Risk-adjusted policies to minimise perioperative staffing shortages during a pandemic: An agent-based simulation...

Area of Science:

• Epidemiology
• Health Systems Management
• Computational Modeling

Background:

• Healthcare worker (HCW) safety and availability are paramount during pandemics like COVID-19.
• Hospital settings pose high infection risks for HCWs across various specialties.
• Protecting the healthcare workforce is critical for maintaining patient care continuity.

Purpose of the Study:

• To develop and simulate staffing policies to mitigate HCW infection and unavailability during a pandemic.
• To evaluate the effectiveness of risk-adjusted staffing strategies compared to existing practices.
• To assess the impact of vaccination rates on the efficacy of these staffing policies.

Main Methods:

• An agent-based simulation model was utilized, running for 90 days with data from a large South Carolina health system.
• Simulated staffing policies included geographic segregation, interpersonal contact limits, and rotating schedules.
• Model parameters encompassed patient census, transmission rates, HCW vaccination status, hospital capacity, and disease-specific factors (incubation, quarantine).

Main Results:

• Restricted teaming and rotating schedules significantly reduced HCW unavailability (22%) and infections (38%) when HCW vaccination rates were below 75%.
• The benefits of these risk-adjusted policies diminished as vaccination rates increased.
• No significant benefits were observed when HCW vaccination rates reached 90% (p=0.09).

Conclusions:

• Risk-adjusted staffing policies, such as restricted teaming and rotating schedules, can effectively enhance HCW protection during pandemics, particularly in lower vaccination scenarios.
• The impact of these policies is contingent on the vaccination status of the healthcare workforce.
• Findings are generalizable to other multi-site health systems, offering valuable insights for pandemic preparedness planning.