Nearly 80 percent of hospital executives indicated that predictive analytics could help them significantly boost care, yet only 31 percent have been using analytics for more than a year, according to a Health Catalyst survey.
The top priority for predictive analytics: 58 percent of respondents agreed that using predictive analytics to alert caregivers about interventions that may prevent health declines among high-risk patients is the most critical reason to use the tools.
The second and third ranked priorities went to predicting financial outcomes (such as patient cost or likelihood of patients to pay their bills) and improving the ability of providers to negotiate contracts with insurers, respectively.
“Survey findings point to a growing need within the provider community for solutions that help to identify long-term rising-risk patients who are on their way to becoming high-cost consumers of healthcare,” Levi Thatcher, director of data science at Health Catalyst, said in a statement. “With so much changing in the industry, providers are hungry for analytics that will help them identify and treat these patients before they deteriorate, both improving their lives and reducing needless spending across the system.”
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The survey drew responses from 136 hospital and health system executives during August, including CEOs chief financial officers, chief information officers, chief medical information officers and range of departmental leadership roles.
Health Catalyst executives said that the results also point to potentially significant barriers to the adoption of predictive analytics.
Thirty-two percent of participants, for instance, cited lack of appropriate data and infrastructure as the top barrier, while 20 percent said a shortage of people, skills and executive support are the highest hurdle.
With only 19 percent of respondents indicating that they have no plans to deploy predictive analytics in the immediate future, the research findings also signal pent up demand for the advanced form of analytics.
Indeed, predictive analytics have been touted as a solution to many of healthcare’s problems and as key to the development of more effective personalized treatments for common diseases such as cancer.
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