Evidence mapPaperPMID 41126161Full record

ArticleBMC health services research2025

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

Wen Zheng, Li-Li Hua, Jie Tan, Jing-Shi Zhang, Yan Liang, Jing Pan, Ming-Xia Yu, Jing-Wen Gan

Abstract read
In one paragraph

Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Wen ZhengLiyuan Community Health Service Center, Tongzhou District, Beijing, China.
Li-Li HuaLiyuan Community Health Service Center, Tongzhou District, Beijing, China.
Jie TanLiyuan Community Health Service Center, Tongzhou District, Beijing, China.
Jing-Shi ZhangLiyuan Community Health Service Center, Tongzhou District, Beijing, China.
Yan LiangLiyuan Community Health Service Center, Tongzhou District, Beijing, China.
Jing PanLiyuan Community Health Service Center, Tongzhou District, Beijing, China.
Ming-Xia YuLiyuan Community Health Service Center, Tongzhou District, Beijing, China.
Jing-Wen GanLiyuan Community Health Service Center, Tongzhou District, Beijing, China. gan8654@sina.com.

Funding

Science and Technology Commission of Tongzhou District, Beijing, China KJ2024CX036
6 · The paper itself

Abstract

backgroundHypertension, 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.

methodsThis 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 registrationChiCTR, ChiCTR2500103556.Registered 30 May 2025.

Indexed as

HypertensionInternet of ThingsPopulation SurveillanceBeijingCost-Benefit AnalysisCost-Effectiveness AnalysisDigital HealthFemaleHumansPrimary Health CareBlood pressure controlCost-effectivenessHypertensionImplementation processIoT technologyPrimary healthcare

Identifiers

PMID41126161
PMCPMC12541987

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.