Data · dataset · 2025
Authors:
Listed in ScienceDB
Description
Methods
Leveraging internet and Internet of Things (IoT) technologies, a dynamic closed-loop management model was developed by integrating hierarchical management, intelligent assessment, personalized interventions, and remote monitoring. A total of 2,344 diagnosed hypertensive patients were enrolled, Currently, 454 people in the management group and 402 in the control group have completed all four follow-ups.Results ‌ The study compared the blood pressure (BP) target achievement rate and changes in BP values between the two groups.
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Using the number of patients with hypertension at baseline as the reference, the study analyzed differences in BP target achievement between the management group and the control group at different follow-up time points. In the management group, the blood pressure compliance rate increased from 36.87% to 69.82% after the first follow-up, and the compliance rates in the second, third, and fourth follow-ups were 75.99%, 75.77%, and 77.53% respectively.
In the same period, the blood pressure compliance rates of the control group in the first to fourth follow-ups were only 42.04%,46.02%,47.01%, and 56.72% respectively. The overall blood pressure compliance rate of the management group was better than that of the control group. ‌Conclusion‌ The system significantly improved blood pressure compliance rates, follow-up adherence, and patient satisfaction, while also providing high-quality data support for clinical research.Purpose/Significance This study aims to optimize the whole-process management procedure for hypertension patients by healthcare providers and enhance blood pressure control efficacy and patient compliance.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.dmh.00615 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Health services and systems 69%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.dmh.00615 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4203 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (69%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |