The U-M Medical School Department of Learning Health Sciences' infrastructure research focuses on how society—using technology, information, and policy as tools—require sustainable infrastructures that continuously improves health.
Our multidisciplinary faculty and research staff specialize in behavioral and social science disciplines, including education, psychology, social work, sociology, anthropology, informatics, and linguistics. The collective goal is to build and study learning health systems, with extensive experience starting numerous learning health system initiatives at local and national levels.
Learning Health Systems (LHS) need infrastructure to thrive. Infrastructure in an LHS can help us discover and implement new knowledge to make this process routine.
LHS aims to improve health through the following interdisciplinary research areas:
- Data, computation and analytics
- Knowledge systems
- Implementation and practice
- Infrastructure and systems design
- Policy, culture and ethics
LHS investigates at multiple levels of scale (global, national, regional, community, organizational, individual). Our team of learning health scientists come together to make learning cycles work to enable continuous improvement through cycles of discovery and change.
We coordinate a pan-university Learning Health System initiative, the LHS Collaboratory, which aims to advance research and development of learning health systems at the University of Michigan. Our faculty also participate on coordination teams for numerous regional and national learning health system events.
The hard working faculty and staff of DLHS launched a number of Learning Health System (LHS) initiatives and partnerships that leverage biomedical knowledge and data to facilitate new, more effective kinds of health care delivery infrastructure.
EMERSE (Electronic Medical Record Search Engine) is software system that enables users to search clinical notes from electronic health records such as CareWeb and MiChart, and supports a Clinical Text Analysis Laboratory. EMERSE was developed to help researchers find and extract critical patient details like diagnoses, medications, procedures, and complications, from clinical notes.
EMERSE is led by David Hanauer, MD, MS, FACMI, a clinical informatician professor in the department. Dr. Hanauer is the Informatics Lead for MICHR, and is a key contributor to MICHR's Network-based Research Unit.
The Knowledge Systems Lab is an open platform designed to make medical best practice knowledge computable and readily available for widespread use.
- Patient Data Dashboard Effort: The department received funding from Genentech’s Corporate Giving Support program in 2016 for “A Novel Knowledge-Delivery Mechanism Empowering Clinicians to Improve Patient Experience of Cancer Care.” The project focuses on making actionable knowledge about the patient experience of chemotherapy computable and on using that knowledge to add customizable decision-support to a prototype Patient data dashboard so that clinicians can provide great support to patients who are at home.
- National Institutes of Taiwan Partnership: This initiative helps health care providers make best use of pharmacogenomic knowledge during patient care.
Experts from academia, government and biomedical libraries came together in October 2017 at University of Michigan for the inaugural Mobilizing Computable Biomedical Knowledge (MCBK) conference to explore how to create a scalable knowledge infrastructure that is sustainable and FAIR (Findable, Accessible, Interoperable and Reusable).
