AI could really help the NHS – but data challenges need to be faced

“To harness the power of AI, we need to get the data right,” says NHS Digital’s Director of Data

Posted 16 January 2018 by Gary Flood

NHS Digital says it is asking partners to check the quality of its data as part of a move to explore the potential of Artificial Intelligence (AI) in UK healthcare.

“We are encouraging partners to evaluate the quality of our statistics [and] we are constantly seeking to improve,” says its Director of Data, Professor Daniel Ray.

“We also need to make sure that the data provided for use in AI algorithms is designed with the best interests of patients at the forefront of all decision making,” he adds.

The comments were made by the organisation on its website, and is a response to think-tank Reform’s report this week on how to harness the power of Artificial Intelligence in the NHS.

In that study, co-written by a speaker at Think Digital’s successful AI conference last year, Eleonora Harwich, the claim is made that AI could support the delivery of the NHS’s Five Year Forward View and address the health and well-being gap by predicting “which individuals or groups of individuals are at risk of illness and allow the NHS to target treatment more effectively towards them”.

Reform also thinks the reduction of the care and quality gap could be supported by AI tools, as they can give all health professionals and patients access to cutting edge diagnostics and treatment tailored to individual need, while AI could also help address the efficiency and funding gap by automating tasks, triaging patients to the most appropriate services and allowing them to self-care.

The study provides 16 specific recommendations on how to achieve these very desirable goals, one of which is that the NHS should “pursue its efforts to fully digitise its data and ensure that moving forward all data is generated in machine-readable format”.

Hence Professor Ray’s response, which includes a commitment to “overcome the challenges of understanding the decisions AI algorithms make when using data”.

“In specialist areas AI has great potential for success and there are good examples of this starting to happen in the NHS, but we need to understand and evaluate this to move it forwards,” he concludes.

“We know that health data is personal and sensitive, so there are rightly strict rules in place about how and when it can be used or shared.

“We need to ensure that any new developments harness the power of data but that they do so responsibly and within the legal frameworks.”