NURS FPX 4905 Assessment 4

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 clinical wellness practice specializing in regenerative medicine, with services including hormone therapy, advanced diagnostics, and preventive health strategies. Its patient population is diverse, often seeking personalized, proactive, and technologically advanced care. However, a recurring challenge within the clinic is diagnostic delays, particularly in complex cases where early detection and rapid intervention are critical for patient outcomes (Sierra et al., 2021).

The purpose of this intervention proposal is to present a structured plan aimed at minimizing diagnostic delays through technological innovation, standardized workflows, and interprofessional collaboration. By implementing evidence-based solutions, the center can significantly improve patient safety, diagnostic accuracy, and cost-effectiveness of regenerative treatments.

Identification of the Practice Issue

Diagnostic delays most frequently occur in patients presenting with multiple or unclear symptoms, complicating decision-making pathways. In regenerative medicine, this can have profound effects on outcomes, as delayed identification of hormone imbalances, nutritional deficiencies, or autoimmune triggers can compromise the success of therapies such as:

• Bioidentical hormone replacement
• Platelet-rich plasma (PRP) therapy
• Peptide protocols
• Cellular rejuvenation therapies

Past assessments of The Longevity Center revealed that lab result interpretation was often delayed due to fragmented communication between staff members and an absence of prioritization protocols (Sierra et al., 2021).

Current Practice

At present, the clinic operates with paper-based intake forms that require manual transcription into the Electronic Health Record (EHR). This process increases the likelihood of data omissions and workflow delays. In addition:

• Lab results are manually reviewed with no automated system to flag critical abnormalities.
• The clinic does not utilize a Clinical Decision Support System (CDSS) to aid diagnostic reasoning or prioritize urgent cases.
• Staff members follow non-standardized workflows, leading to inconsistencies in care delivery and prolonged diagnostic timelines (Sierra et al., 2021).

These inefficiencies are particularly problematic in regenerative medicine, where time-sensitive interventions (e.g., stem cell therapy or hormonal balancing) depend on rapid diagnostic insights.

Proposed Strategy

The proposed strategy introduces a standardized diagnostic intake process supported by an integrated Clinical Decision Support System (CDSS). This dual approach directly addresses issues such as delayed lab interpretations, fragmented communication, and inconsistent decision-making.

Key Components of the Strategy

This strategy emphasizes a gradual rollout, with staff receiving thorough training to ease adoption and ensure sustainability (Wolfien et al., 2023).

Impact on Quality, Safety, and Cost

The integration of a standardized diagnostic process and CDSS will create measurable improvements across quality, safety, and cost dimensions.

Quality

• Enhances diagnostic precision through evidence-based alerts for hormone imbalances, micronutrient deficiencies, or immune dysfunction.
• Prevents omissions by ensuring consistent patient data capture and structured interpretation.
• Strengthens personalized regenerative protocols, ensuring better treatment outcomes (Ghasroldasht et al., 2022).

Safety

• CDSS alerts for critical abnormalities such as high cytokine levels or severe hormonal dysregulation enhance patient safety.
• Shared dashboards reduce handoff errors and ensure that urgent findings are not overlooked during care transitions (White et al., 2023).

Cost

• Prevents costly complications by identifying problems early (saving \$8,000–\$15,000 per avoidable emergency case).
• Reduces unnecessary diagnostic testing, saving \$100–\$500 per test.
• While upfront costs for training and technology are substantial, the long-term return on investment is achieved through efficiency gains and reduced liability (White et al., 2023).

Role of Technology

The core technological intervention is the integration of CDSS into the existing EHR system.

Functions of the CDSS in Regenerative Medicine

• Real-time data analysis of biomarkers such as hormones, cytokines, and inflammatory markers.
• Automated alerts for abnormal results with evidence-based recommendations.
• Clinical dashboards to highlight trends and urgent findings for team-based review.
• Workflow optimization, reducing provider cognitive load and minimizing errors (Derksen et al., 2025).

By standardizing decision-making, the CDSS helps reduce variability, ensuring high-quality, precision-driven regenerative care (Klein, 2025).

Implementation at Practicum Site

Implementation at The Longevity Center will follow a phased approach:

1. Pilot Testing – A small team of clinicians will trial the standardized intake and CDSS integration.
2. Feedback & Adjustment – Data from the pilot phase will inform workflow refinements.
3. Clinic-wide Rollout – Full adoption with continuous IT support and training.

Anticipated Challenges and Solutions

Interprofessional Collaboration

Collaboration across disciplines is critical for success.

• Nurses & Nurse Practitioners – Lead patient intake and ensure complete histories.
• Physicians – Oversee diagnostic accuracy and link findings to regenerative protocols.
• IT Professionals – Integrate and customize CDSS for regenerative-specific needs.
• Administrative Staff – Manage training logistics, scheduling, and compliance.

Daily interdisciplinary huddles and shared EHR dashboards will foster transparency, teamwork, and accountability (Hermerén, 2021).

Conclusion

The proposed intervention of standardized intake and CDSS integration at The Longevity Center addresses critical diagnostic delays that hinder regenerative medicine practices. By improving quality, safety, and cost-effectiveness, this initiative represents a forward-thinking, evidence-based approach to care. Its success will depend on interprofessional collaboration, staff engagement, and careful phased implementation. Ultimately, this project underscores the leadership role of BSN-prepared nurses in driving innovation and advancing patient-centered, technology-enabled care.

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), 1–21. https://doi.org/10.3390/ijms23052850

NURS FPX 4905 Assessment 4 Intervention Proposal

Hermerén, G. (2021). The ethics of regenerative medicine. Biologia Futura, 72(2), 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 Digital health interventions in clinical practice (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. npj Regenerative Medicine, 6(1), 1–23. https://doi.org/10.1038/s41536-021-00144-0

NURS FPX 4905 Assessment 4 Intervention Proposal

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