Developing a COVID-19 WHO Clinical Progression Scale inpatient database from electronic health record data

Author:

Ramaswamy Priya12,Gong Jen J3,Saleh Sameh N456ORCID,McDonald Samuel A47,Blumberg Seth8910,Medford Richard J411ORCID,Liu Xinran1

Affiliation:

1. Division of Hospital Medicine, Department of Medicine, University of California, San Francisco , San Francisco, California, USA

2. Department of Anesthesia and Perioperative Care, University of California, San Francisco , San Francisco, California, USA

3. Center of Clinical Informatics and Improvement Research, Department of Medicine, University of California, San Francisco , San Francisco, California, USA

4. Clinical Informatics Center, University of Texas Southwestern Medical Center , Dallas, Texas, USA

5. Section of Hospital Medicine, Division of General Internal Medicine, University of Pennsylvania Health System , Philadelphia, Pennsylvania, USA

6. Department of Biomedical & Health Informatics, Children’s Hospital of Philadelphia , Philadelphia, Pennsylvania, USA

7. Department of Emergency Medicine, University of Texas Southwestern Medical Center, Clinical Informatics Center , Dallas, Texas, USA

8. Francis I. Proctor Foundation, University of California San Francisco , San Francisco, California, USA

9. C enters of Disease Control’s Modeling infectious Diseases (MInD) Healthcare Program, USA

10. Department of Medicine, University of California San Francisco , San Francisco, California, USA

11. Department of Internal Medicine, Division of Infectious Diseases and Geographic Medicine, University of Texas Southwestern Medical Center, Clinical Informatics Center , Dallas, Texas, USA

Abstract

Abstract 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.

Funder

Centers for Disease Control and Prevention

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

Reference11 articles.

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