Why is health data research important?
Using health data for research helps us to better understand diseases and conditions – their causes, prevalence and symptoms – and it can provide new ways of treating them or spotting them earlier. There are lots of examples of how health data science has improved our knowledge of health and care and has helped solve challenging health problems.
What type of data is used in research?
The datasets used by health data scientists comes from lots of different sources. This includes:
- Patient data from the NHS and social care, including hospital and primary care administration data (e.g. dates and times of appointments) through to information about treatment, medical and diagnostic tests.
- Studies about the health of groups of people, which may be based on a particular health condition (e.g. cancer), or issues which affect the health of people (e.g. smoking).
- Data from blood or tissue samples which can be used to derive genetic information
- Data from images, which include x-rays, MRI, CT images that contain a huge amount of information
- Health and fitness devices, which provide data on things like heart rate, activity and calories.
Who are health data scientists?
Health Data Scientists come from a variety of backgrounds and include health researchers, innovators, technology specialists, mathematicians, and statisticians. At Health Data Research UK our community includes doctors working in the NHS with an interest in using data for research; academics working in universities who are using data to discover new diseases, and we work with colleagues from industry who are using data to develop new drugs.
Anyone using health data for research and innovation works within the legal frameworks, the strict parameters of the Codes of Practice and the standards set out by the National Data Guardian and regulatory bodies including the Information Commissioners Office (ICO).
Read our answers to some commonly asked questions about how health data is used for research.
Video below is courtesy of Understanding Patient Data