Some of the nation’s largest insurance companies are investing heavily in analytics to improve customer experience and manage costs.
But organizations are still challenged by insufficient technology, a lack of analytics professionals and the ability to tease out quality data from their current IT systems.
That’s according to a new report released by the Deloitte Center for Health Solutions which surveyed executives and analytics professionals at health insurance companies with at least 250,000 members. Analysts supplemented the survey with executive interviews.
There’s no question insurers are willing to invest in analytics, both in the short- and long-term. Seventy-seven percent of respondents said their company was budgeting more money for analytics next year, and one-third said their budget would increase “a lot” over the next three years. Executives see that investment as a critical piece of improving member experience and controlling operating and medical costs.
Earlier this year, Humana Chief Medical Officer Roy Beveridge, M.D., told FierceHealthcare his company was morphing into more of an analytics company as it sought to leverage data partnerships with providers. Executives with Humana and the Cleveland Clinic have pointed to the industry’s transition to value-based payments as an opportunity for payers and providers to engage in more data-sharing partnerships.
At the same time, payers struggle with making data suitable for analytics. Sixty percent of respondents in the Deloitte report said data quality is a barrier to analytics implementation. More than half indicated tools and technology were a barrier, and almost a quarter ranked their IT systems as the number one concern.
Insufficient technology combined with a thin analytics workforce compound the data quality problem. Executives told Deloitte that analysts spend most of their time cleaning data, which leaves less time and money to actually perform analytics.
That echoes comments from health insurance executives, who recently told FierceHealthcare that sharing “meaningful and digestible” data is a recurring challenge, and technological barriers have limited information exchange.