In addition to meeting the specific course prerequisites, registering in HRM courses requires enrolment in HRM or eHealth/Health Policy programs, plus the permission of the instructor.
Expandable List
Basic statistical concepts and techniques as they apply to analysis and presentation of data in biostatistical and epidemiology practice. The course covers: graphical presentation of data, elementary probability, descriptive statistics, probability distributions and introduces hypothesis testing using parametric and non-parametric methods. Specific techniques covered include z-tests, t-tests, ANOVA, contingency tables, regression and correlation.
Prerequisites: enrolment in HRM Msc or Master of Public Health (MPH), or by permission of the instructor.
This course is designed to allow students to either tailor their learning to the specific topics in clinical or health care, health policy and research methodology relevant to their clinical or health care and research interests and do advanced work in this area. The topic studied may be synergistic with the students’ thesis topic but must not represent a major overlap with it. Under the guidance of a faculty member, the student will critically examine the pertinent literature. Only one of HRM 722 or HRM 705 can be counted towards the minimum course requirements of the HRM program at the MSc and at the PhD levels.
Prerequisites: HRM 721 and one of HRM 730 or HRM 751; enrolment in the HRM graduate program
This is a course on the economics of health, public health and health care, with special emphasis on the Canadian health care system. We will examine the nature of health care as a commodity, health care financing and insurance, the demand for health and health care, the behaviour and organization of health care providers, methods for evaluating health care programs and interventions, issues of efficiency and equity, the economics of health behaviour and selected other topics. We will give special attention to the attributes of health care markets and the implications of those attributes on the financing, funding, organization, delivery of health care services and public policy. In doing so, we will analyze the roles of externalities, risk, imperfect information, asymmetries of information and institutional arrangements in affecting behaviour in healthcare, as well as the formulation and implementation of health policy. Throughout this course, we will examine the extent to which the health care sector can be analyzed using standard neo-classical economic methods.
Prerequisites: Must be enrolled in graduate plan in HRM or Master of Public Health (MPH)/eHealth/Health policy programs, plus permission of the instructor
Antirequisite(s): HRM 787; students with a strong background in microeconomics should consider taking HRM/ECON 788.
This course will cover advanced topics in research methodology, biostatistics, epidemiology or public health that are not covered in other HRM courses. The course will provide in-depth practical and hands-on learning on a diverse variety of topics and provide students with an opportunity to gain understanding of rare epidemiological principles. Students will learn to design, analyze and report a variety of epidemiological studies using a variety of tools and software.
Prerequisites:
At least two of the following courses: HRM 721, HRM 702, HRM 723, HRM 730, HRM 733, HRM 743, HRM 751 (or equivalent) and permission of instructor
Master of Public Health (MPH) students – any two of: PUBHLTH 701, PUBHLTH 702 and PUBHLTH 704 and permission of instructor
The course is not recommended in the first year of MSc or PhD in the HRM program; antirequisite: HRM 787.
This course examines the application of economic principles to policy-relevant questions in the area of health and health-care. Topics will include applied health economics, economic correlates to health, demand and supply of healthcare and insurance, healthcare system financing, economic evaluation in the pharmaceutical/medical devices industries, costing methodologies, cost-effectiveness and cost-benefit analyses, quality-adjusted life-years (QALYs), decision analysis, modeling and means by which to improve value-for-money in the health sector.
Prerequisites: HRM stream of MBA or permission of instructor
Antirequisite: HRM 788
The course will cover the basic concepts in formulating a research question, literature review, study design, selection of study sample, outcome measurement, research ethics and knowledge translation. The course will provide students the opportunity to develop a research question and determine the appropriate research method for a research proposal. Research designs that will be discussed include randomized clinical trials, cohort and case-control designs and the evaluation of diagnostic test properties.
Prerequisites: Enrolment in HRM or eHealth/Health Policy programs, plus permission of instructor
This special topics course will present leading edge thinking regarding controversies in health, health care and population health research. Only one of HRM 705 or HRM 722 can be counted towards the minimum course requirements of the HRM program at the MSc and at the PhD levels. Students taking this course cannot also receive credit for any subsequent regular course offering on the same topic.
Prerequisites: HRM 721 and HRM 730 or HRM 751 and the permission of the course instructor
This is a Level II course in statistical methods, concentrating on regression models of various types. Topics covered include various main techniques of simple and multiple linear regression and techniques such as: use of dummy variables, covariance adjustment, residual analysis and assessment of model fit. A similar agenda is followed for logistic regression, appropriate for binary outcome variables. We also consider some advanced topics and related methods.
Prerequisites: HRM 702 or permission of instructor
This tutorial-based course will cover a broad range of eHealth topics from the perspective of health care delivery. Topics include a definition of eHealth health care data; hospital and primary care information systems (i.e., electronic health records [EHR] systems); specialty components of an EHR system; how health professionals use data; human/cognitive factors in development and implementation of eHealth applications; standards, vocabulary and nomenclatures and how used; aggregation of health information, especially for research purposes, patient information systems and consumer eHealth; research and evaluation of eHealth applications and research using eHealth applications; implementation issues and privacy, security, and confidentiality; and the future of eHealth.
Prerequisites: N/A
Review the course outline (PDF)
This is an overview course aimed to introduce graduate students to the science and practice of knowledge translation and exchange (KT). This course will be of interest to graduate students who wish to pursue an academic career in the field of KT, students whose primary research is in another domain but wish to strengthen their KT-related skills and students who are interested in doing KT as part of their professional activities. This course is part of the Health Services Research field of the HRM graduate program.
Prerequisites: HRM 721 or permission of instructor
Principles of subjective assessment in topic areas ranging from educational evaluation to patient-based measurement of health attitudes or health status. Discussion includes: principles and methods of constructing rating scales and approaches to assessing the measurement properties of such scales. Special emphasis on assessment of reliability and validity — various forms of reliability (test-re-test, interobserver, split-halves), distinction between reliability and agreement and indirect methods to assess validity of an instrument in the absence of a gold standard. Advanced topics in generalizability theory and Item Response Theory will be introduced. Format is that of lecture, plus small group discussion.
Prerequisites: HRM 702, equivalent introductory statistics course or permission of the instructor
Genetic epidemiology overlaps with molecular epidemiology. It is the epidemiological evaluation of the role of inherited causes of disease in families and in populations; it aims to detect the inheritance pattern of a particular disease, localize the gene and find a marker associated with disease susceptibility. Gene-gene and gene-environment interactions are also studied in genetic epidemiology of a disease. Genetic epidemiology is “a science which deals with the etiology, distribution and control of disease in groups of relatives and with inherited causes of disease in populations” (Morton NE, 1982).
Prerequisites: HRM 702 (or equivalent)
This course will introduce students to the main elements of clinical trial design, execution and analysis. At the end of this course, students should have a firm grasp of clinical trial methodology at a level that would allow them to prepare successful grant applications.
Prerequisites: HRM 721 (or equivalent)
The course is open to all McMaster graduate students in the Faculty of Health Sciences. In recognition of the need for graduate students embarking on research in various disciplines of health science to master the skills needed for writing and publishing in leading journals in their field this course will equip them with essential requirements.
Designed to provide comprehensive insights, HRM 731 covers a spectrum of topics including terminology pertinent to the field, the standard structure of biomedical articles, publication strategies, reporting guidelines, the peer review process, optimal English usage for writing articles, publication ethics, as well as guidance on journal selection, predatory publishing, open-access publishing, and scholarly metrics.
Central to the course is a hands-on approach, allowing students to meticulously craft their own articles under the guidance of experienced tutors. Through iterative feedback loops, students will refine their writing skills and navigate the complex landscape of academic publishing with confidence.
Prerequisites: Enrolment in an FHS graduate program
Randomized clinical trials are the gold standard for testing the effect of a novel intervention. Clinical trials can be expensive, time consuming and can expose subjects to interventions that are potentially harmful and/or ineffective. Standard trial designs generally do not allow for modifications to key design components during the trial but adaptive designs, on the other hand, allow for modifications to be made based on accumulative data or new knowledge that becomes available during the trial. With this adaptive learning nature, adaptive designs can improve the efficiency of the trial and reduce the risk of patients being exposed to harmful and/or ineffective interventions. However, they can be more challenging to design and execute. There are several operational and statistical challenges that must be addressed in order to preserve the integrity of the trial. In this distance education course, we will discuss the principles and characteristics of adaptive designs, the advantages and disadvantages of conducting an adaptive clinical trial compared to a standard, fixed sample design and potential operational and statistical challenges in adaptive designs.
Prerequisites: HRM 702, HRM 721, HRM 730, HRM 733 or permission of instructor
This course will consider important statistical issues relating to the design, analysis and interpretation of randomized clinical trials (RCTs). Specific topics will include issues in large simple trials, factorial designs, cluster randomization, cross-over trials, missing data in RCTs, repeated measures in RCTs, meta-analysis, non-inferiority trials, subgroup analysis, composite outcomes in RCTs, stopping rules, cost-effectiveness analysis, statistical analysis of cost-effectiveness data, survival analysis and new designs in RCTs.
Prerequisites: HRM 702 and HRM 730 or permission of the instructor
Models and methods for research and policy on environment and human health relationships.
Prerequisites: Permission of instructor
This course explores the complex challenges existing within our health system and teaches a design-innovation framework to identify solutions. It uses the aging population and increasing advanced chronic disease as the main case study. Initially, the course examines how major health care services are organized and financed in Ontario, Canada, how this affects care and what are the strengths, challenges and opportunities in the current system. The course then applies design innovation framework to generate system-level solutions. Students will work in groups to identify a problem, learn about its root causes through interviews, design a solution through analysis and present a prototype.
Prerequisites: N/A
This course is a practical “How-To” course in techniques for economic evaluation of health care programs. The methodology of cost-benefit analysis, cost-effectiveness analysis, cost-minimization analysis and health status index models is examined in detail and several applications of each are reviewed during the first-half of the course. During the second-half of the course, each student is expected to complete an economic evaluation of a specific health care program or intervention.
Prerequisites: N/A
This course introduces students to the interdisciplinary field of health policy analysis, providing the concepts and tools needed to be able to critically appraise and carry out policy analyses in a variety of settings. Students are introduced to the field of policy studies, the stages of the policy process and to the different purposes and methods for policy analysis. Through critical examination of key policy analysis concepts and frameworks, students learn how to analyze the relative roles played by different actors in the health system and explore the independent and combined influence of three major determinants of health policy: ideas, interests and institutions. Each week, different concepts and/or analytic frameworks are presented, discussed and applied to a particular problem or case study.
Prerequisites: Permission of instructor
This course provides an overview of the strategies needed for effective biostatistical collaboration with clinical investigators. Topics covered include: strategies of eliciting information required to assist with study design from clinical collaborators; ways to translate the research questions into statistical questions; strategies to facilitate provision of statistical support on design, sampling and analytic plans; approaches of communicating the sampling plan, experimental design, statistical analysis to collaborators; methods to facilitate provision of support on statistical programming; strategies to facilitate provision of help with write-up of methods and reporting of results of studies.
Prerequisites: Registered in PhD HRM with specialization in biostatistics or permission of instructor
This is an advanced course in modeling methods for Health Technology Assessment (HTA). It is a combined theoretical and practical hands-on course that teaches students the essential components of contemporary HTA. Students will be exposed to national and international HTA agencies and government decision making bodies and their HTA guidelines and requirements. The course primarily covers different modeling techniques for economic evaluation, analyses of uncertainty, value of information analyses, Bayesian decision analyses, quality assurance in economic appraisal, budget impact analysis and knowledge translation. There is a heavy emphasis in this course of hands-on learning-by-doing with computer application of ‘real world’ practical examples to cement student learning. Prior knowledge of Excel is essential
Prerequisites: HRM 741 and HRM 737
Health Technology Assessment (HTA) has the tremendous potential to transform the delivery of health care services and improve health outcomes and quality of life for patients. Decisions about whether to purchase and use new health technologies (e.g., drugs, medical devices, surgical procedures, etc.) should be based on high-quality evidence of its impact on health outcomes, the health care system and cost-effectiveness. Payers of health care face the challenge of aligning decision making with the best available evidence. Upon completion of this course, students will be equipped with the skills to evaluate the quality of an HTA, to critically appraise it to make a judgment about a study’s methods, results and conclusions. Additionally, students will gain experience in conducting HTAs and be mindful of the barriers to, and facilitators of, evidence-based decision making in the real world
Prerequisites: HRM 721 or permission from the instructor
This course is designed to prepare students to think creatively and proactively about ethical and legal issues in the design, conduct, analysis and dissemination of research. Topics are divided into two categories:
- Ethical treatment of research participants
- Research integrity.
Sessions will involve case discussion and critical analysis of ethical issues and the relevant principles, guidelines and laws. Exercises will coach students through mock-submission to a Research Ethics Board (REB) and provide insight of how REBs function.
Prerequisites: HRM 721
This course covers the methods of comprehensive syntheses of research evidence. Rigorous review methods will be highlighted, such as searching for potentially relevant articles, selecting primary articles using explicit, reproducible criteria; appraisal of studies; data synthesis; and interpretation. The course uses the framework provided by the GRADE Working Group for evaluating certainty of estimates and present and interpret evidence. The focus of the course is on systematic reviews of interventions, which typically include randomized trials and non-randomized studies that evaluate therapeutic interventions and outcomes. This focus is to ensure that students understand and apply the fundamental processes to conduct a systematic review. The process can be applied to other review topics and study designs (such as diagnostic accuracy and prognosis) which will be briefly covered in the course. Students are required to conduct a systematic review of an intervention during the course. However, students who wish to conduct reviews of other topics will need to ensure they have methodological support in addition to what is provided within the course.
Prerequisites: HRM 721 and HRM 702 or permission of instructor and one-page outline of the topic (PDF)
This course will introduce students to the methodology and statistical concept of diagnostic test accuracy (DTA) meta-analysis. At the end of this course, students should have a firm grasp of methodology of DTA meta-analysis at a level that would allow them to participate in such studies.
Prerequisites: HRM 777, HRM 743 or permission of instructor
This course introduces learners to theoretical traditions and corresponding methods of qualitative research using health and health care research as examples. Specific topics covered include: key paradigms underlying qualitative research, types of research questions best answered by qualitative methods, the role of theory in qualitative research, sampling objectives and procedures, methods of data collection, methods of analysis and interpretation and ethical issues and responsibilities of qualitative researchers. Criteria for evaluating qualitative research will be discussed and applied to specific research studies. Learners will gain hands-on experience using qualitative methods through in-class and take-home exercises.
Prerequisites: N/A
Meta-analytic techniques are applied in a wide range of disciplines including medicine, psychology, sociology, education and economics. The widespread and growing application of meta-analysis to synthesize evidence from studies of diagnosis, intervention and prognosis, as well as its application in health technology assessment, makes it a valuable toolkit for healthcare professionals and researchers. This course covers advanced methodological and statistical topics in evidence synthesis and provides an in-depth practical and hands-on learning on a diverse range of meta-analytic approaches such as trial sequential analysis, individual participant data meta-analysis, meta-analysis of prognosis questions, dose-response meta-analysis, indirect treatment comparisons and network meta-analysis. Students will learn to design, analyze, interpret and report the results of a variety of advanced evidence synthesis methods using a range of software and tools, such as GRADE.
Prerequisites: HRM 743 and at least two of the following: HRM 730, HRM 751, HRM 777 or permission of instructor
An approved one-page project outline must be submitted four weeks prior to the course.
This course provides an overview of core concepts and methods in population health. We will discuss the concept of population health and explore the methods used to define, measure and investigate health outcome and health determinants at a population level.
Prerequisites: HRM 721, HRM 751 and one half-credit graduate course in statistics
The intention of the course is both to introduce students to Bayesian ideas and to equip them to design, analyze and interpret clinical studies from a Bayesian perspective. Instruction will consist of both independent reading and self-guided practice sessions using WinBUGS. The students will be required to have a real project or dataset to use for a project with analysis done using WinBUGS. The project will form the primary basis for learning and implementing the concepts. There will be some weekly meetings for face-to-face discussions with the instructor.
Prerequisites: HRM 702, HRM 723 or permission of instructor
The course is designed to introduce students to the basic concepts and methods used in observational (non-experimental) studies to conduct needs assessments (e.g., prevalence of disease or order), to understand the determinants of health (e.g., association between independent/exposure variables and dependent/outcome variables in analytic research) and to assess the impact of interventions implemented to improve health or alter life quality (e.g., program evaluations). The topics will focus on three broad areas:
- The formulation of research questions and use of theory to explicate the relationships among key variables
- Study design options, sampling, measurement and analysis
- The control of error
Prerequisites: HRM 721 or permission of instructor
This is a Level II course in statistics concentrating on several modeling techniques. Four main regression topic areas:
- Simple and multiple linear regression of continuous outcomes
- Logistic and Poisson regression for binary and count outcomes
- Proportional hazards regression for time to event outcomes
- Advanced regression (multi-level) models for correlated outcomes
The course will use geometry to motivate ordinary least squares (OLS) regression, tie the various models together using generalized linear model (GLM), stress assumptions and thus goodness of fit (GOF) and focus on generalized linear mixed model (GLMM) for correlated data.
Prerequisites: HRM 702
Antirequisites: HRM 723
This course provides learners with a foundation in qualitative research methods with a focus on pragmatic
approaches conducive to mixed-methods research.
Antirequisites: Nursing/HRM 745
This intermediate-level course builds on prior knowledge about qualitative research approaches and their philosophical basis. The emphasis in this course will be on how the approaches affect data analysis and interpretation, as well as presenting findings in written and oral formats. The course is based on active involvement of learners through student-directed discussions and hands-on experiences, guidance and facilitation by graduate faculty with expertise in qualitative research and interdisciplinary collaboration with faculty and classmates.
Prerequisites: HRM/NUR 745 (or equivalent) and/or permission of instructor
This course will cover the main statistical issues in survival analysis. Specific topics of the course are Kaplan-Meier curves, log-rank test, Cox Proportional Hazard Model, Stratified and Extended Cox Model, Parametric Survival Models, Recurrent Events, Competing Risks, Relative Survival Analysis and Model Evaluation. Depending on time and the students’ progress and interests, new advancements in survival analysis will be discussed.
Prerequisites: HRM 723, HRM 731 or permission of instructor; HRM 721 is recommended
The purpose of this course is to apply core epidemiological concepts and develop practical skills in data management, data analysis/ building an epidemiologic model, power and sample size calculations, interpretation of analytic output and potential effect of biases such as confounding on model results, research protocol development, presentation and write-up of findings suitable for publication, and knowledge transfer/media relations.
Pre-req: HRM751/PUBHLTH 701, HRM723/HRM753
This course introduces students to the major concepts and issues involved in mixed methods approaches to tackle important questions in the field of health services and policy. LearnLink is used as the mode of instruction, as well as two classroom sessions at McMaster University. A framework for thinking about mixed methods will be developed that provides guidance to decision-making about when and how to use mixed methods and models to study health services and policy problems. The course will provide students with knowledge of the current controversies and major challenges in the use of mixed methods and models of research. Students are expected to design a mixed method study as part of the course and critically evaluate the design options chosen by a classmate.
Prerequisites: HRM 721/771 and HRM/NUR 745 or HTH POL 747 (or equivalents), or permission of instructor
This is a distance education course offered using McMaster online Avenue to Learn. It focuses on making evidence-based health care recommendations and clinical practice guidelines. The course uses audio-visual presentations, facilitated tutorials, required readings, discussion boards and assignments to highlight the steps of the guideline development process: planning the project, choosing the panel, managing conflicts of interest, defining the scope, finding appraising and summarizing evidence, deciding on the final recommendations, as well as dissemination, implementation and adaptation of guidelines. The course follows the steps of executing one full guideline recommendation and students are required to complete one recommendation with all supporting materials end-to-end.
Prerequisites: HRM 743, having done one’s own systematic review or permission of instructor
This is an advanced course in diagnostic and prognostic test methodology and statistical analysis. For diagnostic testing we will discuss phases of test development, basic and advanced study designs, methodological issues related to choice of population and test verification. In prognostic research we will discuss overall prognosis, risk factor research, prediction modeling and stratified medicine. For both diagnosis and prognosis research, we will consider issues in performing systematic reviews and formulating guidelines.
Prerequisites: HRM 721 and 702
Review the course outline (PDF)
Note: As of spring 2021, this course is evaluated on a pass/fail basis.
This is a basic graduate survey course on the economics of health and health care. Topics include the organization, financing and utilization of health care services. Both theory and evidence relating to patterns of consumer and provider behaviour are examined, as are the functioning and regulation of markets for health services. Major public policy issues in the provision of health care in Canada are identified and the economic aspects of such issues are considered in detail.
Prerequisites: Intermediate micro economics or permission of instructor
This course will provide students with applied secondary data analyses skills to address research questions linked to the social determinants of health across the lifespan. The course will include a:
- Substantive focus on the emergent concepts, methods, frameworks and evidence for examining the role of social factors in shaping health inequalities
- Methodological focus on the use of secondary data analyses to address questions linked to the social determinants of health
Students will be asked to develop and address a research question using secondary data available to the course instructors. Working collaboratively, students will complete an empirical research paper with the purpose of submitting to a peer-reviewed journal by the end of the course.
Prerequisites: Permission of instructor
This course focuses on issues relating to the economics of health and health care. It builds on HRM/Econ 788 and exposes students to more advanced topics and aspects of recent research in health economics. The specific topics presented depend on the instructors for each offering. Recent topics have included methods of economic evaluation and health technology assessment, the economics of work and health, the evaluation of health-care related interventions, advances in the empirical analysis of income and health inequalities, health human resources and the evolution of health from childhood to adulthood
Prerequisites: ECON/HRM 788