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CC BY-NC-ND 4.0 · Gesundheitswesen 2023; 85(S 03): S197-S204
DOI: 10.1055/a-2132-6797
Originalarbeit

Assessment of the Potential of Concentrating Cancer Care in Hospitals With Certification Through Survival Analysis

Artikel in mehreren Sprachen: English | deutsch
Veronika Bierbaum
1   Zentrum für Evidenzbasierte Gesundheitsversorgung, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
,
Jochen Schmitt
1   Zentrum für Evidenzbasierte Gesundheitsversorgung, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
,
Monika Klinkhammer-Schalke
2   Tumorzentrum Regensburg (TZR), Zentrum für Qualitätssicherung und Versorgungsforschung der Universität Regensburg, Regensburg, Germany
,
Olaf Schoffer
1   Zentrum für Evidenzbasierte Gesundheitsversorgung, Universitätsklinikum Carl Gustav Carus, Dresden, Germany
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Fundings Innovationsfonds — 01VSF17020
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Abstract

Background Certification programs seek to improve the quality of complex interdisciplinary models of care such as cancer treatment through structuring the process of care in accordance with evidence-based guidelines. In Germany, the German Cancer Society (Deutsche Krebsgesellschaft, DKG) provides a certification programme for cancer care that covers more than one thousand centers. In a recent retrospective cohort study, it has been shown on a large, nationwide data set based on data from a statutory health insurance and selected clinical cancer registries, that there is a benefit in survival for cancer patients who have received initial treatment in hospitals certified by the DKG. Here, we deduce two absolute measures from the relative benefit in survival with the aim to quantify this benefit if all patients had been treated in a certified center.

Methods The WiZen study analysed survival of adult patients insured by the AOK with a cancer diagnosis between 2009 and 2017 in certified hospitals vs. non-certified hospitals. Besides Kaplan-Meier-estimators, Cox regression with shared frailty was used for 11 types of cancer in total, adjusting for patient-specific information such as demographic characteristics and comorbidities as well as hospital characteristics and temporal trend. Based on this regression, we predict adjusted survival curves that directly address the certification effect. From the adjusted survivals, we calculated years of life lost (YLL) and number needed to treat (NNT), along with a difference in deaths 5 years after diagnosis.

Results Based on our estimate for the 537,396 patients that were treated in a non-certified hospital included in the WiZen study, corresponding to 68,7% of the study population, we find a potential of 33,243 YLL per year in Germany based on the size of the German population as of 2017. The potential to avoid death cases 5 years from diagnosis totals 4,729 per year in Germany.

Conclusion While Cox regression is an important tool to evaluate the benefit that arises from variables with a potential impact on survival such as certification, its direct results are not well suited to quantify this benefit for decision makers in health care. The estimated years of life lost and the number of deaths that could have been avoided 5 years from diagnosis avoid mis-interpretation of the hazard ratios commonly used in survival analysis and should help to inform key stakeholders in health care without specialist background knowledge in statistics. Our measures, directly adressing the effect of certification, can furthermore be used as a starting point for health-economic calculations. Steering the care of cancer patients primarily to certified hospitals would have a high potential to improve outcomes.

Key words

cancer - certification - survival analysis

Zusätzliches Material

Supplementary Material



Publikationsverlauf

Artikel online veröffentlicht:
26. September 2023

© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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