Our vision is that by 2030, patients across the UK will benefit from healthcare decisions informed by large scale data and advanced analytics to identify what will work best for them.
On these pages you can find out about our approach, projects and how we use a continuous learning cycle to support our work.
We support the development of learning healthcare systems that integrate clinical practice, large scale data and advanced analytics in a cycle of continuous improvement by:
- Systematically gathering real-world data about patients’ treatment, experience and outcomes within the setting of routine care
- Collating and providing access to large scale data in a format that is analysis-ready
- Using advanced analytics to derive generalisable evidence and provide critical insights into healthcare delivery
- Developing data-driven tools that make these insights actionable by clinicians and patients when they are making decisions about their care
- Implementing tools to support personalised decision making by clinicians and patients at the point of care
- Gathering data to manage the quality, safety and efficiency of care delivery, underpin research, and generate new insights that can continuously improve decision-making by clinicians and patients
Our focus is on answering the research questions necessary to achieve these goals and seeking solutions that can be implemented at scale across the health and care system.
Health Data Research UK Better Care Loop
The data-based continuous learning cycle which we aim to see implemented through the Better Care programme can be visualised as:
Note: Although the process is shown as a sequential loop, it will often be iterative, since results at any given stage may identify the need for additional work at preceding stages.
Newly Launched Better Care Projects
More information about Better Care
How to get involved
For more information, to get involved in a project or to be involved in our Slack channel, please email email@example.com and it will be forwarded on to the Better Care team.