PT  - JOURNAL ARTICLE
AU  - Gary Abel
AU  - Marc N Elliott
TI  - Identifying and quantifying variation between healthcare organisations and geographical regions: using mixed-effects models
AID  - 10.1136/bmjqs-2018-009165
DP  - 2019 Dec 01
TA  - BMJ Quality & Safety
PG  - 1032--1038
VI  - 28
IP  - 12
4099  - http://qualitysafety.bmj.com/content/28/12/1032.short
4100  - http://qualitysafety.bmj.com/content/28/12/1032.full
SO  - BMJ Qual Saf2019 Dec 01; 28
AB  - When the degree of variation between healthcare organisations or geographical regions is quantified, there is often a failure to account for the role of chance, which can lead to an overestimation of the true variation. Mixed-effects models account for the role of chance and estimate the true/underlying variation between organisations or regions. In this paper, we explore how a random intercept model can be applied to rate or proportion indicators and how to interpret the estimated variance parameter.