Evidence map›Paper›PMID 36776406›Full record

ArticleDigital health

Impact of the development of information society on healthcare efficiency: Empirical evidence from 31 Chinese provinces.

Yuanrong Hu, Ying Wang, Shengkang Lu, Yongqing Li

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

  1. Capacity utilization of China's elderly care service industry during 2010-2022.Cost effectiveness and resource allocation : C/E · 2026
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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

4 authors.

Yuanrong HuSchool of Economics and Management, Hubei University of Education, Wuhan, Hubei, China.ORCID https://orcid.org/0000-0001-9191-8607
Ying WangSchool of Accounting, Zhongnan University of Economics and Law, Wuhan, Hubei, China.
Shengkang LuSchool of Economics and Management, Hubei University of Education, Wuhan, Hubei, China.
Yongqing LiSchool of Management, Huazhong University of Science and Technology, Wuhan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of information society has deeply changed the style of the healthcare service delivery and medical information access. This study aims to investigate how the information society development affects the efficiency of healthcare system in China, and explore provincial disparities in the impact. Based on the two-stage Data Envelopment Analysis (DEA) framework, this paper uses a panel data from 31 Chinese provinces from 2014 to 2017 to estimate efficiency of healthcare service and analyze the influence of the development of information society on efficiency. With the information society index (ISI) increased from 0.423 to 0.488 during the sample period, the healthcare efficiency experienced a slight decrease from 0.892 to 0.869. Moreover, the pure technical efficiency (PTE) is much lower than the scale efficiency (SE), and thus is the key to enhance the overall technical efficiency (TE). The time-fixed Tobit regression analysis suggests that information society development leads to a significant increase in PTE, but results in a decrease in SE, and therefore has little effect on TE. Further analysis reveals that the impact differs sharply between low-efficiency and high-efficiency provinces. For the low-efficiency provinces, the TE increases significantly with the development of the information society, mainly due to a considerable increase in PTE. In contrast, the TE decreases for the high-efficiency provinces, mainly caused by a decrease in SE. This paper highlights the importance of information infrastructure investment in healthcare system and the application of emerging information technologies to breakout the time and space boundaries of healthcare services in improving overall efficiency. In inefficient provinces, it is also necessary to properly control the growth of healthcare inputs.

Indexed as

DEAhealthcare efficiencyhealthcare serviceinformation societyTobit model

Identifiers

PMID36776406
PMCPMC9912566

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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.