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Effective Health Care Program

Relationship Between Use of Quality Measures and Improved Outcomes in Serious Mental Illness

Technical Brief

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Structured Abstract

Background

Provisions of the Affordable Care Act (2010) require the use of validated quality measures (QMs) to evaluate the quality of health care programs, services, and outcomes. The need for such measures is crucial in serious mental illness (SMI), a long-term illness involving substantial functional impairment over multiple symptom domains that affects more than 11 million U.S. adults. Using QMs to assess the effect of programs designed to improve the mental health of SMI populations is an important task in improving the quality of these programs and services and, ultimately, health outcomes. Although stakeholders have proposed a variety of QMs, none are used consistently across all treatment sites or all forms of SMI. Key areas of uncertainty remain. Knowledge gaps for SMI include an agreed-upon list of relevant QMs; identification of the most meaningful outcomes by which to measure the success of QMs; identification of barriers to and facilitators of their implementation; and robust assessments of whether use of such measures improves medical, psychiatric, and patient-centered outcomes.

Purpose

The goal of this Technical Brief is to identify how QMs are currently used in the SMI population and to describe the evidence supporting their use.

Methods

We discussed with Key Informants and performed targeted searches of published and gray literature on questions of (1) a description of QMs; (2) the context for their use; (3) research linking QMs to changes in outcomes; and (4) current key issues in future uptake, use, evidence gaps, and research priorities.

Findings

The evidence base, which was sparse, suggests that no uniformly accepted practices exist on how to define or implement QMs for SMI, nor on which QMs are the most relevant. Outcomes against which to evaluate the effectiveness of QMs are difficult to measure. Time, the additional burden of using QMs on a resource-limited health care system, and a thin evidence base on their use were key barriers to implementation of QMs. Indeed, we found no prospective research evaluating whether the use of QMs for SMI leads to changes in outcomes. Of note, evidence does not exist that indicates that certain measures often used as proxies for quality of care actually measure quality of care or improve outcomes.

Conclusions

The literature does not indicate an agreed-upon list of preferred relevant QMs for the SMI population, and the outcomes against which to assess the effectiveness of QMs are challenging to measure. Relatedly, and possibly of greatest practical importance, no studies have assessed whether the use of QMs improves health outcomes for patients with SMI nor do stakeholders agree on preferred outcomes. Accordingly, critical issues for the field to address include (1) determining the level of evidence (or strength of evidence) necessary to support implementation of QMs, given the complexities of studying the topic and the likely limited research funding; (2) developing the evidence base that assesses the link between QM use and outcomes; (3) considering when to invest the time and resources on measuring outcomes of care to evaluate the impact of QMs, and when process measures (proxies of the outcomes) are a reasonable and more feasible alternative; (4) determining the resource needs for QM implementation; and (5) developing validated and reliable QM tools that can be implemented feasibly in real-world practice.