Data Science - Identifying, combining and analysing health data sets
This course aims to equip students with the necessary analytical skills to analyse linked health care data and to be aware of issues around clinical and information governance relating to their use.
If you would like to find out more about our MSc in Health Technology Assessment which this module is a part of, please see our course page: www.gla.ac.uk/hta
- Course dates:19th April - 2rd July 2021
- Online Distance Learning (ODL)
- Non-accredited, but with a certificate of attendance
- This course will be taught using STATA and/or R
- For more info contact: firstname.lastname@example.org
Purpose: The course delivers core components of identifying, combining and analysing routinely collected health data. It will cover aspects of information governance and disclosure control, as well as focus on data management, manipulation and advanced methods of data analysis.
Aims: The course module is aimed at health, social and clinical researchers, who wish to learn techniques and skills to analyse linked health data. It aims to equip participants with the necessary analytical skills to analyse these types of data and to be aware of issues around clinical and information governance.
Content: The use of observational data in HTA, information governance and disclosure control, theoretical principles of data linkage methods, sources of bias and measurement error in administrative health data, data management and manipulation of datasets with different structures, methods to adjust for confounding in comparative effectiveness analysis when using observational data, advanced survival analysis techniques.
Course Co-ordinator: Claudia Geue
Why this programme?
- Our faculty are world-class experts in their fields, who are active not only in research and teaching, but also involved in HTA decision-making at a national level (e.g. through NICE, SHTAG).
- Our teaching is research-led. The courses have been developed to reflect the latest academic research and up-to-date challenges in HTA decision-making.
- During the course, from week to week you will interact with your teachers and fellow participants. Your teachers will direct and observe the discussion, and respond to participant questions about the course content.
Online distance learning at the University of Glasgow allows you to benefit from the outstanding educational experience that we are renowned for, without having to relocate to our campus.
You do not need to have experience of studying online as you will be guided through how to access and use all of our online resources.
You will connect with your fellow participants and tutors through our virtual learning environment where you will have access to a multitude of learning resources including:
- recorded lectures
- interactive quizzes
Great emphasis is placed on making sure you feel well supported in your learning and that you have good interactions with everyone on the programme. Support is available in a number of ways and you will find out more about this during orientation.
All you need to participate in our online programmes is a computer and internet access.
10 week online course comprising 10 lectures and accompanying practical exercises. The lectures will be 45min/1hr in duration and exercises associated with lectures will take a notional 2 hours for the participants to complete. Each week the academic lead will be responsible for monitoring and contributing to the discussion board. The exercise solutions will be posted on Moodle the following week.
Full details here of the Data science course.
Entry Requirements and Assessment
As this course is not accredited, there are no course-specific entry requirements and there is no assessment. Please note that the course will be taught using STATA and/or R, and some familiarity with this software would be advantageous.
If you have any questions, or if you would like any more information, please don’t hesitate to contact us at email@example.com
If you would like to find out more information about our unit, please see here: www.gla.ac.uk/hehta
If you would like to see more about our MSc in Health Technology Assessment that this module is a part of, please see our course page: www.gla.ac.uk/hta