This article appears in the July/August issue of HealthLeaders magazine.
As healthcare becomes increasingly data-driven, provider organizations find themselves inundated with more information than ever before. Figuring out what to do with all the data may not be easy, but for healthcare finance executives it is a challenge worth tackling because the hospitals and health systems that successfully implement a data analytics program can significantly enhance their economic outcomes and fiscal stability.
The use of data analytics in healthcare is on the rise. Global business consulting firm Frost & Sullivan released a report last year predicting that the adoption of advanced health data analytics in U.S. hospitals would increase from 10% to 50% between 2011 and 2016, a 37.9% compound annual growth rate. Likewise, the February HealthLeaders Media Intelligence Report indicates that 62% of healthcare organizations plan to increase their spending on financial analytics over the next three years; only 3% plan to spend less.
Hospitals in large numbers are being driven to invest in analytics by two factors, says Nancy Fabozzi, connected health principal analyst at Frost & Sullivan, which is headquartered in Mountain View, Calif.
"No. 1 is healthcare reform," she says. "It's the fact that there are going to be more patients coming into the system, and they are going to be a different type of patient in the sense that a lot of these people have not been covered before and may not understand how insurance works. They may not fully understand issues like deductibles and copays."
The second major factor is changing reimbursements, Fabozzi says. "The move away from fee-for-service to value-based payments is a big driver of analytics because it dramatically increases the financial risk … You need to fully understand not just your clinical performance but your operational performance and your financial outcomes. Analytics is at the heart of that."
With these significant threats to revenue on the horizon, hospitals are faced with the need to maximize their data to find efficiencies wherever possible.