{"doi":"10.1016/j.rpth.2023.100162","title":"Development of a computable phenotype using electronic health records for venous thromboembolism in medical inpatients: the Medical Inpatient Thrombosis and Hemostasis study","abstract":"Background: Accurate and efficient methods to identify venous thromboembolism (VTE) events in hospitalized people are needed to support large-scale studies. Validated computable phenotypes using a specific combination of discrete, searchable elements in electronic health records to identify VTE and distinguish between hospital-acquired (HA)-VTE and present-on-admission (POA)-VTE would greatly facilitate the study of VTE, obviating the need for chart review. Objectives: To develop and validate computable phenotypes for POA- and HA-VTE in adults hospitalized for medical reasons. Methods: The population included admissions to medical services from 2010 to 2019 at an academic medical center. POA-VTE was defined as VTE diagnosed within 24 hours of admission, and HA-VTE as VTE identified more than 24 hours after admission. Using discharge diagnosis codes, present-on-admission flags, imaging procedures, and medication administration records, we iteratively developed computable phenotypes for POA-VTE and HA-VTE. We assessed the performance of the phenotypes using manual chart review and survey methodology. Results: Among 62,468 admissions, 2693 had any VTE diagnosis code. Using survey methodology, 230 records were reviewed to validate the computable phenotypes. Based on the computable phenotypes, the incidence of POA-VTE was 29.4 per 1000 admissions and that of HA-VTE was 3.6 per 1000 admissions. The POA-VTE computable phenotype had positive predictive value and sensitivity of 88.8% (95% CI, 79.8%-94.0%) and 99.1% (95% CI, 94.0%- 99.8%), respectively. Corresponding values for the HA-VTE computable phenotype were 84.2% (95% CI, 60.8%-94.8%) and 72.3% (95% CI, 40.9%-90.8%). Conclusion: We developed computable phenotypes for HA-VTE and POA-VTE with adequate positive predictive value and sensitivity. This phenotype can be used in electronic health record data-based research.","journal":"Research and Practice in Thrombosis and Haemostasis","year":2023,"id":360553,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9501,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1084672,"name":"Katherine Wilkinson","orcid":"0000-0001-6190-735X","position":1,"is_corresponding":false},{"id":725393,"name":"Insu Koh","orcid":"0000-0001-9425-077X","position":2,"is_corresponding":false},{"id":285765,"name":"Ang Li","orcid":"0000-0002-8455-2309","position":3,"is_corresponding":false},{"id":697084,"name":"Janine Warren","orcid":"0000-0002-2408-6000","position":4,"is_corresponding":false},{"id":589986,"name":"Nicholas S. Roetker","orcid":"0000-0001-5386-3289","position":5,"is_corresponding":false},{"id":25020,"name":"Nicholas L. Smith","orcid":"0000-0003-3483-353X","position":6,"is_corresponding":false},{"id":997587,"name":"Christopher Holmes","orcid":"0000-0001-9021-3760","position":7,"is_corresponding":false},{"id":399553,"name":"Timothy B. Plante","orcid":"0000-0001-9992-9597","position":8,"is_corresponding":false},{"id":1084673,"name":"Allen B Repp","orcid":"0000-0001-7513-532X","position":9,"is_corresponding":false},{"id":51219,"name":"Mary Cushman","orcid":"0000-0002-7871-6143","position":10,"is_corresponding":false},{"id":374898,"name":"Neil A. Zakai","orcid":"0000-0001-8824-4410","position":11,"is_corresponding":false},{"id":1084674,"name":"Ryan M. Thomas","orcid":"0000-0001-9251-5543","position":0,"is_corresponding":true}],"reference_count":22,"raw_metadata":null,"created_at":"2026-07-19T01:14:06.433417Z","pmid":"37342252","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}