Development and Validation of an Electronic Health Record-Derived Prediction Model for Preventing COVID-19 Hospitalization and Death.

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Bibliographic Details
Title: Development and Validation of an Electronic Health Record-Derived Prediction Model for Preventing COVID-19 Hospitalization and Death.
Authors: Coley RY; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA. rebecca.y.coley@kp.org.; Department of Biostatistics, University of Washington, Seattle, WA, USA. rebecca.y.coley@kp.org., Hays R; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA., Pardee RE; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA., Fuller S; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA., Rogers K; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA., Allen CL; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA., Arterburn DE; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.; Department of Medicine, University of Washington, Seattle, WA, USA., Frazier RK; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA., Kent DJ; Kaiser Permanente Washington, Seattle, WA, USA.; School of Pharmacy, University of Washington, Seattle, WA, USA., Mun S; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA., Mwatha T; Kaiser Permanente Washington, Seattle, WA, USA., Thottingal P; Kaiser Permanente Washington, Seattle, WA, USA., Westbrook EO; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Source: Prevention science : the official journal of the Society for Prevention Research [Prev Sci] 2025 Oct 20. Date of Electronic Publication: 2025 Oct 20.
Publication Type: Journal Article
Journal Info: Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 100894724 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-6695 (Electronic) Linking ISSN: 13894986 NLM ISO Abbreviation: Prev Sci Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1573-6695
DOI:10.1007/s11121-025-01844-5