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Frameworks for Integrating Learning Analytics With the Electronic Health Record
Martin V Pusic1, Robert J Birnbaum, Brent Thoma
1Dr. Pusic: Associate Professor of Emergency Medicine and Pediatrics, Department of Emergency Medicine, New York University School of Medicine, New York, NY. Dr. Birnbaum: Assistant Professor of Psychiatry , Vice President, Office of Continuing Professional Development, Mass General Brigham, Harvard Medical School, Boston, MA. Dr. Thoma: Associate Professor of Emergency Medicine, Department of Emergency Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada. Dr. Hamstra: Professor, Department of Surgery, University of Toronto, Toronto, Ontario, Research Consultant, Accreditation Council for Graduate Medical Education, Chicago, IL, and Adjunct Professor, Department of Medical Education, Feinberg School of Medicine, Northwestern University, Chicago, IL. Dr. Cavalcanti: Associate Professor, Department of Medicine, University of Toronto, Toronto, Ontario, Canada, and director of the HoPingKong Centre, University Heath Network, Toronto, Ontario, Canada. Dr. Warm: Professor of Medicine and Program Director, Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH. Dr. Janssen: Senior Research Fellow, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia, and Industry Postdoctoral Fellow, Digital Health Cooperative Research Centre, Sydney, Australia. Dr. Shaw: Professor of Digital Health Faculty of Medicine, The University of Sydney, Sydney, Australia.
Abstract:
The information systems designed to support clinical care have evolved separately from those that support health professions education. This has resulted in a considerable digital divide between patient care and education, one that poorly serves practitioners and organizations, even as learning becomes ever more important to both. In this perspective, we advocate for the enhancement of existing health information systems so that they intentionally facilitate learning. We describe three well-regarded frameworks for learning that can point toward how health care information systems can best evolve to support learning. The Master Adaptive Learner model suggests ways that the individual practitioner can best organize their activities to ensure continual self-improvement. The PDSA cycle similarly proposes actions for improvement but at a health care organization's workflow level. Senge's Five Disciplines of the Learning Organization, a more general framework from the business literature, serves to further inform how disparate information and knowledge flows can be managed for continual improvement. Our main thesis holds that these types of learning frameworks should inform the design and integration of information systems serving the health professions. An underutilized mediator of educational improvement is the ubiquitous electronic health record. The authors list learning analytic opportunities, including potential modifications of learning management systems and the electronic health record, that would enhance health professions education and support the shared goal of delivering high-quality evidence-based health care.
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