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Real World Evidence

Day-to-day challenges in addressing Real World Data: understanding, generating and transforming it into value

October 6th, 2016 - 0 Comments

Real world data is being rapidly recognized as a powerful tool in generating insightful evidence on the ground reality of a particular disease or drug: how a particular disease is actually poised over the population and how a particular healthcare product is affecting the population suffering from a specific disease.

Tools for collecting real world data such as registries, observational studies and RWE studies are gaining tangible momentum in usage. Firstly, this is due to the fact that regulators and health authorities around the world are requesting local evidence about the value of new and existing healthcare products, linking this evidence to pricing and reimbursement decisions. But also because real world data supports health and economic outcomes, benefiting both healthcare companies and payers.

However, challenges prevail when it comes to collecting and developing meaningful insights from real world data:
• How can meaningful objectives and relevant end-points be defined in a non-RCT environment?
• Is it possible to generalize the collected results to a larger population?
• Given the lack of clinical research rigor, how can one ensure data completeness and accuracy?
• Is it possible to minimize confounders and potential for bias?
• How does the healthcare industry allay the physicians’ fears on potential misuse of the data?

The above challenges can be tackled by engaging the right partners for the design and conduct of the RWE studies and by employing tools, like scientifically designed data collection platforms, to create stakeholders among the physician community for wider dissemination of outcomes.

Analytics is the key interface between real world data and consumers. The role of analytics has gained more prominence with the emergence of non-clinical stakeholders influential in decision making and policy shaping initiatives. The recipients of RWE data can be broadly classified into:
Physicians: Doctors and their associations remain key partners in achieving market access for a product. Nevertheless, the globally occurring healthcare reforms are affecting the prescription dynamics and shifting the balance of decision-making power away from physicians to other stakeholder groups
Payers: Increasing healthcare costs are forcing payers to install cost control mechanisms, leading to new/additional hurdles for patient access demanding real world/observational data. Increasingly payers are collaborating with healthcare companies and other stakeholders to develop shared value offerings, thus optimizing their expenditures and reimbursement process
Advocacy groups: Advocacy groups are non-profit organizations which often exert direct influence on policy shaping. Communicating the value derived from the analyses of observational studies and real world data regularly enables these groups to positively influence other stakeholders to improve patient access to new healthcare products
• Patients: The patient is the ultimate consumer of the product and often the final decision maker through his purchasing power. Understanding patient behaviors and factors involved in converting a prescription into a purchase is a critical factor to achieve access in the right channels. RWE analytics help in providing a realistic view of the patient while moving through the disease journey

The outcome of data analytics allows to clearly identify all the relevant patient segments, pinpointing the number of eligible patients at every stage. It also highlights the clinical and commercial aspects associated with the currently available treatment options.

Through robust analytical techniques the user can discover vital insights instrumental to target the right patients with the right product at the right time. They also enhance the knowledge on the current treatment outcomes and the correlated values.

Only through the marriage of real world data and robust data analytics the above mentioned areas of concern, specifically in health economics and outcomes research, can be addressed. The insights gained from this fusion will be crucial for all healthcare stakeholders.

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