Healthcare systems around the world are under growing pressure to deliver better outcomes with limited resources. At the same time, policymakers must often rely on incomplete or inconsistent data, making choices about healthcare provision complex and uncertain.
This challenge is significant. In the UK alone, the NHS spends more than £200 billion each year, yet much of this expenditure funds interventions whose long-term effectiveness is not fully understood. Globally, the World Health Organisation estimates that 20 - 40% of health spending is wasted due to inefficiencies, often linked to gaps in evidence or the way evidence is applied.
A key issue is that the evidence available is not always the evidence decision-makers need. For instance, while clinical trials are considered the gold standard for determining whether a treatment works, they are typically conducted on carefully selected patients in controlled settings over relatively short timescales. However, in reality, the patients who ultimately receive these treatments are often older and sicker, with more complex health conditions, than trial participants. As a result, the outcomes that matter most to health systems, such as long-term survival, quality of life, and lifetime costs, often cannot be directly observed.
Using Statistical Approaches to Enable Better Decision-Making
Research led by Professor Rhiannon Owen at Swansea University is redefining how critical decisions in healthcare are made, specifically how healthcare interventions are evaluated for effectiveness and cost-efficiency, both in the UK and internationally. Central to this is the development of tools and methodologies that enable healthcare policymakers to make more robust and transparent decisions when evidence is incomplete or uncertain.
In her work, Professor Owen utilises Bayesian statistical methods that combine evidence from multiple sources, including clinical trials and real-world healthcare data, and frequentist methods, which rely on observed data to estimate effects and assess statistical significance.
A key strength of Bayesian statistical methods is their ability to formally incorporate prior knowledge, such as findings from earlier studies, biological plausibility, or clinical expertise, to generate a full probability distribution of possible outcomes. This allows decision-makers to assess the likely effectiveness of each treatment, including which is the best overall, and to understand the uncertainty surrounding those conclusions.
Frequentist methods, on the other hand, provide unbiased, reproducible estimates, and clear rules for hypothesis testing without requiring prior assumptions or subjective input. This makes them particularly valuable for standardised analyses, regulatory settings, and situations where transparency and consistency are essential.
The use of real-world healthcare records enables large-scale analyses of patient outcomes across diverse populations, including often underrepresented groups. As part of her work, Professor Owen accesses linked electronic health records from the SAIL Databank, one of the world’s largest repositories of linked anonymised health records.
Delivering Better Outcomes with Limited Resources
By applying techniques such as network meta-analysis, healthcare professionals and policymakers can compare multiple treatments simultaneously to identify the most effective options.
Combined with economic modelling, this approach helps determine which interventions provide the best value for money, an essential consideration for publicly funded systems like the NHS.
For patients, this translates into:
- more effective diagnostic pathways, helping to diagnose conditions earlier and avoid unnecessary or ineffective procedures
- targeted treatments, providing treatments that are more tailored to individual needs
- improved access to interventions that deliver meaningful benefits
- better representation in decisions, incorporating evidence from real-world populations, ensuring patients who are typically excluded from trials (older adults, those with multiple conditions) are better reflected in the evidence base
- transparency of uncertainty, providing probability-based outputs which support more informed conversations about individual care
For healthcare providers, it means:
- faster adoption of effective treatments, enabling interventions to be approved and implemented more quickly where strong evidence supports their use
- improved patient care, ensuring individuals are more likely to receive treatments that are proven to be effective
- more efficient allocation of resources, targeting limited funding to where it has the greatest impact/benefit
Influencing National Policy and Informing the Response to a Global Crisis
One of the most significant impacts of Professor Owen’s work is its integration into the decision-making processes of the National Institute for Health and Care Excellence (NICE), the public body responsible for determining which medicines, treatments, and health technologies are funded and adopted across the NHS in England and Wales.
As part of NICE frameworks, her methodologies regularly inform technology appraisals for pharmaceuticals, diagnostics and treatment pathways, contributing to more consistent, evidence-based decision-making, and directly influencing which interventions are approved, funded and delivered to patients across the UK. To date, in her role as part of the NICE TAC B Committee, Professor Owen has appraised nearly 100 technologies for use in the NHS.
The importance of this robust, evidence-based approach became especially clear during the COVID-19 pandemic, in which Professor Owen’s research contributed to UK and European vaccination strategies, providing timely, high-quality evidence. At a moment when decisions needed to be both rapid and reliable, her expertise supported the analysis of vaccine safety and effectiveness, including assessments of blood clot risks and insights into COVID-19 vaccine uptake among children and young people.
In Wales, Professor Owen’s work has been used by the Welsh Government to inform health policies around palliative care service provision, and to examine how conditions such as psychosis, diabetes and congestive heart failure develop over time and the impact on life expectancy.
Building Capacity Across the Global Healthcare Sector
Through ongoing training, and the development of software for clinicians, analysts and policymakers in the UK, Professor Owen is helping embed advanced statistical methodologies into everyday practice, improving skills and strengthening capacity in evidence-based decision-making across the health sector.
Her methods are also being adopted and adapted internationally, supporting health technology assessment agencies and pharmaceutical organisations in navigating uncertainty, cost and complexity in their regulatory and policy decision-making processes. Countries that have adopted Professor Owen’s methodologies in their policy-making processes include USA, Canada, UK, Spain, Switzerland, Australia, France, Germany and Ireland.
Together, these efforts are ensuring that the benefits of this research are far-reaching, with the ultimate goal of improving patient outcomes and the resilience of healthcare systems, both in the UK and around the world.
