This paper is in the following e-collection/theme issue:

Electronic Health Records (1068) Data Science (278) Hypertension Prevention and Treatment (229)

Published on in Vol 8, No 2 (2020): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/14777, first published .
Optimizing Antihypertensive Medication Classification in Electronic Health Record-Based Data: Classification System Development and Methodological Comparison

Optimizing Antihypertensive Medication Classification in Electronic Health Record-Based Data: Classification System Development and Methodological Comparison

Optimizing Antihypertensive Medication Classification in Electronic Health Record-Based Data: Classification System Development and Methodological Comparison

Authors of this article:

Caitrin W McDonough1 Author Orcid Image ;   Steven M Smith1 Author Orcid Image ;   Rhonda M Cooper-DeHoff1, 2 Author Orcid Image ;   William R Hogan3 Author Orcid Image
Article Authors Cited by (10) Tweetations (2) Metrics

Journals

  1. McDonough C, Babcock K, Chucri K, Crawford D, Bian J, Modave F, Cooper‐DeHoff R, Hogan W. Optimizing identification of resistant hypertension: Computable phenotype development and validation. Pharmacoepidemiology and Drug Safety 2020;29(11):1393 View
  2. Rethy L, Feinstein M, Achenbach C, Townsend R, Bress A, Shah S, Cohen J. Antihypertensive Class and Cardiovascular Outcomes in Patients With HIV and Hypertension. Hypertension 2021;77(6):2023 View
  3. Wu J, Napoleone J, Linke S, Noble M, Turken M, Rakotz M, Kirley K, Folk Akers J, Juusola J, Jasik C. Long-Term Results of a Digital Hypertension Self-Management Program: Retrospective Cohort Study. JMIR Cardio 2023;7:e43489 View
  4. Jafari E, Cooper-DeHoff R, Effron M, Hogan W, McDonough C. Characteristics and Predictors of Apparent Treatment-Resistant Hypertension in Real-World Populations Using Electronic Health Record-Based Data. American Journal of Hypertension 2024;37(1):60 View
  5. Waters R, Malecki S, Lail S, Mak D, Saha S, Jung H, Imrit M, Razak F, Verma A. Automated identification of unstandardized medication data: a scalable and flexible data standardization pipeline using RxNorm on GEMINI multicenter hospital data. JAMIA Open 2023;6(3) View
  6. Herzog L, Ilan Ber R, Horowitz-Kugler Z, Rabi Y, Brufman I, Paz Y, Lopez-Jimenez F. Causal Deep Neural Network-Based Model for First-Line Hypertension Management. Mayo Clinic Proceedings: Digital Health 2023;1(4):632 View
  7. Servi H, Korkmaz T, Ayaz F. Anti-inflammatory activity of benidipine hydrochloride in LPS-activated mammalian macrophages. Naunyn-Schmiedeberg's Archives of Pharmacology 2024;397(8):5757 View
  8. Vanderbleek J, Owensby J, McAnnally A, England B, Chen L, Curtis J, Yun H. Classifying Multimorbidity Using Drug Concepts via the Rx‐Risk Comorbidity Index: Methods and Comparative Cross‐Sectional Study. Arthritis Care & Research 2024;76(4):559 View
  9. Jafari E, Blackman M, Karnes J, Van Driest S, Crawford D, Choi L, McDonough C. Using electronic health records for clinical pharmacology research: Challenges and considerations. Clinical and Translational Science 2024;17(7) View
  10. Lu Y, Keeley E, Barrette E, Cooper-DeHoff R, Dhruva S, Gaffney J, Gamble G, Handke B, Huang C, Krumholz H, McDonough C, Schulz W, Shaw K, Smith M, Woodard J, Young P, Ervin K, Ross J. Use of electronic health records to characterize patients with uncontrolled hypertension in two large health system networks. BMC Cardiovascular Disorders 2024;24(1) View