Putter, H., Eikema, D.-J., de Wreede, L.C. et al. (5 more authors) (2022) Benchmarking survival outcomes: a funnel plot for survival data. Statistical Methods in Medical Research, 31 (6). pp. 1171-1183. ISSN 0962-2802
Abstract
Benchmarking is commonly used in many healthcare settings to monitor clinical performance, with the aim of increasing cost-effectiveness and safe care of patients. The funnel plot is a popular tool in visualizing the performance of a healthcare center in relation to other centers and to a target, taking into account statistical uncertainty. In this paper, we develop a methodology for constructing funnel plots for survival data. The method takes into account censoring and can deal with differences in censoring distributions across centers. Practical issues in implementing the methodology are discussed, particularly in the setting of benchmarking clinical outcomes for hematopoietic stem cell transplantation. A simulation study is performed to assess the performance of the funnel plots under several scenarios. Our methodology is illustrated using data from the European Society for Blood and Marrow Transplantation benchmarking project.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © The Author(s) 2022. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | Benchmarking; funnel plot; hematopoietic stem cell transplantation; quality of care; survival analysis |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Sheffield Teaching Hospitals |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 May 2022 10:48 |
Last Modified: | 10 Feb 2023 15:38 |
Status: | Published |
Publisher: | SAGE Publications |
Refereed: | Yes |
Identification Number: | 10.1177/09622802221084130 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:186399 |