Evidence map›Paper›PMID 40238801›Full record

ArticlePloS one2025

Factors associated with regional differences in healthcare quality for patients with acute myocardial infarction in Japan.

Shusuke Watanabe, Etsu Goto, Susumu Kunisawa, Yuichi Imanaka

Abstract read
In one paragraph

Article in PloS one, 2025. 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

4 authors.

Shusuke WatanabeDepartment of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Etsu GotoDepartment of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Susumu KunisawaDepartment of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Yuichi ImanakaDepartment of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Kyoto, Japan.ORCID 0000-0003-4613-2159

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe quality of healthcare at the regional level is of great interest. Regional differences in the quality of healthcare for cardiovascular diseases have been pointed out in previous research, but the regional factors that influence the quality remain unclear.

methodsUsing the national Diagnosis Procedure Combination (DPC) database, risk-adjusted mortality (RAM) in each secondary medical area (SMA) was derived as an indicator for the quality of the healthcare for patients with acute myocardial infarction (AMI). Factors associated with RAM were analysed using the partial least squares (PLS) regression model.

resultsThere is a wide variation in RAM in the SMAs; the maximum value was 0.593 and the minimum value was 1.445. The PLS regression identified two components positively correlated with RAM. The first component (Component 1) positively correlates with the proportion of the elderly within the population and negatively correlates with the number of medical facilities per area, the population density, and the intra-SMA access to centres with a high volume of emergency percutaneous coronary interventions (ePCI). The second component (Component 2) positively correlates with the number of medical facilities per area and negatively correlates with the number of doctors per person and the intra-SMA access to centres with a high volume of ePCI.

conclusionsThere was wide regional variation in the quality of in-hospital AMI treatments. Results suggested the degree of rurality, the sufficiency of medical resources, the access to high-volume ePCI centres, and coordination of healthcare delivery were associated with healthcare quality.

Indexed as

Myocardial InfarctionQuality of Health CareAgedFemaleHumansJapanMaleMiddle Aged

Identifiers

PMID40238801
PMCPMC12002444

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