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Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study
被引:33
|作者:
Harris, Stewart B.
[1
]
Glazier, Richard H.
[2
,3
,4
]
Tompkins, Jordan W.
[1
]
Wilton, Andrew S.
[2
]
Chevendra, Vijaya
[1
]
Stewart, Moira A.
[1
]
Thind, Amardeep
[1
,5
]
机构:
[1] Univ Western Ontario, Schulich Sch Med & Dent, Dept Family Med, Ctr Studies Family Med, London, ON, Canada
[2] Inst Clin Evaluat Sci, Toronto, ON, Canada
[3] St Michaels Hosp, Li Ka Shing Knowledge Inst, Keenan Res Ctr, Ctr Res Inner City Hlth, Toronto, ON M5B 1W8, Canada
[4] Univ Toronto, Dept Family & Community Med, Toronto, ON M5S 1A1, Canada
[5] Univ Western Ontario, Dept Epidemiol & Biostat, Schulich Sch Med & Dent, London, ON, Canada
关键词:
PREVALENCE;
PERFORMANCE;
ONTARIO;
SYSTEM;
D O I:
10.1186/1472-6963-10-347
中图分类号:
R19 [保健组织与事业(卫生事业管理)];
学科分类号:
摘要:
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.
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