{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T17:09:33Z","timestamp":1772557773377,"version":"3.50.1"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2022,2,9]],"date-time":"2022-02-09T00:00:00Z","timestamp":1644364800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"ReumaNederland and NIH","award":["U01 HG008685"],"award-info":[{"award-number":["U01 HG008685"]}]},{"name":"ReumaNederland and NIH","award":["P30 AR070253"],"award-info":[{"award-number":["P30 AR070253"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,4,13]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>To facilitate patient disease subset and risk factor identification by constructing a pipeline which is generalizable, provides easily interpretable results, and allows replication by overcoming electronic health records (EHRs) batch effects.<\/jats:p><\/jats:sec><jats:sec><jats:title>Material and Methods<\/jats:title><jats:p>We used 1872 billing codes in EHRs of 102\u00a0880 patients from 12 healthcare systems. Using tools borrowed from single-cell omics, we mitigated center-specific batch effects and performed clustering to identify patients with highly similar medical history patterns across the various centers. Our visualization method (PheSpec) depicts the phenotypic profile of clusters, applies a novel filtering of noninformative codes (Ranked Scope Pervasion), and indicates the most distinguishing features.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We observed 114 clinically meaningful profiles, for example, linking prostate hyperplasia with cancer and diabetes with cardiovascular problems and grouping pediatric developmental disorders. Our framework identified disease subsets, exemplified by 6 \u201cother headache\u201d clusters, where phenotypic profiles suggested different underlying mechanisms: migraine, convulsion, injury, eye problems, joint pain, and pituitary gland disorders. Phenotypic patterns replicated well, with high correlations of \u22650.75 to an average of 6 (2\u20138) of the 12 different cohorts, demonstrating the consistency with which our method discovers disease history profiles.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>Costly clinical research ventures should be based on solid hypotheses. We repurpose methods from single-cell omics to build these hypotheses from observational EHR data, distilling useful information from complex data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>We establish a generalizable pipeline for the identification and replication of clinically meaningful (sub)phenotypes from widely available high-dimensional billing codes. This approach overcomes datatype problems and produces comprehensive visualizations of validation-ready phenotypes.<\/jats:p><\/jats:sec>","DOI":"10.1093\/jamia\/ocac008","type":"journal-article","created":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T20:14:13Z","timestamp":1643314453000},"page":"761-769","source":"Crossref","is-referenced-by-count":12,"title":["A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history"],"prefix":"10.1093","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3266-6232","authenticated-orcid":false,"given":"Marc P","family":"Maurits","sequence":"first","affiliation":[{"name":"Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands"},{"name":"Leiden Computational Biology Center, Leiden University Medical Center, Leiden, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ilya","family":"Korsunsky","sequence":"additional","affiliation":[{"name":"Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Soumya","family":"Raychaudhuri","sequence":"additional","affiliation":[{"name":"Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shawn N","family":"Murphy","sequence":"additional","affiliation":[{"name":"Research Information Science and Computing, Mass General Brigham, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jordan W","family":"Smoller","sequence":"additional","affiliation":[{"name":"Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA"},{"name":"Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Scott T","family":"Weiss","sequence":"additional","affiliation":[{"name":"Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lynn M","family":"Petukhova","sequence":"additional","affiliation":[{"name":"Lynn M. Petukhova, Department of Dermatology at NewYork-Presbyterian\/Columbia University Medical Center (CUMC)"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunhua","family":"Weng","sequence":"additional","affiliation":[{"name":"Chunhua Weng, Biomedical Informatics - Columbia University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei-Qi","family":"Wei","sequence":"additional","affiliation":[{"name":"Wei-Qi Wei, Biomedical Informatics in the School of Medicine at Vanderbilt University Wei"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas W J","family":"Huizinga","sequence":"additional","affiliation":[{"name":"Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcel J T","family":"Reinders","sequence":"additional","affiliation":[{"name":"Leiden Computational Biology Center, Leiden University Medical Center, Leiden, The 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