After a quick glance through many of today’s Digital Innovation and Transformation Blogs, it was not surprising to see so many articles about how healthcare, life-science, and other companies in the field of medicine are using data and analytics. Recent headlines have focused on how organizations – like the ones many of my classmates have written about – are leveraging Big Data and analysis to better serve their customers. Pharmaceutical companies are mining patient data to better understand unmet needs; health insurance companies are analyzing clinical outcome data to determine potential patient risk and appropriate coverage. We are hearing similar stories to these more and more frequently. There is one organization in this space, however, that is starting to use data in a very creative way: Carolinas HealthCare.
Carolinas Healthcare operates approximately 900 care centers, including hospitals, nursing homes, doctors’ offices, and surgical centers. Unlike most healthcare systems which mine patient outcome and health data to reduce total time in high-cost areas of the hospital, or to maximize utilization of specific hospital units, Carolinas Healthcare has been purchasing customer data from brokers who cull public records, store loyalty program transactions, and credit card purchases – a very different model than its competitors.
Carolinas Healthcare has started to incorporate these data on 2 million people in North and South Carolina into algorithms that are designed to identify high-risk patients. The idea is that doctors can intervene before the patients get sick. While Carolinas Healthcare isn’t using new analytical tools (its algorithms are primarily based off of multivariable regression models), it is using “new” data to help inform its decisions, and is the first healthcare system to apply credit card data to health decisions.
Carolinas Healthcare is still in the early stages of acquiring, analyzing, and using this type of data. It has not yet fully changed its operating model to be able to efficiently leverage its analyses to drive change. In the months to come, it will need to better align its processes to ensure its resources (doctors and nurses, primarily) are able to interpret and make informed decisions based off of this data. Even with this novel idea to use consumer spending behavior to predict health risks, Carolinas Healthcare’s business model is only as strong as its weakest link, which right now appears to be its physicians who may be too busy to use this data.
Carolinas Healthcare executives are optimistic about how much money analyzing this type of data can save the entire system if done appropriately (which, at least hypothetically, would benefit both the consumers and Carolinas Healthcare). Others, however, are less optimistic, including one patient who said she is sick of having healthcare companies try to gather or steal her personal information: “it is one thing to have a number I can call if I have a problem or question; it is another thing to get unsolicited phone calls. I don’t like that…” Privacy experts also worry about the potential that this type of data analysis could erode doctor-patient relationships: “If the physician already has the information, the relationship changes from an exchange of information to a potential inquisition about behavior.”
For me, it will be interesting to see two issues play out: 1) how effective will Carolinas Healthcare analysis of this data be? Will consumer purchasing data really improve health-outcomes? And 2) will privacy advocates eventually win the battle and prohibit healthcare systems from using personal data to make health related decisions? Only time will tell.