Aims This course aims to:
introduce you to fundamentals of health data science and the latest advancement of this field
provide you with a robust understanding of terminology used in the field and the distinctive governance required for protection of individuals’ health records while enabling research
enable you to gain an understanding of working with programming approaches to generate insights from health data
Content This course provides a comprehensive exploration of the principles of data science within the context of global healthcare systems, commencing with foundational concepts such as healthcare systems, health data at scale, health research and the pivotal role of data-driven decision-making in enhancing patient outcomes. Participants will engage in an in-depth examination of ensuring secure access to patient data and adherence to governance standards, employing methodologies such as the five-safes framework and Trusted Research Environments (TRE). Through practical sessions, they will acquire proficiency in navigating data exploration, data access requirements, feasibility assessments, and the development of study protocols. The course also provides a hands-on project focusing on fundamentals of exploratory data analysis, followed by guidance on reproducible project management practices.
The course will begin with an exploration of the fundamentals of data science in various types of healthcare systems across the globe. We will look at the concepts of designing a medical study, the importance of data-driven decision-making in improving patient outcomes and reproducible approaches in data science.
Next, we will develop an understanding of how to ensure safe access to patient data and adherence to governance requirements are supplemented by the following: principles of five-safes, working in the Trusted Research Environments (TRE), steps of project development in a TRE, essential tools and software used in a health data science project.
The third session will focus on the requirements for a health data science study. We will look at data exploration and data access requirements, metadata availability, feasibility assessment and study protocols.
The fourth session involves a hands-on practical project, focused on exploratory data analysis.
Building on the previous session, the focus on the last day is to ensure all code syntax and resources generated for the small project are saved in a reproducible and accessible manner.
Presentation of the course The course will take place in a classroom setting using interactive presentations tools to aid with demos of technical methods. It is highly recommended that you bring your personal laptop or IT equipment to be able to follow some of the live voting and technical experiences with tools. Students will be encouraged to contribute to discussions in the classroom by offering opinions, experiences and observations.
Course sessions
Introduction to Data Science in Healthcare Trusted Research Environment Health Data Science study design Practical project Analysis pipeline development
Learning outcomes You are expected to gain from this series of classroom sessions a greater understanding of the subject and of the core issues and arguments central to the course.
The learning outcomes for this course are:
to gain an understanding of the principles of designing medical studies, data access requirements and the governance for ethical use of patient data in trusted research environments
to develop structural and computational thinking skills required for application of theoretical knowledge to real-world scenarios, through a hands-on practical project in exploratory data analysis, including assessing data completeness, utilizing data visualisation techniques, and performing feasibility assessments and correlation analysis
Required reading There are no compulsory readings for this course.
Typical week: Monday to Friday Courses run from Monday to Friday. For each week of study, you select a morning (Am) course and an afternoon (Pm) course. The maximum class size is 25 students.
Courses are complemented by a series of daily plenary lectures, exploring new ideas in a wide range of disciplines. To add to your learning experience, we are also planning additional evening talks and events.
c.7.30am-9.00am
Breakfast in College (for residents)
9.00am-10.30am
Am Course
11.00am-12.15pm
Plenary Lecture
12.15pm-1.30pm
Lunch
1.30pm-3.00pm
Pm Course
3.30pm-4.45pm
Plenary Lecture/Free
6.00pm/6.15pm-7.15pm
Dinner in College (for residents)
7.30pm onwards
Evening talk/Event/Free
Evaluation and Academic Credit If you are seeking to enhance your own study experience, or earn academic credit from your Cambridge Summer Programme studies at your home institution, you can submit written work for assessment for one or more of your courses.
Essay questions are set and assessed against the University of Cambridge standard by your Course Director, a list of essay questions can be found in the Course Materials. Essays are submitted two weeks after the end of each course, so those studying for multiple weeks need to plan their time accordingly. There is an evaluation fee of £75 per essay.
For more information about writing essays see Evaluation and Academic Credit .
Certificate of attendance A certificate of attendance will be sent to you electronically after the programme.
