Current courses in HILS' learning sciences curriculum are described in detail below.
Many of the courses in the program are open to any enrolled University of Michigan student with graduate-level standing.
LHS 610: Exploratory Data Analysis for Health
Students in this course will 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 will 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 will participate in a longitudinal group project spanning the principles learnt during the course using real-life healthcare data sets.
Contact: Karandeep Singh, MD, MMSc
LHS 611: Knowledge Representation and Management in Health
This course 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 who complete the course will become familiar with important knowledge engineering technologies and standards. They will also have mastered foundational methods necessary for more advanced study and mentored research in collaborative knowledge representation and management.
Contact: Zach Landis-Lewis, PhD, MLIS
LHS 621: Implementation Science in Health 1
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.
LHS 622: Learning Cycle Capstone
This course includes developing processes and tools to disseminate findings from the learning cycle capstone project. Other course highlights will focus on methods to evaluate, scale-up, spread, and sustain successful interventions based on strength of clinical evidence, organizational and provider readiness to change, and system-level adoption. This course will be offered Spring/Summer term.
Contact: Caren Stalburg, MD, MA
LHS 631: Learning Analytics: Foundations and Applications
In this course, we will address 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 broadly interested in learning in the classroom, in the home, or on the shop floor.
Contact: Andrew Krumm, PhD
LHS 641: Quality Improvement in Healthcare Systems
This course 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 will include examples and application at Michigan Medicine. The course will help participants perform successful QI activities in healthcare settings.
LHS 650: Health Infrastructures Pro Seminar 1
This course 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: Rachel Richesson, PhD, MPH, MS, FACMI (on-campus course)
LHS 660/SI 648/HMP 648: Evaluation and Research Methods for Health Informatics and Learning Systems
This course provides a foundational introduction to empirical methods, both quantitative and qualitative, that will be applicable to the study of health infrastructures and learning systems. As such, it offers a broad overview that will enable students in the PhD program to begin formulating their interests into researchable problems, and make informed choices of the more advanced research methods courses they will need to pursue their research agenda.
Contact: Charles P. Friedman, PhD
LHS 665: Applied Biostatistics for Health Researchers
This is a PhD-level 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.
LHS 668/SI 542/HMP 668: Introduction to Health Informatics
Introduction to concepts and practices of health informatics. Topics include: a) major applications and commercial vendors; b) decision support methods and technologies; c)analysis, design, implementation, and evaluation of healthcare information systems; and d) new opportunities and emerging trends.
Contact: Allen Flynn, PhD, PharmD
LHS 671: Ethics and Policy Issues for Learning Health Systems
Bioethics is an enterprise in ascendance. In the early 1960s, there were individuals concerned with moral questions occasioned by medicine and medical research, but they were not known as bioethicists, nor did they have the institutional support of centers for bioethics, professional journals, government commissions, or graduate programs and professorships. Today bioethics is part of the landscape of the life sciences: “ethics committees” are now mandatory in American hospitals; all federally funded research that involves human beings or animals must be reviewed by a board constituted to protect the subjects of research; a plethora of seminars offer training in bioethics for those who need, or wish, to offer ethical advice; bioethics courses are now a regular part of the curriculum at universities, colleges and medical schools. Students in this course will learn about the social sources of morality; the organization of professions; the politics of science, medicine and biotechnology; the interface between law and ethics; the place of religion in pluralist societies; the sociology of science; and the social uses of bioethics in the complex context of learning health systems.
Contact: Raymond G. De Vries, PhD
LHS 700/HS 700: Applied Biostatistics for Clinical Practice
This 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.
Contact: Mathew Davis, MPH, PhD
LHS 712: Natural Language Processing on Health Data
This course 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: Implementation Science in Health 2
Students in this course will expand on and apply 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
LHS 750: Health Infrastructures Pro Seminar 2
This capstone-style course 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: Jodyn E. Platt, MPH, PhD
For more information about how these courses fit together, read about the Health Infrastructures and Learning Systems curriculum.