Evidence map›Paper›PMID 34447602›Full record

ArticleIntelligent medicine2021

Digital health interventions for COVID-19 in China: a retrospective analysis.

Mengji Chen, Shan Xu, Lewis Husain, Gauden Galea

Open access · goldAbstract read
In one paragraph

Article in Intelligent medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
7.4field-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

12 citing papers in PubMed, 29 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

4 authors at 1 institution in 1 country.

Mengji ChenWorld Health Organization Representative Office in China, Beijing 100600, China.
Shan XuChina Academy of Information Communications Technology, Beijing 100191, China.
Lewis HusainWorld Health Organization Representative Office in China, Beijing 100600, China.
Gauden GaleaWorld Health Organization Representative Office in China, Beijing 100600, China.
China Academy of Information and Communications Technology · CN

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundThe use of digital health technologies was an integral part to China's early response to coronavirus disease 2019 (COVID-19). Existing literatures have analyzed and discussed implemented digital health innovations from the perspective of technologies, whereas how policy mechanisms contributed to the formulation of the digital health landscape for COVID-19 was overlooked. This study aimed to examine the contexts and key mechanisms in China's rapid mobilization of digital health interventions in response to COVID-19, and to document and share lessons learned.

methodsPolicy documents were identified and retrieved from government portals and recognized media outlets. Data on digital health interventions were collected through three consecutive surveys administered between 23 January 2020 and 31 March 2020 by China Academy of Information and Communication Technology (CAICT) affiliated to the Ministry of Industry and Information Technology (MIIT). Participants were member companies of the Internet Health alliance established by MIIT and the National Health Commission (NHC) in June 2016. Self-report digital interventions focusing on social and economic recovery were excluded. Two hundred and sixty-six unique digital health interventions meeting our criteria were extracted from 175 narratives on digital health interventions submitted by 116 participating companies. Thematic analysis was conducted to describe the scope and priority of policies advocating for the use of digital health technologies and the implementation pattern of digital health interventions. Data limitations precluded an evaluation of the impact of digital health interventions over a longer time frame.

resultsBetween January and March 2020, national policy directives promoting the use of digital technologies for the containment of COVID-19 collectively advocated for use cases in emergency planning and preparedness, public health response, and clinical services. Interventions to strengthen clinical services were mentioned more than the other two themes (

conclusionsThe contextual factors and key enabling mechanisms through the use of policy instruments to promote digital health interventions for COVID-19 in China include pathway of policy directives influencing the private sector using a decentralized system, the booming digital health landscape before COVID-19, agility of the public sector in introducing regulatory flexibilities and incentives to mobilize the private sector.

Indexed as

Artificial intelligenceBig dataCoronavirus disease 2019Digital healthTelemedicine

Identifiers

PMID34447602
PMCPMC8079943
OpenAlexW3157848285

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.