Courses

Students work directly with a faculty member on a directed reading or research project to broaden their scope of knowledge in a topic pertaining to Health Studies that is not addressed in the department's regular course offerings. Permission required.

Students work directly with a faculty member on a directed reading or research project to broaden their scope of knowledge in a topic pertaining to Health Studies that is not addressed in the department's regular course offerings. Permission required.

Students work directly with a faculty member on a directed reading or research project to broaden their scope of knowledge in a topic pertaining to Health Studies that is not addressed in the department's regular course offerings. Permission required.

Introduces students to the various areas of scientific inquiry that impact human health. It will focus on two main areas: the biomedical research paradigm and the relationship between health and environment. The course will also explore the integration between these areas and the relationship between advancements in science and human condition.

Explores the relationship between health, ethics and the law. It focuses on the following key areas of study: bioethical principles and approaches, selected case and statute law and health-related issues which illustrate the intersection between legal and ethical analysis. This intersection will be explored from both individual and social policy perspectives.

One of the major aims of this course is to help health professionals understand the decision-making aspects (rational and non-rational) in health care. This course reviews decision making theories and quantitative techniques used for supporting decision making in health care, the opportunities they offer and the challenges they face.

This course will strike a balance between theory and application in qualitative research in health studies. We will examine a number of issues surrounding qualitative research as well as four of the most common methods for analyzing qualitative data: Thematic Analysis, Grounded Theory, Narrative Analysis and Content Analysis. Opportunities for experiential learning will be interwoven with the course material.

This course emphasizes the evaluation, design, implementation, and documentation of research in the social sciences. The main goal will be for students to be able to identify and evaluate various research techniques that are appropriate for the questions asked.

This course addresses both the measurement and improvement of quality and patient safety in healthcare organizations. Students will learn the principles and processes of quality improvement (QI) and patient safety including QI theory and tools, the importance of system level factors in understanding patient safety failure, and the role that measurement, leadership, culture, and interprofessional teams play in QI and safety. The principles and practices of quality management will be critically assessed including consideration of current methods used to measure and track quality and safety, the state of empirical support for process improvement techniques, and data quality challenges that are central to the measurement of patient outcome in healthcare. Legal and regulatory issues in healthcare quality and safety will also be explored.

This seminar introduces students to the history and process of public policy making ways ways to evaluate them with a focus on health. Course topics include the origins of public-policy making; key concepts, modes and instruments in the process of public policy making; and constraints on public policy analysis along with critical analyses of relevant cases from the field of health.

This course traces the profound shifts and challenges for understanding health inequities that Intersectionality theorists and practitioners from Black, Indigenous, and Feminist Studies have brought to Health Studies and Disability Studies, including new methodological and theoretical approaches to gender and gender identity, sexuality, (dis)ability, trauma, structural violence, settler colonial studies, and environmental studies.

This course considers health from a human rights and social justice perspective, exploring both domestic and international issues. It focuses on three areas: disability, reproductive technology and HIV/AIDS.

This seminar explores how to conduct critical policy analysis of health equity issues. We explore a variety of theoretical, analytical and conceptual frameworks and multiple levels of analysis. We draw from health studies, policy studies, political economy, political science, sociology, anthropology, geography, philosophy, women's, feminist and gender studies, psychology, and aging studies.

This course will introduce the fundamental concepts and principles of data visualization and its application in healthcare. We will explore the history of data visualization and its current uses in healthcare: from infographics informing patients and consumers, to EHR dashboards aiding providers in decision-making, to detailed epidemiology maps driving policymaking aimed at protecting population-health. Students will learn best practices for designing and evaluating health data visualizations, and learn to think critically about literacy, ethics, and the future of the field. By the end of this course, students will be able to use online tools to create powerful visuals that tell a story and inform diverse stakeholders.

This course will explore the move to evidence-informed decision making in healthcare using implementation science (IS) and knowledge translation (KT) lenses. Perspectives from other related disciplines will also be explored. This course will also explore models of KT involving interactions between decision makers and researchers. The conceptual and methodological dimensions of KT and IS will be discussed.

This course will introduce the fundamental concepts and principles of machine learning and its application in healthcare. We will explore machine learning approaches, health cases in relation to machine learning, and best practices for designing, building, and evaluating machine learning applications in healthcare. Opportunities and challenges that machine learning present for health and society will be covered.