Mount Sinai Health System has 15 years of experience working with electronic health records data, but that hasn’t easily translated into deriving value from analytics.
“Analytics has been changing, but now it’s clear it has to drive business value,” said Deepesh Chandra, director of centralized IT services for the New York-based system. “At the early stages of analytics, we collect data but derive little value. The value of data grows as you analyze it and make decisions off of it.”
The spur for analytics maturity has been Mount Sinai’s growing participation in accountable care and population health initiatives, Chandra said Wednesday at the Tableau Conference in Las Vegas. While still in its first year of pursuing a new analytics strategy, the organization already is starting to derive benefits amounting to millions of dollars in savings.
Chandra described three major components of Mount Sinai’s strategy:
- Delivering actionable insights to support population health and value-based payment models. “We need a longitudinal view of the patient as well as the provider.”
- Enabling a culture of self-service to reduce the burden on the information technology department. “We want to promote the use of self-service, data discovery and visualization.” Reliance on IT to perform analytics, in the place of the users, slows the process down and creates a work burden that IT cannot support.
- Scaling the analytics platform across the enterprise. “We want the organization to think analytics at its core,” Chandra said. “Unless it’s using analytics to make decisions, it won’t work.” An enterprisewide focus will boost sharing of data and findings across different groups, and that will increase the impact of findings and decrease the amount of duplicative analysis.
At Mount Sinai, the IT department manages a complex environment; its seven hospitals use various electronic medical records, and its clinical data warehouse collects data from 120 sources.
Also See: Mount Sinai Expands Use of Real-Time Survey Tool
An important issue being studied via analytics is how to reduce claims denials, which annually total $150 million for the health system. Denials typically have been managed with popular office productivity software, but that’s not resulted in finding the reasons for denials across the system, or how to tackle the problem, Chandra said.
End user analysis has raised the hope that denial rates can be affected. In one instance, an emergency department physician who is a member of the Mount Sinai revenue committee began analyzing reasons behind denials. Without formal training in the use of the Tableau analytics tool, the physician began to find common reasons for denials, and drilling down helped determine which clinicians might benefit from discussions about steps to take to reduce denials. The organization said the approach represents a $100 million opportunity to systematically reduce denials.
Similarly, end users with little training in the use of the software are able to use the analytics platform to answer questions with data and create new solutions. Chandra said end users are using analytics in a variety of ways, including studying how to reduce variances in treatment and care delivery; developing system wide disease registries; more accurately stratifying patients into risk groups; and identifying underserved areas in the region.
“It’s been less than 12 months since we’ve started this journey” of empowering end users to participate in the analytics effort, Chandra said. “We are focusing on low-hanging fruit and have proven our value. Now, we are going after the high-hanging fruit,” as analytics will help the organization cope with higher risks associated with new reimbursement models.
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