Common Ground: A Framework for Selecting Core Quality Measures for Mental Health and Substance Abuse Care

Abstract

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.

Clinical Improvement Associated with Conformance to HEDIS-Based Depression Care

“…While providing evidence that depression indicators developed in administrative databases 'work,' these findings suggest that the indicator may need to be calculated in both narrowly and broadly defined populations to be relevant for the range of stakeholders whose decisions quality indicators are meant to influence (Hermann, 2002;Hermann & Palmer, 2002). Applied narrowly to the population in treatment, the indicator provides adherence data that health plans have used to guide adherence improvement initiatives (Roberts, Cockerham, & Waugh, 2002;Hoffman et al, 2003).…”

Depression Quality of Care: Measuring Quality over Time Using VA Electronic Medical Record Data

“…Per the domains identified by Hermann, 31 we expected our measures to be meaningful, feasible, and actionable for quality improvement. For meaningfulness, we relied on literature, guidelines and an expert panel.…”

“…31 Major depressive affective disorder recurrent episode mild degree X X 296. 32 Major depressive affective disorder recurrent episode moderate degree X X 296.…”

Key performance indicators for mental health and substance use disorders: a literature review and discussion paper

“…Actively flexible policies and health care structures that enable accessible community-based health care, which are delivered through evidence-based integrated multidisciplinary approaches addressing the biological, psychological and social factors contributing to MESUDS, are becoming more widely reported (Government of Ireland, 2006;Health Canada, 2002;NHS Department of Health, 2012;Pawsey, Logan, & Castle, 2011;Watkins & Pincus, 2011). Furthermore, in order to maximize limited resources and address the gap between evidence-based best healthcare practices and the care that is actually received, health systems need to address the underdevelopment of their infrastructure, both at local and national levels, thus enabling measurement of system performance (Hermann et al, 2002;Institute of Medicine, 2001) using measures which are both valid and reliable (Hermann et al, 2000) . Such performance measurement is likely to be integral to active evolution of a health system to meet the needs of its users, may form the foundation for accountability and provision of good quality care (Hermann et al, 2004;Pincus et al, 2007) and has contributed to the development, content and application of key performance indicators (KPIs) for MESUDS for several health systems internationally (Hermann et al, 2006;Watkins & Pincus, 2011).…”

“…Glover and KamisGould (Glover & Kamis-Gould, 1996) suggested nine criteria for good performance indicators: "(1) Conceptual clarity, (2) Clear link to an organizational goal, (3) Operationally defined, reliable and valid measures, (4) Measures derived wherever possible from available management information systems, (5) Consisting of proportion and ratios rather than raw numbers, (6) Desired direction for performance is clear, (7) Indicators suitable for comparison (risk adjusted where necessary), (8) Sufficiently universal for comparison with other services, and (9) Decision rules for significant deviations from chance and for establishing high and low performance." These criteria were reflected by Hermann and Palmer (Hermann & Palmer, 2002) in their developmental framework for quality measures specifically for MESUDS care.…”