Outcomes Research

Outcomes Research

Clinical and outcomes research

  • Disease and treatment analysis
    Conduct real world evidence studies on disease burden, treatment patterns, and patient outcomes.
  • Risk and effectiveness
    Perform risk stratification and comparative effectiveness research to evaluate treatment impact.
  • Data-driven insights
    Utilize registry, database, and EHR data to generate robust, evidence-based findings.

Health economics

  • Resource utilization analysis
    Assess healthcare resource use to identify efficiency and cost drivers.
  • Cost evaluation
    Measure both direct and indirect healthcare costs for comprehensive economic insights.
  • Market access support
    Provide evidence that demonstrates value and strengthens market access strategies.

Regulatory-grade real world evidence

  • Regulatory evidence support
    Provide robust evidence to strengthen and complement regulatory submission packages.
  • Innovative trial approaches
    Apply pragmatic trials and synthetic control arms to generate credible, real-world insights.
  • Prospective registries
    Utilize forward-looking registries to enhance data depth and meet compliance standards.

FAQ

Nordic real-world data (RWD) provides a strong foundation for generating high-quality evidence to support clinical development, market access, and public health decision-making.

Nordic RWD is often considered among the most robust in the world, largely due to the structure of Nordic healthcare systems and a long tradition of systematic data collection. Countries like Sweden, Denmark, Norway, and Finland maintain nationwide health registers that cover entire populations and can be linked at the individual level using unique personal identity numbers.

This linkability is a major advantage, as it allows researchers to follow patients over time and across different parts of the healthcare system, including hospital care, prescriptions, and disease-specific quality registers. It also enables linkage to other national registers, making it possible to incorporate socioeconomic data, sick leave and social insurance data, link parents and children, and construct matched cohorts from the general population for comparative analyses.

In Sweden alone, there are more than 100 national quality registers and over 200 biobanks, providing rich clinical detail that is rarely available at scale elsewhere. In addition, laboratory data can often be extracted directly from hospital electronic health records. In countries such as Finland, centralized data lake solutions further enable access to structured lab and clinical data at scale.

Another key strength is data completeness and consistency. Because healthcare is largely publicly funded, most healthcare interactions are captured, reducing gaps commonly seen in RWD collected in other healthcare settings. For instance, insurance claims data, commonly used in other markets, is primarily collected for billing purposes and often lacks clinical depth.

These combined features make Nordic RWD particularly well-suited for a wide range of real-world evidence analyses, including survival and time-to-event analyses, studies of healthcare resource utilization and costs, long-term follow-up of treatment outcomes across large populations, and analyses of indirect costs, such as productivity loss and sick leave, which are often difficult to capture in other data settings.

Nordic real-world evidence (RWE) provides a robust and pragmatic complement to clinical trial in regulatory decision-making.

Nordic RWE supports regulatory decisions by generating population-level evidence that complements clinical trial data. Because Nordic countries maintain comprehensive, linkable health registers, researchers can assess treatment effectiveness, safety, and long-term outcomes across entire populations.

Regulatory agencies such as the European Medicines Agency and the U.S. Food and Drug Administration have expanded the use of RWE, particularly where randomized controlled trials are not feasible or where additional evidence is needed post-approval. Methods such as target trial emulation are increasingly applied to estimate treatment effects from real-world data by explicitly defining and emulating a trial design.

RWE is a key component of an Integrated Evidence Generation Plan, helping to address evidence gaps across the product lifecycle that are not covered in clinical trials. Nordic data are particularly valuable in this context because it allows long-term follow-up of patients and access to clearly-defined, population-based cohorts. 

In practice, Nordic RWE is used to support regulatory submissions, inform label extensions, and generate evidence in settings where trial data is limited. It is also widely applied in post-authorization safety studies, long-term outcome studies, and evaluations in broader, more representative patient populations than those typically included in trials.

Nordic real-world evidence (RWE) helps translate clinical trial results into real-world value, supporting more informed market access decisions.

Nordic RWE supports market access by providing insights on how treatments perform in routine clinical practice, beyond the controlled setting of clinical trials. This includes evidence on effectiveness, safety, and healthcare resource use, all of which are relevant for reimbursement and pricing decisions.

Because Nordic real-world data (RWD) covers entire populations and enables long-term follow-up, it is well suited for demonstrating treatment value in real-world settings. This is particularly relevant for health technology assessment bodies and payers when evaluating whether a treatment should be reimbursed and under what conditions.

The ability to link healthcare data with socioeconomic and social insurance data further makes it possible to assess broader outcomes, such as indirect costs, productivity loss, and sick leave. This strengthens cost-effectiveness evaluations and the overall value story, especially in settings where societal perspective is considered.

In practice, Nordic RWE is used to support reimbursement submissions, inform pricing and negotiation discussions, and generate evidence for value-based agreements. It can also help address uncertainties that remain after clinical trials, for example by providing data on long-term outcomes or clinically-relevant patient subgroups.

Words form our clients

Quote

We are very pleased with the quality and clarity of the analysis provided by Ciencia Research (previously Schain Research). The team delivered efficiently and maintained clear, transparent communication throughout the process. Their work has been instrumental in supporting our study planning, and we appreciate their professionalism and scientific rigor.

– A world leading global consumer products manufacturer: R&D Team 

Jim Baker

Jim Baker
Business Development
Executive

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