The main objective of this course is to provide a basic level of knowledge of auditing in a computer and information technology (IT) based environment. In particular, the course will cover: a) a broad knowledge of the risks and exposures introduced by computer based information systems; b) the types of controls that may be used to reduce such risks to an acceptable level; 3) a framework for and case based practice of controls evaluation in a computer based information system; 4) the impact of computer controls on audit strategy; and 5) the opportunities and risks associated with computer assisted audit tests throughout the audit.

This course will also focus on the understanding and management of the risks associated with computer based information systems. It covers potential means to provide control and how to perform audits in these environments.

The broad objectives of this course are: 1) To develop your understanding of the decisions made and methods used by auditors when verifying management's assertions in corporate financial statements; 2) To obtain an appreciation of the role of the auditing profession in a changing society with the ability to critically evaluate current issues facing auditors and the auditing profession; 3) To further develop problem solving, critical thinking, analytical skills professional judgment and professional skepticism; 4) To enhance your business acumen (systems, controls, risk, etc.) 5) To expand your integrative thinking and abilities; 6) To continue to develop your enabling competencies; 7) To obtain a greater understanding of the general assurance framework and assurance standards; and 8)To obtain a greater knowledge of specific assurance topics such as data management and analysis.

To describe this course in another way, MGT2225H is "MGT1323 plus plus plus.." The first plus — is to add a second layer to auditing technical knowledge previously acquired. This involves revisiting the core materials covered in MGT1323H and adding more illustrations and more professional judgment to certain core materials. The second plus — is to integrate more accounting and more unusual assurance situations. The third plus is to bring in special topics such as standard setting; auditing not-for-profit organizations along with other assurance services. Each “plus” adds layers to the basics acquired in 1323 — what is sometimes referred to as “layered learning” and further develops your technical and enabling competencies.

Auditing is more than just knowing technical material. A good auditor has high-level thinking skills to exercise judgment and apply, analyze, synthesize, and evaluate information effectively. This course will provide a solid framework to organize your thinking. This course presumes that students have acquired a conceptual base in accounting and auditing in their preceding courses and are prepared to deal with more complex issues. This course will build on the technical sections of the CPA Handbook — Assurance (and Accounting), and current developments in assurance in Canada and internationally.

This course focuses on decision making within the financial reporting environment in Canada and internationally. Emphasis is placed on identifying, interpreting and analyzing appropriate Generally Accepted Accounting Principles (IFRS and ASPE) within a case environment in order to enhance problem solving skills and the development of professional judgment. In order to promote integration between accounting and other subject areas such as Auditing and Reporting (MGT1323), Business Finance (MGT1330), Communications (MGT1160), Team Building and Integration and Professional Decision-Making (MGT1181), there will be two integrative initiatives involving these courses/subject areas.

This course continues where MGT2250H left off, focusing on decision making within the financial reporting environment in Canada and internationally. We will continue to place emphasis on identifying, interpreting and analyzing appropriate generally accepted accounting principles within a case environment in order to enhance problem-solving skills and develop professional judgement. More complex issues such as employee future benefits, leases and taxes will be examined and therefore, there will be an increased emphasis on quantitative analysis.

The course addresses two views of Management Control Systems (MCS) which describe managers' guidance of an organization toward its strategic objectives.

In the first view, strategy is designed and translated into plans after which MCS tracks the execution of the plans arising from the strategy. If environmental changes are predictable, strategy can be developed first and MCS can follow this first concept. In the second view, strategy may begin with a plan but it evolves from interactions between the environment and the lessons learned from MCS' feedback.

The view that works best depends on the environment in which the entity operates: But if the environment change rapidly and somewhat unpredictably, then experimentation guided by MCS's is essential. Complexities arise when the environment changes in ways that require changes in the judgmental social influences underlying an organization's MCS.

The course will contrast Management Control Systems and mechanical control systems. In both, the central control problem is of GOAL CONGRUENCE. MCS are more complex and judgmental than mechanical control systems, so the course will seek to cast light on the greater complexities of MCS using perspectives on the political and cultural dimensions as well as technical challenges of management systems.

The goal of financial accounting theory is to provide a set of principles and framework to explain existing accounting practices, and to predict behaviours of stakeholders who prepare, regulate, or use accounting information. This course focuses on the important accounting research and theory developments over the last four decades. We will illustrate the implications of the existing research for future accounting practices using real business examples and cases.

A mainstream of accounting research investigates the economic, social, and institutional forces that influence management's choice of accounting policies. Understanding how investors use and interpret accounting information is critical to guiding future financial reporting and accounting policies. The overarching objective of this course is to develop a good understanding of accounting research to enable a critical assessment of the problems facing the accounting profession now and in the future.

Finally, financial reporting and accounting practices continue to evolve in response to the emerging of new technologies and the advances in society, governance, and economies. We will explore how new technologies and other emerging economic and social issues may affect future accounting practices in the annual MMPA Conference.

The course covers the theory and application of models of business valuation and of mergers and acquisitions. It examines alternative approaches to valuation: Discounted Cash Flow, Relative Valuation, and Contingent Claim Valuation. Although the various approaches of valuation are not mutually exclusive, there can be significant differences in outcomes depending upon the model used. The course analyzes the reasons for such differences, and helps identify the correct model in specific real-world contexts. The course also applies the basic principles of valuation to mergers and acquisitions. It analyzes the determinants of mergers and acquisitions, potential synergies from acquisitions and their valuation.

In this course we will focus on financial planning, with an emphasis on the interaction between the financial and strategic plans of the enterprise. Topics will include financial analysis and forecasting, as well as various aspects of working capital management. We will refresh on the underlying technical materials and then apply financial decision making tools to a variety of practical business situations, using case analyses.

Taxation has an important effect on business and investment decisions. This course is designed to integrate the taxation knowledge and skills gained in MGT2206H, MGT2207H, and MGT2208H with the other technical competency areas of the CPA Competency Map through the use of integrative case simulations.

To complete the CPA Professional Education Program (PEP), a candidate must complete six modules: two core modules, two elective modules and two capstone modules. The Capstone modules are culminating courses; in them, a candidate demonstrates what they have learned over the course of the CPA PEP. Both modules are common to all CPA candidates and are taken after successful completion of the core and elective modules. The MMPA program is unique in that students enrolled in the MMPA program are exempt from the earlier modules and MMPA candidates are allowed to the complete the Capstone Integrative Module as part of their program. Whether an MMPA student plans to pursue a CPA designation or not, the Capstone Simulations that CPA candidates are required to complete are consistent and aligned with the learning objectives and mission of the MMPA program. Accordingly, all MMPA students will participate in this integrative module and this course is a “Capstone” course of the MMPA program.

The focus of this course is on Strategy and Governance (SG) and Management Accounting (MA). Any organization must have controls and activities in place to ensure that its strategic objectives and goals are met. Underlying these controls and activities are issues involving strategic decision-making, effective governance, risk management, and performance evaluation. This course will integrate these issues and other important areas of SG and Management Accounting, such as business valuations, revenue and cost management, and management systems and controls, with other topics covered in other courses using integrative case simulations.

The course is designed to integrate the technical materials learned in performance measurement (financial and management accounting), assurance, tax, finance, information systems, and organizational effectiveness with the practical experience obtained by students to date. The primary objective of the course is to simulate real professional situations, giving students an opportunity to apply technical knowledge and professional judgement to such situations. Application skills will be developed through the use of case materials. An important secondary objective is to develop case writing skills and an approach to writing professional examinations. Given the structure of the MMPA program in response to changes in the CPA program, this course will have a greater emphasis on assurance.

The objective of this course is to expand upon your theoretical background in Finance and to apply these analytical tools to a broad range of investment and financing decisions.

Topics to be addressed in this course begin with Financial Planning and Long Term Financing with Debt and Equity, Practical aspects of Capital Structure Policy, Rights, Warrants and Convertibles and Project Finance. We will also cover International Treasury Management Issues and Multinational Capital Budgeting.

This course will introduce the fundamental concepts of information and communication technology for those students with a health science background, but no formal training in computer or information technology. The course will cover material that is relevant to health informatics and focus on the understanding of hardware and software systems. We will emphasize on the proper design and specification of health information systems. We will provide you a sufficient background to understand the technical details of healthcare ICTs and apply this knowledge in the design and specification of systems.

Course goals: Learn how computers work, as well as file and data structure. Learn how computers and applications communicate over a network. Understand the methods and constraints for communicating health data. Learn the methods for storage and communication of multimedia information in health care. Explain the methods and constraints for providing remote health care. Understand the best practices for securing health information. Explain how technology is developed, implemented and maintained in healthcare institutions. Understand key modelling standards used in the management of health technology.

Learner objectives: upon successfully completing this course, students will be able to: 1) Explain the usage of computer networks for distributed health services. 2) Discuss advanced health technology concepts with stakeholders. 3) Model a computerized solution for a decentralized health care process.

In Complexity of Clinical Care, the implications and practical application of the outputs of AI and Machine learning are discussed in class, and in select assigned readings. This class provides an overview of how clinicians can use the outputs of these methods to benefit clinical care. Students complete an assignment where they shadow a clinician and learn about some of the clinical challenges and questions experienced by the clinician. In a final assignment, students propose solutions to these observed challenges and questions. These solutions may require AI and/or machine learning methods.

Learner objectives: 1) Enhance understanding of the structure and function of the Canadian health care system and roles of various health professionals. 2) Improve awareness and understanding of the complexity of clinical data collection, processing, management, and use, throughout the patient/consumer-health professional encounter. 3) Understand the culture of health care, and how culture may influence care delivery and information processing by health professionals across settings. 4) Increase awareness of health professionals' experience with information systems and barriers to successful adoption. 5) Appreciate the interaction among organizational processes, information sharing and impact on care delivery and health professionals experience in various clinical care settings. 6) Enhance understanding of the powerful role that informatics plays in clinical health care.

This course is designed to provide an introduction of basic concepts and recurrent themes in Health Informatics (HI)- an emergent discipline that deals with the collection, storage, retrieval communication, and use of health-related data, information, and knowledge. During the course we will explore a number of topics central to understanding of the field including the motivation for HI; Biomedical data, information and knowledge; technological support for decision making (including predictive analytics, machine learning, and artificial intelligence); the main types of information systems in health care and their design; and organizational and societal issues.

Objectives: students who participate in this class will get exposure to recurrent themes and IT applications in Health Informatics. Students should be able to: 1) Understand the scope and breadth of Health Informatics. 2) Understand how information and communication technology can be used to capture, store, analyze, and disseminate health and clinical information in order to improve quality, safety, and efficiency. 3) Understand how technology may be used to support decision-making processes in health care. 4) Apply theoretical concepts from social and information sciences in the design, implementation, and evaluation of health informatics initiatives. 5) Discuss societal, organizational, and ethical issues that surround the application of technology in health care settings. 6) Be able to analyze health informatics initiatives and discuss their strengths and weaknesses.

This course is designed for students to understand the issues associated with the use of data management technology and analytics solutions in the health care system. This includes systems and technologies used to generate, harvest, and store clinical data and methods used to create predictive models (including but not limited to methods associated with machine learning). Furthermore, issues related to delivery of predictive analytics and implementation of algorithms in care settings along with clinical, business, and ethical challenges will be explored. In addition, an overview of the issues within the health industry that are driving the use of data, will be reviewed, including population health management, clinical decision support, and advanced research. The goal is for students to be able to gain experience in the description, architecture and implementation planning of data infrastructure in the health care system along with providing a strong foundation in regard to analytics lifecycle and methods.

Objectives: students will enhance abilities to: 1) Describe and conceptualize data infrastructure used in the health care system, including classical and non-classical sources of data and the technologies and methods used to harvest and store clinical data. 2) Utilize statistical and machine learning tools to create and validate predictive models and present analytics results using visualization tools. 3) Identify and problem-solve the organizational, clinical, and ethical implementation challenges associated with predictive algorithms in health care. 4) Gain the ability to position data management and advanced analytics in the context of health system challenges and business models.

Health informatics (HI) has traditionally been focused on technology for health care providers. However, HI is now transforming health care on many other fronts, such as by addressing consumers' needs for health information (i.e., consumer health informatics). This course will provide students with an overview of the role of consumer health informatics in changing the face of our health care system. Consumer health informatics trends and applications such as artificial intelligence, will the explored, and relevant theoretical frameworks for the creation of consumer health informatics will be reviewed. Another emerging area of HI is public health informatics. This is the application of information and communication technology to the field of public health to support and enhance public health practice and business processes, with the ultimate goal of improving population health.

The course will provide students with an overview of the function and activities of public health agencies and authorities in Canada, which will allow for a better understanding of the need and uses of technology in public health practice and research for syndromic surveillance, immunization management, etc. Populations around the world face different health challenges and live within different health care systems. This course will provide examples of the use of HI to improve health in various regions across the world (i.e., global health informatics). This will provide students with a broad perspective of the potential applications of HI appropriate for populations around the world. An overarching theme throughout the course will be the ethical and societal impact of consumer, public, and global health informatics.

Objectives: students will: 1) Gain an understanding of the breadth, relevance, and emerging trends of consumer, public, and global health informatics applications in improving health and health care.2) Examine and analyze select current consumer, public, and global health informatics projects underway nationally and internationally. 3) Compare and evaluate current consumer information technologies. 4) Gain an understanding of the role of health information systems, such as disease registries and surveillance systems in supporting and enhancing public health activities and improving population health. 5) Gain an understanding of the structure, function and activities of public health agencies in Canada.

This course will address the socio-technical challenges of introducing information and communication technology into health care settings. The course will cover contrasting strategies in the successful adoption and deployment of systems by introducing the fundamental concepts of human factors and the principles and strategies associated with organizational change management. The course will focus on psycho-social and behavioural issues and how they affect the design and usability considerations related to clinical applications and devices. Students will learn about how artificial intelligence can be used to support individual behaviour change and its application in precision medicine and personalized care. Case examples will be utilized to demonstrate issues of human-computer interaction in clinical settings. Students will be provided with an opportunity to conduct usability testing, a clinical workflow analysis, clinical process design and engineering, and determine the potential impact of introducing online clinical information tools. End user engagement strategies to influence successful adoption of clinical information systems will also be discussed.

Objectives: 1) Adoption of ICTs in complex socio-technical environments. 2) Human factors principles — Cognition, human performance and behaviour. 3) Human factors and Human-Computer interaction (HCI) — mental models, iterative user-centered design and methods. 4) Clinical and departmental workflow analysis. 5) Process design and engineering in relation to the introduction of clinical computing. 6) Assessing cultural readiness within organizations. 7) Integration of ICTs into clinical practice settings and related strategies. 8) Determining an effective device strategy for the deployment of clinical information systems. 9) Structures to support organizational change including supporting roles and communication tools. 10) End user engagement to secure probability of buy-in and successful implementation of clinical information systems. 11) Technical, organizational, and individual issue management — change leadership, disruptive technologies, innovators, diffusion of innovation.

The required practicum will provide an opportunity to apply the theory and knowledge gained in course work directly in a health care related organization. Students are required to spend a minimum of 600 hours involved in appropriate, supervised field practice for 2.0 FCEs. While it cannot be guaranteed to students, the professional status of the MHI is recognized within the industry and we will endeavour to seek practicum arrangements that offer paid positions. Some examples of positions that may be available in a Health Informatics practicum include Health Information Analysts, Technical Specialists, Technical Architects, Program Coordinators, Project Managers, Special Projects and Team Participants. Examples of HI skills that would be practiced include knowledge of computer and technical applications in health care, pharmaceutical, finance, human resources and telecommunications; problem solving in software engineering, change management or project management, corporate strategizing, facilitation, resolution and crisis management; management skills such as facilitating team effectiveness; leadership through participation and contribution on project teams or committees; communication skills; increase job knowledge; and writing and/or reporting skills. Throughout the practicum the students are expected to record and reflect upon their experiences and to engage in regular discussion with their practicum supervisor. While it cannot be guaranteed to students, the professional status of the MHI is recognized within the industry and we will endeavor to seek practicum arrangements that offer paid positions.

This capstone course is designed for students to apply critical thinking and knowledge built throughout the MHI program to the process of engaging theoretical frameworks for solution architecture within real-world situations. The goal is for students to gain experience in translating knowledge through strategic and best-practice based methods to address 'wicked problems' currently experienced within the informatics spectrum, ranging from the challenges of existing implementations to meeting the potential for AI in health care. Guests are subject matter experts bringing such cases as AI and ethics, policy and hospital governance, and health care communications. Capstone projects include opportunities to problem solve in live settings, to explore solutions with public and private sector interdisciplinary case partners.

Objectives: 1) Students will learn to employ strategic thinking to navigate 'wicked problems' currently experienced with health systems. 2) Students will enhance abilities to apply MHI learning via strategic frameworks that enable effective short and long-range problem solving in working situations. 3) Discovery of environmental impacts: working as a group and individually, students will collaborate to identify and articulate relevant issues effecting the uptake of digital health technologies and related processes. 4) Distillation of strategic insights: students will leverage their MHI competencies developed to date, evidence and best practices to synthesize and integrate research and a range of knowledge, including grey literature, as it relates to proposing viable solutions. 5) Development of strategic directions: students will collaborate to produce viable and pragmatic case responses and capstone project deliverables that address key drivers and disruptors within a real-world context.

This course is designed to give students a working knowledge of different types of data in health care, health data governance, data privacy, data standards, data quality, and selected applied statistical techniques relevant to health care settings. Through this course, students will review common statistical methods used in health research and get familiarized with using SAS to implement these methods for data analysis.In addition, students will learn about clinical data sciences. The emphasis will be placed on the fundamental of clinical data sciences, related skills and conceptual understanding of data analytics techniques (Regex, SQL, RapidMiner). The goal is for students to gain experience in practical statistical and data analytics techniques to handle and manage their daily professional tasks.

This course provides students with an introduction to the theory and practice of project management. It is intended to give students grounding in project management techniques as a preparation for participation in practice. The emphasis will be on practice versus theory; but, grounding in theoretical concepts is important to the Health Informatics Professional as well. This course is intended to prepare students to participate in, contribute to, lead, and succeed in future health informatics projects. Students will combine past of current experiences in projects together with insights from the course textbook and complimentary readings to develop new understandings and knowledge. In addition, this course is intended to integrate concepts learned in other foundational courses in the Health Informatics program.

Objectives: 1) Demonstrate a basic understanding of project management principles and practices. 2) Apply basic project management techniques and choose the appropriate project management supporting tools. 3) Function effectively on a project team of any size and as a project manager for small to medium sized projects.

There is little debate that health information systems have transformed clinical practice and the patient experience. Health information systems hold the promise of improving the flow of information, the coordination and integration of services, and the quality and safety of care. These systems, however, are often imperfect solutions implemented in complex environments. The true impact of health information systems on the health care system still remains relatively unknown. For the many implementations of health information systems, there are relatively few evaluations and a paucity of high quality research studies to assess the impact of health information systems within a wide range of contexts. In addition, the digital landscape is rapidly changing with the emergence of big data and digital tools such as machine learning, process automation, predictive/preventive analytics, and artificial intelligence. This course is designed to demystify the evaluation process and give you the tools that you need to build a solid evaluation plan for every new eHealth project that you work on.

Objectives: students will enhance their abilities to: 1) Understand the various approaches, tools and techniques used to evaluate health information systems. 2) Appropriately apply evaluation and research tools required to implement an evaluation plan. 3) Formulate and assess the merits of a health information system evaluation plan based on project objectives and goals.

This Practicum Extension supports students' ongoing learning and contribution at practicum placement sites. The course is designed to build on work and reflection to date, as achieved via the MHI2005Y Practicum course. The Learning Contract, Discussion Board, and Journal are repeated elements of that course, and the Practicum Report is a document to be prepared to evaluate both practicum and extension work. Note: there is one final evaluation due from preceptor. There are no live group workshops for this course; however, students are welcome to communicate with the course instructor, for any reason related to assignments and/or extension experience throughout the duration of the course.

The goal of the course is to help students gain a better understanding of performance measurement in health care and the importance of health informatics in supporting performance measurement systems. 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.

Objectives: to understand performance measurement frameworks and models that are currently being applied across the health care system, when and why to implement them (what to measure and why). 1) To describe different methods for identifying, selecting and validating specific types of performance measures (how to measure). 2) To become familiar with emerging issues in the calculation, reporting, and uptake of individual components of performance measurement frameworks by a range of stakeholder groups and in a variety of health care settings (appropriateness, feasibility, and relevance of measures and frameworks).

This is a new elective course intended to introduce students to the many types of data and analytical methods now available that will enhance our ability to investigate and explain the health of communities. These include data that are relevant to measurement of the social economic and genetic determinants of health, the quality and outcomes of health care programs and health care interventions. The quantity and variety of relevant data have increased substantially in the last decade and now include data from: health care administration, electronic medical records, diagnostic laboratories, censuses, vital statistics, environmental exposures, disease and device registries, research data-bases and bio-repositories. To this may be added relevant information extracted from social services, taxation records, education, justice, and corrections services. This is a rapidly changing field. The aims of the course are to introduce students to the different types of data, to provide an overview of the different analytical approaches and to assess the potential value of these big data sets by examining a number of examples of their use.

Objectives: the aims of the course are to provide students with an overview of the different types of data, the different analytical approaches, and to assess the potential value of these big data sets by examining a number of examples of their use. 1) Taxonomy of health data, characteristics of structured and unstructured health data. 2) The value of individually linked data. 3) Different analytic approaches to 'wide' and 'deep' data. 4) Data security and privacy, data sharing, de-identification, and governance. 5) Working with distributed data networks. 6) Examples of the use of big data in health and health care. 7) Examples of the use of big data in policy evaluation.

A picture is worth a thousand words. Shear amount digital information collected in health care brings opportunities and challenges at the same time. Decision-makers are challenged to take timely actions with this data yet are not equipped with required tools to help them in this process. Proper visualization of data empowers them in this task. In this course, we will introduce the foundation concepts of data visualization such as proper use of different graphs. The course will cover the complete life-cycle of data visualization including requirement analysis, data preparation, graphing, validation and sustainability plan. We also cover both best practices and latest trends such as interactivity, story-telling, and visual analytics that currently drive the demand in the market. It will include hands-on exercises using the best BI tools as identified by the Gartner's Magic Quadrant and group activities to augment kinesthetic learning.

Objectives: after successful completion of this course, the students will be able to identify the requirements for answering a specific question in health care, graphically representing the evidence with a proposed action plan in an engaging story-based format that is simple, appealing, timely, and sustainable to derive best decisions.