Last week, Cotiviti was honored to sponsor and participate in the 2018 Health Datapalooza conference in Washington, D.C., a gathering of top public- and private-sector leaders discussing how data and technology can improve health for individuals and communities. Here, Cotiviti chief analytics officer David Costello re-caps the event’s hottest topics.
The event’s eight discrete tracks ranged from consumer-facing technologies and digital health to “whole person health” and value-based delivery and payment systems. All presenters made the point that healthcare transformation is well under way, but many of the solutions on display demonstrated the difficulty of standardizing the transformation effort. Change will be costly, presenters agreed, and payer organizations are expected to bear the brunt of those costs.
I was fortunate to participate in a panel discussion about payer and population health analytics with experts from Agilon Health, Leavitt Partners, and the UPMC Center for High-Value Health Care. We focused our attention on the use of data and advanced analytics among payers and others to drive improved health outcomes within the context of the Quadruple Aim: improve the physician experience, improve the patient experience, improve outcomes, and lower costs.
The panel dove right in with the question, “What keeps payers and other risk-bearing companies up at night, and how can analytics help?” It was clear that unbridled specialty pharmacy costs are top of mind, but many other concerns surfaced, including:
In each of these examples, the panelists discussed the critical role of having access to the right data. Of interest was the importance of geographic information system (GIS) data to help clearly identify where patients reside and where they access healthcare. For example, using GIS technology, it’s possible to operationalize a response to the “food desert” concept by identifying where patients live and where healthy food options exist. You can then prepare outreach to individuals who reside in food deserts about healthy food options, given the access available to them, and create new store options for them. Through GIS adoption, we can better identify where nutritional needs are not being met and create plans to close the gaps and improve overall health outcomes.
Another interesting conversation emerged around the use of the “hot spotter” methodology, which focuses on the highest cost, highest utilization patients, as described in this article by Atul Gawande in which Verisk Health (now Cotiviti) was profiled. The panelists all stated that performing outlier analyses, in a directed effort, is a very quick way for an organization to identify enhancements to both savings and the patient experience.
A healthcare specialist from the audience talked about the daily challenge of managing data, stating that in many organizations, data is often taken for granted. He noted the assumption in many organizations is that population health management is simply number crunching—classic identification and stratification.
The panelists agreed with this assessment and pointed out that data is far more strategic—it helps inform the business problems at hand. The panelists talked at length about the need to understand the business problems first, and then tackle questions about data veracity, integrity, and need afterward. Data should only exist to solve a problem, not in a vacuum. This conversation also led to a discussion on the creation of “false metrics”—the use of incorrect or spurious measures that exist solely because organizations can’t obtain data that answers their true business problem (e.g., quality ratings and cost containment efforts).
Last, we discussed the role of external players such as Cotiviti operating within the payer space. In a spirited exchange, one panelist argued in favor of bringing many data analytics activities in house for control and better understanding, while other panelists believed in partnering with outside experts. At Cotiviti, we believe that innovation is best driven by external partners, taking into account the following key factors:
In summary, Health Datapalooza was both exciting and uplifting. It reaffirms that Cotiviti’s product roadmap is headed in the right direction, and that our investments in organizing our data at the enterprise level is the appropriate next step as we look to deliver greater insights and value to our customers.
The concept of “data lakes” is attracting a lot of attention from payers, a group with massive amounts of raw data at its disposal. Data lakes store both structured and unstructured data without the aid of expensive computer infrastructure. Although most healthcare data flows are traditionally unidirectional, a true data lake receives data from transactional systems as well as returns data to those systems to support and enhance decision making.
Cotiviti’s Sumant Rao, senior vice president and business owner of performance analytics, explores the root causes of data lake failure among healthcare payers and offers seven major considerations for those considering a data lake approach.
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