ArticleFrontiers in public health2024
Study on the effectiveness of a community hypertension management model based on home smart blood pressure monitoring using IoT technology.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Smart Home Technologies for Ageing in Place: A Systematic Review of Health Outcomes, Independence, Healthcare Utilisation and Implementation Considerations.Australasian journal on ageing · 2026Pooled it
- Digital Divide or Compensatory Dividend? The Longitudinal Impact of Smart Health Monitoring on Intrinsic Capacity Trajectories.Healthcare (Basel, Switzerland) · 2026Article
- Effects of an Internet of Things-Based Medication Assistance System on Real-World ART Adherence and Treatment Response in People Living with HIV.Journal of clinical medicine · 2026Article
- Smart Community Hypertension Management: A Narrative Review of Promises and Challenges.Journal of multidisciplinary healthcare · 2026Review
- Predicting older adults smart healthcare adoption using an extended TAM.Scientific reports · 2025Article
- Development and evaluation of an IoT-based hypertension surveillance system in community health settings: a mixed-methods quasi-experimental study protocol.BMC health services research · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Hypertension is rapidly increasing in China, but control rates are significantly low. There is a pressing need for effective management models in primary community health settings. Methods: In April 2023, 459 patients from six communities in Jinan City were enrolled using a multi-stage random sampling method and assigned to either a control group comprising 243 participants or an intervention group comprising 216 participants. The control group received standard hypertension care, whereas the intervention group participated in a novel IoT-based remote blood pressure monitoring program for 6 months. Data collection was conducted through detailed questionnaire surveys, cloud platform records, and community management records, both before and after the intervention period. The study employed difference-in-differences (DID) and mediation effect models to assess the effects of the IoT-based management model. Results: The DID model demonstrated that the intervention significantly reduced systolic blood pressure by 9.883 mm Hg and diastolic blood pressure by 6.553 mm Hg. The mediation effect model showed that the frequency of blood pressure measurement and attitudes and beliefs toward hypertension treatment had mediating effects, accounting for 5.82 and 8.07% of the total effect, respectively. The heterogeneity analysis revealed significant regional differences: rural residents experienced a greater decrease in systolic and diastolic blood pressures by 14.85 mm Hg and 6.591 mm Hg, respectively, compared to urban residents, whose diastolic pressure decreased by 6.046 mm Hg. Recommendations: It is advisable to develop differentiated hypertension management strategies tailored to specific regional needs to promote the deep integration and widespread application of smart blood pressure monitoring technology. Enhancing patient awareness and capabilities in managing their health condition is crucial for improving the blood pressure control level among community hypertension patients.
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