Combining regression trees and panel regression for exploring and testing the impact of complementary management practices on short-notice elective operation cancellation rates.

Variation in the performance of providers across healthcare systems is pervasive. It is recognised as both a major concern and an opportunity for learning and improvement. Variation between providers is broadly considered to be due to management practices and contextual factors such as catchment-area demographics. However, there is little understanding of the ways in which these impact on performance and how they can be measured. We use recent developments in both regression trees and panel regression techniques to explore and then statistically test complementary alignments of management practices whilst taking into account contextual factors. We apply this to 5 years of NHS hospital trust data, examining performance on short-notice cancellation rates. We find that different alignments of management practices give rise to quite different short-notice cancellation rates between trusts, with some being substantially lower. Our research offers a data-driven approach for identifying optimal clusters of management practices.