The Power of Data in Driving Transformative Innovation
Payers are investing in data infrastructure that enables value-based care
As the healthcare industry continues its shift to value-based care, payers are looking to “big data” for insights into how they can drive highquality outcomes at lower costs.
Dr. Emad Rizk, who helms the Atlanta-based data analytics giant Cotiviti, explains the steps that innovative payers are taking to spearhead transformative change throughout their organizations, including optimizing data collection, integration and analysis.
WHAT ARE THE MOST EFFECTIVE WAYS FOR PAYERS TO DRIVE INNOVATION IN TODAY’S COMPETITIVE HEALTHCARE ENVIRONMENT?
ER: Innovation requires discipline and partnership; payers know that they can accomplish very little without working with other key groups. Therefore, payers are focused on three primary areas of innovation:
Consumerism: Consumers have always been an important constituent in healthcare, but payers are looking to engage them in new ways as they become more knowledgeable about healthcare and better advocates for their own health.
Technology and data: One of the major transformations benefiting the industry right now is the advancement in data collection, storage and sharing, opening up myriad opportunities to tighten collaboration. If you identify the true leaders in the payer sector, they are the companies that are investing heavily in integrated, streamlined technology infrastructures and using the critical insights that result to bring new value to their clients: for example, new or better performing products or more comprehensive and informed ways to identify gaps in care.
Business models: Payers are continuing to move away from fee-for-service payment and to experiment with a variety of value-based models. Success here, as in other areas, demands close collaboration with providers, including support for their provider partners as they take on increasing risk for clinical outcomes.
WHAT STRUCTURAL FACTORS OF OUR HEALTHCARE SYSTEM ARE INFLUENCING PAYERS’ ABILITY TO INNOVATE?
ER: Disparate technology exists in both payer and provider organizations. The largest of these organizations experience similar issues: they’ve grown through M&A, which has led to a proliferation of often competing systems. This situation can be a real hindrance to productivity and innovation.
Thankfully, the evolution of technology has made integration through a single repository of data much easier and more efficient.The shift to cloud-based data management has accelerated this process, as have advancements in computing power and artificialintelligence. These improvements have enabled the type of robust data sharing that gives payers, providers and other collaborators a more holistic viewpoint and allows them to consider the impact of their decisions from multiple perspectives.
At the same time, a new generation of healthcare professionals has emerged that is more tech-savvy and wanting to integrate data into its decision-making process, ultimately shaping the industry’s future and its approach to value-based care.
WHICH DATA INFRASTRUCTURE INVESTMENTS WILL HAVE THE GREATEST UTILITY?
ER: The emphasis has really shifted to big data: what it is, what it enables and how to leverage it for organizational and systemic transformation. This is why the concept of “data lakes” has grown in popularity. Data lakes bring together structured and unstructured data from disparate sources—including provider notes, patient charts, payment information and quality metrics—and organize it into a single longitudinal profile.
At the most basic level, a payer is managing the health of a population. Data lakes yield information about the financial impact of clinical decisions and the clinical impact of financial decisions. These expanded perspectives improve upon payers’ ability to ensure that they are reimbursing for the appropriate care at the right cost.
WHAT STEPS SHOULD PAYERS TAKE BEFORE IMPLEMENTING A DATA LAKE?
ER: First, they should create a business case for the long-term investment, because a data lake takes time to build. Second, they should carefully build a timeline for the project, with use cases identified, prioritized and properly cadenced. Third, payers are responsible for paying claims, interacting with customers and managing contracts; the expertise possessed by data scientists and analysts who build statistical models, aggregate information and normalize data may not exist within the organization and must be either hired or outsourced. Finally, commitment for an undertaking of this scale and importance to the future of the business must come from all levels of the organization.