Advances in science and technology are helping drive a new era of personalized medicine — one that is anticipated to revolutionize human health in the next decades. However, real systematic challenges around affordability exist and, if they are not addressed, these issues could threaten to stifle much of this innovation from being realized.
This is helping drive a great shift to value-based paradigms such as outcome-based contracts, which can have big implications for biopharmaceutical and medical device innovators.
Success in this value-based, personalized paradigm of healthcare means that they need to be able to nimbly answer the “hard questions” in health care: What works for whom? Why? In what context? And at what cost?
Fortunately, the proliferation of electronic healthcare data in a myriad of forms may hold the answers to our toughest questions — that is, if companies can see inside that data and discern meaningful insights. Many life sciences innovators, health plans, regulators and providers face the task of harnessing a growing array of electronic health data to obtain the specific insights necessary to support decisions in the value-based, personalized healthcare paradigm of the future.
Real-World Evidence 2.0 Emerges in Biopharma
Many life sciences companies and regulators are beginning to view real-world evidence, all of this electronic health data — known as real-world data (RWD) — as a valuable new tool to develop evidence across the pharmaceutical value chain from R&D through to commercial. This real-world evidence is increasingly being used in key decisions, as was highlighted in Deloitte’s recent Real-World Evidence Benchmarking survey.
While claims data sets have been used by many for years to make health economic and value arguments, what’s different about the new emerging paradigm, or RWE 2.0, is that, now, newer types of RWD can be accessed, including electronic medical records, Internet of Things data from wearables, digital health data, next-generation registries, etc. New RWD also has available cloud-based Big Data platforms and approaches to analyzing the data to generate insights.
However, RWE 2.0 is about much more than just data and new technology.
Pharmaceutical companies should consider exploring new operating models that break down the traditional internal silos of evidence generation and think about an end-to-end evidence management strategy.
The new paradigm can also require new external partnerships to get access to the myriad of new data sources emerging with patient advocacy groups, health systems, health plans, new venture-backed entrants, and in some disease areas, the patient themselves. Finally, there is commonly an urgent need for new data science approaches to interrogating the data and thus new talent that is familiar with machine learning-based approaches to analysis.
By way of example, a leading biopharmaceutical organization recently recognized both a need and an opportunity to develop a platform for productivity and performance using RWE to inform decision-making across its value chain. It took an integrated approach that helped increase R&D productivity, product launch effectiveness and overall operational excellence. Time once spent preparing data was refocused on performing analyses and sharing insights. This powered a shift in organizational intelligence around how analytics can be applied going forward.
RWE Can be Key to Innovation, Competitive Advantage
The future of value-based, personalized healthcare is taking shape before our eyes, fueled by the explosion of electronic healthcare data. Navigating the data-driven shift in healthcare often requires new platforms, technologies and advanced data science capabilities.
Collaboration with organizations and stakeholders across the healthcare ecosystem, if done right, can benefit all participants, especially the patient. Not only can evidence strategies advance biomedical research, but they can also help fulfill the promise of precision medicine.
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