Capella FPX 4005 Assessment 4
Student Name
Capella University
NURS-FPX4005 Nursing Leadership: Focusing on People, Processes, and Organizations
Prof. Name
Date
Organizational Issue
- The primary concern at Crouse Hospital (New York) is nursing burnout.
- Causes: Excessive patient loads, overtime, and high-pressure work environments.
- Consequences: Decline in care quality and hospital performance.
- Urgent need for resolution using a multidisciplinary approach.
- Proposed solutions: Predictive workforce models, psychological support services, AI-powered scheduling (Jun et al., 2021).
Why Stakeholders Should Act
- Addressing burnout is vital for:
- Patient safety
- Nurse well-being
- Organizational performance
- Ignoring burnout leads to:
- High turnover
- Staffing shortages
- Lower care quality
- Financial strain due to hiring/training costs
- Psychological and physical distress in nurses (Ryu & Shim, 2021)
Relevance of an Interdisciplinary Team Approach
- Enhances nurse productivity, patient safety, and care quality.
- Reduces absenteeism, turnover, and medical errors.
- Prevents burnout and strengthens system efficiency.
- Collaboration among diverse teams ensures tailored solutions that meet nurses’ needs and improve satisfaction (Jun et al., 2021).
Achieving Improved Outcomes
- Merges knowledge from multiple disciplines to manage workload challenges.
- Encourages communication and shared decision-making.
- Facilitates understanding of nurses’ emotional strain and mitigates burnout.
- Empowers staff to resolve workplace issues positively, improving outcomes (Kong et al., 2024).
Consequences of Inaction
- Continued harm to staff and patients.
- Increased medical errors and healthcare costs.
- Loss of public trust in the hospital.
- Poor patient experiences and fragmented care.
- Higher staff turnover, absenteeism, and reputational damage.
- Competitive disadvantage in hiring skilled nurses (Jun et al., 2021).
Interdisciplinary Plan Summary
- Objective: Reduce burnout and improve nurse retention and care quality.
- Strategies:
- Predictive staffing models to balance patient-nurse ratios.
- SFBT (Solution-Focused Brief Therapy) for psychological support.
- AI-driven scheduling to prevent shift imbalances.
- Reduce administrative load so nurses focus on care delivery. (Hassanein et al., 2025; Kong et al., 2024)
What Will the Team Do?
- Multidisciplinary team roles:
- Nurse managers: Oversee wellness and stress-reduction programs.
- HR/Admin: Provide resources for burnout mitigation.
- Tech staff: Implement AI-based scheduling and staffing models.
- Mental health professionals: Train nurses in stress management. (Kong et al., 2024)
Implementation Plan Using PDSA Framework
- Plan: Form a team, analyze burnout causes, and design interventions.
- Do: Launch a pilot in one department to test new strategies.
- Study: Assess data before and after implementation.
- Act: Refine plan for broader application and ongoing monitoring. (King, 2023)
Managing Human and Financial Resources
- Establish leadership with accountability, reviews, and feedback loops.
- A coordinator monitors progress, resource use, and compliance.
- Assign roles based on skill; adjust resource allocation using data.
- Estimated budget: \$5 million annually.
- Cleveland Clinic model showed AI scheduling reduced fatigue and ensured optimal nurse-patient ratios. (Cleveland Clinic, 2024; Kong et al., 2024)
Success Metrics: Evidence-Based Evaluation
- Key indicators:
- Increased retention, reduced turnover.
- Fewer treatment delays and clinical errors.
- Higher nurse satisfaction scores.
- Improved patient satisfaction linked to lower burnout. (Dall’Ora et al., 2020; Li et al., 2024; Turunç et al., 2024)
Conclusion
- A cross-disciplinary, evidence-informed strategy can effectively reduce nurse burnout.
- Mental health support and strategic use of resources enhance job satisfaction.
- Measurable success ensures the plan’s long-term viability.
- Result: A resilient, satisfied workforce and safer, more efficient patient care.
References
Cleveland Clinic. (2024). How AI assists with staffing, scheduling and once-tedious tasks. Cleveland Clinic. https://consultqd.clevelandclinic.org/how-ai-assists-with-staffing-scheduling-and-once-tedious-tasks
Dall’Ora, C., Ball, J., Reinius, M., & Griffiths, P. (2020). Burnout in nursing: A theoretical review. Human Resources for Health, 18(1). https://doi.org/10.1186/s12960-020-00469-9
Hassanein, S., El Arab, R. A., Abdrbo, A., Abu-Mahfouz, M. S., Gaballah, M. K. F., Seweid, M. M., Almari, M., & Alzghoul, H. (2025). Artificial intelligence in nursing: An integrative review of clinical and operational impacts. Frontiers in Digital Health, 7, e1552372. https://doi.org/10.3389/fdgth.2025.1552372
Jun, J., Ojemeni, M. M., Kalamani, R., Tong, J., & Crecelius, M. L. (2021). Relationship between nurse burnout, patient and organizational outcomes: Systematic review. International Journal of Nursing Studies, 119, 103933–103933. https://doi.org/10.1016/j.ijnurstu.2021.103933
Capella FPX 4005 Assessment 4
King, T. S. (2023). DNP final report: Preventing critical care nurse burnout: An evidence based approach to raising awareness. [University of Texas at Tyler]. https://scholarworks.uttyler.edu/cgi/viewcontent.cgi?article=1052&context=nursingdnp
Kong, Y., Zhang, Y., Sun, P., Zhang, J., Lu, Y., Li, J., & Zheng, Y. (2024). Interdisciplinary cooperation with solution-focused brief therapy to reduce job stress, burnout, and coping in Chinese nurses: A randomised controlled trial. Heliyon, 10(22), e40138–e40138. https://doi.org/10.1016/j.heliyon.2024.e40138
Li, L. Z., Yang, P., Singer, S. J., Pfeffer, J., Mathur, M. B., & Shanafelt, T. (2024). Nurse burnout and patient safety, satisfaction, and quality of care. Journal of American Nedical Association Network Open, 7(11), e2443059. https://doi.org/10.1001/jamanetworkopen.2024.43059
Ryu, I. S., & Shim, J. (2021). The influence of burnout on patient safety management activities of shift nurses: The mediating effect of compassion satisfaction. International Journal of Environmental Research and Public Health, 18(22), 12210–12210. https://doi.org/10.3390/ijerph182212210
Capella FPX 4005 Assessment 4
Turunç, Ö., Çalışkan, A., Akkoç, İ., Köroğlu, Ö., Gürsel, G., Demirci, A., Hazır, K., & Özcanarslan, N. (2024). The impact of intensive care unit nurses’ burnout levels on turnover intention and the mediating role of psychological resilience. Behavioral Sciences, 14(9), 782. https://doi.org/10.3390/bs14090782