A New Weapon in the Fight Against Opioid Addiction: Behavioral Analytics

In this special guest feature, David Hom, Chief Evangelist at SCIO Health Analytics®, supports his belief that sophisticated behavioral analytics is the key to uncovering patients who are likely to be or become addicted to prescription opioids. In his role as the Chief Evangelist for SCIO®, David interacts with strategic audiences with precise messaging of the value proposition of SCIO’s innovative products and services, and engages clients to solve their impending issues. He is an internationally-recognized expert in the field of consumer engagement through programs such as Value Based Benefits and Employee Wellness. David has co-authored two leading books on Value Based Designs which have been read by over 250,000 Benefit and Health Plan executives and co-founded a nonprofit company in 2007.

Fueled by prescription drugs, today’s opioid crisis bears little resemblance to yesteryear’s popular media images of dead-eyed addicts roaming the streets in search of heroin.

When heroin was the primary culprit, opioid addiction was regarded as largely the purview of the young and poor, but today the issue is much broader than just one demographic group. The reality is the face of opioid addiction could be the soccer mom down the block who has been experiencing back pain. It could be the marathon runner who is trying to come back after knee surgery. It could be your grandmother baking cookies as she works on recovering from hip replacement surgery.

In fact, it could be anyone. And that diversity is what has made prescription opioid addiction so difficult to manage.

In 2012, an estimated 2.1 million people were suffering from substance abuse disorders from prescription opioid use, and deaths from accidental overdoses of prescription pain relievers quadruped between 1999 and 2015.  Sales of prescription opioids also quadrupled during this period.

More surgeries equal more prescription pain relievers

What is driving this explosive growth of such a potentially dangerous substance? Part of it, quite frankly, has been the incredible improvements in healthcare over the last 20-some years. Hip replacements, knee replacements, spinal surgery and other procedures that were once rare are now fairly commonplace. More surgeries mean more patients who need pain relievers to help them with recovery.

Here’s how that translates to real numbers. An analysis of 800,000 Medicaid patients in a reasonably affluent state showed that 10,000 of them were taking a medication used to wean patients off a dependency on opiates. This particular medication is very expensive and difficult to obtain – physicians need a specific certification to prescribe it. So it is safe to assume that the actual number of patients using prescription opiates is two to three times higher.

Those numbers aren’t always obvious, however, because the prescriptions may be obscured under diagnoses for other conditions such as depression. Indeed, over half of uninsured nonelderly adults with opioid addiction had a mental illness in the prior year and over 20 percent had a serious mental illness, such as depression, bipolar disorder, or schizophrenia, according to the Kaiser Family Foundation. The result is that without sophisticated behavioral analytics, it can be difficult to determine all the patients who are addicted to opioids. And what you don’t know can have a significant impact on care, costs, and risk.

Address the addiction first

Take two patients with an opioid addiction who are on a withdrawal medication. Patient A also has eye impairment while Patient B is a diabetic. If the baseline for cost is 1, analytics have shown that Patient A will typically have a risk factor of 1.5 times the norm while Patient B, the diabetic, will have a risk factor of 5 times.

Under value-based care, especially an Accountable Care Organization (ACO) where the payment is fixed, the organization can lose a significant amount of money on patients who are costing five times the contracted amount. For example, if the per member per month (PMPM) reimbursement for the year is $2,000, this patient – who is using this medication for withdrawal from an opiate dependency and is a diabetic – will end up costing $10,000.

Healthcare organizations that can use behavioral analytics to uncover patients with hidden opioid dependencies, including those on withdrawal medications, will know they need to address the addiction first, removing it as a barrier to treating other chronic conditions. That will make patients more receptive to managing conditions such as diabetes, helping lower the total cost of care.

Analytics’ potential to identify opioid addiction candidates

Due to the changing face of opioid addiction, it’s more difficult than ever to pinpoint not only who is an addict – but who could be one. But by using behavioral analytics, we can much more effectively identify who the candidates are, giving us a new weapon in the fight against opioid addiction.

 

Sign up for the free insideAI News newsletter.