P038 DIAGNOSIS AND TREATMENT OF HYPERTENSION BY NON-PHYSICIAN HEALTHCARE WORKERS UNDER REMOTE SUPERVISION OF PHYSICIANS IS FEASIBLE AND EFFECTIVE IN RURAL BANGLADESH: PRELIMINARY RESULTS FROM CB-HEARTS PILOT STUDY

Background and Objective: In rural Bangladesh, there are multiple barriers to receiving treatment for hypertension, including distant healthcare facilities [Upazila Health Complex (UHC)] and inadequate numbers of physicians. This pilot aimed to design and assess the feasibility of implementing a community-based (CB) WHO HEARTS package involving non-physician health workers (Community Healthcare Providers [CHCP]) for diagnosing and treating hypertension who are remotely supervised, using telemedicine, by a UHC physician. Methods We are conducting this single-arm pilot study in four Community Clinics (CC) in rural Bangladesh. We included patients with untreated hypertension (blood pressure [BP] 140-180/90-110 mmHg). We excluded patients with diabetes, pregnancy, and cardiovascular and kidney diseases. The CB-HEARTS package intervention components were 1) simplified treatment protocol, 2) reliable medication supply, 3) team-based care, 4) standardized follow-up, and 5) a mobile app to track patients’ BP control. After assessing eligibility, CHCPs from the CC communicated with designated physicians at UHC to confirm hypertension diagnosis and to start anti-hypertensive medications in the CC. Patients with BP controlled (<140/90 mmHg) during follow-up were provided a refill for 3 months. Patients with complications or uncontrolled BP, even after the maximum allowable dose, were referred to the UHC. Outcomes were enrollment and follow-up rates (primary), BP change from baseline and hypertension control (secondary). Results: We screened 4,220 adults, of whom 531 were eligible for the study and 220 were enrolled (Table; mean age 55.9 years, 75.9% female). Enrollment (41.4%) and follow-up within 3 months of enrollment (93.6%) rates were high. Mean systolic and diastolic BP were 153 and 92 mmHg at enrollment, respectively. BP was lowered by 31 mmHg systolic and 15 mmHg diastolic after a mean of 84 days follow-up. After this follow-up duration, 90% of participants had their BP controlled. Conclusions: This pilot study provides evidence that hypertension care provided by non-physician health workers under remote supervision of physicians in rural Bangladesh is feasible and may effectively lower BP and improve hypertension control. Table: Participant screening, enrollment, and follow-up

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Journal
Journal of Hypertension
Published
2024-09-01
DOI
https://doi.org/10.1097/01.hjh.0001063024.54901.f0
Citations
1
Primary Topic
Artificial Intelligence in Healthcare
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article
Field-Weighted Citation Impact
0.71
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article

P038 DIAGNOSIS AND TREATMENT OF HYPERTENSION BY NON-PHYSICIAN HEALTHCARE WORKERS UNDER REMOTE SUPERVISION OF PHYSICIANS IS FEASIBLE AND EFFECTIVE IN RURAL BANGLADESH: PRELIMINARY RESULTS FROM CB-HEARTS PILOT STUDY

Ahmad Khairul Abrar, Mahfuzur Rahman Bhuiyan, Lawrence J. Appel, Shamim Jubayer et al.
1 citations
Journal of Hypertension
Artificial Intelligence in Healthcare
0.71
article

P038 DIAGNOSIS AND TREATMENT OF HYPERTENSION BY NON-PHYSICIAN HEALTHCARE WORKERS UNDER REMOTE SUPERVISION OF PHYSICIANS IS FEASIBLE AND EFFECTIVE IN RURAL BANGLADESH: PRELIMINARY RESULTS FROM CB-HEARTS PILOT STUDY

Ahmad Khairul Abrar, Mahfuzur Rahman Bhuiyan, Lawrence J. Appel, Shamim Jubayer, Md Abbas Ibn Karim, Jubaida Akhtar, Sohel Reza Choudhury, Kathryn Foti, Kunihiro Matsushita, Hairong Liu, Mohammad Abdullah Al Mamun, Noor Nabi Sayem
article en
1 citations

Abstract

Background and Objective: In rural Bangladesh, there are multiple barriers to receiving treatment for hypertension, including distant healthcare facilities [Upazila Health Complex (UHC)] and inadequate numbers of physicians. This pilot aimed to design and assess the feasibility of implementing a community-based (CB) WHO HEARTS package involving non-physician health workers (Community Healthcare Providers [CHCP]) for diagnosing and treating hypertension who are remotely supervised, using telemedicine, by a UHC physician. Methods We are conducting this single-arm pilot study in four Community Clinics (CC) in rural Bangladesh. We included patients with untreated hypertension (blood pressure [BP] 140-180/90-110 mmHg). We excluded patients with diabetes, pregnancy, and cardiovascular and kidney diseases. The CB-HEARTS package intervention components were 1) simplified treatment protocol, 2) reliable medication supply, 3) team-based care, 4) standardized follow-up, and 5) a mobile app to track patients’ BP control. After assessing eligibility, CHCPs from the CC communicated with designated physicians at UHC to confirm hypertension diagnosis and to start anti-hypertensive medications in the CC. Patients with BP controlled (<140/90 mmHg) during follow-up were provided a refill for 3 months. Patients with complications or uncontrolled BP, even after the maximum allowable dose, were referred to the UHC. Outcomes were enrollment and follow-up rates (primary), BP change from baseline and hypertension control (secondary). Results: We screened 4,220 adults, of whom 531 were eligible for the study and 220 were enrolled (Table; mean age 55.9 years, 75.9% female). Enrollment (41.4%) and follow-up within 3 months of enrollment (93.6%) rates were high. Mean systolic and diastolic BP were 153 and 92 mmHg at enrollment, respectively. BP was lowered by 31 mmHg systolic and 15 mmHg diastolic after a mean of 84 days follow-up. After this follow-up duration, 90% of participants had their BP controlled. Conclusions: This pilot study provides evidence that hypertension care provided by non-physician health workers under remote supervision of physicians in rural Bangladesh is feasible and may effectively lower BP and improve hypertension control. Table: Participant screening, enrollment, and follow-up

Journal of HypertensionVol. 42(Suppl 3)
Johns Hopkins University (US), University of Alabama at Birmingham (US), National Heart Foundation Hospital & Research Institute (BD)
Openalex Percentile: Top 22%
Artificial Intelligence in Healthcare
0.71
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