Health Data Immersion Week (March 2023) - 
Working with Real-World Data

If you are considering a career in health data science, have recently transferred from another discipline or are already working in health data science but want to widen your knowledge, our courses are designed to provide a rapid introduction to key areas. 

Delivered in partnership between the University of Birmingham and Health Data Research UK (HDR UK), and in collaboration with the PIONEER Data Hub, the Working with Real-World Data course is part of a series intended to enable graduates with advanced skills in mathematics and computational science to gain insight into key topics in health data science.  

Location: University of Birmingham, Edgbaston, UK (please note this is an in-person event ONLY)
Dates: Monday 27th to Friday 31st March 2023 (inclusive)

PLEASE NOTE APPLICATIONS FOR THIS EVENT ARE NOW CLOSED

Prof Liz Sapey - Institute Director 

Liz Sapey – Director of PIONEER

Liz is a Professor of Acute and Respiratory Medicine at the University of Birmingham and an Acute and Respiratory Medicine Consultant at University Hospitals Birmingham NHS Foundation Trust. She is also the Managing Director of Birmingham’s NIHR Clinical Research Facility.
Find out more about Liz

 Gallier, S

 Suzy Gallier – Technical and Deputy Director of PIONEER

Suzy is Head of Informatics Research & Commercial Development at University Hospitals Birmingham NHS Foundation Trust.  She has over 25 years’ experience of working in both public and private sector healthcare roles, including 10 years as a Director of Operations. This has enabled her to gain a broad understanding of the healthcare environment.
Find out more about Suzy

What are the aims of this course?

PIONEER improves patient care by making routinely-collected health data available to doctors, researchers and academics, under licence. With robust governance and ethics in place, this data can then be used to develop new methods of predicting, diagnosing and monitoring illness in hospital and at home; improving treatment choice and identifying new ways of delivering clinical care.

Working with University Hospitals Birmingham, through the HDR UK supported PIONEER Data Hub, this course will give participants from across the UK an insight into the potential and challenges of real-world health data, and practical experience of working with health data. It will highlight the significant data engineering efforts that underlie the provision of research-ready data and the use of a modern secure computing environment that is the emerging standard for accessing UK health data. 

What will I learn?

Upon completion of this course, you will:

  • Be able to define the primary and secondary use of health data
  • Have increased your understanding of the governance and data legislation which underpin access to unconsented health data 
  • Be able to describe the national data opt out and how this is applied to unconsented health data  
  • Be aware of the benefits and limitations of real-world health data  
  • Be aware of the continuum from identifiable to pseudonymised to anonymised health data, and practice making a dataset anonymised
  • Be familiar with data cleaning and data QA/QC when provided with access to real world health data  
  • Have conducted a statistical analysis of real-world health data, answering a clinical question, with support from clinical experts  
  • Have explored common data models such as OMOP, to understand their benefits and limitations
  • Gain experience of using a secure computing environment 

How will the course be delivered?

This course will combine guided practicals and lectures from experts in health, data, research and governance from both the University of Birmingham and University Hospitals Birmingham. 

Via PIONEER’S Trusted Research Environment, you will have access to an EHR Synthetic data set developed specifically for this programme and configured to offer a snapshot of clinical practice. 

You will also submit a data cleansing and a data analysis exercise for review and receive feedback on your work.

What academic background/experience do I need to take part?

This course is suitable for candidates who: 

  • Have a first degree in a quantitative discipline 
  • Are currently enrolled in a programme of advanced study (e.g. PhD or MRes), or have equivalent professional experience
  • Have experience of programming in Python or R  
  • Have little or no prior experience in working with electronic health record data and systems 

What is included?

Dinner will be provided on one of the evenings, and a light lunch and refreshments all week, but you will be expected to arrange and fund all other meals, travel and accommodation.  

What is the application/booking process?

Applications closed on Sunday 05 March.

 If you have any queries about the immersion weeks, please email dsai@contacts.bham.ac.uk 

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