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The potential of actionable insights in healthcare



The NHS can make more use of its data to provide evidence for change, leading to more efficiency and better patient outcomes, explains Derek Ward of Rainmaker Solutions


The NHS is not making full use of the mountain of data it produces each day. Most of its organisations fail to capitalise on its collection by using it to generate actionable insights that can positively impact on patient, clinical and financial outcomes.

This is a waste: there are insights trapped inside the data that provide a massive opportunity to seek out causes of inefficiency AND act on them.

The key is in bringing together data from hundreds of hospital and primary care systems, asking a series of 'What if?” questions, then cutting the data in different ways to find answers. Being able to do this quickly makes it possible to spot all sorts of relationships that influence the quality and cost of care.

Outcomes and logic

There are three phases. First is selecting the outcome you wish to tackle. Second is to apply human intelligence, drawing on the experience of managers and clinicians to derive a logic model. This involves working backwards: choosing an outcome, such as speeding up hospital discharges for patients who are fit to leave; asking what data could be relevant; then extracting it for investigation.

Third is to deploy the power of computer learning. Data analytics systems are using increasingly sophisticated algorithms, processing massive quantities of data to spot relationships between different stages of an operational process much faster than humans. This provides unexpected insights that are often counter-intuitive but highly valuable.

A key element is 'working out loud' across organisations and providing clear headline messages from the insights. This helps in engaging clinicians and other employees, ensuring they understand the evidence and encouraging them to adopt new approaches.

It also makes it possible to establish how specific inputs can influence outcomes, and look at how they can be changed to produce improvements. For example, for an elderly patient who had suffered a fall, when is the best point to begin physiotherapy, and how early is it possible to identify a need for support at home?

It is important, especially in a hospital, to keep an eye on all the possible consequences of a change. Part of logic modelling is to ensure that a problem is not simply shifted from one stage of a patient pathway to another, and to provide the evidence of where an issue can be addressed most effectively.

Most for the most

All this can ensure that the NHS utilises its limited resources as efficiently as possible, helping to achieve the 'most for the most'. One benefit could be to reduce bed blocking. If the patient's condition is accurately assessed and combined with the insights from data on previous cases, it makes it easier to plan for their discharge days or even weeks ahead, and alert the social care agencies.

On a broader scale, data on patients who make repeated visits and cost most to treat can be used for early interventions, supporting self-care and wider planning for community care services.

All of this requires employees at all levels to change how they work, and this will only happen when they are presented with robust and irrefutable evidence. This is hidden within the data and requires extraction and interpretation; but these skills are in short supply, especially in NHS organisations.

Rainmaker's unique commercial offer, backed up by its public sector expertise, can fill this gap. It can provide the key for unlocking the value of NHS data and produce the evidence for change that leads to better outcomes for all – with no financial risk.

More from here on how Rainmaker can support an organisation's effort to find insights in its data.

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