Evidence map›Paper›PMID 41561560›Full record

ArticleBMJ public health2026

Evaluation of clinical risk factors for quality assessment of treatment of acute myocardial infarction: a cohort study using German claims data linked with clinical data from 14 hospitals.

Melissa Spoden, Patrik Dröge, Christian Günster, Thomas Datzmann, Jochen Schmitt, Ekkehard Schuler, Uwe Zeymer

Abstract read
In one paragraph

Article in BMJ public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Melissa SpodenAOK Research Institute, Berlin, Germany.ORCID https://orcid.org/0000-0002-6730-4469
Patrik DrögeAOK Research Institute, Berlin, Germany.ORCID https://orcid.org/0000-0003-0263-3154
Christian GünsterAOK Research Institute, Berlin, Germany.ORCID https://orcid.org/0000-0003-3085-6259
Thomas DatzmannUniversitätsklinikum Carl Gustav Carus Zentrum für Evidenzbasierte Gesundheitsversorgung, Dresden, Germany.ORCID https://orcid.org/0000-0003-0312-5901
Jochen SchmittUniversitätsklinikum Carl Gustav Carus Zentrum für Evidenzbasierte Gesundheitsversorgung, Dresden, Germany.ORCID https://orcid.org/0000-0003-0264-0960
Ekkehard SchulerHELIOS Kliniken GmbH, Berlin, Germany.ORCID https://orcid.org/0000-0002-5159-6583
Uwe ZeymerInstitut für Herzinfarktforschung Ludwigshafen, Klinikum der Stadt Ludwigshafen am Rhein gGmbH, Ludwigshafen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Statutory health insurance claims data are used for risk adjusted quality assessment of inpatient treatments. This study evaluated the impact of clinical data on quality assessment of the treatment of acute myocardial infarction (AMI), and whether the content of clinical factors can be approximated by claims data. Material and methods: In this observational study, claims data of statutory health insurance in Germany were linked retrospectively with clinical data from 14 hospitals. The hybrid study population encompassed 3148 cases with inpatient treatment of AMI who underwent coronary angiography. Quality indicators for five outcomes were developed by means of stepwise logistic regression. Using claims data from a nationwide study population of 165 130 AMI cases and a subsample of the same size as the hybrid group, the performances of the risk adjustment models were compared by receiver operating characteristic-area under the curve (ROC-AUC) and standardised mortality/morbidity ratios (SMR). Results: As clinical risk factors, a haemoglobin value of ≤10 g/dL and an estimated glomerular filtration rate of ≤60 mL/min/1.73qm were included, but did not result in a gain of ROC-AUC (w/o clinical variables: 0.74-0.86; with: 0.74-0.87). By approximating the content of these clinical factors by means of claims data, an increase in model performance of up to 4.7% was achieved (with surrogates: 0.77-0.89), but did not influence the final quality assessment by SMR. Conclusions: While replication of our findings is necessary, our models for risk adjustment and surrogates for two clinical factors show that comparative quality reporting using claims data is feasible, although with acknowledged limitations. This would minimise the data set for quality assessment of AMI treatment in accordance with the principle of data minimisation and avoid the need for additional manual documentation.

Indexed as

Cardiovascular DiseasesRisk Assessmentstatistics and numerical data

Identifiers

PMID41561560
PMCPMC12815024

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