Risk-adjusted policies to minimise perioperative staffing shortages during a pandemic: An agent-based simulation study
| Autor: | Vishnunarayan G. Prabhu, William R. Hand, Tugce Isik, Yongjia Song, Kevin M. Taaffe |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Epidemiology and Infection. 151 |
| ISSN: | 1469-4409 0950-2688 |
| DOI: | 10.1017/s0950268823000511 |
| Popis: | Healthcare workers’ (HCWs) safety and availability to care for patients are critical during a pandemic such as the one caused by severe acute respiratory syndrome coronavirus 2. Among providers of different specialities, it is critical to protect those working in hospital settings with a high risk of infection. Using an agent-based simulation model, various staffing policies were developed and simulated for 90 days using data from the largest health systems in South Carolina. The model considers staffing policies that include geographic segregation, interpersonal contact limits, and a combination of factors, including the patient census, transmission rates, vaccination status of providers, hospital capacity, incubation time, quarantine period, and interactions between patients and providers. Comparing the existing practices to various risk-adjusted staffing policies, model predictions show that restricted teaming and rotating schedules significantly (p-value p-value = 0.09) benefits. Although these simulated outcomes are specific to one health system, our findings can be generalised to other health systems with multiple locations. |
| Databáze: | OpenAIRE |
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