Key Considerations for Successful Data Collaborations
Why this trend has surfaced and key considerations for pharmaceutical companies actively exploring their own collaborations.
With the recent explosion of healthcare data in the U.S. as well as the announcement of several well-publicized partnerships between manufacturers and providers or payers, the emergence of data collaborations is currently one of the hottest trends in healthcare.
New Demands on Pharma
It’s no secret that the pharmaceutical industry is facing a series of unprecedented challenges. Payers are increasingly demanding that new products and treatments demonstrate both economic and clinical value, as escalating healthcare costs are no longer considered sustainable. With mounting pressure from payers as well as increased regulatory scrutiny and financial penalties tied to clinical performance, providers are also becoming much more focused on cost and outcomes– a trend that’s expected to accelerate as provider consolidation continues.
In this evolving environment, randomized clinical trials (RCTs)– the long-time “gold standard”– are increasingly being viewed as inadequate. Because RCTs typically enroll patients with uncomplicated profiles for the condition of interest, trial results don’t necessarily reflect real-world performance, and potential negative outcomes sometimes go undetected until after launch. RCTs also generally include only an experimental and control group, making direct comparisons with current in-market products and treatments difficult.
As a result of these serious limitations, key stakeholders are shifting their focus to real-world evidence (RWE) when making decisions on market access, reimbursement, and product adoption. Unlike RCTs, RWE studies typically include observational data based on actual product use in “real life” clinical practice. Also, comparative data against the current standards of care are often more readily available in RWE studies.
The Potential of Data Collaborations
In addition to bolstering RWE claims, data collaborations also have the potential to be “game changing,” opening the door to more targeted, innovative therapies and even impacting the way in which drugs are discovered, developed, and marketed.
As key stakeholders increasingly demand products that demonstrate significant economic and clinical value–with value claims justified by RWE– pharmaceutical companies are exploring data collaborations with organizations from across the healthcare industry. Because of the wealth of data now being collected by payers, providers, and other organizations - including genomic data, claims data, research data, and patient medical records – collaborations offer pharmaceutical companies opportunities to leverage data and generate insights like never before. In addition to bolstering RWE claims, data collaborations also have the potential to be “game changing,” opening the door to more targeted, innovative therapies and even impacting the way in which drugs are discovered, developed, and marketed. In fact, several industry leaders, including Pfizer and Merck, are already engaged in data collaborations, partnering with leading healthcare organizations like Mayo Clinic and Harvard Medical School.
Considerations for Successful Data Collaborations
Clearly, data collaborations represent a promising opportunityfor pharmaceutical companies. However, it’s critical to understand that the amount of data isn’t nearly as important as ensuring that it’s being leveraged effectively. Also, actually implementing data collaborations is often complex, requiring pharmaceutical companies to engage in activities that they may have little or no experience with, like sharing potentially sensitive data with payers, providers, and other partners. In light of these potential issues and challenges, here are several key considerations for pharmaceutical companies actively exploring data collaborations:
- Build internal capabilities: To maximize the potential of data collaborations, pharmaceutical companies must shift their focus to developing products that deliver value for all stakeholders, including payers, providers, clinicians, regulators, and patients. In order to do so, companies must work to understand the specific needs of key stakeholders, actively engage with them throughout the product lifecycle, and develop compelling value narratives that resonate with each audience. This also requires an integrated approach across the entire product lifecycle – from R&D to commercialization – that focuses on the open exchange of knowledge, information, and insights between internal teams. At the same time, pharmaceutical companies must shift their attention from large, heterogeneous patient populations to narrowly-defined niches. That’s because these new data sources and analytic capabilities will make it possible to develop highly customized products that can demonstrate significant economic and clinical value to key stakeholders, and greatly improve the lives of these narrowly targeted patient populations. In addition, companies should make sure they have the core capabilities in place to collect, store, and analyze data from a wide variety of sources, including clinical trials, non-interventional observational studies, retrospective database studies, patient reported outcomes, and electronic health records (EHRs).
- Develop effective working relationships: When engaging in data collaborations, it’s critical for pharmaceutical companies to develop effective working relationships with external partners. As part of these efforts, partner organizations should work together to ensure that data quality standards are maintained, data access is limited to only those with appropriate approval, and all relevant laws – including state, federal, and international law – are followed. Attention should also be given to developing comprehensive communication and governance structures that clearly define how information will be exchanged and the specific accountabilities of each partner.
- Address privacy and security concerns: Given that many pharmaceutical companies are probably new to sharing sensitive data (including patient data) with partner organizations, they must work closely with their internal legal and regulatory teams to understand, monitor, and minimize the risks associated with sharing, collecting, storing, and analyzing healthcare data, especially patient-identifiable data (PID). This will also require an extensive review of internal databases to determine the data that can be safely shared with outside parties. Additionally, because of the recent increase in cyber-attacks –like the security breach at Premera Blue Cross, which may have exposed the medical and financial records of 11 million customers1–pharmaceutical companies must ensure that their IT teams have the appropriate skills, resources, and training for dealing with security threats and that best practices are consistently being followed.
Going forward, opportunities for data collaboration will surely continue to arise. However, making the most of these collaborations requires significant time, effort, planning, and resources. Without the right infrastructure and capabilities– along with appropriately-defined working relationships, comprehensive legal and regulatory oversight, and robust data security–pharmaceutical companies are at risk of having data collaborations that are destined for failure, or that may even expose the organization to potential liabilities.
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