UBC Faculty Research and Publications

Identification of validated case definitions for chronic disease using electronic medical records: a systematic review protocol Souri, Sepideh; Symonds, Nicola E; Rouhi, Azin; Lethebe, Brendan C; Garies, Stephanie; Ronksley, Paul E; Williamson, Tyler S; Fabreau, Gabriel E; Birtwhistle, Richard; Quan, Hude; McBrien, Kerry A

Abstract

Background: Primary care electronic medical record (EMR) data are being used for research, surveillance, and clinical monitoring. To broaden the reach and usability of EMR data, case definitions must be specified to identify and characterize important chronic conditions. The purpose of this study is to identify all case definitions for a set of chronic conditions that have been tested and validated in primary care EMR and EMR-linked data. This work will provide a reference list of case definitions, together with their performance metrics, and will identify gaps where new case definitions are needed. Methods: We will consider a set of 40 chronic conditions, previously identified as potentially important for surveillance in a review of multimorbidity measures. We will perform a systematic search of the published literature to identify studies that describe case definitions for clinical conditions in EMR data and report the performance of these definitions. We will stratify our search by studies that use EMR data alone and those that use EMR-linked data. We will compare the performance of different definitions for the same conditions and explore the influence of data source, jurisdiction, and patient population. Discussion: EMR data from primary care providers can be compiled and used for benefit by the healthcare system. Not only does this work have the potential to further develop disease surveillance and health knowledge, EMR surveillance systems can provide rapid feedback to participating physicians regarding their patients. Existing case definitions will serve as a starting point for the development and validation of new case definitions and will enable better surveillance, research, and practice feedback based on detailed clinical EMR data. Systematic review registration: PROSPERO CRD42016040020

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Attribution 4.0 International (CC BY 4.0)