The following info was provided by our friends at Levick Partners. CNSI and IBM just teamed up in Michigan on a tech solution to address opioid addiction.
How predictive analytics can fight the opioid epidemic within the Medicaid population
By Sharif Hussein, CNSI Chief Strategy Officer & President of Health & Human Services
May is Mental Health Awareness Month, which gives lawmakers, government officials, and healthcare experts an opportunity to reflect on the most pressing mental health issues. The stigma associated with mental illness has long prevented the issue from receiving the attention it deserves.
The opioid epidemic is certainly top-of-mind this year, ravaging communities, destroying lives, and killing Americans daily. The staggering statistics associated with opioid abuse have made addressing this epidemic a top priority for almost every Medicaid agency in the country. With more than 115 Americans dying every day from opioids, this epidemic, and the mental health issues that help fuel it, have become too great to ignore.
Now is the time for the health IT community and Medicaid agencies to work together to solve the problem. The Medicaid industry is not alone in the fight – and the only way to combat this growing epidemic is to join forces. If we leverage the data provided by the Medicaid community and the technology developed within the health IT community, we give ourselves a fighting chance to finally tackle this public health crisis.
As the Medicaid community knows all too well, the hundreds of thousands of prescriptions Medicaid beneficiaries are prescribed every day are routed through insurers, resulting in a trove of data. We can use this information to identify where, when, and how opioid abuse is occurring or—better yet—likely to occur. The problem with this data is that the technology to analyze that much information didn’t exist—until now.
CNSI and IBM Watson Health teamed up with the State of Michigan to develop an addiction-identification tool that sorts through health information datasets in Medicaid claims to identify outliers that may be indicative of addictive behavior – such as mental health-related diagnoses, frequent visits to several pharmacies and prescribers, or early prescription refills. By combining the Medicaid administrative data with pharmacy and clinical datasets, the solution can find patterns of opioid abusers at both the client and prescriber level.
Even more, this solution can be used to identify when a patient is most likely to succumb to addiction – ideally preventing an addiction before it even begins.
With reports showing Medicaid beneficiaries are 10 times more likely to abuse substances than the general population, this sort of predictive analytics can be key to solving the growing opioid epidemic. It’s time we focused on how our two industries can play a role in solving the crisis.
Mental illnesses can be incredibly difficult to treat but opioid addiction is preventable. With solutions like the one in Michigan, we can ensure more people get the help they need before they become another casualty.