By Vasko Graklanov, MD, PhD, MPH

This expert commentary is part of Sqilline Health’s ongoing effort to advance real-world evidence generation in hematology and oncology across Europe.

Key Takeaways

  • Fragmented and unstructured data remains a major barrier to effective RWE generation in hematology.
  • Data quality, standardization, and access challenges limit the ability to derive robust clinical insights.
  • Clinical trial populations often fail to represent real-world patients, particularly in Central and Eastern Europe.
  • Regulatory bodies such as the EMA are increasingly integrating real-world evidence into decision-making frameworks.
  • Structured, analysis-ready data has the potential to significantly reduce physician workload and accelerate research.

The Reality: Fragmented Data, Lost Time, Missed Insights

In clinical hematology and oncohematology, the promise of Real-World Evidence (RWE) is increasingly recognized. However, its routine generation and application remain constrained by structural and operational limitations.

Clinical data are rarely captured in a unified or analysis-ready format. Instead, they are distributed across laboratory systems, electronic health records, registries, and pathology reports. This fragmentation imposes a substantial burden on clinicians and researchers, who must manually reconcile disparate data sources to construct longitudinal patient narratives. The consequence is not only inefficiency, but also variability in data interpretation and reduced reproducibility of findings.

Data quality and standardization present additional challenges. Heterogeneous formats, incomplete records, and inconsistent coding practices frequently limit the ability to perform robust analyses at scale. As a result, potentially valuable clinical observations often remain descriptive rather than evidence driven.

Barriers related to governance and data access further restrict the generation of RWE. Regulatory complexity, institutional policies, and fragmented ownership models can delay or prevent the use of existing data for research purposes. In practice, this leads to the abandonment of clinically relevant research questions that would otherwise be feasible.

A further limitation lies in the representativeness of available evidence. Clinical trial populations do not consistently reflect the heterogeneity of patients encountered in routine practice, particularly in Central and Eastern Europe (CEE). This disconnect raises important concerns regarding the external validity of trial-derived evidence in real-world clinical settings.

The Opportunity: A Transition Toward Data-Enabled Hematology

Despite these constraints, the role of RWE in hematology is undergoing a notable transition.

Regulatory authorities, including the European Medicines Agency (EMA), are progressively incorporating real-world data into frameworks for reimbursement and regulatory decision-making. This evolution reflects a broader recognition that traditional clinical trials, while methodologically rigorous, cannot fully capture the complexity and variability of real-world care.

At the same time, inefficiencies in current research workflows remain substantial. Manual chart review and data extraction continue to represent a significant proportion of research effort, introducing both delays and potential sources of error. These constraints limit the scalability of evidence generation and reduce opportunities for participation in multinational collaborations.

The availability of structured, analysis-ready data represents a critical inflection point. By reducing the need for manual data preparation, such approaches can enable more rapid hypothesis testing, facilitate reproducible research, and support integration into international evidence-generation initiatives.

Central and Eastern Europe: From Underrepresentation to Contribution

Central and Eastern Europe remains underrepresented in the global oncology evidence base, despite a substantial clinical and patient population.

Addressing this gap requires not only increased research activity but also improved data infrastructure. The ability to generate standardized, high-quality real-world datasets across multiple institutions and countries would enable the region to contribute more meaningfully to global evidence generation.

Initiatives that aggregate and structure patient-level data at scale, such as those developed by Sqilline Health, illustrate the potential of this approach. By enabling access to harmonized datasets across diverse healthcare settings, such models can support the generation of evidence that is both locally relevant and internationally comparable.

This shift is not solely academic. It has direct implications for clinical decision-making, guideline development, and health policy, particularly in regions where local data have historically been limited.

Reclaiming Clinical Time

In oncohematology, physician time represents a critical and finite resource.

The current reliance on manual data extraction, chart review, and administrative processes imposes a substantial opportunity cost. Time allocated to these activities is necessarily diverted from patient care, clinical reasoning, and scientific inquiry.

Reducing this burden is therefore central to improving both clinical outcomes and research productivity. Approaches that transform fragmented clinical data into structured, analysis-ready formats offer a pathway toward this goal. By minimizing manual effort, such systems allow clinicians to reallocate time toward higher-value activities, including interpretation of evidence and patient-centred care.

Conclusion

The integration of real-world evidence into clinical hematology is no longer a theoretical objective, but an emerging necessity.

While significant challenges persist, including data fragmentation, limited standardization, and governance constraints, the trajectory is clear. Advances in data structuring and interoperability are enabling new models of evidence generation that are more reflective of routine clinical practice.

The extent to which these opportunities are realized will depend on the alignment of clinical, technological, and regulatory stakeholders. If successfully implemented, RWE has the potential to enhance the relevance, equity, and impact of evidence in oncohematology.

Q&A: Practical Perspectives from Clinical Practice

What is the primary limitation in current RWE generation?

The limitation is not the absence of data, but the lack of structured, interoperable data that can be readily used for analysis.

Where are the greatest inefficiencies in current research workflows?

Manual chart review and data extraction remain the most resource-intensive steps, limiting both speed and scalability.

What would most significantly improve research productivity?

Access to standardized, analysis-ready datasets that reduce the need for manual preprocessing.

How can CEE strengthen its contribution to global oncology evidence?

By investing in data infrastructure and systematically generating high-quality real-world evidence from regional patient populations.

What role should digital solutions play in clinical research?

Digital tools should primarily reduce administrative burden and enable clinicians to focus on interpretation, decision-making, and patient care.

How should clinicians view the role of RWE in practice?

As an integral component of modern clinical care, rather than a separate or additional research activity.

About the Author

Dr. Vasko Graklanov, MD, PhD, MPH is a clinical hematologist at UMHAT “St. George,” Plovdiv, and Assistant Professor at the Medical University of Plovdiv. His work focuses on the integration of real-world evidence into clinical practice, with particular emphasis on data quality, research methodology, and the representativeness of oncohematology populations in Central and Eastern Europe. He has authored more than 40 scientific publications.