This course will introduce students to Bayesian data analysis. After a thorough review of fundamental concepts in statistics and probability, an introduction will be given to the fundamentals of the Bayesian approach, including a look at how computer simulation can be used to solve statistical problems. Students will learn how to use the brms package in the R statistical software environment to carry out Bayesian analyses of data commonly seen in health sciences. Bayesian methods will be covered for binary, continuous, and count outcomes in one and two samples, for logistic, linear, and Poisson regression, and for meta-analysis.

Objectives: by the end of this course, students will: 1) Understand what is meant by a "Bayesian Analysis" and how it differs from a typical analysis under the frequentist framework. 2) Understand the role and importance of Markov Chain Monte Carlo in modern Bayesian methods. 3) Understand how modern Bayesian models are fitted. 4) Be able to fit Bayesian models to common types of study designs and data types. 5) Know what aspects of the Bayesian analysis are an essential part of a statistical report. 6) Have worked through some case studies (in lectures, tutorials, and as part of assignments). 7) Have developed expertise in using the brms program within the R environment.

This course will cover topics in measurement theory and application beyond the basic principles covered in HAD5302H Measurement in Clinical Research. Specifically, it will cover the theory, application, and interpretation of more advanced approaches and statistical techniques such as confirmatory factor analysis, structural equation modeling, item response theory approaches, measurement error, minimally clinically important differences, response shift, conjoint analysis, discrete choice experiments, and the mapping of measures to utility functions as they apply to measurement theory. The course mainly will be structured such that the first week will provide the theory and with the subsequent week(s) providing discussion of study design issues and interpretation of data output. Students will not be analyzing data.

Objectives: the intent of the course is that students will understand the theory of the approach such that they can consider when the application is appropriate to use and critique work published work from a methodological and interpretive perspective.

At the end of the course, the student will be able to develop a complex analysis plan to answer a clinical research question, to carry out the analyses using the statistical package SAS, to verify the appropriateness of the analyses based on the findings, and to report and interpret the results.

In particular, the student will be able to: i) understand the purpose of regression analysis, and be able to differentiate between various forms of regression including linear, logistic, poisson, and Cox-proportional hazards regression; ii) understand the requirements for each regression method and be able to adjust the methods to account for or examine: clustering within data structure/sampling frame; hierarchical structures within data; repeated-measures and longitudinal data; iii) be able to evaluate the validity of the results from each type of regression based on statistical criteria; iv) understand different methods for variable selection in regression models; v) be able to interpret and present the results from each type of regression model in a manner that is meaningful to clinicians and applied health scientists.

This course will enable students to conduct and critically appraise mainstream advanced evidence synthesis methods encountered in medical research. Students will be introduced to important topics in evidence synthesis, building on their previous introductory training on basic concepts of meta-analysis. By the end of the course, students will be able to conduct frequentist and Bayesian meta-regression, pairwise and network meta-analysis, properly conduct individual patient data meta-analysis, and meta-analyze diagnostic test accuracy estimates. The course will use a balanced combination of lectures and practical work to introduce concepts and provide students with supervised hands-on experience on these analysis methods. Course assignments will assess the students' ability to appropriately select and conduct the analysis methods taught, and to develop a brief protocol of a future evidence synthesis project they would like to conduct using one of the analysis methods taught.

At the end of the course, the student will be able to understand and apply more advanced biostatistical techniques in the setting of complex observational studies. The student will be able to design and develop a statistical analysis plan, to carry out basic analysis using the statistical package SAS, to verify the findings, and to interpret and report the results in a manner that is meaningful to clinicians and applied health scientists. The course will be given from an applied point of view; more theoretical understanding will be touched upon, but only to the extent of useful in applications and for understanding the models. This course will cover 3 advanced topics:

BLOCK I. Complex Survival Models: Aim is to understand and analyse multivariate survival data when subjects transit between multiple states; including time-dependent covariates recurrent episodes of disease time-to-failure of two “linked subjects” (e.g. kidneys, hips, twins).

BLOCK II. Longitudinal Models and Multi Level Models: Aim is to understand and analyse linear and generalized linear models in the presence of longitudinal and repeated measurements hierarchical structured, nested or clustered data.

BLOCK III. Prediction Models: Aim is to design a prediction model in the setting of binomial outcome and survival data. The process includes building a model for prediction purpose applying validation tools developing a user friendly tool /calculator to be used by clinicians in a day-to-day practice.

The course objective is to teach students to write for medical and health care journals. Students will learn how to frame a paper, how to write clearly, how to prepare the tables and figures, how to succinctly discuss the results, and how to deal with peer and editorial review. Each student is required to bring a topic to pursue as manuscript during the time period of the course. The weekly sessions will consist of a class discussion of the manuscript in preparation with specific feedback from the instructor. This will require each student to continuously write and edit their papers throughout this course. Students planning to publish their research will benefit the most, if their data has already been analysed and is ready for presentation. Students may also wish to write papers that have no new data (e.g. commentaries, editorials, reviews). Students who already have theses prepared are encouraged to use that work to convert into peer review papers. By the end of the course, students will have a manuscript that is suitable for submission to a journal.

Strategic decision makers in today's health services organizations face considerable challenges, many of which are associated with their dynamic operating environments. This course introduces contemporary strategic management theories and practices that are used to guide health services organizations through strategic planning cycles. Through selected readings, case studies, and case presenters, we critically examine the main concepts of strategic planning and management including strategy formulation, implementation/execution and evaluation; strategic "fit" or alignment; the role of governance; and strategic leadership. In-class exercises focus on applying strategic planning tools. Course assignments afford students opportunities to apply these concepts to their workplaces and to the creation of a new health services organization or initiative.

Learner objectives: the overall objective of this course is to provide you with the conceptual tools and the practical skills to enable you to formulate, implement, and critically evaluate organizational strategy and to contribute to the underlying strategic planning processes in organizations in which you work. Upon successful completion of the course, students will be able to: 1) Differentiate between the various motivations for developing a strategic plan. 2) Distinguish among alternative contemporary conceptualizations of strategy. 3) Identify and relate critical steps in the strategic planning process. 4) Anticipate and mitigate common barriers to strategy implementation and leverage facilitators. 5) Critically analyze the fit between organizational design and strategy. 6) Explain and integrate the essential elements of successful organizational strategies into your organization's strategic plan. 7) Acknowledge, value, and capitalize upon the different perspectives of executive, management, and front-line workers during strategic planning processes. 8) Analyze the structure and processes of governance in health care organizations. 9) Anticipate the future challenges for strategic planners in health care. 10) Devise a viable strategic plan based upon knowledge of the strategic planning process and critical elements. 11) Critically evaluate the merits and feasibility of strategic plans using an array of contemporary evaluation tools.

Learner competencies (competencies refer to the National Center for Healthcare Leadership Competency Model): analytical thinking; initiative; organizational awareness; innovative thinking; process management and organizational design; strategic orientation.

In health care, information is a resource equal in importance to financial and human resources. Epidemiology offers valuable methods for compiling and analyzing data that is crucial for managing health care programs, organizations and systems. Epidemiology is the study of the distribution and determinants of diseases and injuries in populations. Managerial epidemiology, which is the focus of this course, is the application of epidemiological perspectives and methods to health care management. Although health care managers are developers, collectors, transformers, users, and disseminators of information, there has been relatively little discussion about how they can enhance their selection and use of information. Many managers feel overwhelmed by massive amounts of data, much of which provides little assistance in meeting the demands of their jobs. This dilemma becomes more pronounced as provinces attempt to increase the coordination and integration of delivery systems necessitating the coordination and integration of information from a variety of sources within institutions and the community. The purpose of this course is to explore how managers can identify what they need to know, how they can access the information they need, and how they can use the information they obtain in order to be more effective decision makers. These issues will be examined in relation to the internal processes of individual organizations, the identification and accommodation of population health service needs, and the formulation of provincial and national health policy.

Learner objectives: upon successful completion of the course, students will be able to: 1) Identify relevant health and socio-economic information sources to construct specific community and/or population profiles. 2) Describe the relationship between social and environmental characteristics and health needs; how they impact health outcomes; and how this knowledge can be used to inform management and policy decision-making. 3) Judge the accessibility, quality, uses, and limitations of available health information in supporting effective and efficient management of health care organizations and related government agencies. 4) Develop a needs assessment for a specific population and geographic area to identify opportunities for and obstacles to the provision of health services. 5) Establish performance criteria for new health or social services programs that impact health outcomes for a specific population. 6) Recognize the implications of transmissible diseases and environmental risks for population health planning and decision making using epidemiological methods and tools. 7) Explain and interpret epidemiological analysis applied to decision making. 8) Display confidence in using health related methods and data for decision making. 9) Present and defend the creation of a new cross-health sector enterprise. 10) Demonstrate the ability to work in a team environment and hold others accountable for their performance.

Learner competencies (competencies refer to the National Center for Healthcare Leadership Competency Model): analytical thinking; collaboration; communication skills; community orientation; information seeking; initiative; innovative thinking; performance measurement; self-confidence.

This course will provide a general introduction to the science of evaluation and prepare students for more advanced courses. Students will acquire foundational and theoretical knowledge (via lectures and readings) and practical skills (tutorials and group project) about program evaluation. Students will learn about different evaluation frameworks, designs for program evaluation, research methods (qualitative, quantitative, mixed) and the strengths and limitations of different approaches.

Objectives: 1) Understand the theoretical and practical underpinnings of evaluation science. 2) Learn about key considerations for different evaluation types and frameworks. 3) Appreciate the limitations and challenges of different approaches to evaluation. 4) Acquire foundational, theoretical, and practical knowledge in preparation for more advanced courses.

The course focuses on the knowledge and skills necessary for health care organizations to strategically measure and improve quality and patient safety. Developing better outcomes at the same (or reduced) costs is a crucial strategic objective for all health care organizations. While most health care organizations have developed quality improvement programs, these often have had limited impact in improving health care. New skills and ideas have entered healthcare that provide the information, methods and tools for managers and front line staff to improve work, to secure better outcomes for patients, and maintain or reduce the costs of providing services. These skills and knowledge require that we analyze and improve work processes, and understand and respond to the needs of patients and other customers. The work in this course will center on understanding the nature of these improvement concepts, developing knowledge about their application in health care organizations, and providing students with an orientation to and experience with basic concepts and principal methods.

Objectives: upon successful completion of the course, students will be able to: 1) Explain the underlying theoretical framework for continual improvement of health care. 2) Explain why quality improvement strategies are critical for health services organizations. 3) Describe and give examples of the roles and responsibilities of health services managers, health professionals, and staff for quality improvement and patient safety. 4) Apply basic improvement methods and tools for analyzing work processes and for assisting groups in developing remedies for improving these processes. 5) Explain methods for testing changes and improving work processes. 6) Create strategies for developing customer knowledge and assess that knowledge for the design or redesign of health care. 7) Understand the nature of variation in health care and its role in improving quality of care. 8) Interpret a control chart and be capable of identifying the uses of a control chart. 9) Explain why analyzing and improving work as a system is critical for effective, safe, and efficient care. 10) Identify how organizations need to create a culture that fosters innovation and continual improvement. 11) Analyze how organizational learning contributes to successful organizational performance. 12) Understand how organizations need to assess risk and deal with organization failures. 13) Understand the challenges related to addressing and improving patient safety and high reliability in health care organizations. 14) Analyze the strengths and weaknesses of different approaches and methods for improving the quality of care.

Learner competencies (competencies refer to the National Center for Healthcare Leadership Competency Model): analytical thinking; innovative thinking; interpersonal understanding; process management and organizational design.

This is the first in a two-course sequence in health care financial management, intended to impart a foundation of accounting and finance knowledge necessary to manage health care organizations and make informed decisions. This first course introduces learners to managerial and financial accounting concepts. The second course, HAD5733H Health Services Finance, focuses on finance topics, such as financing and investment decisions. This course will focus heavily on managerial accounting concepts, to provide learners with the tools necessary to ensure that their organization produces the information that will support their responsibility for decision-making. As a health care manager, it is important to understand what financial reports are prepared by the organization, what information these reports provide and how this information is used.

Objectives: in this course you will learn: 1) Financial Accounting: a) The types of financial reports required by organizations and the type of information in those financial statements. b) The theory and foundation of financial accounting and the 'rules' for the accumulation and reporting of financial information. c) Key financial performance measures and the interpretation of financial performance. 2) Managerial Accounting: a) The concepts and vocabulary in measuring costs, depending on the needs of the decision maker. b) The implications and use of management accounting tools and information for short term and long term decision making. c) Management accounting applications of forecasting, budgeting, and variance analysis. 3) Performance Analysis: a) Perform a performance analysis of a chosen health care organization using financial and managerial information from provincial datasets.

Learner competencies: accountability; achievement orientation; analytical thinking; communication skills; financial skills; performance management; self-confidence.

The objective of this course is to introduce students to quantitative managerial skills. Increasingly managers face decisions that require reliable information and a clear understanding of their agency's profile. Quantitative managerial skills allow for this information and understanding to be provided; it makes possible better decisions in human resources, marketing, operations, finance, accounting, and other functional areas. Objectives of the course are achieved through a combination of Readiness Assessment Tests and critical analysis of evidence based articles and the impact on decision making. Course assignments offer students opportunities to analyze a Patient Satisfaction data set using SPSS and to develop their evidence based decision making skills.

Learner objectives: upon completion of the course, students will be able to: 1) Value the use of statistical analyses for performance management and evaluation of health care services and programs. 2) Display confidence in ability to use quantitative information for management decision making. 3) Reconstruct administrative problems into researchable questions. 4) Evaluate how the characteristics of descriptive statistics can impact management decision making. 5) Select and apply appropriate inferential statistical tests. 6) Relate the results of a hypothesis test with nominal data to "real-life" decision making situations. 7) Demonstrate the ability to work collaboratively in a team environment and hold others accountable for their performance.

Learner competencies (competencies refer to the National Center for Healthcare Leadership Competency Model): accountability; analytical thinking; collaboration; information seeking; innovative thinking; performance measurement; self-confidence.

This course is designed to teach the learner the basic model of microeconomics that underlies much of the thinking and perspective of health economics. The concepts of utility maximization in a perfectly competitive world with no asymmetry of information will be presented, along with the market imperfections and distortions exhibited by the market for health care to guide the learner in interpreting the work of health economists. Specifically, the price wedge between consumers and suppliers that exists with health insurance, along with the asymmetry of information, will be discussed in detail and repeatedly. After introducing the theory and noting how the market for health care differs from other markets, the course will move onto review 6 themes: the impact of public health insurance in Canada, incentives facing physicians, technology and cost effectiveness analysis specifically related to drugs, behavioural economics at play in health, and conflicts of interest. Prior knowledge of economics will be helpful but is not required.

Learner objectives: upon completion of this course, students will be able to: 1) To understand the basic model of microeconomic theory and utility maximization, the assumptions that underlie that model and what happens when they are violated. 2) To understand how Canadian health care and the people who deliver it have been affected by public insurance and payments over the last 60 years. 3) To understand how incentives work to change behaviour of both consumers and suppliers, and the nuances of the difference between intrinsic and extrinsic motivators. 4) To understand what cost-effectiveness analysis is, and what it is not. 5) To understand the uses and limitations in evaluating health care technologies. 6) To be able to identify the parties who are affected by a policy or practice intervention, and the incentives that motivate those parties. 7) To understand how behaviour is motivated by risk and framing, as well as some of the cognitive psychological concepts that influence behaviour. 8) To understand the impact of conflicts of interest and how self-discipline and personal ethics usually fails to curb that influence in health care. 9) At the end of this course, the learner should be able to apply and defend economic concepts that are incorporated in decision making for health care administrators at the policy, public health, and clinical levels.

Learner competencies (competencies refer to the National Center for Healthcare Leadership Competency Model): accountability; achievement orientation; analytical thinking; collaboration; information seeking; innovative thinking; performance measurement; self-confidence.

This will be a weekly seminar course that will introduce advance topics to MSc and PhD students in the study area of, or with interest in, health informatics research. This course will be highly interactive and focus on how to design, conduct, and report evaluations in Health Informatics, with "real-world" examples.

The objective of this course is to provide students with a sound understanding of the fundamental principles and the challenges of conducting evaluation and research in Health Informatics.

The course examines the theoretical and practical dimensions of knowledge transfer and exchange (KT&E). The subject is viewed from a number of perspectives and provides students with an understanding of what knowledge transfer and exchange is, how to assess when knowledge is ready to be transferred, the impacts organizational/cultural and decision-making factors play in the uptake of knowledge, and the skills and knowledge involved in the effective practice of knowledge transfer and exchange. Given the priority to knowledge transfer now being given by granting agencies, governments, and the health care decision-makers, the course will help prepare students involved in research to meet the changing demands and expectations attached to their research. The course will assist students to incorporate knowledge transfer and exchange principles and practices into their thinking about the conduct and communication of their research. for those considering an in-depth program of knowledge transfer and exchange focused research, this course will provide a sound introduction to the field as a whole. The course will use an interactive format and will integrate didactic presentations, case examples and application of the material in independent project work. Learning will take place through various modalities including lectures, small group exercises, and full class discussions. The course instructors' experience and work in mental health and addictions health services research and consulting will be augmented by the expertise of guests from different health areas who will bring their experience as producers, users or brokers of knowledge. Students will be responsible for leading the discussion on the course readings.

Objectives: 1) To develop core knowledge of knowledge transfer and exchange issues, concepts, models, and methods. 2) To understand the uses of knowledge transfer and exchange in research, policy making, management, and clinical practice. 3) To learn how to apply knowledge transfer theory and practice to student research. 4) To learn techniques to help in the measurement and evaluation of knowledge transfer and exchange.

This is an elective for students in graduate research programs who wish to gain a better understanding of performance measurement in health care and the methods available to develop performance measurement systems and specific indicators of performance. The course will provide an overview of different models for performance measurement, indicator development strategies and a discussion of issues specific to several stakeholder groups. Students working in other public sectors, such as education, may also find the course useful.

Objectives: To understand performance measurement frameworks and models that are currently available across the health care system (what to measure and why). To describe several different methods for identifying, selecting and validating specific types of performance measures (how to measure — soundness, relevance).

To become familiar with emerging issues in the calculation, reporting, and uptake of individual components of performance measurement frameworks by varying stakeholder groups (appropriateness, feasibility, and relevance of measures and frameworks).

Health Economics is concerned with the study of resource allocation within the health sector and between that sector and other sectors. This course is designed to introduce participants to an array of economic evaluation methods used to assess health care programs, services, technologies, and other interventions. Prior knowledge of economics is not required; however, participants are expected to possess quantitative skills (e.g., the ability to undertake statistical analyses). Upon completion, participants will not only have analytic skills that are applicable to economic evaluation, they will also know how economists approach important issues in health services research and decision-making.

Objectives: 1) To introduce learners to different types of economic evaluations. 2) To acquaint learners with the approaches and viewpoints that applied health economists bring to health services research. 3) To apply economic evaluation techniques to important contemporary issues in Canadian health services research and decision-making.

This course explores what it means to be a leader moving from personal mastery of leadership behaviours to change leadership at the organizational level. The course uses the four competencies of Goleman's Emotional Intelligence model as a framework, progressing from a focus on self-assessment and management to one of social awareness and skills. You cannot lead others until you know who you are, what you believe in, and why someone might want to follow you; and conversely, others will not follow you if do not understand their motivations, values, and concerns and are not able to manage your relationships with them. In other words, we must first understand and manage ourselves, before we can understand and successfully manage our relationships with others.

This course is designed to ensure that learners appreciate the vital role leadership plays, at all levels of the organizations, in managing and sustaining change for improved health outcomes and performance. Each course module is designed to provide a set of evidence-based learning experiences that will facilitate the learner's leadership development through reflection, practice, and the formation of action goals. Topics covered include the five practices of exemplary leadership; styles of conflict management; communication for engagement, collaboration and enhanced team performance; the role of influence in furthering change; and models of change leadership and management.

Objectives: upon successful completion of this course, students will be able to: 1) Indicate their leadership development needs and construct a set of goals that are challenging but achievable. 2) Exhibit responsibility for their own performance. 3) Identify and align actions to shared values. 4) Describe their image of the future and inspire others to share a common vision. 5) Recognize opportunities to challenge the status quo and improve performance. 6) Create a climate in which people are willing to innovate and learn from mistakes. 7) Identify actions that allow others to excel in their work. 8) Recognize the accomplishment of others in ways that are meaningful to them. 9) Build collaboration, teamwork, and trust. 10) Explain diverse points of view by actively listening to both emotion and content. 11) Develop critical approaches for constructive negotiation and conflict management strategies. 12) Diagnose issues and resolve same using influence strategies. 13) Plan and execute an organizational change.

Learner competencies: accountability; achievement orientation; change leadership; collaboration; impact and influence; information seeking; interpersonal understanding; organizational awareness; professionalism; self-development; talent development; team leadership.

This is the second in a two-course sequence intended to impart to generalist administrators a knowledge of finance and accounting necessary to manage health care organizations. The first course, HAD5723H, focuses on managerial accounting topics. This second course will concentrate on corporate finance topics. In addition, it will integrate corporate finance and accounting theories, institutional knowledge of health care finance, and applications to specific problems.

Objectives: the course will be taught in three major sections with the following objectives: 1) Investments (or capital expenditures): a) Achieving a conceptual understanding of valuation and the effects of project selection, asset acquisition, financing methods and the time value of money; b) Developing an ability to evaluate the desirability of a project, based on net present value calculations and considerations of non-cash values; c) Gaining a facility with the use of spreadsheet technology in conducting financial analyses. 2) Financing: a) Achieving an ability to estimate the cost of various sources of financing, based on projected cash flow; b) Gaining an ability to evaluate leasing versus buying of an asset. 3) Other topics: a) Gaining an understanding of how to develop a strategic long range financial plan; b) Gaining an understanding of capital and operations financial planning for a long-term care facility; c) Gaining an understanding of the financial aspects of public-private partnerships.

Learner competencies: achievement orientation; analytical thinking; financial skills; initiative; innovative thinking; self-confidence; strategic orientation.

This course introduces quantitative methods and their applications to health care decision-making. The use of these methods has recently become an active and growing area of practice and research in contexts including wait list management, patient flow, population demand estimates, health human resource management, and the coordination of resources for elective and emergency services. This course is designed to provide health care decision makers with an introduction to several useful quantitative methods that can provide insight and support for complex decisions. We will cover the following topics: mathematical model formulation; linear programming and optimization; forecasting; queuing theory and simulation modeling; project management; introduction to decision analysis.

This class is not intended for learners who have a background in operations research.

Learner objectives: upon completion of this course, students will be able to: 1) Reconstruct management problems into mathematical models for optimization. 2) Graphically describe the mathematical models to understand the relationship of decision alternatives. 3) Develop Excel spreadsheets to solve mathematical optimization problems. 4) Appraise and justify the value of resource allocation decisions using sensitivity analysis. 5) Interpret retrospective data to predict future states. 6) Develop models using simulation and queuing theory that predict wait times, service demands, and resource utilization. 7) Manage project deadlines using quantitative tools. 8) Display confidence in using quantitative methods to make health care decisions and hold people accountable for making high quality recommendations. 9) Be willing to face quantitative facts even when they are counter-intuitive.

Learner competencies: accountability; achievement orientation; analytical thinking; initiative; innovative thinking; performance measurement; project management; self-confidence.

This course will provide learners with a comprehensive working knowledge of implementation science. Also known as knowledge translation, this subject focuses on the effectiveness and optimizing of approaches and strategies to enhance research utilization through understanding of the complex, interacting factors that can influence health care delivery and outcomes. This knowledge is relevant to health system leaders, continuing education planners, guideline implementers, practicing clinicians, health care managers, and health services researchers. The course will review how educational, social, patient, organizational, incentive, and embedded approaches and strategies can be applied to close the gap between best evidence and practice.

Objectives: at the completion of this course, participants will be able to: 1) Explain the meaning of implementation science/knowledge translation. 2) Identify and explain various theories underlying implementation science/knowledge translation. 3) Describe determinants that influence the utilization of knowledge, practice and technology. 4) Discuss the applicability and mechanism of action of various implementation strategies. 5) Understand the effectiveness of approaches/strategies and how they can be tailored/optimized. 6) Design a quality improvement program or research study involving implementation.

The course is about advanced methods for estimation and uncertainty of cost-effectiveness statistics. The focus is on techniques to create and explain economic information in person-level data (e.g., from a clinical trial or an administrative data set). Students must have taken HAD5730H and be familiar with statistical techniques like regression. Upon completing this course, participants will be able to create and explain the results of a cost-effectiveness analysis of person-level data.

Objectives: this course is designed to attain three general objectives as well as a series of specific competency objectives: 1) To introduce learners to regression as a technique for creating cost-effectiveness estimates. 2) To introduce learners to regression as a technique for handling uncertainty in cost-effectiveness analysis. 3) To acquaint learners with advanced techniques from regression that can be applied to cost-effectiveness analysis.

Upon completion of this course, learners will be able to: 1) Have a better understanding of economic evaluations and their potential roles. 2) Identify multiple ways of creating cost-effectiveness estimates and characterizing their uncertainty; understand their strengths and limitations. 3) Analyze person-level cost-and-effect data in a way that improves the chances of it being published. 4) Explain the results of their cost-effectiveness analysis in a way that improves the chances of it being understood. 5) Write the "economics" section of a grant proposal (e.g., CIHR) in a way that improves the chances of it being funded.

This course will provide intermediate level instruction in the use of qualitative methods in health services research, clinical research, policy, and medical education research. It is intended as part of a suite of qualitative methodology courses available to IHPME students. Students who are in the initial to mid stages of designing and conducting their thesis research will be exposed to intense instruction related to issues in field research, including: study design; data collection; analysis; and writing. Students will be expected to come to class prepared to actively engage in group discussions and to discuss their own thesis work. Students who complete this course will be able to begin conducting qualitative research.

Objectives: after completing this course, students will: 1) Be able to choose and apply the various philosophical foundations, traditions, and methods grouped under the rubric of "qualitative research" and appreciate the complexity of doing qualitative research. 2) Have experience with and able to apply the main techniques used for gathering qualitative data. 3) Have experience with and be able to apply the different analytic strategies used in qualitative research, including coding and development of themes. 4) Have experience with and be able to write up the results of a qualitative study.

A health administrator needs to understand the legal environment within which management decisions occur. The law is often seen as ambiguous and amorphous. This course will provide you with an overview of key legal and ethical concepts and their application to the health field. Among the topics to be addressed are an overview of the law and legal process, business organizations, both "profit" and "not-for-profit," litigation, consent and capacity, contracts, medical records, privacy, tenders, product liability, and research. Specific ethical concerns and situations will be woven throughout the course. This course is not intended to turn health administrators into lawyers.

In this course, students will engage in the theory and practice of mixed methods research. In the past several decades, Mixed Methods Research (MMR) has developed dramatically. Over this timeframe, it has been associated with several different definitions. The working definition we will use in this course involves the collection and analysis of both qualitative and quantitative data in a way that either merges the data, has one build off of the other, embeds one within the other or is developed around a mixed methodological philosophical or theoretical orientation that informs all aspects of the study. Throughout the course a range of mixed methods research designs will be discussed with examples that draw from applications in health research. Students will work through a MMR project that has been pre-designed for this class.

Objectives: 1) To identify key philosophical and theoretical issues in MMR and multiple examples of mixed method designs. 2) To contrast key features of quantitative and qualitative research as they relate to MMR. 3)To articulate and reflect on their own perceptions about the current state of MMR.4) To apply and demonstrate knowledge about collecting and analyzing data within an original MMR project.

The growing focus on learning and accountability in Canada and internationally has resulted in an increasing need for evaluation approaches to understand and assess if interventions/programs work, how they work, and what can be done in the planning and implementing phase to make them work. Given the complexity of some of the health interventions, the designs and approaches required to evaluate need to go beyond standard clinical trials and often will involve the evaluator working with the policymakers and program planners right at the formulation of the intervention/program. This class will focus on development, implementation and evaluation of a variety of complex policy and programmatic interventions, which aim to improve outcomes at the patient, provider, population and system level.

Topics to be covered in this class include: the role of program theory and why we need to think theoretically about complex interventions; the relationships between program theory, threats to validity and evaluation design; stakeholder engagement, needs and evaluability assessment, types of evaluation (process and outcome evaluation) with different approaches and how they respond to complexity (approaches will include realist evaluation and developmental evaluation); varieties of evaluation design including experimental and quasi-experimental designs, economic evaluation.

Objective: at the end of the course, for a given intervention, students will be able to design and execute an evaluation plan that includes consideration of key evaluation questions; is appropriate to the program theory of the intervention; addresses key threats to design validity; and addresses policymaker and practitioner perspectives.

This course is designed to provide an introduction to econometric methods; that is, the basic principles of regression model development and testing that underlie much of applied health economics and health services research. The starting point is the fact that a great number of possible data generating processes yield very similar looking data series. The course deals with how to determine which data generating process, from among the range of possible ones, has actually generated the data you are working with. To that end, the course deals with application of statistical tests and procedures in the context of distinguishing between potential regression models. Students will learn about important methodological considerations when working with both survey and administrative datasets. It is assumed that students have a basic training in statistics.

The goal of this course is to provide students with the necessary tools to address issues that involve the empirical analysis of observational (i.e., non-experimental) data. The focus of the course is on estimating treatment effects and we will review several different approaches that can be helpful in doing so. Theory will be presented and, whenever possible, applied examples will also be presented.

Objectives: at the end of this course, students will be able to use these tools to: 1) Choose the right research question. 2) Use appropriate data and statistical methods to address the question. 3) Interpret results.