Utility analysis for clinical decision-making in small treatment settings

Abstract

Data-driven clinical decision-making can be difficult in settings that service relatively few patients because of the small samples available, the patients' potential dissimilarity from participants in published research, and highly limited resources. This study was designed to demonstrate how utility analyses might assist clinical decision-making in small treatment settings and provide data for promoting programmatic improvements. Data came from a study to identify rural juvenile delinquents suspected to not benefit from residential behavioral treatment. A prospective correlational design was used with data from a midwestern juvenile criminal justice residential unit in which about 30 males were treated annually. Outcomes included treatment performance measures and number of delinquent offenses during the year after treatment. Utility analyses suggested that delinquents who were less likely to benefit from residential treatment could be identified a priori using a modified Psychopathy Checklist, Revised. Cost utility analysis estimated $180,000 less would be spent on residential treatment as a result of selecting residents based on the pretreatment assessment. This money might be reallocated toward alternative intervention for delinquents who are not likely to benefit from the residential treatment. More importantly, results suggested specific alternative interventions for the delinquents who were less likely to benefit from the treatment by providing direct links to existing literature. Advantages of utility analysis research include strong external validity, minimal interference with treatment during data collection, results that estimate clinical and practical significance, and results that are easily communicated to laymen.