Generative Artificial Intelligence Nurse Staffing Study
- Conditions
- Burnout, Healthcare Workers
- Registration Number
- NCT06978790
- Lead Sponsor
- University of Hawaii
- Brief Summary
This study is guided by Maslach's Burnout Theory and with Normalization Process Theory supporting the implementation of the GAINS intervention by facilitating its integration into routine system-level practice. In Year 1, the investigative team will collaborate with hospital-based nursing leadership and key stakeholders to identify staffing-specific factors essential for operationalizing the GAINS AI model/intervention. In Year 1, the investigators will also conduct a survey amongst nursing staff to measure baseline burnout. In Year 2, the AI-staffing intervention will be implemented with the medical-surgical nursing float pool team. In Year 3, the investigators will first repeat the nurse burnout survey and second, expand the intervention to include the nursing assistant float pool team. In Year 4, the investigators will conduct the final burnout survey with nurses, assess feasibility of GAINS (target vs. actual staffing- nurses and nursing assistants), and assess preliminary efficacy of GAINS to reduce costs related to staffing. the investigators will compare outcomes at three time points (pre, mid, and post-intervention). Interviews with nurses, nursing assistants, unit nurse managers, and leadership will further explicate the intervention's acceptability, feasibility, and impact on burnout.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- NOT_YET_RECRUITING
- Sex
- All
- Target Recruitment
- 660
- Registered nurses, nursing assistants, or key stakeholders
- Employed by The Queen's Medical Center
- Working at least 24 hours per week
- Position associated with medical-surgical units where float pool nurses work
- Employees working less than 24 hours per week at The Queen's Medical Center
- Employees whose roles are not related to medical-surgical units
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SEQUENTIAL
- Primary Outcome Measures
Name Time Method Qualitative Interviews to Evaluate Feasibility, Normalization, and Acceptability of the GAINS Intervention Up to 3 years We will interview 10-20 key stakeholders to collect and analyze qualitative data to evaluate the feasibility, normalization, and acceptability of the GAINS intervention.
T3here are two phases of the GAINS intervention.
1. Phase I: GAINS study applied to nurses in Year 2
2. Phase 2: GAINS study applied to nurses and nursing assistants in Year
These qualitative interviews will be held in Year 3 after Phase 1 over a 1-month time frame and Year 4 after Phase 2 completion of the study over a 1-month time frame. Interviews will be conducted to gather in-depth feedback on the intervention's feasibility, acceptability, and normalized into nursing practice.Maslach's Burnout Inventory Up to 2.5 years Using Maslach's Burnout Inventory, burnout is the primary outcome measure and will assess burnout (1) at baseline over a time frame of 2 weeks, (2) 12-months after the GAINS intervention is applied to the float pool nurses over a time frame of 2 weeks, and 12-months after the GAINS intervention is applied to the float pool nurses and nursing assistants over a time frame of 2 weeks.
- Secondary Outcome Measures
Name Time Method Total Cost: Travel Nurse and Nurse Overtime Up to 2 years There are two phases of the GAINS intervention.
1. Phase I: GAINS study applied to nurses in Year 2.
2. Phase 2: GAINS study applied to nurses and nursing assistants in Year 3.
The total cost of travel nurses and nurse overtime will be tracked at baseline over 2-weeks, after Phase 1 is complete over a 2-week time frame, and at the end of Phase 2 over a time frame of 2-weeks.Optimization Staffing Rates [Target staffing rate - Actual staffing rate] Up to 2 years Optimization staffing rates (target staffing rate - actual staffing rate) will be tracked at baseline over a 2-weeks, after Phase 1 over 2-weeks, and at the end of the study over 2-weeks.