The U-M Medical School Department of Learning Health Sciences Health Infrastructures & Learning Systems (HILS) program empowers learners to transform health systems through data science, implementation science and quality improvement.
Our courses emphasize applied learning, collaboration, and real-world impact, preparing students to drive meaningful change in diverse settings.
Current courses in HILS' learning sciences curricula are described in detail below. Many courses are open to any enrolled University of Michigan students with graduate-level standing.
With a mix of guest speakers and instructor-led sessions, LHS 601 is designed for first year HILS students to synthesize, integrate learning, and foster professional development and lifelong learning. It meets in Fall and Winter for 1.0 credit hour each semester.
Contact: Gretchen Piatt, MPH, PhD
Students in LHS 610 learn foundational topics in data science focused on healthcare data. The course is based on two large themes: (a) understanding and becoming familiar with healthcare data, and (b) making inferences based on data.
Students develop a working understanding of R, one of the most widely used languages for data science, and an introductory understanding of several other tools used in analyzing healthcare data.
Students participate in a longitudinal group project spanning the principles learnt during the course using real-life healthcare data sets.
Contact: Andrew Krumm, PhD, and Keith Feldman, PhD
LHS 611 provides an intensive introduction to methods and topics for knowledge representation and management, with an emphasis on symbolic methods and the social context of knowledge use in learning health systems.
Students become familiar with important knowledge engineering technologies and standards. They also master foundational methods necessary for more advanced study and mentored research in collaborative knowledge representation and management.
Contact: Zach Landis-Lewis, PhD, MLIS
Many evidence-based health care interventions fail to produce successful outcomes when implemented into practice. Implementation and dissemination sciences comprise a multidisciplinary set of theories and methods to improve and expedite translating research evidence to everyday health-related practices. Both disciplines are systematic approaches to understanding how healthcare interventions can be better integrated into diverse practice settings, and emphasize direct engagement with institutions and communities where health interventions take place. In order to optimize public health, it is essential to not only understand how to create the best interventions, but how to best ensure that they are effectively delivered within clinical and community practice.
Contacts: Gretchen Piatt, PhD, MPH, John Donnelly, MSPH, PhD, and Rama Mwenesi Musalia, MSE, PhD
LHS 622 is designed to challenge students to reflect on concepts learned throughout their previous HILS coursework — specifically focusing on the learning health system — to explore issues associated with learning health systems in low-resource settings, both domestically and globally.
Drawing upon the expertise of faculty and researchers across the department, across the University, and from partners in Ghana and Kenya, this course is designed to challenge assumptions about high- vs. low-resource settings and help students grapple with the question of what equity truly means for learning health systems.
Contact: Cheryl Moyer, PhD, MPH
LHS 631 addresses efforts to use novel data sources and diverse analytical techniques to improve learning opportunities in K-16 and professional settings. This course is for students who are interested in learning in the classroom, in the home, within clinical settings, or in health systems more broadly.
Contact: Andrew Krumm, PhD
LHS 641 addresses QI in healthcare using a multi-level systems perspective. The course addresses both conceptual foundations of QI and direct application of QI tools and processes.
Course materials include examples and application at Michigan Medicine. The course will help participants perform successful QI activities in healthcare settings.
Contacts: Andrew Krumm, PhD and R. Van Harrison, PhD
LHS 650 provides theoretical and practical perspectives on the evolution of major infrastructures, focusing in particular on health and information infrastructures.
The course begins by examining how infrastructures emerge, evolve, and decay in the context of social systems. Students gain fluency in the language of infrastructure as a technological and social phenomenon linking people, processes, policy, and technology. The course focuses on the organization of health as a problem of infrastructure and considers how this perspective might inform research, practice, and the capacity for change.
Contact: Jodyn Platt, PhD, MPH (on-campus course) or Timothy Pletcher, DHA (online course)
Read the LHS 660 Syllabus | Schedule
LHS 660/SI 648/HMP 648 examines health informatics, and the related concept of learning health systems, as an empirical science and as “people science.” The course focuses on formal studies of applications of information resources applied to health care, population health, and personal health. Sometimes these studies focus on the information resource itself, but more often they focus on the resource along with its user community and the context in which it is used. These studies can be conducted while an information resource is under development, in trial use, or after it is deployed in routine service. All methods will be introduced and discussed with reference to case study papers selected from the informatics literature.
Contact: Charles P. Friedman, PhD
LHS 665 is a biostatistics course that covers fundamental statistical concepts and methods for researchers who need to analyze health and/or healthcare data and interpret research. Major topics include descriptive statistics, probability theory, statistical inference, hypothesis testing, correlation, regression (linear and logistic), survival analysis, reliability/validity of diagnostic tests, and epidemiological study designs. Relevance of analytic techniques to healthcare will be demonstrated via a series of 10 labs that focus on applications. Students will become proficient in basic data management and analysis using a statistical software program including data importation/exportation, management of datasets (creating new variables, merging and appending datasets), and statistical analyses. Effective presentation of quantitative results in tables and graphics will be emphasized throughout the course.
Contact: Matthew A. Davis, MPH, PhD
This course explores the relationship between learning health systems and health equity. It will cover: 1) historical conceptual foundations of health and healthcare equity and justice, 2) the role of LHSs in addressing health equity problems, 3) effective partnerships with health equity advocates, and 4) design considerations for equity-centered LHS projects.
Contact: Francesca Williamson, PhD
LHS 700 is a clinically-oriented, graduate-level biostatistics course that covers fundamental statistical concepts and methods for health professionals who need to analyze clinical data and interpret research. Major topics include descriptive statistics, probability theory, statistical inference, hypothesis testing, correlation, regression, survival analysis, and diagnostic test performance. Relevance of analytic techniques to healthcare will be demonstrated via a series of assignments that focus on clinical applications. Students will become proficient in basic data analysis using a statistical software program including data importation/exportation, management, and analyses. Effective presentation of quantitative results in tables and graphics will be emphasized throughout the course
NOTE: This is a School of Nursing course that is cross-listed by LHS
Contact: Mathew Davis, MPH, PhD
LHS 701 familiarizes HILS students with important research in learning health systems.Seminar sessions are conducted by faculty and students who discuss projects addressing topics such as implementation science, informatics, artificial intelligence/machine learning, policy and ethics and a host of other areas currently significant to learning health systems.
Contact: Janice Firn, PhD, MSW, HEC-C
LHS 712 explores the challenges and advances in health informatics to extract actionable information hidden in free text in electronic records, published literature, and social media.
Contact: VG Vinod Vydiswaran, PhD
LHS 721 expands on and applies concepts learned in Implementation Sciences I and other Learning Health Sciences courses to build on their knowledge of how dissemination and implementation science fits into the LHS learning cycle. Students will learn and apply practical skills to implement and evaluate complex, multi-level interventions and initiatives that aim to improve health care practice and policy. Students will complete a small-scale project related to implementation of evidence-based practice and prepare reports for multiple audiences.
Contact: Amy Kilbourne, PhD, MPH
The focus of LHS 731 will vary from term to term based on the interests of HILS faculty and students.
For Winter 2025 contact: Rachel Richesson, PhD, MPH, MS, FACMI
LHS 750 is capstone-style course that requires students to synthesize the theoretical and applied learning from the HILS core curriculum. Infrastructure II focuses on health infrastructure at various levels of scale and comparative analyses. The course will focus on case studies and will invite speakers to present current research and practice in health infrastructure. Students will develop an independent project that will focus on recognizing barriers to adaptive learning, and on infrastructural approaches to problem solving.
Contacts: Rachel Richesson, PhD, MPH, MS, FACMI, or Alexandra Vinson, PhD
Read the Preliminary LHS 760 Syllabus
LHS 760 will focus on the two most commonly used qualitative methods: ethnographic fieldwork and in-depth interviewing. Students will have a chance to practice these methods, to learn about their epistemological foundations, and to discuss how the affordances and limitations of these methods shape knowledge-making in social research.
Contact: Alexandra Vinson, PhD
