Use of Electronic Health Records to Characterize Patients with Uncontrolled Hypertension in Two Large Health System Networks.

Autor:	Lu Y; Yale School of Medicine., Keeley EC; University of Florida., Barrette E; Medtronic (United States)., Cooper-DeHoff RM; University of Florida., Dhruva SS; University of California, San Francisco., Gaffney J; Medtronic (United States)., Gamble G; Yale New Haven Hospital., Handke B; Medtronic (United States)., Huang C; Yale School of Medicine., Krumholz H; Yale School of Medicine., Rowe C; University of Florida., Schulz W; Yale New Haven Hospital., Shaw K; University of Florida., Smith M; University of Florida., Woodard J; University of Florida., Young P; Yale New Haven Hospital., Ervin K; National Evaluation System for health Technology Coordinating Center (NESTcc), Medical Device Innovation Consortium., Ross J; Yale School of Medicine.
Jazyk:	angličtina
Zdroj:	Research square [Res Sq] 2024 Feb 15. Date of Electronic Publication: 2024 Feb 15.
DOI:	10.21203/rs.3.rs-3943912/v1
Abstrakt:	Background: Improving hypertension control is a public health priority. However, consistent identification of uncontrolled hypertension using computable definitions in electronic health records (EHR) across health systems remains uncertain. Methods: In this retrospective cohort study, we applied two computable definitions to the EHR data to identify patients with controlled and uncontrolled hypertension and to evaluate differences in characteristics, treatment, and clinical outcomes between these patient populations. We included adult patients (≥ 18 years) with hypertension receiving ambulatory care within Yale-New Haven Health System (YNHHS; a large US health system) and OneFlorida Clinical Research Consortium (OneFlorida; a Clinical Research Network comprised of 16 health systems) between October 2015 and December 2018. We identified patients with controlled and uncontrolled hypertension based on either a single blood pressure (BP) measurement from a randomly selected visit or all BP measurements recorded between hypertension identification and the randomly selected visit). Results: Overall, 253,207 and 182,827 adults at YNHHS and OneFlorida were identified as having hypertension. Of these patients, 83.1% at YNHHS and 76.8% at OneFlorida were identified using ICD-10-CM codes, whereas 16.9% and 23.2%, respectively, were identified using elevated BP measurements (≥ 140/90 mmHg). Uncontrolled hypertension was observed among 32.5% and 43.7% of patients at YNHHS and OneFlorida, respectively. Uncontrolled hypertension was disproportionately higher among Black patients when compared with White patients (38.9% versus 31.5% in YNHHS; p < 0.001; 49.7% versus 41.2% in OneFlorida; p < 0.001). Medication prescription for hypertension management was more common in patients with uncontrolled hypertension when compared with those with controlled hypertension (overall treatment rate: 39.3% versus 37.3% in YNHHS; p = 0.04; 42.2% versus 34.8% in OneFlorida; p < 0.001). Patients with controlled and uncontrolled hypertension had similar rates of short-term (at 3 and 6 months) and long-term (at 12 and 24 months) clinical outcomes. The two computable definitions generated consistent results. Conclusions: Our findings illustrate the potential of leveraging EHR data, employing computable definitions, to conduct effective digital population surveillance in the realm of hypertension management. Competing Interests: Competing Interest: Yuan Lu received support from the Sentara Research Foundation, the National Heart, Lung, and Blood Institute of the National Institutes of Health (under awards R01HL69954 and R01HL169171), and the Patient-Centered Outcomes Research Institute (under award HM-2022C2–28354) outside of the submitted work. Sanket S. Dhruva receives research funding from the National Evaluation System for health Technology Coordinating Center (NESTcc), The Greenwall Foundation, Arnold Ventures and the National Institute for Health Care Management (NIHCM). In the past 36 months, He has also received funding from the Food and Drug Administration and the National Heart, Lung, and Blood Institute of the National Institutes of Health (K12HL138046). Dr. Dhruva also reports serving on the Institute for Clinical and Economic Review (ICER) California Technology Assessment Forum. Wade Schulz collaborates with the National Center for Cardiovascular Diseases in Beijing, is a technical consultant to HugoHealth, a personal health information platform, and co-founder of Refactor Health, an AI-augmented data management platform for healthcare, as well as a consultant for Interpace Diagnostics Group, a molecular diagnostics company. In the past three years, Harlan Krumholz received expenses and/or personal fees from Element Science, Eyedentify, and F-Prime. He is a co-founder of Hugo Health, Refactor Health, and Ensight-AI. He is the co-editor of Journal Watch: Cardiology of the Massachusetts Medical Society and is a section editor of UpToDate. He is associated with contracts, through Yale New Haven Hospital, from the Centers for Medicare & Medicaid Services and through Yale University from Janssen, Johnson & Johnson Consumer, and Pfizer. Joseph S. Ross currently receives research support through Yale University from Johnson and Johnson to develop methods of clinical trial data sharing, from the Medical Device Innovation Consortium (MDIC) as part of NEST, from the FDA for the Yale-Mayo Clinic Center for Excellence in Regulatory Science and Innovation (CERSI) program (U01FD005938), from the Agency for Healthcare Research and Quality (R01HS022882), from the NHLBI of the NIH (R01HS025164, R01HL144644) and from the Laura and John Arnold Foundation to establish the Good Pharma Scorecard at Bioethics International; in addition, Dr. Ross is an expert witness at the request of Relator’s attorneys, the Greene Law Firm, in a qui tam suit alleging violations of the False Claims Act and Anti-Kickback Statute against Biogen Inc. Eric Barrette, Jenny Gaffney, and Bonnie Handke are employees of Medtronic, Inc. All other coauthors have no conflict of interests.
Databáze:	MEDLINE
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