This month, I had the opportunity to speak at the 2021 Medicare Supplement Summit in Chicago, Illinois. The panel discussed how medical data can be leveraged to predict the cost of care. Read on for my top takeaways from this meeting.
1. Not all analytics are created equal:
As the meme above demonstrates, different levels of analytics create new and deeper insights into data. At Neurocern, our analytics predict who may have a high risk neurological disease (first level analytics), find undiagnosed neurological cases (second level analytics), and identify interventions to predict the cost of care (third level analytics). Unlike analytics that only query known ICD-10 or prescription data to find financial risk, Neurocern’s AI- expert system utilizes multi-modal data processing, years of research data, and clinical informatics, and to enrich data and create value across the insurance and financial services industries.
2. Your data should be working for you:
It was surprising for many carriers to learn that their own claims data lake could be used to gain deeper insights into predicting risk ahead instead of purchasing access to data. For example, using claims data from payers, Neurocern’s AI processing engine can predict who may have a high health utilization risk or who may qualify for a new emerging therapeutic.
3. Advanced analytics are key to forecasting uncaptured risk:
Analytics today often provide the “current” state of the patient (for instance, who may have Parkinson’s in a given population). Advanced analytics can leverage claims data to segment populations into who may get Parkinson’s in three years and what might be the cost of care. With that level of insight, organizations can see into the future, using their own data to find hidden diagnoses, identify the right care pathway earlier, and ultimately, reduce costs.