TY - JOUR
T1 - Using the CER Hub to ensure data quality in a multi-institution smoking cessation study
AU - Walker, Kari L.
AU - Kirillova, Olga
AU - Gillespie, Suzanne E.
AU - Hsiao, David
AU - Pishchalenko, Valentyna
AU - Pai, Akshatha Kalsanka
AU - Puro, Jon E.
AU - Plumley, Robert
AU - Kudyakov, Rustam
AU - Hu, Weiming
AU - Allisany, Art
AU - McBurnie, Mary Ann
AU - Kurtz, Stephen E.
AU - Hazlehurst, Brian L.
N1 - Funding Information:
Funding This research, and the CER Hub project (http://www.cerhub.org), is funded by grant R01HS019828 (Hazlehurst, PI) from the Agency for Health Care Research and Quality (AHRQ), US Department of Health and Human Services.
PY - 2014/7/3
Y1 - 2014/7/3
N2 - Comparative effectiveness research (CER) studies involving multiple institutions with diverse electronic health records (EHRs) depend on high quality data. To ensure uniformity of data derived from different EHR systems and implementations, the CER Hub informatics platform developed a quality assurance (QA) process using tools and data formats available through the CER Hub. The QA process, implemented here in a study of smoking cessation services in primary care, used the 'emrAdapter' tool programmed with a set of quality checks to query large samples of primary care encounter records extracted in accord with the CER Hub common data framework. The tool, deployed to each study site, generated error reports indicating data problems to be fixed locally and aggregate data sharable with the central site for quality review. Across the CER Hub network of six health systems, data completeness and correctness issues were prevalent in the first iteration and were considerably improved after three iterations of the QA process. A common issue encountered was incomplete mapping of local EHR data values to those defined by the common data framework. A highly automated and distributed QA process helped to ensure the correctness and completeness of patient care data extracted from EHRs for a multi-institution CER study in smoking cessation.
AB - Comparative effectiveness research (CER) studies involving multiple institutions with diverse electronic health records (EHRs) depend on high quality data. To ensure uniformity of data derived from different EHR systems and implementations, the CER Hub informatics platform developed a quality assurance (QA) process using tools and data formats available through the CER Hub. The QA process, implemented here in a study of smoking cessation services in primary care, used the 'emrAdapter' tool programmed with a set of quality checks to query large samples of primary care encounter records extracted in accord with the CER Hub common data framework. The tool, deployed to each study site, generated error reports indicating data problems to be fixed locally and aggregate data sharable with the central site for quality review. Across the CER Hub network of six health systems, data completeness and correctness issues were prevalent in the first iteration and were considerably improved after three iterations of the QA process. A common issue encountered was incomplete mapping of local EHR data values to those defined by the common data framework. A highly automated and distributed QA process helped to ensure the correctness and completeness of patient care data extracted from EHRs for a multi-institution CER study in smoking cessation.
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U2 - 10.1136/amiajnl-2013-002629
DO - 10.1136/amiajnl-2013-002629
M3 - Article
C2 - 24993545
AN - SCOPUS:84940291527
SN - 1067-5027
VL - 21
SP - 1129
EP - 1135
JO - Journal of the American Medical Informatics Association
JF - Journal of the American Medical Informatics Association
IS - 6
ER -