{"doi":"10.1093/ajh/hpad081","title":"Leveraging Electronic Health Records to Construct a Phenotype for Hypertension Surveillance in the United States","abstract":"BACKGROUND: Hypertension is an important risk factor for cardiovascular diseases. Electronic health records (EHRs) may augment chronic disease surveillance. We aimed to develop an electronic phenotype (e-phenotype) for hypertension surveillance. METHODS: We included 11,031,368 eligible adults from the 2019 IQVIA Ambulatory Electronic Medical Records-US (AEMR-US) dataset. We identified hypertension using three criteria, alone or in combination: diagnosis codes, blood pressure (BP) measurements, and antihypertensive medications. We compared AEMR-US estimates of hypertension prevalence and control against those from the National Health and Nutrition Examination Survey (NHANES) 2017-18, which defined hypertension as BP ≥130/80 mm Hg or ≥1 antihypertensive medication. RESULTS: The study population had a mean (SD) age of 52.3 (6.7) years, and 56.7% were women. The selected three-criteria e-phenotype (≥1 diagnosis code, ≥2 BP measurements of ≥130/80 mm Hg, or ≥1 antihypertensive medication) yielded similar trends in hypertension prevalence as NHANES: 42.2% (AEMR-US) vs. 44.9% (NHANES) overall, 39.0% vs. 38.7% among women, and 46.5% vs. 50.9% among men. The pattern of age-related increase in hypertension prevalence was similar between AEMR-US and NHANES. The prevalence of hypertension control in AEMR-US was 31.5% using the three-criteria e-phenotype, which was higher than NHANES (14.5%). CONCLUSIONS: Using an EHR dataset of 11 million adults, we constructed a hypertension e-phenotype using three criteria, which can be used for surveillance of hypertension prevalence and control.","journal":"American Journal of Hypertension","year":2023,"id":340178,"datarank":0.4755227971174147,"base_score":2.833213344056216,"endowment":2.833213344056216,"self_citation_contribution":0.42498200160843247,"citation_network_contribution":0.05054079550898222,"self_endowment_contribution":0.42498200160843247,"citer_contribution":0.05054079550898222,"corpus_percentile":59.897888141100026,"corpus_rank":5185,"citation_count":16,"citer_count":6,"citers_with_citation_signal":3,"citers_with_endowment":3,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.6753,"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":430528,"name":"So-Youn Park","orcid":"0000-0003-1862-6370","position":1,"is_corresponding":false},{"id":430322,"name":"Elena V. Kuklina","orcid":"0000-0002-9686-6495","position":2,"is_corresponding":false},{"id":710037,"name":"Nicole L. Therrien","orcid":"0000-0001-7306-0280","position":3,"is_corresponding":false},{"id":410877,"name":"Elizabeth A. Lundeen","orcid":"0000-0002-4249-8455","position":4,"is_corresponding":false},{"id":307075,"name":"Hilary K. Wall","orcid":"0000-0001-6088-0706","position":5,"is_corresponding":false},{"id":1075164,"name":"Katrice Lampley","orcid":null,"position":6,"is_corresponding":false},{"id":410876,"name":"Lyudmyla Kompaniyets","orcid":"0000-0003-0634-689X","position":7,"is_corresponding":false},{"id":1075165,"name":"Samantha L. Pierce","orcid":null,"position":8,"is_corresponding":false},{"id":307077,"name":"Laurence Sperling","orcid":"0000-0001-9417-6370","position":9,"is_corresponding":false},{"id":230978,"name":"Sandra L. Jackson","orcid":"0000-0003-4810-0572","position":10,"is_corresponding":false},{"id":442065,"name":"Siran He","orcid":"0000-0002-0452-355X","position":0,"is_corresponding":true}],"reference_count":30,"raw_metadata":null,"created_at":"2026-07-19T01:10:54.145367Z","pmid":"37696605","pmcid":"PMC10898654","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":[]}