{"doi":"10.1093/jamia/ocac008","title":"A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history","abstract":"OBJECTIVE: 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. MATERIAL AND METHODS: We used 1872 billing codes in EHRs of 102 880 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. RESULTS: 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 \"other headache\" 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 ≥0.75 to an average of 6 (2-8) of the 12 different cohorts, demonstrating the consistency with which our method discovers disease history profiles. DISCUSSION: 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. CONCLUSION: 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.","journal":"Journal of the American Medical Informatics Association","year":2022,"id":270567,"datarank":0.6425548310795834,"base_score":2.639057329615259,"endowment":2.639057329615259,"self_citation_contribution":0.3958585994422889,"citation_network_contribution":0.2466962316372946,"self_endowment_contribution":0.3958585994422889,"citer_contribution":0.2466962316372946,"corpus_percentile":69.1343699234161,"corpus_rank":3991,"citation_count":13,"citer_count":11,"citers_with_citation_signal":8,"citers_with_endowment":8,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8217,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":20.8333,"fair_percentile":36.38031183124427,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":76148,"name":"Ilya Korsunsky","orcid":"0000-0003-4848-3948","position":1,"is_corresponding":false},{"id":35259,"name":"Soumya Raychaudhuri","orcid":"0000-0002-1901-8265","position":2,"is_corresponding":false},{"id":225293,"name":"Shawn N. Murphy","orcid":"0000-0002-1905-8806","position":3,"is_corresponding":false},{"id":104618,"name":"Jordan W. Smoller","orcid":"0000-0002-0381-6334","position":4,"is_corresponding":false},{"id":25033,"name":"Scott T. Weiss","orcid":"0000-0001-7196-303X","position":5,"is_corresponding":false},{"id":557174,"name":"Lynn Petukhova","orcid":"0000-0002-1573-1653","position":6,"is_corresponding":false},{"id":2012,"name":"Chunhua Weng","orcid":"0000-0002-9624-0214","position":7,"is_corresponding":false},{"id":58249,"name":"Wei‐Qi Wei","orcid":null,"position":8,"is_corresponding":false},{"id":935332,"name":"Thomas W J Huizinga","orcid":null,"position":9,"is_corresponding":false},{"id":37194,"name":"Marcel J.T. Reinders","orcid":"0000-0002-1148-1562","position":10,"is_corresponding":false},{"id":218345,"name":"Elizabeth W. Karlson","orcid":"0000-0001-5455-7443","position":11,"is_corresponding":false},{"id":245359,"name":"Erik B. van den Akker","orcid":"0000-0002-7693-0728","position":12,"is_corresponding":false},{"id":350959,"name":"Rachel Knevel","orcid":"0000-0002-7494-3023","position":13,"is_corresponding":false},{"id":934820,"name":"M. 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