4 Considerations for Taking the Lead in Real-World Evidence
This is the first 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.
However, there is a catch.
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).
Real-world evidence: A definition
To understand what RWE is, let’s look at a couple of definitions.
Real world data = data used for decision-making that are not collected in conventional randomized controlled trials (RCTs), includes clinical and economic data reported by patient registries, claims databases, electronic health records, patient-reported outcomes, and literature review.
When it comes to building an RWE ecosystem, there are four considerations companies should keep top of mind:
- Better research demands better privacy
Secondary use of individual-level patient data for health research has unparalleled potential to improve healthcare quality and drive medicines innovation, benefiting individual patients and society as a whole. To optimize its value for scientific research and meet tightening privacy regulations, there is a pressing need for a systematic approach to privacy management and de-identification of data. Life sciences companies can take a lead in implementing best practice using risk-based privacy-enhancing techniques.
- Greater RWE sophistication, greater privacy consideration
Pharma is accessing an unprecedented depth and breadth of clinical data. Leading companies have built RWE platforms across multiple countries, encompassing vast real-world data (RWD) collections and analytics technology. The variety of RWD has exploded, spanning hundreds of databases or registries, including data directly sourced from providers, and extensive data linkage. This significantly expands research potential, but also creates elevated re-identification risk.
- From blunt tools to risk-based privacy techniques
Current de-identification methods, and commonly used data masking in particular, do not appropriately address ever increasing RWE data sophistication nor changing privacy regulation. RWE leadership, therefore, requires privacy leadership and the application of new standards in risk-based privacy. Use of risk-based de-identification software, which enables holistic overall privacy governance frameworks, both accelerates RWE strategies and ensures a continuous compliant flow of RWD.
- Extended opportunities from privacy leadership in RWE
Risk-based privacy techniques can be applied systematically in a relatively short period of time to achieve a step-change in RWE capabilities. Their adoption also opens up new opportunities for companies to partner in knowledge and data sharing with health systems, which are also embracing risk-based approaches, to collectively work towards the ultimate goal of improving health outcomes.
Watch for the next post in this series, which will take a closer look at why better research demands greater privacy.
- RWE: Better Research Demands Better PrivacyJuly 12, 2017
- 4 Considerations for Taking the Lead in Real-World EvidenceJuly 5, 2017
- Finding Clinical Trials TransparencyApril 3, 2017
- How to Safely Navigate Beyond MaskingFebruary 6, 2017
- The Problem with Data Masking TechniquesJanuary 9, 2017