Development and evaluation of an IoT-based hypertension surveillance system in community health settings: a mixed-methods quasi-experimental study protocol

在社区卫生环境中开发和评估基于物联网的高血压监测系统:一项混合方法准实验研究方案

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Abstract

BACKGROUND: Hypertension, affecting over 1.3 billion people globally, poses a significant public health challenge. Despite its widespread impact, hypertension management in primary healthcare settings faces challenges such as fragmented data collection, low patient adherence, and insufficient real-time monitoring. This study evaluates the effectiveness, cost-effectiveness, and implementation process of an Internet of Things (IoT)-based hypertension surveillance system designed to address these gaps in community health settings. METHODS: This pragmatic quasi-experimental trial involves 2,000 hypertensive patients managed under family doctor contract services in Beijing, China. The intervention group (n = 1,000) utilizes an IoT-based hypertension monitoring platform, which integrates smart blood pressure devices and real-time data transmission for dynamic tracking and management. The control group (n = 1,000) receives standard care without IoT integration. The primary outcome is blood pressure control rate, while secondary outcomes encompass standardized management rate, measurement completion rate, referral rates and biomarker profiles. Cost-effectiveness is evaluated using administrative data on healthcare utilization and intervention costs. Qualitative data, collected through patient surveys and focus groups with healthcare providers, explores implementation barriers and user experiences. DISCUSSION: The study aims to provide comprehensive evidence on the clinical effectiveness, cost-effectiveness, and implementation process of IoT-based hypertension management in primary care. By combining quantitative and qualitative methods, it seeks to understand how the intervention works in real-world settings and identify facilitators and barriers to its implementation. The findings could inform policy decisions and optimize resource allocation for chronic disease management in primary care. TRIAL REGISTRATION: ChiCTR, ChiCTR2500103556.Registered 30 May 2025. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-025-13562-3.

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