Quality Gaps of Electronic Health Records in Diabetes Care.

Objectives: Electronic health records (EHRs) allow standardized data capture for robust quality and performance assessments, but data quality issues may exist. This study compared extracted structured EHR data with chart review from endocrinologists' health-care records at a large, academic ambulatory hospital in Toronto, Ontario.

Methods: Consecutive chart review for the first 10 patients with either type 1 or type 2 diabetes seen between January 1, 2015 and March 1, 2016 was sampled for each of the 10 endocrinologists within the diabetes program, and electronic data extraction was also completed for a core set of structured diabetes care elements. Fisher exact test was used to determine differences in data availability between extracted EHR data and chart review.

Results: Out of 100 charts, there was significant under-representation of care elements using EHR extraction compared with chart review for glycated hemoglobin (45% vs 100%; p<0.0001), low-density lipoprotein (36% vs 89%; p<0.0001), urine albumin to creatinine ratio (38% vs 86%; p<0.0001), insulin use (20% vs 72%; p<0.0001), glomerular filtration rate (42% vs 87%, p<0.0001) and use of oral hypoglycemic agent (14% vs 64%; p<0.0001), respectively. EHR data extraction could not be obtained for driving status, hypoglycemia and driving counselling, smoking cessation counselling, family planning counselling and eye examination documentation.

Conclusions: There is poor accuracy of using EHR data extraction during the early adoption phase to understand diabetes care, limiting EHR-based quality assessments.