Introduction to the Big Data Era & Opportunities for Better Health Care

This course is part of the UBC Micro-certificate in Health Data Analytics: Opportunities and Applications program. The program consists of three courses that can be taken individually or combined into the Micro-certificate.

Introduction to the Big Data Era & Opportunities for Better Health Care explores how data science is changing health care. You will learn about the current state of health data in British Columbia, how it is used in the health system, and the long-term outlook for this field. The course covers how to access health data appropriately and understand its sources and limitations. You will see how data science can solve clinical and operational health system challenges, when to use different data science methods, and the role of different data types like text, images and genomics in patient care. This course will demonstrate the ways in which data and analytics can improve delivery of health care and health system operations, and how to start applying a data analytics approach in your own work.

By the end of the course, you will be able to:

• discuss the impact of data science on diverse fields including health care delivery, research, technology, manufacturing and more
• describe the current state of health data collection and sharing in BC; recognize current applications of data science in the health system (clinical and administrative/operational decision making); understand the long-term vision and health data strategy for BC; and describe the building blocks necessary to achieve this vision
• identify key considerations when working with health data in BC, including ethical, privacy and data governance aspects
• describe health data sources in BC; understand the origin, intention and limitations of data sets and the implications for interpretation
• develop a basic understanding of clinical problems in medicine that would benefit or have benefitted from data science approaches
• demonstrate which data science approach is appropriate for a given scenario
• obtain a basic understanding of the characteristics and opportunities presented by imaging, time series, natural language and genomics data to better patient care
• explain how the collection of various types of data can improve clinical operations, or the clinical diagnosis, prognosis and treatment of diseases

Course activities include readings, videos, tutorials, virtual small group discussions and online discussion boards.

How am I assessed?

Assessment takes place on successful completion of short assignments, student reflections and quizzes each week. These activities are marked using a proficiency scale, and your instructor provides you with informal feedback. The minimum passing grade for this course is 70%.

Expected effort

The duration of each course is four weeks, and the approximate time commitment expected for completing the course is 25 hours. Participants are expected to allocate approximately six hours per week to engage with the course materials, which encompass lecture videos, readings and activities.

Technology requirements

To take this course, and for the best experience, we recommend you have access to:

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

Course format

This course is 100% online instructor supported with weekly office hours.

Each week there will be an opportunity to attend instructor or teaching assistant office hours if you need any help with course content. There will also be weekly small group discussions with your peers to provide you with a community of practice and enable you to network with others working in this field in BC.

The weekly live, virtual office hours are Mondays, 6 to 7pm Pacific Time (subject to change).