Evidence map›Paper›PMID 40289105›Full record

ArticleBMC health services research2025

The status and challenges of online consultation service in internet hospitals operated by physical hospitals in China: a large-scale pooled analysis of multicenter data.

Ming Yang, Yiwei Yan, Zhong Xu, Hongli Liu, Jing Ran, Yingbin Zheng, Zhefeng Cai, Zhengwei Liu, Kai Gong

Abstract readMulticenter Study
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. 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

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

5 citing papers in PubMed.

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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

9 authors.

Ming Yang *The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, 10 Shanggu Road, Siming District, Xiamen City, 361003, China.
Yiwei Yan *The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, 10 Shanggu Road, Siming District, Xiamen City, 361003, China.
Zhong XuThe First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, 10 Shanggu Road, Siming District, Xiamen City, 361003, China.
Hongli LiuCollege of Public Health, Zhengzhou University, Zhengzhou, 450001, China.
Jing RanThe First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, 10 Shanggu Road, Siming District, Xiamen City, 361003, China.
Yingbin ZhengThe First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, 10 Shanggu Road, Siming District, Xiamen City, 361003, China.
Zhefeng CaiZoenet Health Company Limited, Xiamen, China.
Zhengwei LiuZoenet Health Company Limited, Xiamen, China.
Kai GongThe First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, 10 Shanggu Road, Siming District, Xiamen City, 361003, China. freatink@xmu.edu.cn.

Funding

2021 Xiamen Medical and Health Guidance Project "Research on Theoretical and Empirical Evaluation of Internet Hospital Services" 3502Z20214ZD1003Fujian Provincial Clinical Research Center for Brain Diseases 2021FJSLCYX01Xiamen Clinical Research Center for Neurological Diseases 2021XMSLCYX0Xiamen Municipal Health Commission, Xiamen Municipal Bureau of Science and Technology 3502Z20209005
6 · The paper itself

Abstract

backgroundWhile Internet hospitals have rapidly developed as China's dominant digital healthcare model, critical evidence gaps persist regarding operational status and challenges of their core online consultation services. This study aimed to evaluate the current status and challenges of online consultation in Internet hospitals services through large-scale multi-center business data analysis.

methodsRetrospective analysis of 594,695 online consultations (2020-2021) from 30 Internet hospitals across 11 Chinese provinces. Descriptive analyses were conducted on counselee demographics, consultant qualifications, and order informations. A novel five-category consultation classification was applied. Multivariate logistic regression identified the inflencing factors for order, while locally weighted regression (LOESS) modeled workload-response relationships.

resultsThere were 244,678 counselees (median age 29) and 5,781 providers (91.89% doctors) involved. Service are concentrated in pediatrics, obstetrics and gynecology (48.25%). Senior-title providers handled 43.79% consultations but showed reduced completion probability (OR = 0.77). The main types of consultations were re-visit (44.89%) and first visit (34.57%). Temporal patterns revealed peak consultation hours at 10:00 (8.11%) and 16:00 (7.29%), with provider response peaks at 12:00 (5.38%), 16:00 (6.61%), and 21:00 (6.63%), averaging 3.64-hour response delays. Provided medical history (OR = 2.13) could independently increase the response probability, whereas senior title (OR = 0.77) could reduce such probability. Workload-response efficiency transitioned from positive (< 78 orders) to negative correlation (> 1,700 orders), with 27.69% uncompleted orders attributed to consultant factors (75.87%).

conclusionsEven with the increased momentum, the online consultation service still faces many challenges mainly including the relative absence of elderly patients with chronic diseases, personnel qualification issues, the imbalance of service supply and demand, the unfitness of order contents with official regulations, and the insufficient quality control of response rate and timeliness. Comprehensive measures should be carried out to promote the effectiveness of online consultation for better disease prevention and control.

Indexed as

InternetReferral and ConsultationRemote ConsultationAdultChinaFemaleHumansMaleRetrospective StudiesChinaDigital healthInternet hospitalOnline consultationOnline health care services

Identifiers

PMID40289105
PMCPMC12036205

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Registered trials

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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.