Healthcare Industry Eyes Savings with Predictive Analytics

Most healthcare executives are banking on predictive analytics — the core of Big Data — to help them keep costs under control, according to a study from the Society of Actuaries.

Predictive analytics, one of Datamation’s top big data trends for 2017, employs machine learning, a subset of artificial intelligence, to predict future data points based on an analysis of past data. Advances in the field are making it easier for businesses to better detect patterns and spot anomalies, enabling employees to make better business decisions based on future expectations.

Like many other industries that have discovered the benefits of a data-driven crystal ball, healthcare organizations are jumping on the bandwagon.

Currently, nearly half (47 percent) of the 223 health providers and payers surveyed by the group earlier this year said they are using predictive analytics. Eighty-nine percent expect to be using predictive analytics within five years, if they’re not already doing so. Finally, nearly all executives (93 percent) agree that predictive analytics is critical to their business’ future.

For many healthcare organizations, that future involves optimizing costs.

“More than half of healthcare executives at organizations currently using predictive analytics (57 percent) expect to save 15 percent or more of their total budget – with 26 percent forecasting saving 25 percent or more – over the next five years by using predictive analytics processes,” states the report (PDF).

It won’t be smooth sailing for some firms, unfortunately. The report notes that “despite the financial benefits from predictive analytics, 16 percent of healthcare executives still indicate a lack of budget is the biggest challenge to implementation within their organization.”

The use of predictive analytics is currently higher among healthcare payers (63 percent) than providers (47 percent). Within the next five years, adoption is expected to practically even out at 89 percent for providers and 87 percent for payers.

Besides controlling costs, healthcare providers are looking to predictive analytics to help with hospital readmissions (48 percent), staffing needs (46 percent) and improving patient satisfaction (53 percent). Payers, meanwhile, are focused on profitability (47 percent), clinical outcomes (37 percent) and patient satisfaction (35 percent).

The report also offers the industry a glimpse of the predictive analytics capabilities that healthcare executives expect to see in the future. Some top priorities include honing data collection methods to improve security (20 percent) and investing in the proper talent (18 percent). Data visualization (13 percent) and process automation (13 percent) also ranked high.

Pedro Hernandez is a contributing editor at Datamation. Follow him on Twitter @ecoINSITE.

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