# A test for monitoring under- and overtreatment in Dutch hospitals

## TL;DR

This paper introduces a statistical test for monitoring over- and undertreatment in Dutch hospitals, using risk-adjusted funnel plots on large administrative data to identify hospitals with unusual treatment patterns.

## Contribution

It presents a novel, systematic method to detect over- and undertreatment in hospitals using aggregated administrative data and a random effects model.

## Key findings

- Identified hospitals with potential over- or undertreatment outside control limits.
- Provided a risk-adjusted monitoring tool for healthcare quality assessment.
- Facilitated discussions with hospitals to refine treatment practices.

## Abstract

Over- and undertreatment harm patients and society and confound other healthcare quality measures. Despite a growing body of research covering specific conditions, we lack tools to systematically detect and measure over- and undertreatment in hospitals. We demonstrate a test used to monitor over- and undertreatment in Dutch hospitals, and illustrate its results applied to the aggregated administrative treatment data of 1,836,349 patients at 89 hospitals in 2013. We employ a random effects model to create risk-adjusted funnel plots that account for natural variation among hospitals, allowing us to estimate a measure of overtreatment and undertreatment when hospitals fall outside the control limits. The results of this test are not definitive, findings were discussed with hospitals to improve the model and to enable the hospitals to make informed treatment decisions.