Developing a COVID-19 WHO Clinical Progression Scale inpatient database from electronic health record data
Author(s) -
Priya Ramaswamy,
Jen J. Gong,
Sameh N. Saleh,
Samuel McDonald,
Seth Blumberg,
Richard J Medford,
Xinran Liu
Publication year - 2022
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1093/jamia/ocac041
Subject(s) - covid-19 , electronic health record , scale (ratio) , health records , medicine , medline , data science , computer science , database , health care , virology , geography , cartography , infectious disease (medical specialty) , political science , disease , outbreak , law
Objective There is a need for a systematic method to implement the World Health Organization’s Clinical Progression Scale (WHO-CPS), an ordinal clinical severity score for coronavirus disease 2019 patients, to electronic health record (EHR) data. We discuss our process of developing guiding principles mapping EHR data to WHO-CPS scores across multiple institutions. Materials and Methods Using WHO-CPS as a guideline, we developed the technical blueprint to map EHR data to ordinal clinical severity scores. We applied our approach to data from 2 medical centers. Results Our method was able to classify clinical severity for 100% of patient days for 2756 patient encounters across 2 institutions. Discussion Implementing new clinical scales can be challenging; strong understanding of health system data architecture was integral to meet the clinical intentions of the WHO-CPS. Conclusion We describe a detailed blueprint for how to apply the WHO-CPS scale to patient data from the EHR.
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