Key result
mHealth-assisted CHWs achieve substantial agreement with physicians in diagnosing hypertension.
Why the study?
Does assessment by a Community Health Worker aided by an mHealth application accurately diagnose hypertension compared to physician evaluation in adults in rural Guatemala?
Cross-Sectional (n=359)
Blinded
No
Does assessment by a Community Health Worker aided by an mHealth application accurately diagnose hypertension compared to physician evaluation in adults in rural Guatemala?
Community health workers using an mHealth application can accurately screen for hypertension in low-resource settings, demonstrating high agreement with physician diagnosis.
May support CHW-led hypertension screening with mHealth in low-resource settings; hypothesis-generating and requires prospective validation before adoption.
Background: Hypertension is a leading global cause of morbidity and mortality and is increasing in low- and middle-income countries, where unawareness of hypertension is a primary obstacle to management. Community health workers (CHWs) in combination with mobile health (mHealth) tools are increasingly used in LMIC health systems to strengthen primary care infrastructure. In this study, we applied this care model to hypertension in rural Guatemala by comparing the accuracy of CHWs equipped with an mHealth clinical decision support application in diagnosing hypertension to concurrent physician evaluation. Methods: We performed a prospective diagnostic accuracy study in which adults from rural Guatemalan communities were assessed independently by a CHW aided by a mHealth application and a physician. Assessment included medical history; measurement of blood pressure, height and weight; and determination of hypertension status. CHW-physician agreement on hypertension status and past medical history elements was assessed by Kappa analysis and proportional agreement, with a priori thresholds of Kappa = 0.61 and agreement of 90%. Agreement on patient measurements was evaluated using Bland-Altman and regression analyses. Results: Of 359 participants enrolled, 47 (13%) were confirmed to have hypertension and another 11 (3%) had possible hypertension. CHW-physician agreement was high for hypertension diagnosis, with Kappa = 0.8 (95% CI = 0.72, 0.88) and overall agreement 92.8% (95% CI = 90.1%, 95.4%). Bland-Altman analysis showed small biases toward lower systolic blood pressure, higher height, and lower BMI measurements by CHWs. Most patient history characteristics showed moderate to almost perfect (Kappa: 0.41–1) agreement between physicians and CHWs. Conclusions: In this study based in rural Guatemala, CHWs using a mHealth clinical decision support application were found to screen adult patients for hypertension with similar accuracy to a physician. This approach could be adapted to other low-resource settings to reduce the burden of undiagnosed and untreated hypertension.
No takes yet. Share an insight, caveat, or question.
Duffy et al. (2025) conducted a cross-sectional in Hypertension (n=359). Community health worker diagnosis aided by an mHealth application vs. Physician diagnosis was evaluated on Agreement between CHW and physician on hypertension status (weighted Kappa 0.8, 95% CI 0.72-0.88). Community health workers using an mHealth clinical decision support application accurately diagnosed hypertension, demonstrating substantial agreement with concurrent physician evaluation (weighted Kappa 0.8).
Synapse has enriched 5 related papers. Consider them for comparative context: