Email updates

Keep up to date with the latest news and content from BMC Health Services Research and BioMed Central.

Open Access Highly Accessed Research article

Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study

Stewart B Harris1*, Richard H Glazier234, Jordan W Tompkins1, Andrew S Wilton2, Vijaya Chevendra1, Moira A Stewart1 and Amardeep Thind15

Author Affiliations

1 Centre for Studies in Family Medicine, Department of Family Medicine, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada

2 Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada

3 Centre for Research on Inner City Health, in the Keenan Research Centre at the Li Ka Shing Knowledge Institute of St. Michael's Hospital, Toronto, Ontario, Canada

4 Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada

5 Department of Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry, The University of Western Ontario, London, Ontario, Canada

For all author emails, please log on.

BMC Health Services Research 2010, 10:347  doi:10.1186/1472-6963-10-347

Published: 23 December 2010

Abstract

Background

Electronic medical records contain valuable clinical information not readily available elsewhere. Accordingly, they hold important potential for contributing to and enhancing chronic disease registries with the goal of improving chronic disease management; however a standard for diagnoses of conditions such as diabetes remains to be developed. The purpose of this study was to establish a validated electronic medical record definition for diabetes.

Methods

We constructed a retrospective cohort using health administrative data from the Institute for Clinical Evaluative Sciences Ontario Diabetes Database linked with electronic medical records from the Deliver Primary Healthcare Information Project using data from 1 April 2006 - 31 March 2008 (N = 19,443). We systematically examined eight definitions for diabetes diagnosis, both established and proposed.

Results

The definition that identified the highest number of patients with diabetes (N = 2,180) while limiting to those with the highest probability of having diabetes was: individuals with ≥2 abnormal plasma glucose tests, or diabetes on the problem list, or insulin prescription, or ≥2 oral anti-diabetic agents, or HbA1c ≥6.5%. Compared to the Ontario Diabetes Database, this definition identified 13% more patients while maintaining good sensitivity (75%) and specificity (98%).

Conclusions

This study establishes the feasibility of developing an electronic medical record standard definition of diabetes and validates an algorithm for use in this context. While the algorithm may need to be tailored to fit available data in different electronic medical records, it contributes to the establishment of validated disease registries with the goal of enhancing research, and enabling quality improvement in clinical care and patient self-management.