MHI2024H

Prerequisite

There is no formal prerequisite course. However, students are expected to come with critical thinking skills, as exemplified in the 5 critical thinking modules provided by Student Life at: https://studentlife.utoronto.ca/task/critical-thinking/

We are looking for a broad cross-section of students from multiple disciplines, and invite Master’s and PhD students from across IHPME, DLSPH, the Faculty of Information, the Munk School and the Rotman School of Management.

Ideally, students should have some prior experience with working with health data or social services data in government or a health services delivery setting. This could be in a decision-making capacity or information support capacity.

Given the limited space, permission of the instructor is required.

Objectives

• Identify the multiple objectives served by data governance;
• Describe the key approaches to governing data flows in Western societies;
• Identify and diagnose data governance gaps in their organization;
• Identify, critically appraise, and apply the appropriate data governance tools to facilitate intra- and inter-institutional data flows appropriate to the context.

Description

The course will be run in seminar format with a maximum of 12 students. Students are expected to come prepared to actively participate in class sessions, based on readings and pre-recorded lectures.

Data are increasingly being collected digitally throughout our healthcare system. New sources and uses of data could help improve patient outcomes, lower health system costs, and improve health care provider productivity. They also present challenges:

• New types of data, (e.g., from DNA testing) may increase risk to privacy.
• Modern data analytics methods commonly link multiple datasets, sometimes from multiple jurisdictions, to achieve sample sizes appropriate for analytics needs. This creates challenges with data security and data flows (due to legislative restrictions). Further, data science approaches to analyses challenge current data minimization principles.
• Many entities would like to monetize health data or use them for commercial purposes. The public are uneasy over this. Commercial interests must be balanced with public interests.
• Governments and payers want access to data to develop better policies and allocate resources more effectively.
• Healthcare organizations will need to share data more frequently to provide care to complex patients whose needs cannot be met by a single entity.
• Patients are increasingly asking for access to their data for personal use.

Current policies and mechanisms for data governance struggle to meet these challenges, as there are no simple solutions.

The fundamental theme of this course is how the health care system can optimize and leverage the information collected to meet our evolving need for data to be used (and re-used) by and across organizations while meeting our legal and privacy obligations. We will consider both theoretical/conceptual and operational aspects of data quality, responsible use of data, and outcomes assessment using real-world applications. We will also provide case examples of initiatives leading the way in this new data environment. The course will identify emerging frameworks and technological solutions for solving key data governance issues.

Instructors

Evaluation Breakdown