Staffing With Disease-Based Epidemiologic Indices May Reduce Shortage of Intensive Care Unit Staff During the COVID-19 Pandemic.

Anesth Analg

Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.

Published: July 2020

AI Article Synopsis

  • Health care worker safety is crucial during pandemics like COVID-19, especially in ICUs where specialized staff is hard to replace.
  • Various staffing models were tested to see how scheduling could minimize staff shortages by considering disease epidemiology, leading to the creation of a pandemic model.
  • The results showed adjusted staffing could significantly reduce workforce shortages, with reductions of up to 38% depending on the infection likelihood, highlighting the importance of strategic staffing in maintaining health care operations.

Article Abstract

Background: Health care worker (HCW) safety is of pivotal importance during a pandemic such as coronavirus disease 2019 (COVID-19), and employee health and well-being ensure functionality of health care institutions. This is particularly true for an intensive care unit (ICU), where highly specialized staff cannot be readily replaced. In the light of lacking evidence for optimal staffing models in a pandemic, we hypothesized that staff shortage can be reduced when staff scheduling takes the epidemiology of a disease into account.

Methods: Various staffing models were constructed, and comprehensive statistical modeling was performed. A typical routine staffing model was defined that assumed full-time employment (40 h/wk) in a 40-bed ICU with a 2:1 patient-to-staff ratio. A pandemic model assumed that staff worked 12-hour shifts for 7 days every other week. Potential in-hospital staff infections were simulated for a total period of 120 days, with a probability of 10%, 25%, and 40% being infected per week when at work. Simulations included the probability of infection at work for a given week, of fatality after infection, and the quarantine time, if infected.

Results: Pandemic-adjusted staffing significantly reduced workforce shortage, and the effect progressively increased as the probability of infection increased. Maximum effects were observed at week 4 for each infection probability with a 17%, 32%, and 38% staffing reduction for an infection probability of 0.10, 0.25, and 0.40, respectively.

Conclusions: Staffing along epidemiologic considerations may reduce HCW shortage by leveling the nadir of affected workforce. Although this requires considerable efforts and commitment of staff, it may be essential in an effort to best maintain staff health and operational functionality of health care facilities and systems.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7173088PMC
http://dx.doi.org/10.1213/ANE.0000000000004849DOI Listing

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