Student Name
Capella University
NURS-FPX4905 Capstone Project for Nursing
Prof. Name
Date
Intervention Proposal
The Longevity Center is a specialized clinical facility that emphasizes regenerative and preventive medicine. Its services include hormone therapy, advanced diagnostic testing, and individualized wellness plans. The clinic caters to a wide range of patients seeking proactive healthcare solutions. However, a recurring challenge within the organization involves delays in diagnostic processes, especially in cases with multiple complex symptoms where prompt intervention is vital (Sierra et al., 2021). This proposal presents an evidence-based intervention designed to minimize such delays by integrating technology-driven solutions and streamlining workflows.
Identification of the Practice Issue
Diagnostic delays are commonly seen in patients with overlapping or unclear symptoms, which prolongs treatment initiation. In regenerative medicine, timely recognition of hormonal deficiencies, nutritional imbalances, or immune dysfunctions is crucial for the success of treatments such as bioidentical hormone therapy, peptide regimens, or cellular rejuvenation strategies. Investigations at the clinic indicate that delays often stem from fragmented communication among staff members and an absence of prioritization guidelines for lab interpretation (Sierra et al., 2021).
Table 1. Practice Issue Summary
| Issue Identified | Impact on Care | Underlying Cause |
|---|---|---|
| Delayed diagnostics in complex cases | Prolonged treatment planning; reduced treatment efficacy | Poor communication, lack of prioritization protocols |
| Manual lab review | Missed or late recognition of abnormalities | No structured alert system |
| Non-standardized workflows | Variability in care quality | Absence of uniform clinical guidelines |
Current Practice
At present, The Longevity Center uses paper-based intake forms followed by manual entry into the electronic health record (EHR). This outdated method leads to data inconsistencies and information loss. Lab findings are assessed manually, with no systematic process to highlight urgent abnormalities. Furthermore, the clinic lacks a Clinical Decision Support System (CDSS), making diagnostic reasoning dependent on variable provider judgment.
Because staff do not follow standardized workflows, the time to diagnosis varies considerably, which negatively influences the effectiveness of regenerative medicine therapies like platelet-rich plasma (PRP) injections, stem cell treatments, and hormone optimization (Sierra et al., 2021).
Proposed Strategy
The proposed intervention involves the implementation of a standardized diagnostic intake system integrated with a CDSS. This initiative directly addresses current inefficiencies by reducing discrepancies in documentation, accelerating lab result interpretation, and supporting structured decision-making.
Key Features of the Strategy
- Standardized Digital Intake – All patient histories, red-flag symptoms, and initial assessments will be completed electronically and uploaded to the EHR.
- CDSS Integration – Automated alerts will flag abnormal labs, provide evidence-based recommendations for regenerative medicine, and prompt timely follow-up (Wolfien et al., 2023).
- Staff Training – Nurses and providers will be trained in standardized workflows and EHR use, ensuring accuracy and consistency in data collection.
- Interdisciplinary Huddles – Regular meetings will be held to discuss flagged CDSS alerts and lab trends, especially those relevant to regenerative therapies such as PRP or stem cell protocols.
These measures are expected to optimize diagnostic efficiency, reduce missed abnormalities, and strengthen evidence-based care delivery (Khalil et al., 2025).
Impact on Quality, Safety, and Cost
Quality of Care
The intervention promotes accurate and consistent diagnostic practices, essential for patients with complex regenerative health needs. Standardized documentation ensures no critical information is overlooked, improving the precision of personalized therapies such as peptide regimens or cellular rejuvenation (Ghasroldasht et al., 2022).
Patient Safety
Automated CDSS alerts will highlight high-risk abnormalities like cytokine elevation or hormonal imbalances, improving real-time safety monitoring. This reduces the likelihood of errors during patient handoffs and enhances interdisciplinary communication (White et al., 2023).
Cost-Effectiveness
Although initial expenses include staff training and technology procurement, long-term savings result from avoiding unnecessary testing, minimizing emergency interventions, and enhancing treatment outcomes. For instance, preventing late-diagnosed complications can reduce patient costs by thousands of dollars annually (White et al., 2023).
Role of Technology
The integration of a CDSS into the existing EHR system represents the central technological intervention. This system will:
- Flag abnormal laboratory results automatically (e.g., hormonal deficiencies, immune dysregulation).
- Provide evidence-based recommendations aligned with regenerative medicine.
- Reduce provider cognitive burden by streamlining access to patient data.
- Support team-based communication through shared dashboards and real-time alerts (Derksen et al., 2025).
By aligning with The Longevity Center’s focus on precision and innovation, CDSS-EHR integration ensures consistent delivery of high-quality regenerative treatments (Hermerén, 2021).
Implementation at Practicum Site
The intervention will follow a phased implementation strategy.
- Pilot Phase – A small group of providers will trial the standardized intake and CDSS system.
- Feedback and Adjustment – Stakeholder feedback will refine workflows.
- Full Rollout – The system will expand to the entire clinic, supported by IT staff to ensure seamless integration.
Anticipated Challenges and Solutions
| Challenge | Description | Proposed Solution |
|---|---|---|
| Staff resistance | Preference for manual documentation and old workflows | Leadership communication, peer champions, continuing education incentives |
| Financial constraints | Limited budget for advanced CDSS | Apply for grants, phased licensing agreements, academic partnerships |
| Technical limitations | Potential EHR-CDSS compatibility issues | Early IT involvement, simulation of workflow scenarios before launch |
Interprofessional Collaboration
The success of the intervention relies on team-based collaboration. Nurses and nurse practitioners will ensure accurate patient history intake and symptom assessment. Physicians will define regenerative diagnostic criteria and treatment protocols. IT specialists will maintain CDSS-EHR integration and resolve technical challenges, while administrative staff will oversee scheduling, training logistics, and compliance monitoring.
Daily interdisciplinary huddles will serve as a platform for discussing flagged labs, patient eligibility for regenerative therapies, and care coordination (Makhni & Hennekes, 2023).
Conclusion
Implementing a standardized diagnostic intake process integrated with a CDSS has the potential to streamline diagnostics, reduce delays, improve patient safety, and lower costs at The Longevity Center. By leveraging technology and interprofessional teamwork, the clinic can enhance its ability to deliver cutting-edge regenerative treatments with precision and efficiency. This initiative highlights the essential leadership role of nurses in promoting sustainable, evidence-based clinical improvement.
References
Derksen, C., Walter, F. M., Akbar, A. B., Parmar, A. V. E., Saunders, T. S., Round, T., Rubin, G., & Scott, S. E. (2025). The implementation challenge of computerised clinical decision support systems for the detection of disease in primary care: Systematic review and recommendations. Implementation Science, 20, 1–33. https://doi.org/10.1186/s13012-025-01445-4
Ghasroldasht, M. M., Seok, J., Park, H.-S., Liakath Ali, F. B., & Al-Hendy, A. (2022). Stem cell therapy: From idea to clinical practice. International Journal of Molecular Sciences, 23(5). https://doi.org/10.3390/ijms23052850
NURS FPX 4905 Assessment 4 Intervention Proposal
Hermerén, G. (2021). The ethics of regenerative medicine. Biologia Futura, 72, 113–118. https://doi.org/10.1007/s42977-021-00075-3
Khalil, C., Saab, A., Rahme, J., Bouaud, J., & Seroussi, B. (2025). Capabilities of computerized decision support systems supporting the nursing process in hospital settings: A scoping review. BMC Nursing, 24(1). https://doi.org/10.1186/s12912-025-03272-w
Klein, N. J. (2025). Patient blood management through electronic health record [EHR] optimization (pp. 147–168). Springer Nature. https://doi.org/10.1007/978-3-031-81666-6_9
Makhni, E. C., & Hennekes, M. E. (2023). The use of patient-reported outcome measures in clinical practice and clinical decision making. The Journal of the American Academy of Orthopaedic Surgeons, 31(20), 1059–1066. https://doi.org/10.5435/JAAOS-D-23-00040
Sierra, Á., Kim, K. H., Morente, G., & Santiago, S. (2021). Cellular human tissue-engineered skin substitutes investigated for deep and difficult to heal injuries. Regenerative Medicine, 6(1), 1–23. https://doi.org/10.1038/s41536-021-00144-0
White, N., Carter, H. E., Borg, D. N., Brain, D. C., Tariq, A., Abell, B., Blythe, R., & McPhail, S. M. (2023). Evaluating the costs and consequences of computerized clinical decision support systems in hospitals: A scoping review and recommendations for future practice. Journal of the American Medical Informatics Association, 30(6), 1205–1218. https://doi.org/10.1093/jamia/ocad040
Wolfien, M., Ahmadi, N., Fitzer, K., Grummt, S., Heine, K.-L., Jung, I.-C., Krefting, D., Kuhn, A. N., Peng, Y., Reinecke, I., Scheel, J., Schmidt, T., Schmücker, P., Schüttler, C., Waltemath, D., Zoch, M., & Sedlmayr, M. (2023). Ten topics to get started in medical informatics research. Journal of Medical Internet Research, 25. https://doi.org/10.2196/45948
NURS FPX 4905 Assessment 4 Intervention Proposal
Topaz, M., Ronquillo, C., Peltonen, L. M., Pruinelli, L., Sarmiento, R. F., Badger, M. K., & Nibber, R. (2021). Nurse informaticians report low satisfaction with electronic health records: Findings from an international survey. Journal of the American Medical Informatics Association, 28(9), 1970–1976. https://doi.org/10.1093/jamia/ocab084