Benchmarking survival outcomes: A funnel plot for survival data

TL;DR

This paper develops a new methodology for constructing funnel plots tailored for survival data, accounting for censoring and differences across centers, to improve benchmarking in healthcare outcomes.

Contribution

It introduces a novel approach for funnel plots in survival analysis, addressing censoring and heterogeneity, with practical implementation guidance and validation through simulations and real data.

Findings

Method effectively accounts for censoring in survival data.

Simulation shows accurate performance under various scenarios.

Application to EBMT data demonstrates practical utility.

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 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 EBMT benchmarking project.