Real World Evidence (RWE)

We offer strategic Real World Evidence (RWE) input throughout the lifecycle of your product identifying data gaps and the best opportunities to show value, whether for payer negotiations, clinical decision making or post-marketing real world effectiveness. We help you stay up to date with your evidence generation strategy to provide you with the best tools for success.

We offer our customers Real World Evidence (RWE) workshops where we together define data gaps and needs in selected therapeutical areas or products and generate a real world evidence plan.

• We assess together with our customers the Real World Data (RWE) needs and gaps and generate a Real World Evidence plan
• Identify data sources to address the identified data needs
• Recognize the various strategic utilization targets of RWE

We offer our customers comprehensive services to generate Real World Evidence (RWE), including all aspects from (pre-)planning to publication and beyond. The services include

• Strategic advice and support – advice and support for your Real World Evidence strategy and insight on the Finnish and Nordic Real World Data landscape
• Planning – defining study objectives, identifying data sources and the most suitable study design
• Study execution – project management, protocol development, study approval application, and data analysis
• Publications and communication – scientific writing and content creation
• Post study activities – utilizing results to the fullest, updating RWE strategy

A full-scale Real World Evidence study is not always the optimal solution, both cost and timewise. For light and defined data needs, FastTrack requests may be the better approach. If you have a specific data need in mind, please contact us to plan the opportunities and discuss strategies.

Data from various sources, including RWE studies, clinical trials and sales data, can be processed to a user-friendly format and used in communication with internal and external stakeholders. We help you make the most out of your data for informed decision making, utilizing our interactive value tools.

Real world data is often used in health economic analyses to support market access and health care decision making. Our experts support your evidence generation process from defining the research question to generating health economic evidence for payer and decision-maker discussions.

Read more about our Health Economic Modelling and Pricing and Reimbursement services.

Local data on patient numbers, outcomes, treatments and healthcare resource utilization are crucial aspects for cost-effectiveness and all stakeholders, especially the payer. This data is increasingly being utilized in budget impact and cost-effectiveness analyses to reduce the ever present uncertainty in health economic analyses.

In addition, showing the effectiveness in real life after the medication’s market entry is also becoming increasingly important. Real World Evidence studies can readily assess these topics.

Information on incidence and prevalence, as well as the survival of patients and patient subgroups, may sound trivial, but often there is a lack of recent data on these. Patient numbers are of significance for the healthcare system when planning care, for the payer to assess the budget impact and for the marketing company when planning new launches.

Real World Evidence is highly appreciated and often mandatory in negotiations with payers. Further, current treatment and outcomes and questions on healthcare resource utilisation can be assessed with Real World Evidence studies or FastTrack requests.

Data from RWE publications and other sources can also be used in discussions with decision makers and can be processed to a user-friendly format utilizing our interactive value tools.

Standard of care and outcomes are essential to understand when a new product enters the market, both from a clinical and payer perspective. Especially oncology drugs and treatments can enter the market with phase 2 data as clinical evidence.

A control group for a clinical trial can be generated from retrospective registry data. This control group is called a virtual control arm. Patients in the virtual control arm are selected from registry data using the selection criteria of the clinical trial. Virtual control arms are used to supplement one and two armed clinical trials with Real World Evidence.

In some cases virtual control groups are formed because a clinical trial would be unethical. For example, in the case of cancer medicines patients cannot be left without treatment. Virtual control arms aim to act as comparators receiving standard of care when assessing the same outcomes as in the patients treated in clinical trials.

We at Medaffcon have conducted successful virtual control arm studies. Contact us, if you want to discuss more!

Patients move between primary and specialty care, and treatment pathways may be intricate and variable by region. The overview of the treatment pathway can be assessed in studies, including occupational healthcare, to gain a holistic view of differences and optimal approaches in care.

Real World Evidence studies can describe patient population subgroups and identify those that may gain most of some treatments or to detect groups in need of intensified monitoring. These results may guide healthcare resource allocations.

Regional difference in healthcare utilization and patient outcomes, incidence and prevalence, can be studied both within Finland, and across the Nordics to gain insight into how the care is organized.

Medaffcon can manage the publication process of the Real world evidence studies.

The vast amount of data behind the real-life evidence, publications and sales contain valuable information that can transform into visually pleasant interactive communication tools.

Interactive value tools

After a drug has become available for patients, information on patient adherence to different medications and treatment persistence is of importance for a successful treatment. These aspects can be assessed in Real World Evidence studies to guide treatment and evaluate the impact on real world effectiveness.