuo, J., Wong, F. K. Y., Yuen, W. S., Lee, A. Y. L., Chang, P. K., & Lai, J. T. C. (2022). Effects of a nurse-led telehealth self-care promotion program on the quality of life of community-dwelling older adults: Systematic review and meta-analysis. Journal of Medical Internet Research, 24(3). https://doi.org/10.2196/31912