Developing a New Zealand casemix classification for mental health services

Area of Science:

• Health Services Research
• Mental Health Economics
• Healthcare Management

Background:

• Accurate classification of mental health service users is crucial for understanding cost drivers.
• Existing systems may not adequately capture the complexity of user needs and associated service costs.
• New Zealand faces challenges in optimizing mental health service funding and resource allocation.

Purpose of the Study:

• To develop a casemix classification system for users of New Zealand mental health services.
• To identify service user characteristics that best predict the costs of provided services.
• To provide a foundation for informed service management and funding strategies.

Main Methods:

• Data collection over six months from 8 district health boards.
• Inclusion of patient information, staff time, and service costs.
• Statistical analysis to identify a classification predicting cost drivers.

Main Results:

• A novel casemix classification emerged from the analysis.
• The classification explained over two-thirds of the variance in service user costs.
• Key user characteristics were identified as significant cost predictors.

Conclusions:

• The developed casemix classification is a valuable tool for informing mental health service management.
• While useful for informing funding, the classification is not yet ready to solely determine funding levels.
• Further refinement and validation may be necessary before full implementation in funding allocation.