Hospital Episode Statistics: Unlocking faster, fairer care
Harnessing Hospital Episode Statistics (HES) data is transforming how we understand patient pathways and optimise healthcare delivery. In this article, Phil King explores how linking HES with other datasets provides powerful insights into service utilisation, outcomes, and system pressures. By leveraging this rich source of real-world evidence, health systems can identify trends, target interventions, and design models of care that improve efficiency and equity. The piece underscores why data-driven planning is essential for sustainable healthcare
Imagine waiting months for a routine operation, not knowing when you’ll be seen. For millions in England, this is reality. Over 7.4 million people are currently on waiting lists, compared to 4.4 million before the pandemic. And with only 59% of patients starting treatment within 18 weeks, far below the 92% target, delays are becoming the norm.
These numbers tell a bigger story. Hospital admissions involving patients with multiple chronic conditions now account for over 40% of cases, while the average length of stay for elective procedures remains at 5.1 days, despite record NHS funding of £188.5 billion in 2023/24. Add to that the complexity of 42 Integrated Care Systems and the challenge of knowing which innovations truly deliver value. It’s clear the system faces mounting pressure.
So where do we start? With data. Hospital Episode Statistics (HES) offers a powerful way to understand what’s happening and where improvements can be made. When used effectively, it can turn insight into action, helping the NHS deliver better, faster, and fairer care.
What are Hospital Episode Statistics (HES)?
Hospital Episode Statistics (HES) is one of the richest sources of healthcare data in England. It captures detailed information about every hospital admission, outpatient appointment, and emergency department (A&E) visit. This isn’t just about numbers; it’s about gaining insight into patient journeys, treatment patterns, and system bottlenecks.
Yet, much of this data remains underutilised. When harnessed effectively, HES can reveal where delays occur, which specialities face the greatest pressure, and how resources can be better allocated. For example, predictive analytics using HES can identify trends in elective surgery demand, helping hospitals plan capacity several months in advance.
How can HES data help?
1. Planning care: HES data can indicate where care could be transitioned from hospitals to local clinics, or from treating illnesses to preventing them in the first place.
2. Modernising practice: It can highlight where new technologies, such as robotic surgery or remote patient monitoring, could help patients recover faster and avoid complications.
3. Redesigning pathways: It can reveal areas where care could be improved, such as reducing hospital stays or preventing unexpected readmissions.
Real-life impact
For example, using robotic surgery can help patients recover in half the time and reduce complications. In other areas, HES data has enabled hospitals to offer care closer to home, particularly for individuals residing in disadvantaged communities.
The big idea
HES data shouldn’t just be a bunch of numbers on a spreadsheet. Used wisely, it’s a powerful tool that can help the NHS deliver better, faster, and fairer care for everyone.
Ready to turn data into action? Learn more about leveraging HES for better outcomes.
