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

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 diagnose...

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Autores principales: Harris, Stewart B, Glazier, Richard H, Tompkins, Jordan W, Wilton, Andrew S, Chevendra, Vijaya, Stewart, Moira A, Thind, Amardeep
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3022877/
https://www.ncbi.nlm.nih.gov/pubmed/21182790
http://dx.doi.org/10.1186/1472-6963-10-347
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author Harris, Stewart B
Glazier, Richard H
Tompkins, Jordan W
Wilton, Andrew S
Chevendra, Vijaya
Stewart, Moira A
Thind, Amardeep
author_facet Harris, Stewart B
Glazier, Richard H
Tompkins, Jordan W
Wilton, Andrew S
Chevendra, Vijaya
Stewart, Moira A
Thind, Amardeep
author_sort Harris, Stewart B
collection PubMed
description 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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spelling pubmed-30228772011-01-19 Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study Harris, Stewart B Glazier, Richard H Tompkins, Jordan W Wilton, Andrew S Chevendra, Vijaya Stewart, Moira A Thind, Amardeep BMC Health Serv Res Research Article 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. BioMed Central 2010-12-23 /pmc/articles/PMC3022877/ /pubmed/21182790 http://dx.doi.org/10.1186/1472-6963-10-347 Text en Copyright ©2010 Harris et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (<url>http://creativecommons.org/licenses/by/2.0</url>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Harris, Stewart B
Glazier, Richard H
Tompkins, Jordan W
Wilton, Andrew S
Chevendra, Vijaya
Stewart, Moira A
Thind, Amardeep
Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study
title Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study
title_full Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study
title_fullStr Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study
title_full_unstemmed Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study
title_short Investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study
title_sort investigating concordance in diabetes diagnosis between primary care charts (electronic medical records) and health administrative data: a retrospective cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3022877/
https://www.ncbi.nlm.nih.gov/pubmed/21182790
http://dx.doi.org/10.1186/1472-6963-10-347
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