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The adoption of an electronic health record did not improve A1c values in Type 2 diabetes.

Overview of attention for article published in BMJ Health & Care Informatics, April 2016
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Title
The adoption of an electronic health record did not improve A1c values in Type 2 diabetes.
Published in
BMJ Health & Care Informatics, April 2016
DOI 10.14236/jhi.v23i1.144
Pubmed ID
Authors

Harry B Burke, Dorothy A Becher, Albert Hoang, Ronald W Gimbel

Abstract

A major justification for the clinical adoption of electronic health records (EHRs) was the expectation that it would improve the quality of medical care. No longitudinal study has tested this assumption. We used hemoglobin A1c, a recognized clinical quality measure directly related to diabetes outcomes, to assess the effect of EHR use on clinical quality. We performed a five-and-one-half-year multicentre longitudinal retrospective study of the A1c values of 537 type 2 diabetic patients. The same patients had to have been seen on at least three occasions: once approximately six months prior to EHR adoption (before-EHR), once approximately six monthsafter EHR adoption (after-EHR) and once approximately five years after EHR adoption (five-years), for a total of 1,611 notes. The overall mean confidence interval (CI) A1c values for the before- EHR, after-EHR and five-years were 7.07 (6.91 - 7.23), 7.33 (7.14 - 7.52) and 7.19 (7.06 - 7.32), respectively. There was a small but significant increase in A1c values between before-EHR and after-EHR, p = .04; there were no other significant differences. There was a significant decrease in notes missing at least one A1c value, from 42% before-EHR to 16% five-years (p < .001). We found that based on patient's A1c values, EHRs did not improve the clinical quality of diabetic care in six months and five years after EHR adoption. To our knowledge, this is the first longitudinal study to directly assess the relationshipbetween the use of an EHR and clinical quality.

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Mendeley readers

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The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 5%
Unknown 19 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 15%
Student > Bachelor 2 10%
Lecturer 1 5%
Student > Doctoral Student 1 5%
Librarian 1 5%
Other 4 20%
Unknown 8 40%
Readers by discipline Count As %
Medicine and Dentistry 4 20%
Computer Science 2 10%
Unspecified 1 5%
Economics, Econometrics and Finance 1 5%
Nursing and Health Professions 1 5%
Other 2 10%
Unknown 9 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 June 2016.
All research outputs
#22,805,112
of 25,425,223 outputs
Outputs from BMJ Health & Care Informatics
#1
of 1 outputs
Outputs of similar age
#271,123
of 313,975 outputs
Outputs of similar age from BMJ Health & Care Informatics
#1
of 1 outputs
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