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Feasibility study of a novel mHealth clinical decision support application to enable community health workers to manage hypertension in rural Guatemala

Bibliographic Data

ID23311646
AuthorsSean Duffy (0000-0002-1993-7835, University of Wisconsin School of Medicine and Public Health, Department of Family Medicine and Community Health, Madison, Wisconsin, USA), Alejandro Chavez (0000-0001-5626-7140, University of California, San Francisco), Ian Stanley Arthur (University of Wisconsin School of Medicine and Public Health, Department of Family Medicine and Community Health, Madison, Wisconsin, USA), Gabriella Lucia Ortiz (University of Wisconsin–Madison), Alvaro Bermudez-Cañete (Stanford University), Pablo Nuñez-Perez (Stanford University), Elizabeth White (0000-0001-5090-1729, Insall Scott Kelly Institute), Valerie Aguilar (Medical College of Wisconsin), Juan Aguirre (Northwestern University), Do Dang (NYU Langone Health), Celina Sonia Perez Abaj (Roosevelt Hospital), Yoselin Emelina Letona López (Hospital Obras Sociales Monseñor Gregorio Schaffer, San Lucas Tolimán, Sololá, Guatemala), Y López (0000-0002-0826-0021, Roosevelt Hospital), Rafael Tun (Roosevelt Hospital), Taryn M Valley (0000-0003-2866-9518, University of Wisconsin–Madison)
Year2026
Volume16
Pages04232-04232
Publication date2026-07-31
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Global Health (JOURNAL)
Journal identifiersISSN: 2047-2978 • E-ISSN: 2047-2986
PublisherInternational Society of Global Health (PUBLISHER • GB)
DOI10.7189/jogh.16.04232
PMID42533611
OpenAlexW7171961683
LanguageEN
References cited37

Background: Hypertension is a leading global cause of morbidity and mortality, especially in low- and middle-income countries, where low healthcare access limits diagnosis and treatment. Community health workers (CHWs) supported by mobile health (mHealth) clinical decision support (CDS) tools may help. This study evaluated the feasibility of CHW-led hypertension management using an mHealth CDS application in rural Guatemala. Methods: We conducted a single-group feasibility study in San Lucas Tolimán, Guatemala. Trained CHWs assisted by a CommCare-based CDS application provided direct patient care. Application algorithms were based on World Health Organization guidelines and assisted with medication titration, lifestyle counselling, and physician consultation. Adults (≥18 years) with diagnosed hypertension were followed monthly for six months. The primary feasibility outcome was prescribing agreement between CHWs and supervising physicians with application of antihypertensive recommendations (minimum acceptable agreement was 90%). Primary clinical outcomes were changes in systolic (SBP) and diastolic (DBP) blood pressure. Secondary outcomes included retention, patient satisfaction, and safety. Results: In total 32 participants were enrolled and 30 (93.8%) completed six-month follow-up, with 96.4% of possible visits completed. CHW-physician agreement with application recommendations was 98.9%. The median decrease in SBP was 7.5 mm Hg (95% confidence interval (CI) = 1.0, 12.0), and the mean decrease in DBP was 3.1 mm Hg (95% CI = 0.1, 6.1). The proportion of patients with controlled SBP (<140 mm Hg) increased from 66.7% to 76.7% (P = 0.505). A total of 11 application errors (5.0% of 217 visits) occurred, none of which resulted in adverse events. Only three patients experienced significant adverse events, none of which required hospitalisation. Patient satisfaction remained high. Conclusions: In this pilot, CHWs supported by an mHealth CDS application safely managed hypertension with high physician agreement, patient retention, and blood pressure improvement. These findings demonstrate the feasibility of CHW task-sharing hypertension management in low-resource settings and support evaluation of this approach in larger trials. Registration: ClinicalTrials.gov: NCT05479097.

Adverse effect · Blood pressure · Clinical decision support system · Community health · Community health workers · Confidence interval · mHealth · Primary care · Primary health care · Blood Pressure and Hypertension Studies · Electronic Health Records Systems · Mobile Health and mHealth Applications

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