{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T09:45:16Z","timestamp":1775727916691,"version":"3.50.1"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T00:00:00Z","timestamp":1662508800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"NCATS","doi-asserted-by":"publisher","award":["R21 TR002513"],"award-info":[{"award-number":["R21 TR002513"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000092","name":"NLM","doi-asserted-by":"publisher","award":["R01 LM012517"],"award-info":[{"award-number":["R01 LM012517"]}],"id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000092","name":"NLM","doi-asserted-by":"publisher","award":["T15 LM013977"],"award-info":[{"award-number":["T15 LM013977"]}],"id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"NCATS","doi-asserted-by":"publisher","award":["UL1 TR001450"],"award-info":[{"award-number":["UL1 TR001450"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Electronic (e)-phenotype specification by noninformaticist investigators remains a challenge. Although validation of each patient returned by e-phenotype could ensure accuracy of cohort representation, this approach is not practical. Understanding the factors leading to successful e-phenotype specification may reveal generalizable strategies leading to better results.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>Noninformaticist experts (n\u2009=\u200921) were recruited to produce expert-mediated e-phenotypes using i2b2 assisted by a honest data-broker and a project coordinator. Patient- and visit-sets were reidentified and a random sample of 20 charts matching each e-phenotype was returned to experts for chart-validation. Attributes of the queries and expert characteristics were captured and related to chart-validation rates using generalized linear regression models.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>E-phenotype validation rates varied according to experts\u2019 domains and query characteristics (mean\u2009=\u200961%, range 20\u2013100%). Clinical domains that performed better included infectious, rheumatic, neonatal, and cancers, whereas other domains performed worse (psychiatric, GI, skin, and pulmonary). Match-rate was negatively impacted when specification of temporal constraints was required. In general, the increase in e-phenotype specificity contributed positively to match-rate.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussions and Conclusions<\/jats:title>\n                  <jats:p>Clinical experts and informaticists experience a variety of challenges when building e-phenotypes, including the inability to differentiate clinical events from patient characteristics or appropriately configure temporal constraints; a lack of access to available and quality data; and difficulty in specifying routes of medication administration. Biomedical query mediation by informaticists and honest data-brokers in designing e-phenotypes cannot be overstated. Although tools such as i2b2 may be widely available to noninformaticists, successful utilization depends not on users\u2019 confidence, but rather on creating highly specific e-phenotypes.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocac157","type":"journal-article","created":{"date-parts":[[2022,9,7]],"date-time":"2022-09-07T14:22:01Z","timestamp":1662560521000},"page":"213-221","source":"Crossref","is-referenced-by-count":6,"title":["Not all phenotypes are created equal: covariates of success in e-phenotype specification"],"prefix":"10.1093","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4559-299X","authenticated-orcid":false,"given":"Bashir","family":"Hamidi","sequence":"first","affiliation":[{"name":"Biomedical Informatics Center, Medical University of South Carolina , Charleston, South Carolina 29425, USA"}]},{"given":"Patrick A","family":"Flume","sequence":"additional","affiliation":[{"name":"Department of Medicine, Medical University of South Carolina , Charleston, South Carolina 29425, USA"}]},{"given":"Kit N","family":"Simpson","sequence":"additional","affiliation":[{"name":"Department of Healthcare Leadership and Management, Medical University of South Carolina , Charleston, South Carolina 29425, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5748-2085","authenticated-orcid":false,"given":"Alexander V","family":"Alekseyenko","sequence":"additional","affiliation":[{"name":"Biomedical Informatics Center, Medical University of South Carolina , Charleston, South Carolina 29425, USA"},{"name":"Department of Healthcare Leadership and Management, Medical University of South Carolina , Charleston, South Carolina 29425, USA"},{"name":"Department of Public Health Sciences, Medical University of South Carolina , Charleston, South Carolina, 29425, USA"},{"name":"Department of Oral Health Sciences, Medical University of South Carolina , Charleston, South Carolina 29425, 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