Health Services Research in 2020 A Summit on the Future of HSR Data & Methods Washington, DC June 1-2, 2009.

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Presentation transcript:

Health Services Research in 2020 A Summit on the Future of HSR Data & Methods Washington, DC June 1-2, 2009

Background 2007 Summit on Future of HSR Workforce Field has more than doubled in size in last decade The sponge challenge Growing role of private sector, but training geared to academia. The search for core competencies Health Services Research October 2009.

Current Context Surge in funding for HIT CER Health reform (modeling and evaluation) Will HSR be able to meet expectations?

SUMMIT OBJECTIVES To collectively: Identify the data and methods limitations that could diminish the ability of the field to produce the timely, rigorous and relevant research that our nations needs. Generate a set of proposals that will strengthen the data and the methods needed to produce high quality health services research.

Advisory Committee David Abrams, American Legacy Foundation Linda Bilheimer, National Center for Health Statistics Francis Chesley, Agency for Healthcare Research and Quality Carolyn Clancy, Agency for Healthcare Research and Quality David Colby, Robert Wood Johnson Foundation Kelly Devers, Virginia Commonwealth University Bryan Dowd, University of Minnesota Richard Gliklich, Outcome Sciences Grant Huang, VA Cooperative Studies Program Susan Law, Canadian Health Services Research Foundation Patricia Mabry, National Institutes of Health Vincent Mor, Brown University School of Medicine Pauline Sieverding, Department of Veterans Affairs Michael Stoto, Georgetown University School of Nursing & Health Studies Philip Wang, National Institute of Mental Health

Papers: Multiple Perspectives Data and Methods Challenges in 2020 Data Papers Policy Topic Papers Methods Papers

WORKGROUPS A Health Systems Data Leadership & Coordination Alison Rein & Claudia Williams C Health Survey Data Leadership and Coordination Michael Gluck & Marsha Gold B Health Systems Data Training, Methods and Knowledge Transfer Sharon Arnold & Grant Huang D Health Survey Data Training, Methods and Knowledge Transfer Erin Holve & Vince Mor

Group A: Systems Data: Leadership Scope: Priority setting processes for data collection Data standardization and mechanisms of collection Data quality and transparency Data linkage and aggregation Data access (including terms of use) and liquidity Legal and regulatory framework Targets: Public and private plans and their associations Providers and their associations Other (e.g., consumer / patient groups, employers) Federal and State policymakers Sample issues: Privacy: what are the roles and responsibilities of different players? When and for what reasons (big picture) should data be aggregated? How should different types of data be aggregated: when distributed versus centralized? What are the best incentives to improve provider stake in data quality? Do we need legislation to facilitate researchers access to data? Is there a need to better define what constitutes a registry, or different types of registries? Is there a need for a registry of registries?

Group B: Systems Data: Methods Scope: Definition and measurement Applications and modules for implementation Training KT/communications Targets: Health systems and providers Researchers Vendors Associations, such as AcademyHealth Sample issues: What kind of investment (and by whom) to improve measures? How to promote implementation research by providers and systems that takes into account context? What are the incentives and training needs? How to promote pragmatic trials, collective intelligence, positive deviance? How to generate interdisciplinary dialogue around best practices in observational research? How to incorporate that interdisciplinary understanding into review processes?

Group C Survey Data: Leadership Scope: Identification of gaps and priorities Data standardization and collection to facilitate linkages Data quality and transparency Data access (including terms of use) and dissemination Targets: Federal agencies, including the HHS Data Council. Current data repositories such as ResDAC IRBs/research institutions leadership NLMs Health Services Research Resources and other databases of databases Professional provider and trade associations that conduct surveys of members or track licensure data Federal and possibly state legislators and staff Sample issues: Do we need a central inventory of federal surveys (overlap, gaps, variable definitions and sampling frames)? Do we need centralization of the access process? Do we need greater federal stewardship of IRBs? Do we need technical recommendations and training materials to encourage linkages among surveys and with health system data? Is HIPAA interpretation that linked data must be discarded after research reasonable?

Group D Survey Data Methods Scope: Definition and measurement Training KT/communications Targets: NIH and AHRQ training programs Foundations AcademyHealth Sample issues: How can best practices in linking data (survey to survey, or survey to system data) be developed and disseminated? What training opportunities are needed to assist researchers in linking data? How much and on what kinds of topics is new experimentation needed, i.e. HIE?