Evidence map›Paper›PMID 40221780›Full record

ArticleBMC health services research2025

Impact of Health All-in-One Machines on access to healthcare of rural areas in China: an interrupted time series analysis.

Yan Xie, Hanning Zhang, Wenqi Li, Hui Yan, Huilong Duan

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
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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

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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

5 authors.

Yan XieState Key Laboratory of Digital Medical Engineering, Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya, Hainan, 572024, China.
Hanning ZhangChina Unicom (Hainan) Innovation Research Institute, Haikou, 570100, China.
Wenqi LiChina Unicom (Hainan) Industrial Internet Co., Ltd, Haikou, 570100, China.
Hui YanState Key Laboratory of Digital Medical Engineering, Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya, Hainan, 572024, China. yanhui@hainanu.edu.cn.
Huilong DuanCollege of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, 310027, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSmart healthcare systems are expected to have a positive impact on addressing challenges in healthcare. However, the real-world adoption and widespread integration of Smart healthcare systems still face many barriers, and their clinical utility lacks empirical research with large sample sizes, particularly in rural areas. The aim of this study is to evaluate the impact of a new smart healthcare system, the Health All-in-One Machines (HAMs), on improving the health services in rural areas of China.

methodsThe data included health services information from 1,866 village clinics in Hainan, China, covering the period November 30, 2020, to April 30, 2023. The impact of Health All-in-One Machines on access to healthcare was measured using four outcome indicators: the number of patient visits, medical revenue, pharmaceutical revenue, and medical expense per patient. We conducted a three-phase interrupted time series study to explore the effects of the Health All-in-One Machines intervention on these indicators across two distinct periods: the second phase (26 weeks, adaptation period) and the third phase (74 weeks, full-scale implementation period).

resultsThe interrupted time-series analysis revealed that the Health All-in-One Machines intervention had no significant impact on outcome indicators comparing the pre-intervention period to the adaptation period. However, from the adaptation period to full implementation, significant impacts were observed. Specifically, notable level changes were observed: the number of patient visits increased by 37.85% (p < 0.01), medical revenue increased by 54.03% (p < 0.001), pharmaceutical revenue increased by 32.84% (p < 0.05), and medical expense per patient increased by 2.368 CNY (p < 0.001). Additionally, a significant trend change was observed in medical expense per patient, with a decrease of 0.15 CNY per week (p < 0.05).

conclusionsThis study provides empirical evidence of some positive changes in the Health All-in-One Machines intervention on the outcome indicators regarding the access to healthcare. Moreover, our analysis indicates that the Health All-in-One Machines intervention would at least take longer to take effect when implemented in large-scale rural healthcare institutions. The findings from this study provide insights for future delivery and policy making of Smart healthcare systems in rural areas.

Indexed as

Health Services AccessibilityRural Health ServicesChinaHumansInterrupted Time Series AnalysisRural PopulationAccess to healthcareARIMA modelsHAMs interventionHealth all-in-one machinesITS studySmart healthcare systems

Identifiers

PMID40221780
PMCPMC11992834

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LicenceCC BY
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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 OpenQuestion graph.