NURS FPX 4905 Assessment 4 Intervention Proposal
NURS FPX 4905 Assessment 4 Intervention Proposal
Name
Capella university
NURS-FPX4905 Capstone Project for Nursing
Prof. Name
Date
Intervention Proposal
The Longevity Center is a wellness-oriented clinical practice that emphasizes regenerative medicine by offering therapies such as hormone replacement, advanced diagnostics, cellular rejuvenation, and preventive interventions. Its patients represent a diverse population seeking individualized and proactive health solutions. However, a major concern within the practice involves diagnostic delays, particularly in complex cases where timely recognition and treatment are critical. This proposal outlines a comprehensive intervention that utilizes technological integration and workflow restructuring to minimize diagnostic delays and optimize patient outcomes (Sierra et al., 2021).
Identification of the Practice Issue
Delays in diagnosis often occur when patients present with multiple or ambiguous symptoms. In regenerative medicine, this lag can reduce treatment efficacy in procedures like peptide therapy, bioidentical hormone replacement, and stem cell-based interventions. Timely identification of hormonal imbalances, nutrient deficiencies, and autoimmune triggers is vital for successful treatment. Assessments at the site revealed fragmented communication and lack of prioritization protocols, which resulted in delayed interpretation of lab results and prolonged treatment planning (Sierra et al., 2021).
Current Practice
At present, The Longevity Center depends heavily on manual and paper-based processes. Patient intake relies on handwritten forms, which are later entered into the electronic health record (EHR), raising the risk of incomplete or lost information. Lab results are reviewed manually without an automated alert system, which means urgent abnormalities may be overlooked. Moreover, the absence of a Clinical Decision Support System (CDSS) forces staff to rely on non-standardized workflows, creating inconsistencies in diagnostic accuracy and timeliness.
Table 1
Current Practice vs. Gaps
| Area of Practice | Current Method | Identified Gaps |
|---|---|---|
| Patient Intake | Paper-based, manually entered into EHR | Risk of data loss, delays |
| Lab Result Review | Manual review, no alerts | Critical values missed |
| Clinical Decision-Making | Based on clinician judgment alone | No CDSS to support decisions |
| Workflow Standardization | Non-standardized, varies by provider | Care variability, inefficiency |
Proposed Strategy
The primary solution involves implementing a standardized diagnostic intake system integrated with a CDSS. This approach directly addresses issues of delayed lab interpretation, inconsistent documentation, and unstructured decision-making. Standardized intake will ensure uniform, complete data collection, while CDSS integration will provide automated alerts, evidence-based recommendations, and prioritized case management (Wolfien et al., 2023).
Key elements of the strategy include:
- Digitalized intake process integrated into the EHR.
- Staff training to recognize red flags and document patient history systematically.
- CDSS integration to flag abnormal labs, suggest evidence-based pathways, and prompt timely interventions.
- Regular interprofessional huddles to review flagged alerts and coordinate treatment plans.
- IT support to maintain seamless integration with minimal disruption (Khalil et al., 2025).
Impact on Quality, Safety, and Cost
The implementation of this strategy will enhance quality, safety, and financial sustainability of care delivery.
Table 2
Impact of Intervention
| Dimension | Expected Improvement |
|---|---|
| Quality | Accurate, timely diagnosis; reduced omissions; alignment with evidence-based regenerative medicine |
| Safety | Automated alerts for abnormal results (e.g., cytokine spikes, hormonal deficiencies); improved interdisciplinary communication |
| Cost | Reduced unnecessary tests (\$100–500 per test avoided); prevention of costly acute episodes (\$8,000–\$15,000 per case); long-term savings outweigh initial investment |
This system ensures patient outcomes are improved while reducing unnecessary procedures and increasing patient satisfaction (White et al., 2023).
Role of Technology
The CDSS-EHR integration is the cornerstone of this intervention. This technology allows for:
- Real-time guidance by flagging abnormal lab results and offering tailored recommendations.
- Seamless access to patient records to prevent duplication and improve diagnostic precision.
- Shared dashboards that enhance communication during interdisciplinary rounds.
- Analytics tools for identifying workflow bottlenecks and continuously improving processes (Derksen et al., 2025).
By minimizing human error and reducing cognitive burden, the CDSS ensures that regenerative protocols—such as PRP injections, cellular therapies, or hormonal optimization—are guided by timely, accurate data (Klein, 2025).
Implementation at Practicum Site
A phased implementation plan is recommended. Initially, a pilot phase will introduce standardized intake and CDSS for a small group of providers. Feedback will be collected, and workflows will be refined before full deployment (Klein, 2025).
Anticipated Challenges and Solutions
| Challenge | Description | Solution |
|---|---|---|
| Staff Resistance | Staff may prefer current manual methods | Leadership buy-in, interactive training, peer champions |
| Financial Limitations | High upfront cost for CDSS integration | Grants, phased licensing, partnerships with academic institutions |
| Technical Integration | EHR-CDSS compatibility issues | Early IT involvement, test environments before full rollout |
Interprofessional Collaboration
The proposed intervention requires robust interprofessional cooperation.
- Nurse practitioners and nurses: Manage intake, document history, identify red flags.
- Physicians: Define regenerative diagnostic pathways and oversee clinical integration.
- IT staff: Ensure smooth CDSS-EHR integration and customize features.
- Administrative personnel: Organize training sessions and monitor compliance.
Daily interdisciplinary huddles using shared dashboards will promote real-time discussions on flagged results, ensuring patient safety and precision in regenerative care (Makhni & Hennekes, 2023).
Table 3
Team Roles in Implementation
| Professional Group | Primary Role in Intervention |
|---|---|
| Nurses/NPs | Standardized intake, patient history documentation |
| Physicians | Clinical oversight, diagnostic criteria definition |
| IT Staff | CDSS-EHR integration, system maintenance |
| Administrators | Scheduling, training, compliance monitoring |
Conclusion
The intervention—centered on standardized intake procedures and CDSS integration—addresses diagnostic delays by improving accuracy, timeliness, and communication at The Longevity Center. It enhances patient safety, lowers costs, and supports individualized regenerative medicine. Success depends on strategic planning, staff engagement, and interdisciplinary collaboration. This project highlights the leadership role of BSN nurses in promoting evidence-based clinical change.
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), 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), 2850. https://doi.org/10.3390/ijms23052850
Hermerén, G. (2021). The ethics of regenerative medicine. Biologia Futura, 72(1), 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), 1–15. https://doi.org/10.1186/s12912-025-03272-w
Klein, N. J. (2025). Patient blood management through electronic health record [EHR] optimization. In EHR Optimization for Patient Care (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. 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, e45948. https://doi.org/10.2196/45948
Additional References
Kruse, C. S., Mileski, M., Vijaykumar, A. G., Viswanathan, S. V., Suskandla, U., & Chidambaram, Y. (2022). Impact of electronic health records on the quality of patient care: A systematic review. Healthcare, 10(3), 486. https://doi.org/10.3390/healthcare10030486
Shahmoradi, L., Safdari, R., & Ghazisaeidi, M. (2022). Clinical decision support systems: A review on knowledge representation and management. Journal of Biomedical Informatics, 127, 104020. https://doi.org/10.1016/j.jbi.2022.104020
