Skip to main navigation Skip to search Skip to main content

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

  • Edward J. Mascha
  • , Patrick Schober
  • , Joerg C. Schefold
  • , Frank Stueber
  • , Markus M. Luedi*
  • *Corresponding author for this work
  • Cleveland Clinic Foundation
  • University of Amsterdam
  • University of Bern
  • From the Departments of Quantitative Health Sciences and Outcomes Research, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio.
  • Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Department of Anaesthesiology and Pain Medicine, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.

Research output: Contribution to journalArticleAcademicpeer-review

20 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)24-30
Number of pages7
JournalAnesthesia and analgesia
Volume131
Issue number1
DOIs
Publication statusPublished - 1 Jul 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Anesthesiology/organization & administration
  • Computer Simulation
  • Coronavirus Infections
  • Critical Care/organization & administration
  • Epidemiologic Methods
  • Health Workforce
  • Humans
  • Infectious Disease Transmission, Patient-to-Professional
  • Models, Organizational
  • Pandemics
  • Personnel Staffing and Scheduling/organization & administration
  • Pneumonia, Viral
  • Quarantine

Fingerprint

Dive into the research topics of 'Staffing With Disease-Based Epidemiologic Indices May Reduce Shortage of Intensive Care Unit Staff During the COVID-19 Pandemic'. Together they form a unique fingerprint.

Cite this