AI and Data Could Save the NHS £20 Billion Lost to Waste Annually

AI and Data Could Save the NHS £20 Billion Lost to Waste Annually

Mitchell Wilson
Mitchell Wilson
2 Min.
A chart comparing Medicaid spending changes under the Better Care Reconciliation Act with CBO's extended baseline, divided into sections labeled "Medicaid Spending" and "Better Care Reconciliation Act", with a legend explaining each section.

AI and Data Could Save the NHS £20 Billion Lost to Waste Annually

A senior panel at this year's Counter Fraud Conference in London will tackle the issue of waste in the NHS. The discussion, hosted by healthcare analytics firm Pulselight, comes as the health service loses an estimated £20 billion each year to inefficiency and duplication. Experts will explore how technology can help recover funds and improve patient care.

The event, titled The Efficiency Drive: How Technology Can Detect and Prevent Systemic Waste in the NHS, takes place at the QEII Centre on 10 July. Running from 11:55 AM to 12:40 PM in the Wesley room on Level 4, the session will be chaired by Irene Manautou, Pulselight's founder and CEO. She will be joined by Lord James Bethell and Professor Sir Jonathan Van-Tam, both of whom bring extensive experience in health policy and public health.

Pulselight specialises in AI-driven analytics that identify waste patterns in healthcare systems. Their platform has already helped clients uncover over £210 million in inefficiencies, with £130 million successfully recovered. The technology scans existing NHS data in seconds, flagging redundancies and errors that would otherwise go unnoticed.

The panel will focus on practical steps to cut waste using the data the NHS already collects. Recovering even a portion of lost funds could ease pressure on services, shorten waiting lists, and free up resources for frontline care.

The discussion aims to highlight immediate opportunities for the NHS to reduce financial leaks. With AI tools already proving effective in other healthcare settings, the panel will argue for wider adoption of data-driven solutions. Better use of existing information could help protect public funds while directly benefiting patient outcomes.

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