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Staffing With Disease-Based Epidemiologic Indices May Reduce Shortage of Intensive Care Unit Staff During the COVID-19 Pandemic.
Mascha, Edward J; Schober, Patrick; Schefold, Joerg C; Stueber, Frank; Luedi, Markus M.
  • Mascha EJ; From the Departments of Quantitative Health Sciences and Outcomes Research, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio.
  • Schober P; Department of Anaesthesiology, Amsterdam University Medical Centres, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
  • Schefold JC; Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Stueber F; Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Luedi MM; Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Anesth Analg ; 131(1): 24-30, 2020 07.
Article in English | MEDLINE | ID: covidwho-159435
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 21 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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Personnel Staffing and Scheduling / Pneumonia, Viral / Epidemiologic Methods / Coronavirus Infections / Critical Care / Pandemics Type of study: Observational study Limits: Humans Language: English Journal: Anesth Analg Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Personnel Staffing and Scheduling / Pneumonia, Viral / Epidemiologic Methods / Coronavirus Infections / Critical Care / Pandemics Type of study: Observational study Limits: Humans Language: English Journal: Anesth Analg Year: 2020 Document Type: Article