Deployment of an Interdisciplinary Predictive Analytics Task Force to Inform Hospital Operational Decision-Making During the COVID-19 Pandemic

Mayo Clin Proc. 2021 Mar;96(3):690-698. doi: 10.1016/j.mayocp.2020.12.019. Epub 2020 Dec 30.

Abstract

In March 2020, our institution developed an interdisciplinary predictive analytics task force to provide coronavirus disease 2019 (COVID-19) hospital census forecasting to help clinical leaders understand the potential impacts on hospital operations. As the situation unfolded into a pandemic, our task force provided predictive insights through a structured set of visualizations and key messages that have helped the practice to anticipate and react to changing operational needs and opportunities. The framework shared here for the deployment of a COVID-19 predictive analytics task force could be adapted for effective implementation at other institutions to provide evidence-based messaging for operational decision-making. For hospitals without such a structure, immediate consideration may be warranted in light of the devastating COVID-19 third-wave which has arrived for winter 2020-2021.

Publication types

  • Review

MeSH terms

  • COVID-19 / epidemiology
  • COVID-19 / therapy*
  • Decision Making*
  • Disease Management*
  • Forecasting
  • Hospitals / statistics & numerical data*
  • Humans
  • Intensive Care Units / statistics & numerical data*
  • Pandemics*
  • SARS-CoV-2*