Use of predictive analytics among payers and providers has seen a 13 point increase, from 47 percent in 2018 to 60 percent in 2019, a new survey from the Society of Actuaries shows.

WHY IT MATTERS
The report further finds that 89 percent of healthcare executives plan to use predictive analytics in the next five years, as health systems and health plans alike understand how critical good clinical and business intelligence is to organizational success.

That's translating into big investments, as healthcare orgs plan to boost their spending on predictive analytics software and initiatives, the Society of Actuaries research shows: 60 percent say they'll be upping their budgets by 15 percent or more.

Largely, that's because "executives who implement predictive analytics are experiencing results that align with the outcomes they’re targeting," according to the the report, which sees cost reduction and patient satisfaction as the top sought-after results. Increased profitability, interestingly was only third on the list, cited by 33 percent of the healthcare leaders polled.

As they adopt these new tools, hospitals and payer organizations are expecting them to evolve in the year ahead, with improvements in data visualization, refinements in data collection methods, innovations in machine learning and natural language processing.

Still, despite the benefits they've enabled, executives say they're grappling with challenges too. They "cite shifting barriers to adoption, suggesting that new issues are arising as they navigate predictive analytics implementation," according to the report. Hurdles cited include lack of budget, regulatory issues, incomplete data, too much data, and lack of employees with the necessary skills.

THE LARGER TREND
Despite those challenges, healthcare organizations of all shapes and sizes can and should be taking advantage of predictive analytics. This past year we spoke with Michael Johnson, a decision support data scientist at Bend, Oregon-based St. Charles Health System, who offered some advice on launching DIY analytics projects.

"I'm not going to kid you," said Johnson. "You have to roll up your sleeves and make some decisions. You'll probably need to make some investments, too – in technology and in staff training."

But the upside, he said, is hard to beat. "There are many tangible benefits to doing it in-house, but there are even more intangible benefits. Things like being able to have spinoff models that are closely related, but not exactly the same, that can answer a similar question. Or more closely involving the stakeholders, so they have increased confidence in the way the model was created and how it should be used."

ON THE RECORD
"This data underscores the importance of achieving the Triple Aim for both payers’ and providers’ bottom lines: two of the three pillars are represented in executives’ top priorities," said Sarah Osborne, a fellow of the Society of Actuaries, in a statement. "And the good news is that organizations using predictive analytics are actually achieving their desired results. Our hope is that this trend will continue through additional predictive analytics implementation across the industry."

"By efficiently utilizing emerging technologies to analyze complex datasets and uncover actionable insights that ultimately solve industry challenges, actuaries are adept at filling the roles employers are seeking," said Osborne. "An example of this is using machine learning to increase data analysis efficiency. By training an algorithm to identify severe medical conditions in health care data, the actuary is able to swiftly uncover data with major implications for patient costs and health outcomes."

Twitter: @MikeMiliardHITN
Email the writer: mike.miliard@himssmedia.com

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