Skip to main content
Top
Published in: Systematic Reviews 1/2017

Open Access 01-12-2017 | Protocol

Identification of validated case definitions for chronic disease using electronic medical records: a systematic review protocol

Authors: Sepideh Souri, Nicola E. Symonds, Azin Rouhi, Brendan C. Lethebe, Stephanie Garies, Paul E. Ronksley, Tyler S. Williamson, Gabriel E. Fabreau, Richard Birtwhistle, Hude Quan, Kerry A. McBrien

Published in: Systematic Reviews | Issue 1/2017

Login to get access

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
Appendix
Available only for authorised users
Literature
1.
go back to reference Murdoch TB, Detsky AS. The inevitable application of big data to health care. JAMA. 2013;309:1351–2.CrossRefPubMed Murdoch TB, Detsky AS. The inevitable application of big data to health care. JAMA. 2013;309:1351–2.CrossRefPubMed
2.
4.
go back to reference Quan H, Smith M, Barlett-Esquilant G, Johansen H, Tu K, Lix L, Hypertension Outcome and Surveillance Team. Mining administrative health databases to advance medical science: geographical considerations and untapped potential in Canada. Can J Cardiol. 2012;28:152–4.CrossRefPubMed Quan H, Smith M, Barlett-Esquilant G, Johansen H, Tu K, Lix L, Hypertension Outcome and Surveillance Team. Mining administrative health databases to advance medical science: geographical considerations and untapped potential in Canada. Can J Cardiol. 2012;28:152–4.CrossRefPubMed
5.
go back to reference Williamson T, Green ME, Birtwhistle R, Khan S, Garies S, Wong ST, et al. Validating the 8 CPCSSN case definitions for chronic disease surveillance in a primary care database of electronic health records. Ann Fam Med. 2014;12:367–72.CrossRefPubMedPubMedCentral Williamson T, Green ME, Birtwhistle R, Khan S, Garies S, Wong ST, et al. Validating the 8 CPCSSN case definitions for chronic disease surveillance in a primary care database of electronic health records. Ann Fam Med. 2014;12:367–72.CrossRefPubMedPubMedCentral
6.
go back to reference Broemeling AM, Watson DE, Prebtani F. Population patterns of chronic health conditions, co-morbidity and healthcare use in Canada: implications for policy and practice. Healthc Q. 2008;11:70–6.CrossRefPubMed Broemeling AM, Watson DE, Prebtani F. Population patterns of chronic health conditions, co-morbidity and healthcare use in Canada: implications for policy and practice. Healthc Q. 2008;11:70–6.CrossRefPubMed
7.
go back to reference Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;380:37–43.CrossRefPubMed Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;380:37–43.CrossRefPubMed
8.
go back to reference Tonelli M, Wiebe N, Fortin M, Guthrie B, Hemmelgarn BR, James MT, et al. Methods for identifying 30 chronic conditions: application to administrative data. BMC Med Inform Decis Mak. 2015;15:31.CrossRefPubMedPubMedCentral Tonelli M, Wiebe N, Fortin M, Guthrie B, Hemmelgarn BR, James MT, et al. Methods for identifying 30 chronic conditions: application to administrative data. BMC Med Inform Decis Mak. 2015;15:31.CrossRefPubMedPubMedCentral
9.
go back to reference Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151:264–9.CrossRefPubMed Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151:264–9.CrossRefPubMed
10.
go back to reference Herrett E, Gallagher AM, Bhaskaran K, Forbes H, Mathur R, van Staa T, et al. Data resource profile: clinical practice research datalink (CPRD). Int J Epidemiol. 2015;44:827–36.CrossRefPubMedPubMedCentral Herrett E, Gallagher AM, Bhaskaran K, Forbes H, Mathur R, van Staa T, et al. Data resource profile: clinical practice research datalink (CPRD). Int J Epidemiol. 2015;44:827–36.CrossRefPubMedPubMedCentral
12.
go back to reference Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003;3:25.CrossRefPubMedPubMedCentral Whiting P, Rutjes AW, Reitsma JB, Bossuyt PM, Kleijnen J. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol. 2003;3:25.CrossRefPubMedPubMedCentral
Metadata
Title
Identification of validated case definitions for chronic disease using electronic medical records: a systematic review protocol
Authors
Sepideh Souri
Nicola E. Symonds
Azin Rouhi
Brendan C. Lethebe
Stephanie Garies
Paul E. Ronksley
Tyler S. Williamson
Gabriel E. Fabreau
Richard Birtwhistle
Hude Quan
Kerry A. McBrien
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Systematic Reviews / Issue 1/2017
Electronic ISSN: 2046-4053
DOI
https://doi.org/10.1186/s13643-017-0431-9

Other articles of this Issue 1/2017

Systematic Reviews 1/2017 Go to the issue