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
Dr. McGowan has served in leadership positions in numerous medical educational organizations and commercial supporters and is a Fellow of the Alliance (FACEhp). He founded the Outcomes Standardization Project, launched and hosted the Alliance Podcast, and most recently launched and hosts the JCEHP Emerging Best Practices in CPD podcast. In 2012 he Co-Founded ArcheMedX, Inc, a healthcare informatics and e-learning company to apply his research in practice.
