The results of the cost-effectiveness model presented here suggest that donepezil may be cost-effective but additional controlled data on long-term drug efficacy are needed.

There is widespread interest throughout the mental health system in routine quality assessment to facilitate quality improvement, oversight, purchasing, and consumer choice. In the absence of agreement on a limited number of meaningful and feasible quality measures, delivery systems, payers, managed care organizations, regulators, and accreditors have each implemented unique measures and specifications. The resulting heterogeneity among measures has increased the burden on providers, limited the comparability of results, and hindered efforts to focus limited resources on further development of the most promising measures. Policy makers have initiated efforts for stakeholders to reach consensus on a core set of measures for common use, but barriers to progress remain, including differences in stakeholder needs and trade-offs between prioritizing desirable attributes of measures and representing the mental health system broadly. The authors present a framework for the selection of a core set of measures, clarify divergent perspectives, and make recommendations for further development of core quality measures for mental health care.

Although limited, the proposed measure set provides a starting point for international benchmarking of mental health care. It addresses known quality problems and achieves some breadth across diverse dimensions of mental health care.

A structured consensus process identified a core set of quality measures that are meaningful and feasible to multiple stakeholders, as well as broadly representative of the mental healthcare system. By yielding quantitative assessments of meaningfulness, feasibility and degree of consensus among stakeholders, these results can inform ongoing national efforts to adopt common quality measures for mental healthcare.

There is a paucity of literature on cost-utility analysis of depression management. High-quality cost-utility analysis should be considered for further research in depression management.