A Multisite Electronic Health Record Integrated Remote Monitoring Intervention for Hypertension Improvement: Protocol for a Randomized Pragmatic Comparative Effectiveness Trial.

EHR RCT blood pressure electronic health record hypertension hypertensive improvement science monitor monitoring randomized controlled trial remote blood pressure monitoring

Journal

JMIR research protocols
ISSN: 1929-0748
Titre abrégé: JMIR Res Protoc
Pays: Canada
ID NLM: 101599504

Informations de publication

Date de publication:
30 Oct 2023
Historique:
received: 12 04 2023
accepted: 19 07 2023
revised: 14 07 2023
medline: 30 10 2023
pubmed: 30 10 2023
entrez: 30 10 2023
Statut: epublish

Résumé

Hypertension is a major contributor to various adverse health outcomes. Although previous studies have shown the benefits of home blood pressure (BP) monitoring over office-based measurements, there is limited evidence comparing the effectiveness of whether a BP monitor integrated into the electronic health record is superior to a nonintegrated BP monitor. In this paper, we describe the protocol for a pragmatic multisite implementation of a quality improvement initiative directly comparing integrated to nonintegrated BP monitors for hypertension improvement. We will conduct a randomized, comparative effectiveness trial at 3 large academic health centers across California. The 3 sites will enroll a total of 660 participants (approximately n=220 per site), with 330 in the integrated BP monitor arm and 330 in the nonintegrated BP control arm. The primary outcome of this study will be the absolute difference in systolic BP in mm Hg from enrollment to 6 months. Secondary outcome measures include binary measures of hypertension (controlled vs uncontrolled), hypertension-related health complications, hospitalizations, and death. The list of possible participants will be generated from a central data warehouse. Randomization will occur after enrollment in the study. Participants will use their assigned BP monitor and join site-specific hypertension interventions. Cross-site learning will occur at regular all-site meetings facilitated by the University of California, Los Angeles Value-Based Care Research Consortium. A pre- and poststudy questionnaire will be conducted to further evaluate participants' perspectives regarding their BP monitor. Linear mixed effects models will be used to compare the primary outcome measure between study arms. Mixed effects logistic regression models will be used to compare secondary outcome measures between study arms. The study will start enrolling participants in the second quarter of 2023 and will be completed by the first half of 2024. Results will be published by the end of 2024. This pragmatic trial will contribute to the growing field of chronic care management using remote monitoring by answering whether a hypertension intervention coupled with an electronic health record integrated home BP monitor improves patients' hypertension better than a hypertension intervention with a nonintegrated BP monitor. The outcomes of this study may help health system decision makers determine whether to invest in integrated BP monitors for vulnerable patient populations. ClinicalTrials.gov NCT05390502; clinicaltrials.gov/study/NCT05390502. PRR1-10.2196/45915.

Sections du résumé

BACKGROUND BACKGROUND
Hypertension is a major contributor to various adverse health outcomes. Although previous studies have shown the benefits of home blood pressure (BP) monitoring over office-based measurements, there is limited evidence comparing the effectiveness of whether a BP monitor integrated into the electronic health record is superior to a nonintegrated BP monitor.
OBJECTIVE OBJECTIVE
In this paper, we describe the protocol for a pragmatic multisite implementation of a quality improvement initiative directly comparing integrated to nonintegrated BP monitors for hypertension improvement.
METHODS METHODS
We will conduct a randomized, comparative effectiveness trial at 3 large academic health centers across California. The 3 sites will enroll a total of 660 participants (approximately n=220 per site), with 330 in the integrated BP monitor arm and 330 in the nonintegrated BP control arm. The primary outcome of this study will be the absolute difference in systolic BP in mm Hg from enrollment to 6 months. Secondary outcome measures include binary measures of hypertension (controlled vs uncontrolled), hypertension-related health complications, hospitalizations, and death. The list of possible participants will be generated from a central data warehouse. Randomization will occur after enrollment in the study. Participants will use their assigned BP monitor and join site-specific hypertension interventions. Cross-site learning will occur at regular all-site meetings facilitated by the University of California, Los Angeles Value-Based Care Research Consortium. A pre- and poststudy questionnaire will be conducted to further evaluate participants' perspectives regarding their BP monitor. Linear mixed effects models will be used to compare the primary outcome measure between study arms. Mixed effects logistic regression models will be used to compare secondary outcome measures between study arms.
RESULTS RESULTS
The study will start enrolling participants in the second quarter of 2023 and will be completed by the first half of 2024. Results will be published by the end of 2024.
CONCLUSIONS CONCLUSIONS
This pragmatic trial will contribute to the growing field of chronic care management using remote monitoring by answering whether a hypertension intervention coupled with an electronic health record integrated home BP monitor improves patients' hypertension better than a hypertension intervention with a nonintegrated BP monitor. The outcomes of this study may help health system decision makers determine whether to invest in integrated BP monitors for vulnerable patient populations.
TRIAL REGISTRATION BACKGROUND
ClinicalTrials.gov NCT05390502; clinicaltrials.gov/study/NCT05390502.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) UNASSIGNED
PRR1-10.2196/45915.

Identifiants

pubmed: 37902819
pii: v12i1e45915
doi: 10.2196/45915
pmc: PMC10644190
doi:

Banques de données

ClinicalTrials.gov
['NCT05390502']

Types de publication

Journal Article

Langues

eng

Pagination

e45915

Subventions

Organisme : NIA NIH HHS
ID : K24 AG047899
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001881
Pays : United States

Informations de copyright

©David R Lee, Matthew Chenoweth, Linh H Chuong, Chad W Villaflores, Miguel Cuevas, Sitaram Vangala, Jeff Borenstein, Hannah Kwak, Chidinma Chima-Melton, Maria Han, Samuel A Skootsky, Therese Chan Tack, Linda Branagan, Heather Martin, Reshma Gupta, Linda Phan, Michael A Sanchez, Mina M Malaak, Anna Dermenchyan, Kandyce N Pearson, Marine Altunyan, Peter F Barakat, Ray Pablo, Catherine Sarkisian. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 30.10.2023.

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Auteurs

David R Lee (DR)

Division of Geriatrics, University of California, Los Angeles, Los Angeles, CA, United States.
Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.

Matthew Chenoweth (M)

Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.

Linh H Chuong (LH)

Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.

Chad W Villaflores (CW)

Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.

Miguel Cuevas (M)

Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States.

Sitaram Vangala (S)

Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.

Jeff Borenstein (J)

Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.

Hannah Kwak (H)

Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.

Chidinma Chima-Melton (C)

Division of Pulmonary and Critical Care Medicine, University of California, Los Angeles, Los Angeles, CA, United States.

Maria Han (M)

Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.

Samuel A Skootsky (SA)

Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
University of California Health, Oakland, CA, United States.

Therese Chan Tack (T)

Division of General Internal Medicine, University of California, San Francisco, San Francisco, CA, United States.

Linda Branagan (L)

Telehealth Resource Center, University of California, San Francisco, San Francisco, CA, United States.

Heather Martin (H)

Department of Pharmacy, University of California Davis Health, Davis, CA, United States.

Reshma Gupta (R)

Department of Internal Medicine, University of California, Davis Health, Sacramento, CA, United States.

Linda Phan (L)

Department of Pharmacy, University of California Davis Health, Davis, CA, United States.

Michael A Sanchez (MA)

University of California Office of the President, Oakland, CA, United States.

Mina M Malaak (MM)

Ambulatory and Community Practices, University of California, Los Angeles, Los Angeles, CA, United States.

Anna Dermenchyan (A)

Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.

Kandyce N Pearson (KN)

Ambulatory and Community Practices, University of California, Los Angeles, Los Angeles, CA, United States.

Marine Altunyan (M)

Ambulatory and Community Practices, University of California, Los Angeles, Los Angeles, CA, United States.

Peter F Barakat (PF)

Ambulatory and Community Practices, University of California, Los Angeles, Los Angeles, CA, United States.

Ray Pablo (R)

University of California Health Data Warehouse, University of California Health, Irvine, CA, United States.

Catherine Sarkisian (C)

Department of Medicine, University of California, Los Angeles, Los Angeles, CA, United States.
Geriatrics Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States.

Classifications MeSH