Healthcare decisions increasingly rely on data from routine practice. Their value is considerable, but interpretation requires particular rigor.
Why real-world evidence matters
Clinical trials remain essential to demonstrate the efficacy and safety of an intervention. But they do not always reflect routine practice: adherence, comorbidities, care organization, patient pathways, or available resources.
Real-world evidence complements this view and helps assess how an intervention performs in contexts closer to practice.
Useful inputs for economic models
Real-world data can inform key parameters: observed costs, resource use, event frequency, treatment duration, persistence, care pathways, or quality of life.
It can also help adapt an international model to a local setting, which is particularly important for payers, ministries, and institutions.
Powerful data, but never neutral
Real-world data may be affected by selection bias, missing data, coding differences, or confounding. Its value therefore depends heavily on analytical methods and transparent assumptions.
A strong analysis does not present these data as raw truth. It explains their scope, limitations, and influence on the decision.
The link with the decision should be defined before analysis
Before using real-world evidence, the decision question must be clarified: is the objective to confirm observed effectiveness, estimate local costs, document a care pathway, measure treatment persistence, or inform a budget impact analysis?
This prevents teams from producing descriptive work that is interesting but hard to use. Data should be organized around a specific use: reimbursement, HTA, local adoption, prioritization, or negotiation.
Data governance is part of credibility
The quality of an analysis also depends on source traceability, variable definitions, handling of missing data, and consistency of statistical choices. These elements may seem technical, but they shape the confidence decision-makers place in the result.
A credible deliverable should therefore explain not only what the data show, but also how they were prepared, cleaned, analyzed, and interpreted.
A lever for more contextualized decisions
Used well, real-world evidence makes economic evaluations more aligned with local constraints and adoption conditions.
Santicxis helps transform these data into clear, robust analyses that support funding, reimbursement, and care organization decisions.