Health Data Analytics: Opportunities and Applications

Using real-world cases and data, the UBC Micro-certificate in Health Data Analytics: Opportunities and Applications offers students the hands-on training to gain confidence using data analytics techniques in a data-intense health system. The program blends foundational data analytics proficiency with health system context and data.

By the end of this program, you will be able to:

• recognize and discuss current applications of data science in the health system
• identify key considerations when working with health data in BC, including ethics, privacy and governance
• explain how the collection of data can improve clinical operations and the diagnosis, prognosis and treatment of diseases
• understand and discuss the basic concepts of data cleansing and data warehouses
• compare experimentally generated data and observational data
• identify and categorize the different types of data analysis questions
• discuss algorithmic bias, including its causes and consequences, to mitigate bias in machine learning
• demonstrate how data science storytelling can lead to policy and plan changes
• master the usage of WEKA software for data preprocessing, analysis, visualization and implementation of machine learning algorithms
• introduce principal component analysis and data clustering
• develop a basic understanding of natural language processing (NLP) and feature extraction techniques

This program is designed for health care professionals and researchers, either clinical or operational, looking to enhance career performance and prepare for future opportunities, or those wanting to transition into an administrative or leadership role. No prerequisite knowledge of the course topics is required.

Roles that may benefit from this program include:

• physicians
• nurses
• paramedics
• pharmacists
• administrators

Each course costs $995. The total cost of the program is $2,985.

All fees are in Canadian dollars, subject to change and to GST (where applicable). For details on forms of payment accepted, please see How to pay.

Find more details on refunds, cancellations and transfers.

The micro-certificate program consists of three courses of five weeks each. Combined, the courses take approximately 90 hours to complete.

You can take the courses on their own, in any order. However, to earn your micro-certificate and gain the most value from the program, we recommend taking the courses in succession as they build upon one another:

1. Introduction to the Big Data Era & Opportunities for Better Health Care (0114)
2. Health Data and Visualization (0115)
3. Health Data Analysis and Machine Learning (0116)

This part-time 100% online program is instructor supported and combines weekly real-time classes and independent study.

Outside of class, you can access online materials on your own time. Each week, you’ll have an opportunity to review readings and videos and apply your knowledge through quizzes, data analysis coding exercises and work-related mini projects. Students are also encouraged to contribute to and connect with one another on a discussion board.

Expected effort

Expect to spend approximately six hours per week completing all learning activities, including attending real-time sessions online.

Technology requirements

To take this program, you need access to:

• an email account
• a computer, laptop or tablet, using Windows, macOS or Linux
• the latest version of a web browser (or previous major version release)
• a reliable internet connection
• a video camera and microphone

In the Health Data Analysis and Machine Learning course, you will be using WEKA (Waikato Environment for Knowledge Analysis) data analysis software, which requires a computer less than 5 years old equipped with:

• a dual-core processor
• a minimum of 4GB RAM (8GB recommended)
• a minimum of 2GB free disk space
• Java 8 or higher software development platform installed

Assessment

You are assessed on successfully completing weekly assignments and quizzes, as well as your contributions to discussion posts. These activities are marked using a proficiency scale, and your instructor provides you with informal feedback during online classes. You must achieve a minimum of 70% in each course to earn your micro-certificate.

While you are not assessed on your attendance of the real-time classes, we encourage you to attend so you don’t miss the opportunity to learn and interact with your instructor and other participants.

Our program is co-developed by UBC leaders in medicine and data science to meet the emerging analytic needs of professionals working in the health sector.

Anita Palepu, MD is a Professor, Eric W. Hamber Chair, and the Head of the Department of Medicine at the University of British Columbia and Providence Health Care. She is the Co-Lead of the Data Science and Health (DASH) Cluster.

Raymond Ng, PhD is a professor of Computer Science at the University of British Columbia and the Director of the Data Science Institute. He is also the holder of the Canadian Research Chair on Data Science and Analytics.

Guest instructors

• Brandon Wagar, PhD - Senior Director, Methodologies and Cross Sector Analysis, BC Ministry of Health; Adjunct Professor, School of Health Information Science, University of British Columbia
• Alexandra (Lexie) Flatt, MBA - Vice President, Pandemic Response & Chief Data Governance & Analytics Officer, Provincial Health Services Authority
• Eric Grafstein, MD - Regional Head, Department of Emergency Medicine & Chair, Regional Emergency Services Program, Providence Health Care & Vancouver Coastal Health
• Holly Longstaff, PhD - Director, Privacy and Access, Provincial Health Services Authority; Ethicist, BC Cancer Research Ethics Board
• Kimberlyn McGrail, PhD - Professor, School of Population and Public Health & Centre for Health Services and Policy Research, University of British Columbia; Scientific Director, Population Data BC & Health Data Research Network Canada
• Antonio Avina-Zubieta, MD, PhD - Senior Research Scientist, Arthritis Research Canada; Associate Professor, Department of Medicine, University of British Columbia
• Lianping Ti, PhD - Research Scientist & Health Administrative Data Lead, BC Centre for Substance Use; Assistant Professor, Department of Medicine, University of British Columbia
• Richard Lester MD - Director, Neglected Global Diseases Initiative & Associate Professor in Global Health, Department of Medicine, University of British Columbia; Scientific & Executive Director, WelTel International mHealth Society
• Teresa Tsang, MD - Director, UBC-VGH Artificial Intelligence Echo Core Lab & VGH-UBC Echo Lab; Clinician Scientist & Professor of Medicine, Department of Medicine, University of British Columbia; Co-Lead, Data Science and Health (DASH) Cluster
• Thalia Field, MD - Researcher, Djavad Mowafaghian Centre for Brain Health & Associate Professor, Department of Medicine, University of British Columbia
• Jennifer MacGregor, MBA - Vice President, Digital Patient and Provider Experience, Fraser Health Authority
• Jonathan Simkin, PhD - Scientific Director, BC Cancer Registry, BC Cancer
• Kevin Doerksen, PhD - Director, Department of Organizational Performance, BC Emergency Health Services
• Aline Talhouk, PhD - Assistant Professor, Department of Obstetrics and Gynecology, University of British Columbia
• Yulia Egorova, PhD - Trainee Lead, Data Science and Health (DASH) Cluster
• Robert Bergen, PhD - Health Data Scientist, Data Science Institute, University of British Columbia
• Daniel Holmes, MD - Head & Medical Director, Department of Pathology and Laboratory Medicine, St. Paul’s Hospital; Clinical Professor, Department of Pathology and Laboratory Medicine, University of British Columbia
• Dr. Daniel Chen - Postdoctoral Research and Teaching Fellow, Master of Data Science, University of British Columbia
• Lynn Hancock, PhD - Director, Strategic Priorities Research and Reporting, Health Workforce Planning and Implementation, BC Ministry of Health