by Priya Sapra | April 11, 2016 2:28 pm |
Perhaps no industry is drowning in data more than healthcare. The industry is spending millions of dollars on Real World Evidence (RWE) as organizations seek to measure the health, outcomes, and cost of care of patients across settings to understand the real-world impacts of pharmacologic and non-pharmacologic treatments on patients and healthcare systems. The breadth and depth of RWE data are growing at an exponential rate, and we are only scratching the surface of its value; physician utilization patterns, patient treatment journey, and drug comparative effectiveness are just a small sampling of the use cases for which institutions across the clinical and commercial continuum want to leverage RWE today.
While the industry is in agreement about the value of RWE data, the question remains: Will the industry be able to fully leverage all this available data to drive better patient outcomes? To date, the answer has been a resounding no. Despite investment in systems and processes, people, and platforms, the industry as a whole has experienced little return. Perhaps none is as frustrated as the pharmaceutical industry; conservative market estimates suggest that big pharma spends in an average of $20 million annually on RWE and yet is no closer to fully understanding patient health and treatment.
To capitalize on the available RWE data, the industry should consider cloud-based analytics. The reasons are as diverse as the perspectives in the healthcare market, but they all share a common thread – the need to quickly access, analyze, and deliver insights from real-world data for broad use across their organizations. Let’s take a closer look at three players in the healthcare market and the analytics challenges they currently face.
The Three P’s of Healthcare and the Cloud Analytics Challenge
The healthcare market comprises a diverse set of participants: payers, providers, and pharmaceutical companies – the three P’s, if you will.
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Payers. Payers include any entity other than a patient that finances or reimburses the cost of a healthcare service, such as insurance carriers, third-party payers, or health-plan sponsors. These entities they need to determine contracting, formulary statuses, and tiering structure with respect to drug manufacturers. However, without knowing which products are the most effective among certain segments of patients, they are not able to make a fully informed decision about relative formulary status or about which drugs should be first tier, second tier, and so on. How can they effectively negotiate their contracts without such insight? Under pressure to reduce overall costs, payers need analytics to avoid operating uniformed in a highly complex market.
Providers. Providers are hindered by the same lack of insight, but in a very different way. Speed and access to data are paramount for these caregivers. For example, community-based provider organizations need to understand the quality of care they are providing and whether or not they will incur pay-for-performance penalties. However, without an understanding of what is going on with patients within their current healthcare system, they cannot take any action to protect against such penalties. Correcting issues after the fact is of little use; time is of the essence if they are going to ensure that optimal interventions, treatment guidelines, and best practices are in place.
Providers in academic medical centers are often responsible for setting the norms and benchmarks for the rest of the industry to follow. Without RWE-based analytics, they simply cannot access enough information to evaluate how community-based physicians are practicing. This hinders their ability to set the standards of care, as they cannot gain a clear picture of how patients are being treated or understand the real patient outcomes based on specific treatments.
Pharmaceutical. The pharmaceutical industry needs real-time access to RWE data to speed up drug development, conduct observational research, and understand which patients to target for clinical trials and marketing campaigns. As mentioned above, the pharma industry continues to rely too heavily on a small group of specialized individuals to evaluate and analyze data to provide insights across the enterprise. The ability to bring the best new products to market depends on the organization’s ability to share the power of analytics across the organization and keep pace with market dynamics.
How Analytics via the Cloud Deliver Insight and Opportunity
While each of these contributors to the healthcare industry has unique queries, they all have similar requirements of their analytics. Unlike solutions of the past, cloud-based offerings can provide rapid access to the data and derived insights in the language that resonates with each entity. Here are the key factors that separate cloud-based analytics from the rest:
Scalability. Delivery via the cloud enables the rapid scalability necessary for RWE data. As the variety, volume, and velocity of data continue to increase, on-premise solutions simply cannot scale rapidly enough to contend with terabytes of data and the analytic demands of its users.
Speed. Time is of the essence for many of these players – speed of data access and speed of results are equally important. Cloud-based analytics are quicker to stand up and quicker to process, delivering immediate insights from RWE data when needed most. Overall performance of any analytics solution is critical, as the shorter the time from business question to business answer, the greater the competitive advantage for the organization.
Security. Much of this data can exist in an identifiable format and may include patient health information. Cloud-based providers remain adamant that a cloud-based solution can maintain a higher level of security and better adhere to HIPAA compliance guidelines. Such solutions involve more rigorous business rules, more security protocols, and no actual server in order to limit vulnerabilities and keep the data safe.
Think Solutions, not Services
For so long, data have been stuck in silos; the evolution of the industry requires an integrated technology solution to galvanize and empower this data. This includes a rigorous uniform, longitudinal way to leverage and disseminate data and insights across the organization. This simply cannot be accomplished via services. Organizations have tried this approach in the past and failed; services alone cannot keep up with the organizational need to track and evaluate information constantly and consistently over time.
A cloud-based analytics platform that can democratize that data across the organization provides a holistic approach that is so desperately needed while also automating and accelerating the delivery of data to the constituents who need it.
As payers, providers, and pharmaceutical companies continue to collect a tidal wave of real-world evidence data, each of them must be able to turn that information into actionable insights to impact treatment options, reduce costs, and improve patient outcomes. By capitalizing on cloud-based capabilities that deliver the rapid data access and analytic insights, the impact of real-world data can quickly go from basic theory to pervasive practice and deliver on its promise to transform treatment strategies and the overall health of patients.
A passionate advocate for improving patient health and outcomes, Priya Sapra leads the Analytics team at SHYFT Analytics, where she helps create novel approaches, methodologies, and products for data use and analysis within the SHYFT Platform. She has 15 years of life-science and healthcare consulting, market research, and data analytics experience – building expertise in leveraging primary and secondary market and real-world data for the design of optimal data metrics and analytic insights. Prior to joining SHYFT, Priya served as the Director of Analytics for Phreesia, a patient-centered health care technology company in New York, and the Vice President of Quantitative Services for MedPanel, a research and analytics firm in Cambridge, MA.
Priya earned her MBA from Babson College, as well as a Master’s degree in Epidemiology and Biostatistics from Boston University. She received her undergraduate degree in Biology and Literature from MIT.
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