Does the Implementation of a Model of Care Improve the Value for Money of Mental Health Services in Prisons?

Abstract

BACKGROUND: There is little research into appropriate measures of value for money in prison mental health services.

AIMS: To develop and evaluate an accountability framework for an enhanced Prison Model of Care for people with serious mental illness in five New Zealand prisons. A key objective was to identify people with such illnesses who were missing from existing caseloads.

METHODS: A generic public sector accountability framework was modified to provide measures of value for money around efficiency in its three component criteria of effectiveness and economy using a pre/post design, allowing measurement of flows between successive stages of this prison healthcare model. Measures were arranged into common dimensions around outcomes, outputs, inputs and costs, varied across the stages. The framework was populated with data collected from five prisons for the pre- and post-implementation periods.

RESULTS: Improvements in the three criteria were generally obtained across all five areas of service delivery but especially in the screening, assessment, intervention and reintegration stages. Since these three criteria are major components of value for money, they provide evidence for improvement in value for money of the mental health services in these prisons. Other desired operational changes achieved were a threefold increase in the nurse to doctor ratio at the triage stage and slight increase in doctor to nurse ratio at the treatment stage. Overall, the implementation of this model of care achieved an increase in the size of caseload from 6.1% to 7.3% of the prison muster, equivalent to an increase in caseload of 21%.

CONCLUSIONS: This accountability framework confirmed the value for money of the Prison Model of Care for severe mental illness, highlighting areas of good performance as well as areas requiring further development. The framework also provides measures that can be used as key performance indicators in ongoing monitoring.