As part of the University of Chicago Graham School Master of Science in Biomeidcal Informatics (MScBMI) program’s monthly special topics seminar series, Swati Abbott, CEO of Blue Health Intelligence (BHI), gave a presentation on March 8 spotlighting the latest developments in predictive analytics for healthcare to an audience at the University of Chicago’s Gleacher Center. Entitled “Leveraging Big Data Analytics to Improve Health Outcomes and Reduce Cost,” her talk explored several examples stemming from productive engagements with clients as a way to showcase how data and advanced analytics are changing the way healthcare is delivered. The audience composed of students across Graham’s professional studies programs was deeply engaged with the multiple disciplines addressed by the talk: analytics, biomedical informatics, project management, and leadership.
With degrees in physics and computer science, Abbott is a respected industry leader who was recognized by Frost and Sullivan in 2010 as one of the Movers and Shakers in healthcare. A regular speaker at industry conferences on topics related to predictive modeling and healthcare clinical analytics, Abbott served before joining BHI as President of Elsevier/MEDai, an industry leader in predictive analytics, and earlier as Managing Director for the Medical Management Strategic Business Unit at ViPS, where she led strategic solutions development for medical management data warehousing.
At BHI, Abbott and her teams have access to the broadest, deepest pool of integrated medical and pharmacy claims in the healthcare industry, reflecting medical utilization from every zip code in the USA. Ten years of data including one hundred and seventy-two million people with BlueCross BlueShield insurance have been combined in a safe, HIPAA-compliant, secure database. BHI leverages a team of analytics experts with advanced technology to use these data to provide cross-system insight about healthcare trends and best practices.
“While the regional Blues have extremely deep knowledge locally,” Abbott said, “they don’t have the capacity to look across their system in an efficient manner. That is the ability BHI brings to the table. The question becomes what we do with so much data. When I arrived at BHI,” she noted, “I made a decision. Rather than going after every last additional piece of data out there, which would have been an endless quest, I decided first to identify the business problems, and then to go after the applicable data.”
Giving an example of the sort of business problem to be solved in this manner, Abbott mentioned an instance of an employer noticing an extravagant increase in the cost of a particular service. By drilling down into the data, it was determined that the increase did not derive from an uptick in the number of instances the service was provided. Drilling down still further, this time into the top ten drivers of cost for that service, Abbott noted the peculiarity of the seventh item on the list: surgical supplies.
“The feeling was that the cost of surgical supplies shouldn’t be this significant as a cost driver,” Abbott said. “But without data it’s not always possible to substantiate a hunch like that. We used our data to look at the regional and national averages for surgical supplies as a driver of cost in that service. It was 250th and 308th, respectively, compared to 7th for this employer. This is the power of benchmarking data,” she added. “If we know there’s a cost going up, we can drill down and begin to get a sense for what’s atypical or too high. These sorts of analyses allow things to surface that you might not have thought of or seen otherwise.”
Abbott went on to highlight how these insights derived from data serve to identify potential risks, curb costs, and improve care across the spectrum of healthcare, providing employers, payers, patients, and hospitals with tangible benefits. Speaking to the value of Accountable Care Organizations (ACOs), where doctors, hospitals, and other healthcare providers voluntarily work together to coordinate care for their patients, Abbott added that results yielded by the analytics work at BHI serve to strengthen the ties already bringing these different domains together.
“What we’re learning,” she said, “is that how we think about healthcare is a process. There’s no one answer. But if we can bring together employers, providers, and payers, integrating their disparate sources of data with consistent methodologies and shared analytics platforms, then we’re able to use these results to more effectively drive decisions and orient how we think about problems. Nobody in healthcare has the magic bullet yet, but we’re all trying.”