NHS digital transformation and AI offer vast opportunities, but access to quality data and skilled analysts is crucial for improving patient care and tackling challenges like antibiotic resistance and cancer detection
Sponsored and written by
Open access to data is key
Many NHS trusts are currently implementing Electronic Patient Record systems through the frontline digitisation program. This rich source of organisational-specific data, combined with data collated within our integrated healthcare systems, means access to a wider spectrum of data.
The question is, do we know what to do with it? Is it of good quality? Do we have enough data scientists to analyse it?
In today’s digital age, the data the NHS has is arguably its biggest digital asset and opens up a world of opportunities. By investing to digitally upskill the workforce, we will be in a better position to put this data to work in ways that benefit patients.
AI is coming into its own
Before we invest funds and resources into another large-scale program, it’s important to conduct proof of concepts or studies.
And DXC Technology is working with several healthcare organisations to do exactly that.
For example, in collaboration with Singapore General Hospital and the national health agency Synapxe, DXC developed an AI system to tackle pneumonia and combat growing antibiotic resistance. The AI model, which processes symptom data from patients, helps distinguish between viral and bacterial infections, ensuring antibiotics are only prescribed when necessary.
Piotr Chlebicki, a senior consultant at SGH, said the technology’s ability to sift through vast data to detect infection patterns is key in deciding whether antibiotics are required.
The AI system, called Augmented Intelligence in Infectious Diseases, was trained on data including clinical symptoms, responses to infection, X-rays, and vital signs from approximately 8,000 SGH patients.
The study team believes the AI system could save doctors up to 20 minutes per case and help curtail drug-resistant infections.
AI for breast cancer detection
Another example is a PoC that DXC conducted in partnership with a large medical group in California. This study required limited funding and a low utilisation of resources, yet was significant in its use of historical data pulled from the Epic EPR system to assist in the early detection, improved tracking, and diagnosis of breast cancer.
By using historical EPIC data, the PoC’s aim was to determine if AI could significantly improve outcomes for patients, by successfully identifying false positives and false negatives in breast cancer radiology results.
The PoC established a high accuracy rate (>96 per cent) for negative and (>70 per cent) for positive mammogram predictions.
Opportunities ahead
These examples show the value that AI is going to play in delivering better care outcomes. The NHS must insist that it has access to patient data, or it risks missing out on the benefits AI can offer caregivers and clinicians in their decision-making and, more importantly, the benefits it can bring to patients.
Discover more about how DXC is shaping the future of healthcare by visiting our website. Together, we can turn today’s innovations into tomorrow’s care practices, improving outcomes, and transforming lives — one innovation at a time.
