25gmds090 10.3205/25gmds090 urn:nbn:de:0183-25gmds0905 Meeting Abstract Rauh Rauh Johannes J

Institut für Qualitätssicherung und Transparenz im Gesundheitswesen, Berlin, Germany

author German Medical Science GMS Publishing House

Düsseldorf

610 Bayesianische Verfahren Patient preferences Health Care Research Qualitätsindikatoren 20251103 engl This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). M0631 090 Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie 70. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS) V: Soziotechnische Systeme und Entscheidungsunterstützung Jena 20250907 20250911 Abstr. 323 TextThe eQS programme has the goal to assure and improve quality of care in German health care. This programme is based on around 300 quality indicators. These indicators are often (risk-adjusted) complication rates or rates that count deviations from medical guidelines. They are computed using clinical or administrative data or patient reported data (PROMs/PREMs). The indicators are used to detect performance outliers and to initiate quality improvement measures. They are also publicly reported for each hospital in order to inform patients.There are however two key challenges when reporting the results of indicators to support patient decision-making:Reports typically account for large variations in hospital case numbers by adding uncertainty intervals. However, non-statisticians tend to ignore these intervals, focusing only on point estimates.A single indicator often does not capture the full complexity of quality of care. Yet it is even more difficult to compare multiple indicators, especially if they are measured on different scales.To address these challenges, IQTIG has developed a Bayesian approach. This approach calculates for each indicator the posterior probability that a given hospital meets a predefined threshold. These probabilities are averaged over multiple indicators to obtain a composite index aggregating all quality information.In this talk, we discuss technical details of this approach, including the choice of prior distributions and thresholds, as well as some consequences towards decision-making.The talk presents joint work and ideas developped by various persons at IQTIG for different projects commissioned by the Federal Joint Committee (G-BA) and the Federal Ministry of Health (BMG), most notably the Qualitätsportal and the Bundes-Klinik-Atlas.The author declares that he has no competing interests.The author declares that an ethics committee vote is not required. Institut für Qualitätssicherung und Transparenz im Gesundheitswesen (IQTIG) 2021 Gesamtkonzept für das G-BA-Qualitätsportal. Abschlussbericht Institut für Qualitätssicherung und Transparenz im Gesundheitswesen (IQTIG). Gesamtkonzept für das G-BA-Qualitätsportal. Abschlussbericht. Berlin (Germany): IQTIG; 2021. Available from: https://iqtig.org veroeffentlichungen/g-ba-q-portal/ https://iqtig.org veroeffentlichungen/g-ba-q-portal/ 0 0 0 0