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93% of Payers, Providers Say Predictive Analytics are the Future

Predictive analytics are in high demand among payers and providers who plan to use big data to address an array of clinical and financial concerns.

Predictive analytics for payers and providers

Source: Thinkstock

- Healthcare organizations will not be able to navigate the financial and clinical challenges of the future without investing in predictive analytics tools, said more than 90 percent of respondents to a Society of Actuaries (SOA) survey.

The vast majority of payers and providers participating in the February 2017 poll believe predictive insights will be critical for the future of their businesses, with more than a quarter of the 225 respondents stating that they expect these big data analytics tools to save them 25 percent or more on costs over the next five years.

The pressures of value-based care have already driven 47 percent of providers and 63 percent of payers to invest in predictive analytics tools.  While providers currently lag behind payers in adoption, the ecosystem will soon even out.

Over the next five years, just under 90 percent of both payer and provider organizations say they will have adopted some form of forward-looking big data analytics capabilities.

“As value-based care gains prominence, smart organizations are leveraging predictive analytics to forecast health and clinical outcomes to help achieve the Triple Aim, said Ian Duncan, FSA, FIA, FCIA, FCA, MAAA.  “This data underscores the value executives place on predictive analytics across both payer and provider organizations.”

READ MORE: Predictive Analytics, Accountable Care Markets to See Rapid Growth

Payers and providers may understand the value of predictive analytics technologies that will allow them to engage in personalized medicine, management chronic diseases, and mitigate clinical and financial risks, but challenges still lie ahead.

The Society of Actuaries survey follows several other recent industry assessments that point to budget constraints and lack of qualified data analytics staff as barriers to successful adoption.

Sixteen percent of respondents to the SOA poll said they may not have the budget to invest sufficiently in predictive tools over the next five years, while 11 percent pointed to a dearth of talent as a major obstacle.

In a September 2016 survey from Health Catalyst, twenty-five percent of hospitals complained that top-notch data scientists for predictive analytics were impossible to find.  Earlier in 2017, HealthITAnalytics.com readers were almost twice as likely to report open jobs at their organizations, with close to 50 percent trying to fill big data positions.

A number of data integrity issues also made the SOA list, including incomplete data (12 percent), patient matching concerns (8 percent), and lack of confidence in the accuracy of results (7 percent).

READ MORE: Predictive Risk Score Targets Highest Cost Patients

Encouragingly, the proportion of participants in the SOA poll indicating a lack of executive buy-in was extremely low.  Just five percent of organizations believed their C-suite wasn’t on board with big data, compared to 20 percent in the Health Catalyst survey and a similar number in the HealthITAnalytics.com reader poll.

For organizations that overcome their challenges, the rewards and many and varied.  Providers and payers both have a number of use cases in mind for predictive analytics, including improving patient satisfaction and patient flow, reducing avoidable readmissions, adverse events, and mortality rates, and engaging in risk stratification.

Clinical and financial use cases for predictive analytics

Source: Society of Actuaries

Financial concerns are also on the table.  Stakeholders hope to leverage analytics to understand and meet inventory needs, slash fraud and waste, optimize their workforces, reduce costs, and boost profitability.

Perhaps not surprisingly, payers expressed slightly more interest in the financial outcomes of these tools.  Around half of payers said cost and profitability improvements were most valuable to them, followed by assessing clinical risk and understanding population patterns.

Providers, meanwhile, are likely hoping that predictive analytics will help them avoid quality penalties and perform well in regulatory programs like meaningful use and MACRA.  Patient satisfaction, readmissions, and clinical outcomes were all top of mind for a large proportion of provider respondents.

READ MORE: For Predictive Analytics, Not All Data is Created Equal

In order to meet these goals, payers and providers are planning to invest in a number of improvements to their data collection and analytics capabilities.  In addition to investing in building strong data analytics teams, seventeen percent of organizations are aiming to spruce up their data visualization abilities.

Future investment in predictive analytics

Source: Society of Actuaries

Twenty percent are planning to refine their data collection methods with security and privacy in mind, while 13 percent are looking at strategies for automating the prediction process.

A relatively small number, just 10 percent, are likely to invest in machine learning, despite a growing industry emphasis on its potential to overhaul the healthcare big data analytics landscape.

A similarly limited proportion of participants believe that the Internet of Things (IoT) will be a breakthrough technology for predicting patient behaviors and managing their risks.

Despite their reservations about tools and strategies that are receiving a great deal of hype, the survey reiterates that the healthcare industry has largely accepted the important role that data plays in their clinical and financial success.

While both payers and providers will still need to address a number of difficult challenges over the coming half-decade, their strong commitment and pervasive sense of inevitability about leveraging health IT tools that will generate actionable insights is a positive indication that they will succeed.

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