Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension

被引:13
|
作者
Horth, Roberta Z. [1 ,2 ]
Wagstaff, Shelly [2 ]
Jeppson, Theron [2 ]
Patel, Vishal [3 ]
McClellan, Jefferson [2 ]
Bissonette, Nicole [2 ]
Friedrichs, Michael [2 ]
Dunn, Angela C. [2 ]
机构
[1] CDC, Epidem Intelligence Serv, Div Sci Educ & Profess Dev, Atlanta, GA 30333 USA
[2] Utah Dept Hlth, Salt Lake City, UT 84114 USA
[3] Utah Hlth Informat Network, Murray, UT USA
关键词
Health information exchange; Electronic health records; Chronic disease epidemiology; Diabetes; Hypertension; Utah epidemiology; Public health surveillance; Health informatics; Prevalence; CHALLENGES; ETHNICITY; LANGUAGE; RACE;
D O I
10.1186/s12889-019-7367-z
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background Electronic health record (EHR) data, collected primarily for individual patient care and billing purposes, compiled in health information exchanges (HIEs) may have a secondary use for population health surveillance of noncommunicable diseases. However, data compilation across fragmented data sources into HIEs presents potential barriers and quality of data is unknown. Methods We compared 2015 patient data from a mid-size health system (Database A) to data from System A patients in the Utah HIE (Database B). We calculated concordance of structured data (sex and age) and unstructured data (blood pressure reading and A1C). We estimated adjusted hypertension and diabetes prevalence in each database and compared these across age groups. Results Matching resulted in 72,356 unique patients. Concordance between Database A and Database B exceeded 99% for sex and age, but was 89% for A1C results and 54% for blood pressure readings. Sensitivity, using Database A as the standard, was 57% for hypertension and 55% for diabetes. Age and sex adjusted prevalence of diabetes (8.4% vs 5.8%, Database A and B, respectively) and hypertension (14.5% vs 11.6%, respectively) differed, but this difference was consistent with parallel slopes in prevalence over age groups in both databases. Conclusions We identified several gaps in the use of HIE data for surveillance of diabetes and hypertension. High concordance of structured data demonstrate some promise in HIEs capacity to capture patient data. Improving HIE data quality through increased use of structured variables may help make HIE data useful for population health surveillance in places with fragmented EHR systems.
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页数:7
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