lexity of medicine demands new kinds of relationships between patients, clinicians, and researchers, and that the digital infrastructure can serve as a platform for this going forward.
The perspective of the healthcare team is explored by Jim Walker of Geisinger Health System. He defines a learning health system as one of goal-oriented feedforward and feedback loops that create actionable information. Dr. Walker describes his experiences with health information technology (HIT) implementation at Geisinger and highlights the complex, sociotechnical nature of the challenge—requiring as much attention to the social aspects as is currently being given to technical capacity. Citing examples of healthcare system learning needs—such as the proper second-line treatment for diabetes—Walker lays out the potential for a learning system to address these questions and feed that information back to healthcare team members. He concludes by noting that this goal will require fundamental HIT systems redesign in order to support healthcare team decision making.
Janet Corrigan from the National Quality Forum (NQF) observes that little progress had been made to improve quality and safety since the publication of the Quality Chasm report (IOM, 2001), and that value has concurrently decreased. She states that increases in safety, quality, and effectiveness of health care will require investments in a digital infrastructure capable of collecting information across the longitudinal “patient-focused episode,” and feeding back performance results along with clinical decision support for patients and clinicians. Dr. Corrigan describes the framework used by NQF to develop measures for reporting and value-based purchasing, and explores how a digital infrastructure could support capturing the relevant data. Finally, she states that achieving better health outcomes will require collecting information from, and enabling communication with, individuals both within and outside of traditional healthcare settings.
The growing information intensity of modern medicine and biomedical research, coupled with advances in computing capabilities, define the clinical research perspective as articulated by Christopher Chute from the Mayo Clinic. He observes that given these concurrent conditions, the technical requirements for information and knowledge management in health should be high-priority issues. Drawing from examples of “big science” disciplines such as astronomy and physics, he suggests that the future of biology and medicine will be characterized by collaborative efforts and shared data and knowledge. As such, he points to the need for standardization in order to allow for comparability and consistency in health information. Reviewing the historical state of standards uptake and development efforts, he suggests that meaningful use may be a transformative effort that moves health care in this direction.
Martin LaVenture, Sripriya Rajamani, and Jennifer Fritz from the Minnesota State Department of Health share their account of the opportunities