The Nuffield Trust undertakes a range of projects that seek to exploit the large amounts of existing data on care. The scale and sophistication of these data sets continue to grow and with the right analytical techniques they can make significant contribution in many areas of research, policy analysis and patient care.

The range and volume of information collected about health services continues to grow every year. The NHS spends millions of pounds in setting up IT systems that perform a range of tasks from logging basic administrative information to decision making tools for clinicians.

Though these information systems do an important job in running health services, they also collect vital information about the services that are delivered and the patients themselves.

By linking these data it is possible to see an individual’s pathway through care services

The Nuffield Trust is interested in ways that we can exploit these data sets to inform health policy. We are particularly interested in the how linkage between data sets can reveal a fuller picture of what is happening to people as they use services. The linkage may be:

The Nuffield Trust is developing a series of linked pseudonymous data sets for use as a data laboratory. These data sets cross organisational divides, spanning health and social care.

Their purpose is to capture events for whole populations in order to promote more comprehensive analysis and greater understanding of care services provided at the person level. By using linked data from operational systems it is possible to gain new perspectives on the ways in which different care services interact for individual people. Linked data allow us to observe real pathways and transitions in care.

The diagram below shows how we have been using linked data sets in the evaluation of telehealth and telecare, and is an example of how operational information can be used in structured evaluation that look across services.

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Click on the image to enlarge

By linking these data it is possible to see an individual’s pathway through care services. We can use this in evaluation and in developing models that predict the likelihood of future events. For example, work on predictive risk looks at how an individual’s health history can be used to predict admission to hospital. These tools have a potentially important role in prioritising preventive care.

We will continue to provide updates on our progress in exploiting existing information in new ways via this project page.

Project outputs


  1. Making the best use of administrative data

    27 Feb 2013
    British Medical Journal
  2. Understanding patterns of complex care: putting the pieces together

    1 Oct 2012
    Journal of Health Services Research & Policy

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