The key to improving patient outcomes and ensuring the sustainability of the NHS is through better managing the provision of quality care and the complexities of risk prediction, argues Dr. Vladimir Ljubicic, director of business development at healthcare analytics specialist C2-Ai.
C2-Ai
Dr. Vladimir Ljubicic
Quality as a necessity
I often hear that, given the rising demand and limited resources, it’s expected that the quality and safety of NHS services will inevitably suffer. In some ways, this is a fair point; comprehensive healthcare systems are expensive. They require a large number of highly skilled professionals, advanced facilities and equipment, and an ever-growing list of costly materials. There is no inexpensive way to deliver high-quality healthcare services.
However, we must make an important distinction. While resource constraints are real, the services provided within those limits must remain of the highest quality. This is not just an ethical obligation, patients obviously deserve the best care, but also a practical necessity. Providing high-quality care is more affordable in the long run for the NHS and society.
When we provide good care, whether managing diabetes or performing hip replacements, we don’t just improve patients’ health. They spend less time in hospital, experience fewer complications, require fewer medications and treatments, and are more productive for society. These factors save significant resources for the NHS, while a healthier population contributes more to NHS funding. Although this may seem obvious, it bears repeating. We sometimes fall into the mindset that we’re too busy dealing with crises to focus on a detailed analysis of quality and safety.
For instance, the UK currently has 2.8 million working-age residents who are economically inactive due to illness, a figure that has increased by around 40% in the past five years. This has two major implications: rising costs for health and social care systems, and significant lost value to the economy. If this trend continues, it will impose enormous costs and cause unsustainable pressure on public services.
This is why I’m convinced that high-quality care is not just important, but essential. We cannot afford to view it as a secondary goal, subordinate to operational targets. Preventing illness, identifying health issues early, and treating them proactively with quality care must be central to the NHS strategy. Otherwise, we risk an unmanageable surge in healthcare demand.
We need to shift our focus towards prevention and proactive care. Where health needs arise, we must identify them early, treat them promptly, and ensure care is of the highest quality. Only through this approach can we safeguard both patient outcomes and the sustainability of the NHS. Achieving this requires transparent, near-real-time monitoring of clinical quality and safety metrics. After all, what gets measured, gets improved.
The true value of proactive care is in its potential to improve patient health while saving NHS resources. Far too often, patients on elective waiting lists or with long-term conditions only receive attention when their condition worsens or an emergency arises. Early intervention can prevent this, leading to better outcomes and fewer expensive treatments down the line. For instance, a routine keyhole day surgery can escalate into a major operation if delayed, resulting in longer hospital stays, more ICU utilisation, and poorer outcomes for the patient.
Measurement and monitoring of quality
Of course, the NHS already engages in extensive quality measurement and reporting, with many passionate professionals involved and participating through a growing Q community – the Health Foundation project set up to connect numerous health professionals to explore and share ways to improve care quality and experience. The delivery of safe, quality services is a core value for most people working in the NHS. We have recently heard from the Health Secretary about plans for more formal performance measures and quality monitoring through a kind of league table for the NHS.
However, we need to examine what exactly we’re measuring, and how. Typically, we monitor average outcomes—such as complications, infections, and falls—and compare them across trusts and integrated care boards (ICBs). Often operational targets are given priority and short-term focus. While this is useful, it offers limited insight into the unique characteristics of different patient groups across organisations or even within the same organisation over time.
To generate meaningful comparisons, we must account for the specific risks associated with different patient cohorts. This could be at the level of a hospital department or even an individual clinician. Quality of care is a combination of outcomes and clinical risk, and outcomes alone don’t tell the full story. Without factoring in personalised clinical risks, we often end up with misleading conclusions from average outcomes.
For example, two hospitals may show similar mortality or complication rates, but without adjusting for the unique risks of their patient populations, we cannot accurately assess the quality of care provided. This is why risk adjustment and cohort matching are essential in academic research, where they increase the credibility of results. Yet, these techniques are often considered too difficult to implement in real-world operational analysis.
This presents a significant challenge. The difficulty lies not just in understanding clinical risk, but in doing so at scale, consistently, accurately, and cost-effectively. A consultant reviewing an individual patient’s records can assess risk quite effectively, but with around 600 million patient encounters each year in the NHS, individualised risk assessments are impractical. Instead, this needs to happen in the background, using existing data without requiring additional input from clinicians.
While existing records may be limited in detail, combining them with sophisticated algorithms and extensive datasets allows for large-scale, automated risk prediction. This approach can generate valuable insights into care quality without overburdening NHS staff.
This is a challenge that has been worked on for over 30 years by Dr Graham Copeland and Steve Mackenny, the founders of C2-Ai. They sought to better understand quality and performance, beyond merely counting things that go wrong. They realised that true insight comes from understanding patient risk across different organisations and time periods. Originally an academic pursuit, this work led to the development of the POSSUM score—a predictive model for assessing risk in surgical patients.
With advances in information technology, analytics, and AI, they saw an opportunity to scale this risk prediction using existing data, without requiring additional data input from clinical teams. This has been the driving force behind C2-Ai for over a decade, and their work has since spread globally, including within the NHS.
Productivity and sustainability
Quality care and risk prediction also play an essential role in improving NHS productivity. Routine, predictable care is far more productive than complex, urgent treatment. Without better control over quality and more proactive care pathways, meaningful improvements in NHS productivity will be difficult to achieve. The current productivity gap is not because NHS staff are working less; in fact, they are working harder than ever. Instead, the gap arises from the increasing complexity and unpredictability of healthcare demand, which makes it difficult to improve output.
If we can manage this complexity and provide more consistent, quality care, we will see significant improvements in productivity, allowing the NHS to meet the growing demand for services without being overwhelmed.
The NHS is clearly at a crossroads, facing an array of unprecedented challenges. There is a pressing need for systemic reform, and this reform must place quality care and patient-centred approaches at its core. I think the current focus on monitoring quality and increasing accountability is most welcome, but it must be done in a way which is transparent and with objective, comparable measures of quality.
Granular quality monitoring, personalised patient care, and proactive interventions are key to improving health outcomes and ensuring the sustainability of the NHS. Without reversing current trends in population health and outcomes, no matter how creative or well-intentioned other reforms may be, they will ultimately be overwhelmed by ever-increasing demand.
