ReviewR: a light-weight and extensible tool for manual review of clinical records

Author:

Mayer David A1,Rasmussen Luke V2ORCID,Roark Christopher D3,Kahn Michael G4,Schilling Lisa M5,Wiley Laura K1ORCID

Affiliation:

1. Department of Biomedical Informatics, Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus , Aurora, Colorado, USA

2. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine , Chicago, Illinois, USA

3. Department of Neurosurgery, University of Colorado Anschutz Medical Campus , Aurora, Colorado, USA

4. Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus , Aurora, CO, USA

5. Division of General Internal Medicine, Department of Medicine, Data Science to Patient Value Program, University of Colorado Anschutz Medical Campus , Aurora, Colorado, USA

Abstract

Abstract Objectives Manual record review is a crucial step for electronic health record (EHR)-based research, but it has poor workflows and is error prone. We sought to build a tool that provides a unified environment for data review and chart abstraction data entry. Materials and Methods ReviewR is an open-source R Shiny application that can be deployed on a single machine or made available to multiple users. It supports multiple data models and database systems, and integrates with the REDCap API for storing abstraction results. Results We describe 2 real-world uses and extensions of ReviewR. Since its release in April 2021 as a package on CRAN it has been downloaded 2204 times. Discussion and Conclusion ReviewR provides an easily accessible review interface for clinical data warehouses. Its modular, extensible, and open source nature afford future expansion by other researchers.

Funder

National Institutes of Health

National Center for Advancing Translational Science

National Institute of General Medical Sciences

National Human Genome Research Institute

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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