Although randomised controlled trials (RCTs) remain the gold standard for generating clinical evidence, they are not designed to answer every question relevant to everyday healthcare. In fact, a significant proportion of hospital care today is not strongly evidence-based. Not due to a lack of rigour, but because many real-world clinical questions cannot be studied ethically or practically through RCTs. As Platt et al. explain in Health Affairs, the “efficacy–effectiveness gap” is driven by challenges such as narrow trial populations, limited follow-up durations, and the inability to use untreated control groups where standard care cannot ethically be withheld.¹ In this context, real-world data (RWD) provides a valuable complementary source of evidence, capturing care as it happens, across a diverse range of patients and settings.
Common use of RWD today
RWD is increasingly used to supplement clinical research, support regulatory submissions, and inform guidelines. Yet significant challenges remain. In Europe especially, hospital data is fragmented—not only across countries but also between institutions and departments. Variability in data formats, privacy regulations, and analytic standards makes it difficult to generate insights at scale.
Moreover, real-world research often focuses narrowly on single-disease registries or even single drugs. While these are valuable, they do not reflect the interconnected nature of many diseases. Patients commonly present with multimorbidity or benefit from treatments applicable across indications. Understanding these overlapping patterns of care requires integrated, cross-specialty datasets. This is something that traditional registries struggle to accommodate.
How Healthcare Observatories Address These Challenges
Healthcare Observatories offer a structured way to address common limitations in real-world data research. A Healthcare Observatory is a construct equipped for observing information about the diagnostics and/or treatment of a disease area across a pre-determined geographical area by gathering, harmonising, and analysing data shared by relevant healthcare stakeholders that have opted into participation. By bringing together hospitals across different regions and clinical domains, Observatories enable collaborative data sharing and support studies that reflect the complexity of routine care with insights that are representative to the greater public. Unlike traditional disease registries, they are designed to capture patterns across related conditions and specialties. Their flexible setup accommodates varying levels of data maturity, allowing both structured and semi-structured information to be analysed. This helps generate evidence that complements existing clinical research and supports a broader understanding of care delivery.
Our Methodology in Action
At LOGEX, we’ve developed Observatories in key therapeutic areas where evidence gaps are most pressing:
- IMID (Immune-Mediated Inflammatory Diseases) Observatory
- RTI (Respiratory Tract Infection) Observatory
Each Observatory aggregates anonymised, longitudinal data from multiple hospitals and applies a consistent, scientifically robust analytics framework. This supports comparative effectiveness research, safety signal monitoring, and the generation of actionable insights.
A recent example of our methodology in practice is the REACH study, conducted in collaboration with Sanofi. This multi-country, retrospective analysis used data from the LOGEX RTI Observatory to assess the public health impact of different infant RSV immunisation strategies in Spain and the UK. The study helped address a key evidence gap by quantifying real-world reductions in RSV-related hospitalisations in a late-breaker session.
Conclusion
As healthcare systems strive to become more data-driven, real-world evidence will be essential to guide better decision-making. Our Observatory methodology is designed to meet this need, enabling scalable, ethical, and clinically relevant research that reflects how care is delivered and what the actual effectiveness of that care is.
If you are interested in joining one of our Observatories, we’d love to hear from you.
¹ Platt, R., Davis, R., & Finkelstein, J. (2018). The Efficacy–Effectiveness Gap In Health Care: Limitations Of Randomized Trials Create Challenges In Clinical Decision Making. Health Affairs, 37(2), 216–222. https://doi.org/10.1377/hlthaff.2017.1110
