Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring.

ABSTRACT: COVID-19 has challenged health systems to learn how to learn. This paper describes the context, methods and challenges for learning to improve COVID-19 care at one academic health center. Challenges to learning include: (1) choosing a right clinical target; (2) designing methods for accurate predictions by borrowing strength from prior patients' experiences; (3) communicating the methodology to clinicians so they understand and trust it; (4) communicating the predictions to the patient at the moment of clinical decision; and (5) continuously evaluating and revising the methods so they adapt to changing patients and clinical demands. To illustrate these challenges, this paper contrasts two statistical modeling approaches - prospective longitudinal models in common use and retrospective anal

SUBMITTER: Wang Z 

PROVIDER: S-EPMC10198065 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature