Evidence map›Paper›PMID 38739628›Full record

ArticlePloS one2024

Medical resource usage for COVID-19 evaluated using the National Database of Health Insurance Claims and Specific Health Checkups of Japan.

Keita Fukuyama, Yukiko Mori, Hiroaki Ueshima, Shiho Ito, Masaki Tanabe, Tomohiro Kuroda

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Keita FukuyamaDivision of Medical Information Technology and Administration Planning, Kyoto University Hospital, Sakyo-ku, Kyoto city, Kyoto, Japan.ORCID 0000-0001-8176-6961
Yukiko MoriDivision of Medical Information Technology and Administration Planning, Kyoto University Hospital, Sakyo-ku, Kyoto city, Kyoto, Japan.
Hiroaki UeshimaDivision of Medical Information Technology and Administration Planning, Kyoto University Hospital, Sakyo-ku, Kyoto city, Kyoto, Japan.
Shiho ItoDepartment of Clinical Laboratory, Mie University Hospital, Edobashi, Tsu city, Mie, Japan.
Masaki TanabeDepartment of Clinical Laboratory, Mie University Hospital, Edobashi, Tsu city, Mie, Japan.
Tomohiro KurodaDivision of Medical Information Technology and Administration Planning, Kyoto University Hospital, Sakyo-ku, Kyoto city, Kyoto, Japan.ORCID 0000-0003-1472-7203

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe coronavirus disease 2019 (COVID-19) pandemic exhibited several different waves threatening global health care. During this pandemic, medical resources were depleted. However, the kind of medical resources provided to each wave was not clarified. This study aimed to examine the characteristics of medical care provision at COVID-19 peaks in preparation for the next pandemic.

methodsUsing medical insurance claim records in Japan, we examined the presence or absence of COVID-19 infection and the use of medical resources for all patients monthly by age group.

resultsThe wave around August 2021 with the Delta strain had the strongest impact on the working population in terms of hospital admission and respiratory support. For healthcare providers, this peak had the highest frequency of severely ill patients. In the subsequent wave, although the number of patients with COVID-19 remained high, they were predominantly older adults, with relatively fewer patients receiving intensive care.

conclusionsIn future pandemics, we should refer to the wave around August 2021 as a situation of medical resource shortage resulting from the COVID-19 pandemic.

Indexed as

COVID-19Databases, FactualInsurance, HealthAdolescentAdultAgedFemaleHealth ResourcesHospitalizationHumansInsurance Claim ReviewJapanMaleMiddle AgedPandemicsSARS-CoV-2

Identifiers

PMID38739628
PMCPMC11090316

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LicenceCC BY
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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.