We often talk about the importance of capturing the patient perspective in clinical trials. But these insights can add tremendous value across the commercial product lifecycle.
When leveraged as part of the commercial strategy, real-world patient data can help pharma companies get the right products to the right patients at the right time in order to improve patient outcomes.
Prior to launch, these insights help pharma leaders better understand the current disease landscape, patient characteristics and unmet need, build budget impact models, and establish brand messaging and outreach plans. Once a product is in the market, real-world patient data can be used to identify relevant healthcare professionals (HCPs) who treat patients of interest, and to embed tools in clinical practice to inform treatment decisions to improve population health.
All of this adds value across the stakeholder landscape. But it only works if pharma companies have the access, technology, and local domain expertise to use real-world patient data as part of their commercial plan. European markets in particular present unique challenges around the availability of data sources. Strict data privacy regulations, the fragmentation of data sources across primary and secondary care, and the decentralization of decision-making are the main limitations.
In a recent webinar, entitled Improve Your Brand Opportunity Using Precise Patient Identification, IQVIA’s real-world patient data experts, Ban Tawfik, Andrea Seltmann, and Ashley Pitcher, discussed how companies can leverage advanced analytics with real-world data throughout the product lifecycle, and how it can add value at every step in this journey.
Patient identification is the foundation for everything pharma does. Knowing who the patient is, how they suffer, and what outcomes will improve their quality of life is the basis of research and the framework for commercial strategy.
Gathering these insights is even more critical now that the industry is shifting to niche indications with narrow patient populations. Finding, diagnosing, and treating these patients is more complicated today, but it can be done.
The volume and variety of real-world patient data now available offers an untapped gold mine of insights about patients of interest. These insights can be found in structured data sets, like disease registries, electronic medical records, and pharmacy reports, along with less structured resources including genomics data, literature reviews, social media, and images captured from labs and connected devices.
All of these resources hold valuable information. But with so much data, it is getting harder to uncover useful insights to rapidly support decision-making.
These real-world data sets can be fragmented, delivery options are often limited, and each country and owner adheres to a different set of data privacy rules, which can limit accessibility.
To overcome these obstacles, pharma companies need a real-world commercial data plan that includes the data, technology, and expertise they will use to find the results they need. IQVIA brings all of these assets to the table. We have one of the largest real-world databases in the world, along with scalable infrastructure that can run AI-driven analytics, and a team of experts who build algorithms for each function and purpose.
IQVIA’s experts have built dozens of algorithms that have helped clients support medical, commercial, and health system decisions as part of their commercial strategy.
In one project, IQVIA worked with a clinical commissioning group and clinical experts to develop an algorithm based on clinical rules to identify patients with heart failure who were not already on the appropriate heart failure register. Presence on the register is important both for GP practice reimbursement and to ensure that patients are receiving the appropriate care and treatment for their condition.
When assessing the impact of the algorithm, the pilot program identified more than 1000 patients to be added to the heart failure register or left ventricular systolic dysfunction register across 12 pilot practices. This resulted in additional revenue of more than £113,000 for the pilot practices, and the algorithm is now used by over 1000 practices today. IQVIA has subsequently demonstrated that AI can be used to further increase the precision of heart failure patient identification.
Building such algorithms requires a deep understanding of the disease area, the data available, and how it is being collected. When pharma companies combine the right data, advanced technology, and industry expertise, they can create AI-driven solutions that transform the mass of real-world data into useful insights to support medical, commercial, and health system decisions.
You can view the entire webinar here or contact an expert to learn more about IQVIA’s approach to real-world patient analytics.