Despite rumblings from Washington, momentum is continuing to build for the healthcare industry’s transition from fee-for-service to value-based care. In fact, according to a 2017 survey, C-level healthcare executives around the world expect that value-based care will become the dominant payment method by 2020.
This trend has some serious implications for life sciences organizations. The most important is that life sciences organizations will be expected to assume some level of risk around outcomes.
No longer will commercial effectiveness teams simply be able to sell a product, or encourage/incentivize providers to prescribe it, without any thought as to what happens next. Instead, life sciences organizations will increasingly be required to deliver concrete proof of exactly how and by how much their products will deliver better outcomes for patients.
To seize the opportunity, however, demonstrating effectiveness on current patients isn’t enough. Value-based care is highly focused on prevention not just treatment, which means that life sciences organizations will be expected to contribute to providers’ ability to impact their entire patient population not just those known to be sick.
This is a much larger challenge that not only requires a massive amount of data but a different approach to big data and analytics than that taken currently by most life sciences organizations.
Following are six strategies that can be a difference-maker in the value-based care future:
1. Gain a better understanding of the data you already have
Life sciences organizations have a unique view of the data around their products whereas providers only collect information about specific patients – a small subset of those taking a medication or using a device. Health payers can see across providers but only for their own members.
However, with data on all of them, life sciences organizations can drill down to what is most impactful and use predictive analytics to spot trends (for example, an increase in chronic conditions among a population or a more effective approach to care management) that can have a huge impact in reaching value-based goals.
2. Layer in additional data to make the picture clearer
Most organizations using analytics tend to rely on the data they gather and own, yet so much more can be done by layering data from multiple sources – including clinical, financial, demographic, sociographic, behavioral, and more – collected outside as well as inside the organization.
For example, Zip+4 data can help spot trends localized to a particular population, offering an opportunity to forewarn providers serving populations that fit the profile/persona. By alerting providers to developing trends that could affect reimbursement, life sciences organizations deliver a value add that helps mitigate pricing differences and protects brands when they come off exclusivity.
3. Take advantage of predictive and prescriptive analytics
While it is important to understand the past, it cannot be changed. By using next-generation predictive and prescriptive analytics, commercial effectiveness teams can show providers both the benefits of using their products and the potential consequences of going in another direction or taking no action at all. Providers can then determine the best strategy to reach their desired outcomes.
4. Guide providers toward quality improvements
To meet the value-based care demands of the future, every provider will need to focus on delivering higher-quality care while improving cost-effectiveness and efficiency – even those who are already well on their journey toward it. Showing providers how they can improve outcomes through proven programs that drive down costs again helps you add value to the relationship.
5. Think in terms of populations
Providers are looking to life sciences companies to help them transition to value-based care by assuming some of the risk. The more an organization understands where risk exists relative to its product areas, and can identify high ROI opportunities to reduce that risk at the population level, the better prepared it will be to meet this demand.
6. Optimize care delivery
Analytics can help you guide providers on the best approach to take to maximize success around a treatment. For example, if you can demonstrate that offering a consumer hotline improves compliance and outcomes (over prescribing the drug alone or prescribing competitor products), the commercial effectiveness team can make a strong case to providers that you will help them optimize care delivery to deliver the best value-based results.
Although providers are currently at many different points along their journey to value-based care, their overall commitment is accelerating rapidly. Life sciences organizations that make effective use of data and analytics to deliver valuable information that helps them succeed in reaching their goals faster will be the winners once the journey is complete. Which is likely to be sooner rather than later.
Mark Feeney is Life Sciences Solution Consultant with SCIO Health Analytics.
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