Effect of cancer waiting time standards in the English National Health Service: a threshold analysis

英国国家医疗服务体系癌症等待时间标准的影响:阈值分析

阅读:1

Abstract

BACKGROUND: The English National Health Service has multiple waiting time standards relating to cancer diagnosis and treatment. Targets can have unintended effects, such as prioritisation based on targets instead of clinical need. In this case, a `threshold effect' will appear as a spike in hospitals just meeting the target. METHODS: We conducted a retrospective study of publicly available cancer waiting time data, including a 2-week wait for a specialist appointment, a 31-day decision to first treatment and a 62-day referral to treatment standard that attracted a financial penalty. We examined the performance of hospital trusts against these targets by financial year to look for threshold effects, using Cattaneo et al. manipulation density test. RESULTS: Trust performance against cancer waiting targets declined over time, and this trend accelerated since the start of the Covid-19 pandemic. Statistical evidence of a threshold effect for the 2-week and 31-day standard was only present in a few years. However, there was strong statistical evidence of a threshold effect for the 62-day standard across all financial years (p < 0.01). CONCLUSION: The data suggests that the effect of threshold targets alters hospital behaviour at target levels but does not do so equally for all standards. Evidence of threshold effects for the 62-day standard was particularly strong, possibly due to some combination of a smaller volume of eligible patients, a larger penalty, multiple waypoints where hospitals can intervene, baseline performance against the target and where the target is set (i.e. how much headroom is available). RCTs of the use of threshold targets and of different designs for such targets in the future would be extremely informative.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。