challenging on an individual or population level. The increase in potentially interoperable electronic and personal health datasets—integrated with laboratory values, diagnostic images, and patient demographic information and preferences—and development of approaches to link and network these data offer even greater opportunity to create and use rich data resources to help transform healthcare delivery and improve the public’s health. Concerns about privacy of health data, as well as the treatment of medical data—even those generated with public funds—as proprietary goods pose additional challenges to data use (Blumenthal, 2006; Nass et al., 2009, editors, Nature 2005, Ness, 2007; Piwowar et al., 2008).
The utility of clinical data as a transformative agent in the U.S. healthcare system was the focus of the February 2008 Institute of Medicine (IOM) workshop, Clinical Data as the Basic Staple of Health Learning: Creating and Protecting a Public Good. Issues motivating discussion include the potential for clinical data as a resource for continuous learning and key component of an efficient healthcare system; the opportunities presented by vastly larger and potentially interoperable data resources—particularly those developed with public funds; the challenges and barriers to more appropriate use of these resources (e.g., related to the fragmentation of data, proprietary nature of data, and privacy concerns); the lag of public policy development and public awareness of and attention to these issues; and the need to address key issues, including the extent to which data constitute a public good (Box S-1).
During the 2-day workshop, participants representing a variety of healthcare perspectives, reviewed current use of data for benchmarking and generating new clinical and operational insights, and discussed a sampling of innovative efforts to aggregate data for greater insights. In evaluating the current marketplace for care data, participants presented opportunities to increase access to and sharing of health information as private and public goods, while devoting particular attention to legal and social aspects of privacy and security of healthcare data. The workshop addressed multiple health-sector perspectives in the identification of specific policy areas for developing strategies and next-generation health data systems. Engaging the public in the advances necessary to develop a learning health system was viewed as a particularly important area for further discussion.
Convened by the IOM in 2006, the Roundtable on Value & Science-Driven Health Care (formerly the Roundtable on Evidence-Based Medicine) serves as a mechanism for bringing stakeholders from multiple sectors together to evaluate means through which improving the generation and application of evidence will accelerate progress toward an efficient, effective