Elizabeth Tant

Identifying Priorities for Patient-Centered Outcomes Research for Serious Mental Illness

OBJECTIVE The purpose of this project was to engage a diverse group of stakeholders (N=38) to help establish priorities to guide patient-centered outcomes research (PCOR) in serious mental illness. METHODS Three meetings, two Web-based and one on site, were held to generate and prioritize an initial list of topics. Topics were then sorted and organized into common themes. RESULTS About 140 topics were identified and sorted into 21 main themes, ranked by priority. Three of the top four themes focused on how research was conducted, particularly the need to develop consensus measurement and outcomes definitions; improving infrastructure for research, longitudinal studies, and new data sets and investigators; and developing PCOR methodology. Stakeholders also identified a need to focus on service delivery, treatment settings, and structure of the delivery of care. CONCLUSIONS Engagement by a broad group of stakeholders in a transparent process resulted in the identification of priority areas for PCOR. Stakeholders clearly indicated a need to fundamentally change how research on serious mental illness is conducted and a critical need for the development of methodology and infrastructure. Most current PCOR has been focused on relatively short-term outcomes, but real world, long-term studies providing guidance for treatment over the lifetime of a serious mental illness are needed.

CLINICAL HETEROGENEITY IN SYSTEMATIC REVIEWS AND HEALTH TECHNOLOGY ASSESSMENTS: SYNTHESIS OF GUIDANCE DOCUMENTS AND THE LITERATURE

OBJECTIVES The aim of this study was to synthesize best practices for addressing clinical heterogeneity in systematic reviews and health technology assessments (HTAs). METHODS We abstracted information from guidance documents and methods manuals made available by international organizations that develop systematic reviews and HTAs. We searched PubMed® to identify studies on clinical heterogeneity and subgroup analysis. Two authors independently abstracted and assessed relevant information. RESULTS Methods manuals offer various definitions of clinical heterogeneity. In essence, clinical heterogeneity is considered variability in study population characteristics, interventions, and outcomes across studies. It can lead to effect-measure modification or statistical heterogeneity, which is defined as variability in estimated treatment effects beyond what would be expected by random error alone. Clinical and statistical heterogeneity are closely intertwined but they do not have a one-to-one relationship. The presence of statistical heterogeneity does not necessarily indicate that clinical heterogeneity is the causal factor. Methodological heterogeneity, biases, and random error can also cause statistical heterogeneity, alone or in combination with clinical heterogeneity. CONCLUSIONS Identifying potential modifiers of treatment effects (i.e., effect-measure modifiers) is important for researchers conducting systematic reviews and HTAs. Recognizing clinical heterogeneity and clarifying its implications helps decision makers to identify patients and patient populations who benefit the most, who benefit the least, and who are at greatest risk of experiencing adverse outcomes from a particular intervention.

Using health information exchanges to calculate clinical quality measures: A study of barriers and facilitators.

BACKGROUND A key motivation for the large national investment in electronic health record systems is to promote electronic reporting of quality measures that can be used as the basis for moving to value-based payment. Given the fragmented delivery system, robust quality reporting requires aggregating data across sites of care. Health information exchanges (HIEs) have emerged to facilitate exchange of clinical data across provider organizations and, therefore, should be well-positioned to support clinical quality measure reporting. METHODS By interviewing representatives from 36 HIEs across the United States, we aimed to determine whether HIEs are capable of computing National Quality Forum measures for 6 cardiovascular disease preventive services. RESULTS Eleven HIEs (30%) reported computing at least one CQM; six computed one or more of the measures, and no HIE computed a measure in each of the 6 areas. Barriers to computing CQMs included data quality, completeness, sharing, and transmission issues; organizational structure, maturity, and sustainability issues; and vendor issues. CONCLUSIONS The ability to compute CQMs at the HIE level is still yet to be developed; currently, very few HIEs are able to do so for a variety of reasons. As HIE services expand and HIEs mature organizationally, the viability and utility of CQM reporting at the HIE level will increase. IMPLICATIONS As the healthcare system migrates towards a value-based payment system these broad challenges will need to be addressed. LEVEL OF EVIDENCE Cross-sectional semi-structured qualitative interviews.

Assessing the impact of systematic reviews on future research: two case studies.

AIMS To evaluate the impact of systematic reviews on research funded by the Agency for Healthcare Research and Quality (AHRQ) through Evidence-based Practice Centers (EPCs), and to identify barriers to and facilitators for the effects of these documents on future research. METHODS & MATERIALS Two AHRQ systematic reviews were selected as case studies to evaluate their impact on future research. Key citations generated by these reports were identified through ISI Web of Science and PubMed Central and traced forward to identify effects on subsequent studies through citation analysis from updated systematic reviews on the topics. Requests for applications and program announcements from the NIH Guide for Grants and Contracts website were reviewed and dissemination data were obtained from AHRQ. Finally, interviews were conducted with 13 key informants to help identify short-, medium- and long-term impacts of the EPC reviews. RESULTS The measurable impact of the two EPC reviews is demonstrably greater on short-term outcomes (greater awareness of the issues) than on medium-term (e.g., the generation of new knowledge) or long-term outcomes (e.g., changes in patient practice or health outcomes). Factors such as the topic and the timing of the report relative to the development of the field may explain the impact of these two AHRQ reports. The degree to which the new research can be directly attributed to the AHRQ reviews remains unclear. Key informants discussed several benefits stemming from the EPC reports, including providing a foundation for the research community on which to build, heightening awareness of the gaps in knowledge, increasing the quality of research and sparking new directions of research. However, the degree to which these reports were influential hinged on several factors including marketing efforts, the very nature of the reports and other influences external to the EPC domain. CONCLUSIONS The findings outlined in this article illustrate the importance of numerous factors influencing future research: the breadth, specificity and readiness of the topic for more research, ongoing developments in the field, availability of funding and active engagement of champions. AHRQ and the EPCs may be able to improve the likelihood of impact by creating more targeted products, planning for and expanding dissemination activities, improving the readability and other attributes of the reports themselves, and actively involving funders early on and throughout the process of creating and publishing the reviews.