{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:28:54Z","timestamp":1760956134384,"version":"3.37.3"},"reference-count":16,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T00:00:00Z","timestamp":1634688000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T00:00:00Z","timestamp":1634688000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000738","name":"U.S. Department of Veterans Affairs","doi-asserted-by":"publisher","award":["#I01-BX003362","#I01-BX003362","#I01-BX003362","#I01-BX003362"],"award-info":[{"award-number":["#I01-BX003362","#I01-BX003362","#I01-BX003362","#I01-BX003362"]}],"id":[{"id":"10.13039\/100000738","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000194","name":"U.S. Department of State","doi-asserted-by":"publisher","award":["#5I01-HX002487","#5I01-HX002487","#5I01-HX002487","#5I01-HX002487"],"award-info":[{"award-number":["#5I01-HX002487","#5I01-HX002487","#5I01-HX002487","#5I01-HX002487"]}],"id":[{"id":"10.13039\/100000194","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>To describe an automated method for assessment of the plausibility of continuous variables collected in the\u00a0electronic health record (EHR)\u00a0data for real world evidence research use.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>The most widely used approach in quality assessment (QA) for continuous variables is to detect the implausible numbers using prespecified thresholds. In augmentation to the thresholding method, we developed a score-based method that leverages the longitudinal characteristics of EHR data for detection of the observations inconsistent with the history of a patient. The method was applied to the height and weight data in the EHR from the Million Veteran Program Data from the Veteran\u2019s Healthcare Administration (VHA). A validation study was also conducted.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The\u00a0receiver operating characteristic (ROC)\u00a0metrics of the developed method outperforms the widely used thresholding method. It is also demonstrated that different quality assessment methods have a non-ignorable impact on the\u00a0body mass index (BMI) classification calculated from height and weight data in the VHA\u2019s database.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>The score-based method enables automated and scaled detection of the problematic data points in health care big data while allowing the investigators to select the high-quality data based on their need. Leveraging the longitudinal characteristics in EHR will significantly improve the QA performance.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12911-021-01643-2","type":"journal-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T12:27:05Z","timestamp":1634732825000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A statistical quality assessment method for longitudinal observations in electronic health record data with an application to the VA million veteran program"],"prefix":"10.1186","volume":"21","author":[{"given":"Hui","family":"Wang","sequence":"first","affiliation":[]},{"given":"Ilana","family":"Belitskaya-Levy","sequence":"additional","affiliation":[]},{"given":"Fan","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Jennifer S.","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Mei-Chiung","family":"Shih","sequence":"additional","affiliation":[]},{"given":"Philip S.","family":"Tsao","sequence":"additional","affiliation":[]},{"given":"Ying","family":"Lu","sequence":"additional","affiliation":[]},{"name":"on behalf of VA Million Veteran Program","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,10,20]]},"reference":[{"key":"1643_CR1","doi-asserted-by":"crossref","unstructured":"Mathur R, Bhaskaran K, Edwards E, et al. 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