Evidence map›Paper›PMID 35500013›Full record

ArticleJMIR medical informatics2022

Experiences and Challenges of Emerging Online Health Services Combating COVID-19 in China: Retrospective, Cross-Sectional Study of Internet Hospitals.

Fangmin Ge, Huan Qian, Jianbo Lei, Yiqi Ni, Qian Li, Song Wang, Kefeng Ding

Open access · goldAbstract read
In one paragraph

Article in JMIR medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
6.2field-weighted citation impact, top 3% of its field
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

21 citing papers in PubMed, 31 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Fangmin Ge *The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.ORCID https://orcid.org/0000-0002-1543-451X
Huan Qian *The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.ORCID https://orcid.org/0000-0003-0358-9669
Jianbo LeiCenter for Medical Informatics, Health Science Center, Peking University, Beijing, China.ORCID https://orcid.org/0000-0002-1744-0235
Yiqi NiThe Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.ORCID https://orcid.org/0000-0001-8749-3925
Qian LiThe Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.ORCID https://orcid.org/0000-0002-1282-5494
Song WangSchool of Management, Zhejiang University, Hangzhou, China.ORCID https://orcid.org/0000-0002-7073-4179
Kefeng DingThe Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.ORCID https://orcid.org/0000-0002-2380-3717
Second Affiliated Hospital of Zhejiang University · CNPeking University · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInternet-based online virtual health services were originally an important way for the Chinese government to resolve unmet medical service needs due to inadequate medical institutions. Its initial development was not well received. Then, the unexpected COVID-19 pandemic produced a tremendous demand for telehealth in a short time, which stimulated the explosive development of internet hospitals. The Second Affiliated Hospital of Zhejiang University (SAHZU) has taken a leading role in the construction of internet hospitals in China. The pandemic triggered the hospital to develop unique research on health service capacity under strict quarantine policies and to predict long-term trends.

objectiveThis study aims to provide policy enlightenment for the construction of internet-based health services to better fight against COVID-19 and to elucidate future directions through an in-depth analysis of 2 years of online health service data gleaned from SAHZU's experiences and lessons learned.

methodsWe collected data from SAHZU Internet Hospital from November 1, 2019, to September 16, 2021. Data from over 900,000 users were analyzed with respect to demographic characteristics, demands placed on departments by user needs, new registrations, and consultation behaviors. Interrupted time series (ITS) analysis was adopted to evaluate the impact of this momentous emergency event and its long-term trends. With theme analysis and a defined 2D model, 3 investigations were conducted synchronously to determine users' authentic demands on online hospitals.

resultsThe general profile of internet hospital users is young or middle-aged women who live in Zhejiang and surrounding provinces. The ITS model indicated that, after the intervention (the strict quarantine policies) was implemented during the outbreak, the number of internet hospital users significantly increased (β_2=105.736, P<.001). Further, long-term waves of COVID-19 led to an increasing number of users following the outbreak (β_3=0.167, P<.001). In theme analysis, we summarized 8 major demands by users of the SAHZU internet hospital during the national shutdown period and afterwards. Online consultations and information services were persistent and universal demands, followed by concerns about medical safety and quality, time, and cost. Users' medical behavior patterns changed from onsite to online as internet hospital demands increased.

conclusionsThe pandemic has spawned the explosive growth of telehealth; as a public tertiary internet hospital, the SAHZU internet hospital is partially and irreversibly integrated into the traditional medical system. As we shared the practical examples of 1 public internet hospital in China, we put forward suggestions about the future direction of telehealth. Vital experience in the construction of internet hospitals was provided in the normalization of COVID-19 prevention and control, which can be demonstrated as a model of internet hospital management practice for other medical institutions.

Indexed as

China health systemCOVID-19dynamics of health care topicse-consultationtelehealth

Identifiers

PMID35500013
PMCPMC9162135
OpenAlexW4225278432

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.