In the evolving landscape of healthcare, real-world data (RWD) has emerged as a vital resource. But what exactly is RWD? It encompasses information about patient health, experiences, and care delivery collected outside the controlled environment of clinical trials. This data is increasingly used for marketing authorisations and health technology assessments (HTA) in the EU. However, while RCTs (randomised controlled trials) remain the gold standard for demonstrating causality, RWD presents unique challenges.
The Complexities of Real-World Data
Have you ever wondered why RWD is so complex? It's often plagued by noise, biases, and confounding factors, making the demonstration of causality a complex and time-consuming process. Data can be incomplete, subject to measurement error, or just not fit for purpose. For instance, registry data may have limited follow-up visits and endpoints that are not routinely captured. Additionally, methods such as propensity score adjustment are often data-driven and not fully pre-specified, introducing potential subjectivity. Due to the unknown risk of bias, many sensitivity analyses, like Quantitative Bias Assessment (QBA), may have to be performed. This requires careful planning and sufficient time for programming.
The Need for Rigorous Standards
Not all RWD analyses are equally feasible or scientifically sound. So, what can be done to ensure quality? A gatekeeper is essential to scrutinise and prioritise PICO requests based on rigorous scientific standards of internal validity. With the challenging EU HTA JCA timelines this need is more urgent than ever.
Collaboration for Better Outcomes
How can stakeholders make a difference? Collaboration is key. Stakeholders must work together to establish robust frameworks and standards for RWD analysis. By prioritising scientific rigour and internal validity, we can ensure that RWD contributes effectively to healthcare decision-making and improves patient outcomes.
Potential Benefits of Collaboration
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Enhanced Analysis Quality: Collaborative efforts can lead to the development of standardised methodologies, reducing biases and improving the reliability of RWD.
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Accelerated Innovation: By working together, stakeholders can streamline processes, leading to faster approvals and access to innovative treatments.
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Improved Patient Outcomes: Effective use of RWD can lead to more personalised and effective healthcare interventions, ultimately benefiting patients.
In conclusion, while RWD holds great promise for HTA, it requires meticulous attention to detail and collaboration among stakeholders to realise its full potential. Above all, the time required to plan, collect, and analyse RWD in a sound scientific manner should not be underestimated. By working together, we can navigate the complexities of RWD and harness its power to improve healthcare outcomes for all.
