Sixty percent of healthcare executives are using predictive analytics within their organizations, which represents an increase from last year’s version of the survey (47 percent), according to a new report from the Society of Actuaries.
The survey, in its third year, included more than 200 health payer and provider executives. “The survey’s purpose was to reveal insights about future predictive analytics trends in the healthcare industry including usage, valuable outcomes to predict and challenges to implementation,” according to officials from the Society of Actuaries, a global professional organization for actuaries.
The increase in executives using predictive analytics was driven almost equally by both payers (63 percent) and providers (56 percent). Similarly, a majority (89 percent) of survey respondents indicated that they use or plan to use predictive analytics in the next five years—a 4-point year-over-year increase from 2018. Just 4 percent of respondents said they do not using predictive analytics and have no plans to in the future.
The results also showed that 60 percent of payers and providers said they expect to dedicate 15 percent or more of spending to predictive analytics in 2019. And they are expecting that investment to pay off: nearly two-thirds of executives (61 percent) forecasted that predictive analytics will save their organization 15 percent or more over the next five years.
Comparatively, in 2018, payers (82 percent) were less likely than providers (92 percent) to view predictive analytics as important for the future of their business. However, in 2019, these numbers leveled out with 92 percent of payers and 93 percent of providers agreeing that predictive analytics is important to the future of their business.
Additionally, the top two desired outcomes executives cite for using predictive analytics are “reduced cost” (54 percent) and “patient satisfaction” (45 percent). This is closely aligned with the top two actual results that executives are seeing from the implementation of predictive analytics: “improved patient satisfaction” (42 percent and “reduced cost” (39 percent). Last year, “reduced cost,” “improved clinical outcomes” and “improved patient satisfaction” were all cited as equal (36 percent) results that healthcare executives experienced after implementing predictive analytics.
What’s more, 16 percent of providers cited “too much data” as the top barrier to implementing predictive analytics, while payers site “lack of skilled workers” (15 percent) as the greatest hurdle.
Further, in a shift from previous years, payer and provider executives believe the future of predictive analytics lies in data visualization (23 percent) and machine learning (16 percent), the results showed. Factors including data visualization and machine learning have the potential to create future cost reductions by increasing efficiency—an outcome that payer and provider executives cited as the most valuable result they hope to achieve when implementing predictive analytics within their organizations.