ReviewOrthopadie (Heidelberg, Germany)2026
[Risk adjustment as a prerequisite for quality assessment in certification and registry analyses].
Review in Orthopadie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundQuality assessment in arthroplasty is gaining increasing importance in the context of growing transparency requirements in healthcare systems. With the introduction of the German Hospital Transparency Act and the Federal Hospital Atlas, the comparable presentation of treatment outcomes has become a central focus. Reliable risk adjustment models are a prerequisite for this, as they must adequately account for differences in patient case mix.
objectiveThis article aims to describe the current state of risk adjustment in arthroplasty, highlight existing limitations, and discuss potential future developments based on the authors' own research.
methodsA narrative review of national and international approaches to risk adjustment in registries and certification systems was conducted. The focus is on the observed-to-expected (O/E) ratios used in the German Arthroplasty Registry (EPRD) and their comparison with model-based approaches applied in international registries. In addition, results from the authors' own studies on the integration of joint-specific risk factors and machine learning methods are presented.
resultsCurrent risk adjustment models are largely based on routine data and patient-specific risk factors and capture clinically relevant joint-specific risk factors insufficiently. The authors' own studies demonstrate that systematic inclusion of such parameters improves the prediction of postoperative complications following total knee arthroplasty.
conclusionFurther development of risk adjustment is essential for fair and valid quality assessment in arthroplasty. In particular, joint- and procedure-specific risk factors should be more strongly integrated in future models to avoid bias in quality comparisons.
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Registered trials
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.