MANUSCRIPT: Making the Case for Continuous Learning from Routinely Collected Data
In “Making the Case for Continuous Learning from Routinely Collected Data,” the authors suggest that in order to achieve better health, patients and clinicians will need to view every health care encounter as providing an opportunity to improve outcomes. The paper cites widely-reported examples of routinely collected digital health data being applied to improve services, inform patients, avoid harm, and speed research. Developed by individual participants from the IOM’s Clinical Effectiveness Research Innovation Collaborative, it asserts that patients and the public are the most effective advocates for resetting expectations that their data be used to advance knowledge and support continuous learning. Citing examples of efforts to engage patients and clinicians in continuous learning efforts, the authors see broader application of these approaches as critical to ensuring the success of a learning health system in achieving better care, lower costs and improved health.
via Making the Case for Continuous Learning from Routinely Collected Data – Institute of Medicine.
Written by Brian S McGowan, PhD
Brian is a research scientist and educational technologist. He helped transform Pfizer’s Medical Education Group and previously served in educational leadership roles at HealthAnswers, Inc.; Acumentis, LLC.; Cephalon; and Wyeth. He taught graduate medical education programs at Arcadia University for 10 years. Dr. McGowan recently authored the book "#socialQI: Simple Solutions for Improving Your Healthcare" and has been invited to speak internationally on the subject of information flow, technology, and learning in healthcare.
