Health Data Immersion Week One - Experimental and Observational Methods for Health Data Science

Appropriate health study design is critical to ensure that we can answer the questions we are interested in, for example, is a drug effective for treating a condition? Does daily monitoring of your blood pressure lead to reduced chance of a heart attack? However, health studies often need to consider a number of complex factors which might lead to biased or misleading results.

This course aims to give participants an insight into how health studies are designed and implemented. Using a combination of lectures, seminars, and interactive, group-based problem-solving sessions, you will learn about key aspects of health study design. You will also hear from academic and industry-based experts as to how they implement studies in the real-world.

Upon completion of this course, you will:

• Have developed an understanding of how health studies are conducted
• Have understood the difference between interventional and observational health studies
• Be able to identify some suitable study designs for specific health problems
• Have understood how study design impacts the potential uses of health data
• Have been introduced to the utility of genetics in health studies
• Have applied statistical techniques to account for forms of bias in observational studies
• Be able to design simple interventional studies to test for a particular hypothesis

Each day will focus on a particular topic:

• The scientific method in health sciences
• Randomised controlled trials and interventional data
• Mendelian randomisation and instrumental variables
• Observational studies and dealing with bias
• Designing an experimental study

Each morning will consist of lessons and activities that test your existing knowledge and then introduce the essential concepts, followed by a talk from a guest speaker that illustrates a real-world example.

Each afternoon will consist of a practical computational activity that will allow you to put the knowledge you have learned that day into practice.

This course is suitable for candidates who:

• Have a first degree in a quantitative discipline
• Are currently enrolled in a program of advanced study (eg PhD or MRes)
• Have little or no prior experience in Health Data Science
• Are familiar with programming in Python or R (or are familiar with programming in general and have the ability and willingness to learn Python or R)

Dinner will be provided on the first evening, and a light lunch and refreshments all week, but you will be expected to arrange and fund all other meals, travel and accommodation (a list of suitable accommodation will be provided after booking).

• Please complete our Health Data Immersion Week application form.
• We will assess your application to check that you meet the academic requirements of the course.
• Applications that meet the academic criteria will be approved to register for the course. We will then contact you via email with a password and a link to our online shop.
• You will need to use this password when you pay your registration fee and secure your place.

Important information

• Your place will not be confirmed until you have paid the registration fee.
• We will allocate places on a first-come, first-served basis, so we strongly encourage you to apply as early as possible, ideally by Sunday 18 December 2022 (unless you are applying for a stipend – see below)
• If your application is not approved, we will contact you with feedback on the criteria you did not meet.
• Any applications received between Friday 23 December 2022 & Monday 2 January 2023 will not be checked until Tuesday 3 January 2023.
• We will continue to receive applications until Sunday 11 January 2023, but if places are filled before then, your name will be added to a waiting list in case further places become available.