{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T18:52:34Z","timestamp":1773514354245,"version":"3.50.1"},"reference-count":63,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T00:00:00Z","timestamp":1639353600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Patient-Centered Outcomes Research Institute award","award":["RI-CRN-2020-003-IC"],"award-info":[{"award-number":["RI-CRN-2020-003-IC"]}]},{"name":"National Institutes of Health Clinical and Translational Science"},{"name":"University of Kansas for Frontiers: University of Kansas Clinical and Translational Science Institute","award":["UL1TR002366"],"award-info":[{"award-number":["UL1TR002366"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>The Greater Plains Collaborative (GPC) and other PCORnet Clinical Data Research Networks capture healthcare utilization within their health systems. Here, we describe a reusable environment (GPC Reusable Observable Unified Study Environment [GROUSE]) that integrates hospital and electronic health records (EHRs) data with state-wide Medicare and Medicaid claims and assess how claims and clinical data complement each other to identify obesity and related comorbidities in a patient sample.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>EHR, billing, and tumor registry data from 7 healthcare systems were integrated with Center for Medicare (2011\u20132016) and Medicaid (2011\u20132012) services insurance claims to create deidentified databases in Informatics for Integrating Biology &amp; the Bedside and PCORnet Common Data Model formats. We describe technical details of how this federally compliant, cloud-based data environment was built. As a use case, trends in obesity rates for different age groups are reported, along with the relative contribution of claims and EHR data-to-data completeness and detecting common comorbidities.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>GROUSE contained 73 billion observations from 24 million unique patients (12.9 million Medicare; 13.9 million Medicaid; 6.6 million GPC patients) with 1\u00a0674\u00a0134 patients crosswalked and 983\u00a0450 patients with body mass index (BMI) linked to claims. Diagnosis codes from EHR and claims sources underreport obesity by 2.56 times compared with body mass index measures. However, common comorbidities such as diabetes and sleep apnea diagnoses were more often available from claims diagnoses codes (1.6 and 1.4 times, respectively).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>GROUSE provides a unified EHR-claims environment to address health system and federal privacy concerns, which enables investigators to generalize analyses across health systems integrated with multistate insurance claims.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocab269","type":"journal-article","created":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T20:13:05Z","timestamp":1637352785000},"page":"660-670","source":"Crossref","is-referenced-by-count":22,"title":["Enhancing PCORnet Clinical Research Network data completeness by integrating multistate insurance claims with electronic health records in a cloud environment aligned with CMS security and privacy requirements"],"prefix":"10.1093","volume":"29","author":[{"given":"Lemuel R","family":"Waitman","sequence":"first","affiliation":[{"name":"Department of Health Informatics, University of Missouri School of Medicine, Columbia, Missouri, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3712-2904","authenticated-orcid":false,"given":"Xing","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Health Informatics, University of Missouri School of Medicine, Columbia, Missouri, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dammika Lakmal","family":"Walpitage","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, Enterprise Analytics, University of Kansas Medical Center, Kansas City, Kansas, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel C","family":"Connolly","sequence":"additional","affiliation":[{"name":"Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8626-137X","authenticated-orcid":false,"given":"Lav P","family":"Patel","sequence":"additional","affiliation":[{"name":"Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8036-2110","authenticated-orcid":false,"given":"Mei","family":"Liu","sequence":"additional","affiliation":[{"name":"Division of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mary C","family":"Schroeder","sequence":"additional","affiliation":[{"name":"Division of Health Services Research, Department of Pharmacy Practice and Science, University of Iowa, Iowa City, Iowa, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey J","family":"VanWormer","sequence":"additional","affiliation":[{"name":"Center for Clinical Epidemiology & Population Health, Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abu Saleh","family":"Mosa","sequence":"additional","affiliation":[{"name":"Department of Health Informatics, University of Missouri School of Medicine, Columbia, Missouri, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ernest T","family":"Anye","sequence":"additional","affiliation":[{"name":"Office of Information Security, University of Missouri Health, Columbia, Missouri, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ann M","family":"Davis","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, University of Kansas Medical Center, Kansas City, Kansas, USA"},{"name":"Center for Children\u2019s Healthy Lifestyles & Nutrition, Kansas City, Missouri, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,12,13]]},"reference":[{"issue":"4","key":"2022031509050256200_ocab269-B1","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1136\/amiajnl-2014-002747","article-title":"Launching PCORnet, a national patient-centered clinical research network","volume":"21","author":"Fleurence","year":"2014","journal-title":"J Am Med Inform Assoc"},{"key":"2022031509050256200_ocab269-B2","year":"2015"},{"issue":"4","key":"2022031509050256200_ocab269-B3","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1136\/amiajnl-2014-002756","article-title":"The Greater Plains Collaborative: a PCORnet Clinical Research Data Network","volume":"21","author":"Waitman","year":"2014","journal-title":"J Am Med Inform 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