Evidence map›Paper›PMID 34010976›Full record

Observational studyApplied clinical informatics2021

Health Information System's Responses to COVID-19 Pandemic in China: A National Cross-sectional Study.

Jiancheng Ye

Abstract readObservational Study
In one paragraph

Observational study in Applied clinical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Multimodal Data Hybrid Fusion and Natural Language Processing for Clinical Prediction Models.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
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

1 author.

Jiancheng YeInstitute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAfter the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, Chinese hospitals and health information technology (HIT) vendors collaborated to provide comprehensive information technology support for pandemic prevention and control. This study aims to describe the responses from the health information systems (HIS) to the COVID-19 pandemic and provide empirical evidence in the application of emerging health technologies in China.

methodsThis observational descriptive study utilized a nationally representative, cross-sectional survey of hospitals in China (

resultsAmong all the responses, the most popular interventions and applications include expert question-and-answer sessions and science popularization (61.74%) in online medical consultation, online appointment registration (58.97%) in online medical service, and remote consultation (75.15%) in telehealth service. A total of 63.71% of the participating hospitals expanded their fever clinics during the pandemic, 15.38% hospitals used new or upgraded mobile ward rounds systems, and 44.68% hospitals applied online self-service systems. Challenges and barriers include protecting network information security (57.00%) since some hospitals experienced cybersecurity incidents. 71.79% participants hope to shorten wait time and optimize the treatment process. Health care workers experienced increased amount of work during the pandemic, while hospital information departments did not experience significant changes in their workload.

conclusionIn the process of fighting against the COVID-19, hospitals have widely used traditional and emerging novel HITs. These technologies have strengthened the capacity of prevention and control of the pandemic and provided comprehensive information technology support while also improving accessibility and efficiency of health care delivery.

Indexed as

Health Information SystemsPandemicsSARS-CoV-2ChinaComputer SecurityCOVID-19Cross-Sectional StudiesDelivery of Health CareHospital Information SystemsHospitalsHumansRemote ConsultationSurveys and QuestionnairesTelemedicine

Identifiers

PMID34010976
PMCPMC8133837

What OpenQuestion holds

Textmetadata
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.