Economic evaluation of a collaborative model of pharmaceutical care in an Irish hospital: cost-utility analysis.

Background: A complex, collaborative pharmaceutical care intervention including medication review and reconciliation demonstrated a statistically significant reduction in the prevalence of discharge medication error and improved quality of prescribing for hospitalised adults.  This study sought to assess the cost-effectiveness of this intervention. Methods: A cost-utility analysis was undertaken using a decision-analytic framework. The evaluation was undertaken from the Health Service Executive's perspective, the payer for primary and secondary care settings. Direct costs associated with managing hypothetical harm consequent to intercepted discharge medication error and consequences in terms of quality-adjusted life years loss were key input parameters. Analysis was structured within a decision tree model in Microsoft Excel® populated with consequences as utilities, estimated costs using macro- and micro-costing approaches, and event probabilities generated from the original study. Incremental analysis, one-way and probabilistic sensitivity analyses were performed. Results: The results of analysis for the base-care demonstrated that the intervention dominated standard care with an incremental cost-effectiveness ratio of -€36,537.24/quality-adjusted life year, indicating that the intervention is less costly and more effective. The one-way and probabilistic sensitivity analyses both demonstrated that the intervention dominated standard care. The model was relatively robust to variation in input parameters through one-way sensitivity analysis. The cost of discharge medication error and effect parameters relating to standard care were most sensitive to change. Discussion: The analysis demonstrated the cost-effectiveness of a complex pharmaceutical intervention which will support decision-making regarding implementation. This is the first cost-utility analysis of a complex, collaborative pharmaceutical care intervention, adding to the scant evidence-base in the field.