From predictions to prescriptions: A data-driven response to COVID-19

Bertsimas, Dimitris, Boussioux, Leonard, Cory Wright, Ryan, Delarue, Arthur, Digalakis, Vassilis, Jacquillat, Alexandre, Lahlou Kitane, Driss, Lukin, Galit, Li, Michael L, Mingardi, Luca, Nohadani, Omid, Orfanoudaki, Agni, Papalexopoulos, Theodore, Paskov, Ivan, Pauphilet, J, Skali Lami, Omar, Stellato, Bartolomeo, Tazi Bouardi, Hamza, Villalobos Carballo, Kimberly, Wiberg, Holly and Zeng, Cynthia (2021) From predictions to prescriptions: A data-driven response to COVID-19. Health Care Management Science. ISSN 1386-9620 (In Press)

Abstract

The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at a steep economic price. We design analytical tools to support these decisions and combat the pandemic. Specifically, we propose a comprehensive data-driven approach to understand the clinical characteristics of COVID-19, predict its mortality, forecast its evolution, and ultimately alleviate its impact. By leveraging cohort-level clinical data, patient-level hospital
data, and census-level epidemiological data, we develop an integrated four-step approach, combining descriptive, predictive and prescriptive analytics. First, we aggregate hundreds of clinical studies into the most comprehensive database on COVID-19 to paint a new macroscopic picture of the disease. Second, we build personalized calculators to predict the risk of infection and mortality as a function of demographics, symptoms, comorbidities, and lab values. Third, we develop a novel epidemiological model to project the pandemic’s spread and inform social distancing policies. Fourth, we propose an optimization model to re-allocate ventilators and alleviate shortages. Our results have been used
at the clinical level by several hospitals to triage patients, guide care management, plan ICU capacity, and re-distribute ventilators. At the policy level, they are currently supporting safe back-to-work policies at a major institution and vaccine trial location planning at Janssen Pharmaceuticals, and have been integrated into the US Center for Disease Control’s pandemic forecast.

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Item Type: Article
Subject Areas: Management Science and Operations
Additional Information:

© 2021 Springer Nature. This is a post-peer-review, pre-copyedit version of an article published in Health Care Management Science. The final authenticated version is available online at: https://doi.org/10.1007/s10729-020-09542-0

Funder Name: National Science Foundation
Date Deposited: 08 Jan 2021 11:20
Date of first compliant deposit: 08 Feb 2021
Subjects: C > Crises
D > Data collection and recording
H > Health service
Last Modified: 18 Sep 2021 00:21
URI: https://lbsresearch.london.edu/id/eprint/1621
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