This is the final post in a five-part blog series focusing on how life sciences companies can establish leadership in the field of real-world evidence.
Increasing leverage of electronic health records (EHRs), imaging systems and social media is delivering groundbreaking patient-centric insight like never before. But as companies seek deeper understanding of health outcomes via patient-level data, privacy-enhancing capabilities are becoming not only an imperative but also a critical source of leadership. These same capabilities are key to unlocking the full value of real-world evidence (RWE).
In our previous blog posts we introduced considerations life sciences companies should keep top of mind when building an RWE ecosystem. We also explored: how better research demands better privacy, and how leveraging RWE sophistication and how moving to risk-based privacy techniques can help establish leadership in the industry.
Today’s post focuses on the consideration: Extended opportunities from privacy leadership in RWE.
Opportunities through Learning Health Systems
Various healthcare stakeholders and governments advocate learning health systems with their ability to progress healthcare through knowledge sharing. Protected Health Information (PHI) from millions of people can rapidly advance the evidence base for clinical care. It can enable personalized medicine, or fill major gaps in understanding healthcare costs, the benefits and risks of drugs and procedures, and geographic variations.
One such learning health system is CancerLinQ, an initiative of ASCO. This is first and foremost a quality measurement and reporting system, allowing oncologists to harness the depth and power of their patients’ clinical records to improve care delivery.vi Having triggered important questions about the use of big data in healthcare, CancerLinQ is now required to provide oncologists with up-to-date access to de-identified EHR data from millions of cancer patients to enable more personalized treatment plans. Risk-based methods were deployed to de-identify these records before adding them to the CancerLinQ portal, ensuring a continuous flow of real-world data (RWD) between oncologists, with no compromise on privacy.
As more health systems embrace risk-based privacy methods for de-identification, broader opportunities open up for companies leveraging these approaches to partner, share data, and directly participate in learning health systems to drive improved patient outcomes.
Some Final Words about Taking the Lead in RWE
Increasingly, the onus of RWE leadership in Pharma lies with a select number of senior executives responsible for systematically building dedicated RWE capabilities. Working together with the head of privacy or compliance and commercial franchise leads, they can act to accelerate their RWE strategy using risk-based privacy and industrialized software platforms by:
- Baselining key RWE datasets across the organization and users of the data
- Creating an RWE governance framework for different departments and data types
- Evaluating risk-based privacy software and engaging RWE technical leads on application
- Collaborating with third parties, including health systems partners, on implementation
- Developing a final execution plan to deploy technologies
Privacy requirements are many and varied, and an increasing challenge for companies accessing ever growing numbers of diverse datasets. Risk-based approaches enable consistency in governing privacy by allowing the same methodology to be applied systemically across multiple complex scenarios.
Companies that establish a holistic information governance framework can advance their RWE strategy with continuous automated flows of RWD, confident that all appropriate privacy measures are in place. They can further be positioned to collaborate with other stakeholders embracing risk-based privacy management, to share data and knowledge as part of a learning health system. This both strengthens their own evidence base and enhances their ability to advance health outcomes at a broader level.
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