The advent of “Big Data” and its accelerated usage in healthcare has greatly prioritized the paradigm shift toward lower cost, lower utilization and higher quality healthcare. Big Data is merely the rapid expansion of large and diverse data sets formed thanks to the digitization of clinical and research data. Its premise in healthcare is to collect, aggregate and analyze the data correlating to improved quality and efficiency of patient care. These data enable healthcare stakeholders, in particular life sciences organizations, to understand better the long-term value of their products.
Today’s healthcare environment has driven demand for more evidence of value in the context of significant regional and local variation in both incentives and data access. As treatment costs continue to rise, businesses find it harder to pay for their employees’ healthcare, which forces patients to take on much of the cost burden out-of-pocket. The current system also broadly showcases a misaligned, and perverse, payment system, incentivizing volume and quantity over quality. This volume-based structure often leads to the overall lack of free-flowing information, and broadcasts limited cost and quality data, ultimately branding the data infrastructure as incomplete. Treatments vary, and due to the limited amount of open information, providers do not, and cannot, follow the best practices.
All in all, many healthcare stakeholders recognize the potential for increased Big Data usage, and see it as a valuable tool to drive healthcare advancement. Key improvement scenarios include:
- Facilitating a “learning” healthcare system.
- Improving care treatment patterns, especially for chronic conditions.
- Deriving new quality measures and supporting the ongoing collection and reporting of existing measures in the push for a value-based payment system.
- Managing utilization, or the quantity and mix of delivered services.
- Maximizing the potential for new research and development.
- Streamlining the post-market evidence generation process.
Payers, providers, patients and other stakeholders continue to rely on new and different types of evidence to inform healthcare decision making. While payers use Big Data and evidence to justify the coverage and benefit design decisions, providers use real-world evidence to make decisions on which treatments are appropriate for different patients. And for patients themselves, increased data usage can lead to better and more informed decision making surrounding the risks and benefits of available treatment options. Life science companies use big data to explore benefit/risk of treatments and treatment sequences in patient subpopulations, speed enrollment in clinical trials and identify potential new targets for research and development.
As public data sources expand, data availability also expands. Currently, 39 states have between one and four health information exchanges (HIEs), six states have between five and nine HIEs, and four states have between 10 and 19 HIEs. In addition, 21 states have a strong interest in developing an all-payer claims database (APCD), 11 states have existing APCDs, five states are currently developing APCDs, and three states have an existing but voluntary interest in APCDs. PCORI, initially created to generate ultimately patient-centered outcomes research, has awarded $94 million in funding toward data infrastructure (PCORnet) through 11 clinical data research networks and 18 powered research networks. Avalere expects that moving further into 2014, federal and state governments, as well as groups like PCORI, will increase these efforts to build new data infrastructures. In parallel, strong advocacy will likely ensure that the quality of the data and its availability consider the needs of all stakeholders.
Finally, Avalere expects life sciences companies will play a big role in the Big Data boom, as many are sponsoring cross-sector collaborations among such stakeholders as payers, patient organizations, health care providers and researchers. Collaborations take many forms, they include:
- Joint industry payer studies to evaluate product effectiveness and impact on health care utilization such as emergency room visits and hospitalization.
- Multi-industry clinical trial data sharing through online portals permitting researchers to analyze anonymized, patient level clinical trial data.
- Collaboration with health plans and providers to test the impact of behavioral interventions to improve medication adherence and lifestyle modifications.
In addition, both pharmaceutical and medical device companies are involved in supporting clinical data registries, which can be facilitated by increased electronic health record adoption. These registries can be used to conduct comparative effectiveness studies and monitor product safety, addressing both FDA post-marketing and CMS coverage requirements and providing information about patient needs to inform and enhance product development and research.
For more information, contact Chris Boone, Vice President, Evidence Translation and Implementation, at CBoone@Avalere.com. Avalere will also host several Big Data webinars this year, and will present on similar data topics this fall at ISPOR.
Tanisha Carino is the Executive Vice President of Avalere Health. She oversees strategic advisory and research services for the nation’s leading life sciences companies.