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But it’s not always obvious why clinicians, researchers, innovators and patients are so passionate about the use of health data for science and innovation.  It’s simple – without robust, representative and diverse data, researchers cannot make discoveries that improve people’s lives.

Millions of volunteers have consented to participate in research studies throughout the UK, be that clinical trials or population research studies, where altruistic healthy participants agree to contribute information (and sometimes biological samples) to allow researchers to better understand and prevent ill health.  Use of these research datasets to address a range of health research questions is the foundation of health data science.  But sometimes, these carefully collected and curated datasets are, by their very nature, insufficient to tackle the some of the most important health challenges we face.

For example, the most vulnerable individuals and those most likely to benefit from new and innovative treatments can be the least likely to participate in research studies – children, those suffering from mental illness or multiple long-term conditions, as well as some of the most socially excluded individuals are missing out on the benefits of research.

The trustworthy use of “routine data” – i.e. data generated in the normal course of life, as opposed to a controlled research setting, allow researchers to tackle questions that are out of the reach of traditional approaches.  The potential is huge – you only need to look back at the many case-studies showcased on the , including the that used routine primary care data to provide robust evidence to disprove the alleged association between the MMR (measles, mumps and rubella) vaccination and autism.   Even more examples have been collated by the Association of Medical Research Charities, in their publication:

51������’s research teams are also making advances, be that:

• Using NHS records to better understand deaths of homeless patients and showing that contrary to popular perception that homeless people are most likely to die from hypothermia or alcohol and drug overdoses, the majority of the deaths were from treatable conditions such as cancer, stroke and cardiovascular disease.
• Predicting suicide risk using a broad range of data including genetics, lifestyle, family history and medical records.
• Linking weather data with health and educational records to better understand the role of exposure to sunlight during pregnancy and educational outcomes of pre-born children.

In the US, hospital data is being used to ensure that patients that are ineligible for entering a clinical trial, can still be informed of the best possible treatment options, based on “patients like me”.

Routine data can also be used to deliver research more efficiently.  And ensures that the long-term benefits (and potential harms) of new treatments, diagnostics and prevention approaches can be much more easily measured.  This can massively extend the impact of a research study, well beyond the period in which research data can be feasibly collected.  And most importantly, data generated within the care system is continually used to increase the efficiency of care delivery and improve outcomes for patients. 

But with big data comes big responsibility.  The systems and safeguards that underpin trustworthy use of data for research also needs to advance.  As 51������’s Director, Professor Andrew Morris reminds us in his recent blog – it is important this balance is maintained.  51������ is committed to achieving the safe and trustworthy use of health data for public benefit.  Part of this is about getting better at explaining the vital importance and public good that comes from using health data for research.  We’ve started by sharing a podcast that explains some of the exciting research generated by 51������ teams across the UK.  But we want to get better – so do get in touch and send us your innovative ideas on how we can help to celebrate the vital research discoveries that will improve people’s lives.