Beyond Fraud: Using Data Analytics to Tackle Waste, Inefficiency and Abuse in the NHS

A panel session at Counter Fraud 2026, hosted by Pulselight, brought together a former health minister, one of the UK's most prominent public health figures, and two healthcare data analytics specialists to discuss how data can be used to address not just fraud in the NHS, but the far larger problem of waste, inefficiency and duplication.

The panel comprised Irene Manautou, Founder and CEO of Pulselight; Lord James Bethell, former Health Minister; Sir Jonathan Van-Tam, Emeritus Professor of Public Health at the University of Nottingham and former Deputy Chief Medical Officer for England; and Mallika Thanky, VP of Product Strategy at Pulselight. Here is a summary of their discussion:

Fraud, waste and inefficiency

Irene Manautou opened by drawing a parallel between Pulselight's work with US public healthcare programmes - Medicaid and Medicare - and the challenge facing the NHS. The same analytical techniques that identify fraud can also identify waste, duplication and inefficiency. Every pound matters and every patient matters, she said, and the data that the NHS generates every day contains the intelligence needed to do both better.

Lord Bethell framed the distinction clearly. Criminal fraud - providers systematically extracting money they are not entitled to, or staff falsifying activity - is real, reputationally damaging and must be pursued. But it is not, he said, the financial big prize. The NHS spends around £200 billion a year. The larger opportunity lies in what he called optimisation: closing the gap between the decisions that hard-pressed frontline staff make under pressure and the decisions that data and analytical tools would support them to make. That is where the significant financial return sits.

Sir Jonathan Van-Tam was characteristically direct: the NHS is not a system that is good at spotting its own inefficiencies, not because the people within it are negligent, but because they are simply too busy. Clinicians and administrators are focused on the task immediately in front of them. They do not have the bandwidth to look across the system and identify patterns. The tools to do that exist; the challenge is deploying them.

What the data can reveal

Mallika Thanky gave three concrete examples from Pulselight's work in the US that have direct relevance to the NHS:

The first was upcoding: providers consistently billing for more complex treatments or patient categories than the data supports. In isolation, a single provider billing for complex cases looks unremarkable. Across a population, when you can see that those same patients are coded as routine when they see other providers, the anomaly becomes visible. That kind of pattern is invisible without integrated data and automated analysis.

The second was the downstream impact of services not being delivered. Where a patient is not receiving a service they should be receiving, their condition deteriorates and they become a more expensive patient further down the line. Detecting that gap early - whether it is fraud or simply a failure in coordination - prevents a larger cost later.

The third was a utilisation example that illustrated the waste hiding in plain sight. Analysis of emergency department admissions for an ageing population identified a pattern: one elderly woman was attending A&E every Wednesday. She had in-home care six days a week but not on Wednesdays. She was going to A&E because she was lonely. The cost of one hour of in-home care on a Wednesday: around $40. The cost of an A&E attendance: around $400. Across a population, the savings from that single insight were significant. The data made the pattern visible. Human judgement then decided what to do about it.

Lord Bethell added a prescription example that NHS counter fraud professionals will recognise. Between 20 and 40% of prescriptions are estimated to go uncollected or unused - against a total prescription budget of around £8 billion. Patients on rolling repeat prescriptions who have stopped taking their medication, or who have died, continue to generate prescriptions because the data on cancellation is not meeting the data on need. That is not fraud. It is a failure of data integration. But the financial scale is comparable to many fraud loss estimates, and the analytical approach to identifying it is the same.

The data are messy

A recurring theme in questions from the floor was the fragmented state of NHS data. An investigator from the NHS Counter Fraud Authority described working across multiple disconnected systems, with data that is inconsistent, incomplete and difficult to integrate. Will there ever be a single unified data source?

The panel's answer was honest: no. Healthcare data is necessarily messy and always will be. But Mallika Thanky pushed back firmly on the idea that messiness is a barrier to progress. Pulselight meets every client where their data actually is. Some have sophisticated digital systems. Some have records in spreadsheets or paper files. In every case, there is something to find. She made a direct offer to the room: run a pilot, and if the analysis does not identify recoverable value, Pulselight will refund the cost. That confidence, she said, comes from experience - there is always something in the data, however impoverished it appears.

The practical implication for NHS counter fraud teams is significant. The absence of a clean, integrated data environment is not a reason to wait. It is a reason to develop the analytical capability to work with what exists now, while pushing for better integration over time.

Patient fraud: Under-investigated and under-discussed

During the discussion, an NHS investigator in the audience brought up the point of patient fraud - specifically, patients in overseas locations continuing to receive NHS prescriptions and services they are no longer entitled to. Cases, they said, typically only come to light when the patient complains about a delay. The question was direct: why is patient fraud so rarely discussed?

Mallika Thanky acknowledged that patient fraud is systematically underplayed in the US too. The perception is that individual patient fraud involves small sums compared to provider fraud, and there is a cultural reluctance to be seen to be pursuing patients or deterring people from accessing services. But the analytical techniques are the same, and geospatial analysis - looking at where prescriptions and services are being directed and whether those locations make sense - can surface this category of fraud at scale.

Risk appetite and the prevention agenda

An investigator from NHS Wales raised the tension at the heart of NHS counter fraud work: the NHS is designed to be easily accessible, and there is an institutional culture that accepts a degree of fraud risk in order to preserve that accessibility. How do you manage risk appetite without undermining the service?

Lord Bethell's response: Accessing NHS services is a right, but rights come with reciprocal responsibilities. The framing of that conversation - which the UK has never seriously had - is part of what needs to change. Irene Manautou made the parallel point from a leadership perspective: intelligent leaders have to make the call on where the balance sits, and counter fraud professionals need to have a voice in that conversation as much as anyone, because they see the consequences of getting it wrong.

Sir Jonathan Van-Tam connected this to the government's Prevention agenda in the NHS Fit for the Future: 10 Year Health Plan for England. The shift from treating illness to preventing it requires data integration across primary care, secondary care and social care - the same integration that counter fraud work depends on. The case for investment in data infrastructure is not just a fraud prevention argument. It is a whole-system argument, and NHS counter fraud professionals are well placed to make it.