This arm represents the control or standard of staffing practice to assign float pool nurse and nursing assistants.

Generative Artificial Intelligence Nurse Staffing (GAINS) intervention applied to float pool nurses.

Generative Artificial Intelligence Nurse Staffing (GAINS) intervention applied to float pool nurses and nursing assistants.

The Generative Artificial Intelligence intervention is an industrial engineering and nursing-informed innovation developed to optimize team-based staffing of registered nurses and nursing assistants. We anticipate that the GAINS intervention will enhance staffing efficiency, reduces reliance on travel nurses, minimizes overtime costs, and supports nurse well-being by proactively managing workload distribution and reducing burnout. At the core of GAINS is a generative AI model that predicts future unit-level staffing needs using historical staffing patterns, patient turnover (admissions and discharges), and patient acuity scores (based on ICU versus medical/surgical status, physician orders, charge nurse input, and other clinical factors) reflective of workload. Based on the prediction, the intervention dynamically recommends float pool assignments by evaluating staffing gaps across units and optimally deploying available nurses and nursing assistants to where they are most needed.

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.

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.

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.