Cargando…

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

BACKGROUND: Computable phenotypes have the ability to utilize data within the electronic health record (EHR) to identify patients with certain characteristics. Many computable phenotypes rely on multiple types of data within the EHR including prescription drug information. Hypertension (HTN)-related...

Descripción completa

Detalles Bibliográficos
Autores principales:	McDonough, Caitrin W, Smith, Steven M, Cooper-DeHoff, Rhonda M, Hogan, William R
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications 2020
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068459/ https://www.ncbi.nlm.nih.gov/pubmed/32130152 http://dx.doi.org/10.2196/14777

Ejemplares similares

2246: Characterization of resistant hypertension in a statewide electronic health record-based database (OneFlorida)
por: McDonough, Caitrin W., et al.
Publicado: (2018)

Genome-Wide Association Study Identifies Pharmacogenomic Loci Linked with Specific Antihypertensive Drug Treatment and New-Onset Diabetes
por: Chang, Shin-Wen, et al.
Publicado: (2016)

Influence of Genetic West African Ancestry on Metabolomics among Hypertensive Patients
por: Mehanna, Mai, et al.
Publicado: (2022)

Use of Electronic Health Records to Characterize Patients with Uncontrolled Hypertension in Two Large Health System Networks
por: Lu, Yuan, et al.
Publicado: (2023)

Metabolomics Signature of Plasma Renin Activity and Linkage with Blood Pressure Response to Beta Blockers and Thiazide Diuretics in Hypertensive European American Patients
por: Mehanna, Mai, et al.
Publicado: (2021)

Genetic Variants Associated With Uncontrolled Blood Pressure on Thiazide Diuretic/β‐Blocker Combination Therapy in the PEAR (Pharmacogenomic Evaluation of Antihypertensive Responses) and INVEST (International Verapamil‐SR Trandolapril Study) Trials
por: Magvanjav, Oyunbileg, et al.
Publicado: (2017)

Antihypertensive Drug Class Interactions and Risk for Incident Diabetes: A Nested Case–Control Study
por: Cooper‐DeHoff, Rhonda M., et al.
Publicado: (2013)

Hypertension in Florida: Data From the OneFlorida Clinical Data Research Network
por: Smith, Steven M., et al.
Publicado: (2018)

Atenolol Induced HDL-C Change in the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) Study
por: McDonough, Caitrin W., et al.
Publicado: (2013)

Initial Antihypertensive Regimens in Newly Treated Patients: Real World Evidence From the OneFlorida+ Clinical Research Network
por: Smith, Steven M., et al.
Publicado: (2022)

Genome Wide Analysis Approach Suggests Chromosome 2 Locus to be Associated with Thiazide and Thiazide Like-Diuretics Blood Pressure Response
por: Singh, Sonal, et al.
Publicado: (2019)

Medication Adherence—Still the Holy Grail
por: Cooper‐DeHoff, Rhonda M., et al.
Publicado: (2023)

Genome‐Wide Meta‐Analysis of Blood Pressure Response to β(1)‐Blockers: Results From ICAPS (International Consortium of Antihypertensive Pharmacogenomics Studies)
por: Singh, Sonal, et al.
Publicado: (2019)

Genomic Association Analysis Reveals Variants Associated With Blood Pressure Response to Beta‐Blockers in European Americans
por: Singh, Sonal, et al.
Publicado: (2019)

Comparing marginal structural models to standard methods for estimating treatment effects of antihypertensive combination therapy
por: Gerhard, Tobias, et al.
Publicado: (2012)

Lack of association of the HMGA1 IVS5-13insC variant with type 2 diabetes in an ethnically diverse hypertensive case control cohort
por: Karnes, Jason H, et al.
Publicado: (2013)

Whole Transcriptome Sequencing Analyses Reveal Molecular Markers of Blood Pressure Response to Thiazide Diuretics
por: Sá, Ana Caroline C., et al.
Publicado: (2017)

Power to identify a genetic predictor of antihypertensive drug response using different methods to measure blood pressure response
por: Turner, Stephen T, et al.
Publicado: (2012)

Genome-wide study of resistant hypertension identified from electronic health records
por: Dumitrescu, Logan, et al.
Publicado: (2017)

Large‐Scale Gene‐Centric Analysis Identifies Polymorphisms for Resistant Hypertension
por: Fontana, Vanessa, et al.
Publicado: (2014)

Blood pressure signature genes and blood pressure response to thiazide diuretics: results from the PEAR and PEAR-2 studies
por: Sá, Ana Caroline C., et al.
Publicado: (2018)

Pairwise comparison of hydrochlorothiazide and chlorthalidone responses among hypertensive patients
por: Chekka, Lakshmi Manasa S., et al.
Publicado: (2022)

Pneumonia and Pulmonary Thromboembolism Classification Using Electronic Health Records
por: Siordia-Millán, Sinhue, et al.
Publicado: (2022)

In Reply: Probability of Reduced Follow-up Health Care Visits for Controlled Hypertensive Patients
por: Chamberlain, Alanna M., et al.
Publicado: (2023)

Optimizing Precision of Hypertension Care to Maximize Blood Pressure Control: A Pilot Study Utilizing a Smartphone App to Incorporate Plasma Renin Activity Testing
por: Mehanna, Mai, et al.
Publicado: (2020)

Automated Classification of Alcohol Use by Text Mining of Electronic Medical Records
por: Lix, Lisa, et al.
Publicado: (2017)

Diabetes-related Bias in Electronic Health Records and International Classification of Diseases
por: Zilbermint, Mihail
Publicado: (2022)

Genetic Contributors of Efficacy and Adverse Metabolic Effects of Chlorthalidone in African Americans from the Genetics of Hypertension Associated Treatments (GenHAT) Study
por: Armstrong, Nicole D., et al.
Publicado: (2022)

Association of 1-Year Blood Pressure Variability With Long-term Mortality Among Adults With Coronary Artery Disease: A Post Hoc Analysis of a Randomized Clinical Trial
por: Dasa, Osama, et al.
Publicado: (2021)

Ontology-driven weak supervision for clinical entity classification in electronic health records
por: Fries, Jason A., et al.
Publicado: (2020)

Ontology-driven weak supervision for clinical entity classification in electronic health records
por: Fries, Jason A., et al.
Publicado: (2021)

Multi-Institutional Implementation of Clinical Decision Support for APOL1, NAT2, and YEATS4 Genotyping in Antihypertensive Management
por: Schneider, Thomas M., et al.
Publicado: (2021)

International Classification of Diseases, Tenth Revision, Clinical Modification social determinants of health codes are poorly used in electronic health records
por: Guo, Yi, et al.
Publicado: (2020)

Pharmacogenomics of Hypertension: A Genome‐Wide, Placebo‐Controlled Cross‐Over Study, Using Four Classes of Antihypertensive Drugs
por: Hiltunen, Timo P., et al.
Publicado: (2015)

Records classification: information, systems, context
por: Mokhtar, Umi Asma', et al.
Publicado: (2017)

Classification of Mediterranean hedgerows: A methodological approximation
por: Alvarez, Fernando Allende, et al.
Publicado: (2021)

Melatonin Pathway and Atenolol‐Related Glucose Dysregulation: Is There a Correlation?
por: Chang, SW, et al.
Publicado: (2016)

Association of Chromosome 12 locus with antihypertensive response to hydrochlorothiazide may involve differential YEATS4 expression
por: Duarte, Julio D., et al.
Publicado: (2012)

Predicting the outcome for COVID-19 patients by applying time series classification to electronic health records
por: Rodrigues, Davi Silva, et al.
Publicado: (2022)

Discovering and identifying New York heart association classification from electronic health records
por: Zhang, Rui, et al.
Publicado: (2018)

Cannot write session to /tmp/vufind_sessions/sess_70sm1bk7riittajh2rjde8rssl