Developing a case mix classification for child and adolescent mental health services: the influence of presenting problems, complexity factors and service providers on number of appointments*

Abstract

Background: Case-mix classification is a focus of international attention in considering how best to manage and fund services, by providing a basis for fairer comparison of resource utilization. Yet there is little evidence of the best ways to establish case mix for child and adolescent mental health services (CAMHS).

Aim: To develop a case mix classification for CAMHS that is clinically meaningful and predictive of number of appointments attended and to investigate the influence of presenting problems, context and complexity factors and provider variation.

Method: We analysed 4573 completed episodes of outpatient care from 11 English CAMHS. Cluster analysis, regression trees and a conceptual classification based on clinical best practice guidelines were compared regarding their ability to predict number of appointments, using mixed effects negative binomial regression.

Results: The conceptual classification is clinically meaningful and did as well as data-driven classifications in accounting for number of appointments. There was little evidence for effects of complexity or context factors, with the possible exception of school attendance problems. Substantial variation in resource provision between providers was not explained well by case mix.

Conclusion: The conceptually-derived classification merits further testing and development in the context of collaborative decision making.

Keywords:

• child and adolescent mental health services
• case mix
• payment systems
• resource use
• outpatient care
• cluster analysis
• regression trees

Acknowledgements

We thank the members of the CAMHS Payment System Project Group, the Advisory Group and attendees at our public consultation events for their contributions and the staff of the child and adolescent mental health services that participated in the data collection for generously devoting their time and effort.

Declaration of interest

This paper reports on results from the CAMHS Payment System Project (formerly CAMHS PbR), which was supported by a grant from the Department of Health and NHS, England.

Supplementary materials available online.

Notes

¹ The NICE guideline CG78 (“borderline personality disorder”) is represented in our conceptualisation, but was not included in the algorithmic allocation, as we judged that presenting information was not sufficient to identify personality disorder. In practice, allocation to this grouping would be matter of clinical judgement using additional information from case histories not captured by the current view form.