How analytics helps reduce opioid use disorder among Medicare patients
Connecting state and local government leaders
Using spatial economic modeling on a high-powered analytics platform, the Centers for Medicare and Medicaid Services has been able to identify high-risk clusters of patients.
There has long been a perception that victims of the opioid epidemic fall into a certain category: Young adults that become hooked on a drug like heroin and overdose. While that number, like many others related to the opioid crisis, continues to increase, it only tells a partial story.
Opioid use disorder among senior citizens continues to rise. Senior citizens are not using heroin, although that number is going up as well, but becoming hooked on opioids their doctor prescribed for everything from minor aches and pains to more serious chronic conditions. The Medicare population, in particular, has among the highest and fastest-growing rates of diagnosed opioid use disorder, currently at more than 6 of every 1,000 beneficiaries.
Using data to find new insights
Data analytics has helped to shine a light on the opioid use disorder struggles of older Americans. An analysis of data from the Centers for Medicare and Medicaid Services (CMS) identified 225,000 beneficiaries who received potentially unsafe opioid dosing.
Analyzing the data reveals trends that can answer questions about the opioid issue. For instance, are these patients clustered geographically? Do they suffer from a similar ailment? Is there a pattern in the type of doctor they see? Do they have similar medical histories? If trends and patterns can be identified, health officials can create policies and procedures inside the larger Medicare program to curtail the factors that lead to opioid use disorder.
In fact, CMS has already used spatial economic modeling on a high-powered analytics platform to identify high-risk clusters of patients. With this information, the agency can make changes in treatment and policies to ensure older patients do not get prescribed opioids they don't need and risk addiction.
The opioid crisis is a varied and layered problem. There is no one solution to help patients. The crisis affects different segments of the population in different ways. Federal agencies collect an untold amount of data through different programs, but also on the population in general. This data, though, only has true value when analyzed for actionable insights. Data analytics can go beyond human analysts, not only finding larger trends and relationships in large amounts of data, but exploring relationships traditional analysts may miss.
Using data for good
The use of data analytics to help battle the opioid crisis is an example of government using data for good. While federal agencies have turned to data analytics to help improve internal operations, there is a movement to use these same platforms to better help the public.
By using data analytics to improve public programs, government agencies at all levels can make improvements in the lives of citizens. Data analytics can help deliver real insights into the problems citizens face and give agencies the information they needs to make dramatic change.
Government agencies have already used data analytics to help protect at-risk children, reduce human trafficking and improve high school graduation rates. This is only the starting point. Data analytics can help improve almost every government program.
Every agency has a mission that comes down in some way to helping people. As the opioid crisis has shown, delivery of that mission can be incredibly difficult. Data analytics can be a catalyst for change and provide government officials with vital information to make a true difference.
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