Harm Prevention

Prescriptive Analytic Technology Gives Hope in the Fight Against Opioid Addiction

The staggering, tragic toll of opioid-related deaths and overdoses seems to grow daily.
The CDC reported that emergency room visits for overdoses increased 30 percent from July 2016 through September 2017. Overdoses increased among men and women in every age group and every region of the country. Illinois alone saw a 66 percent increase in opioid overdose trips to the ER.
opioid abuse
The number of deaths from opioid overdose in 2016 (the most recent full year reported) was almost 46,000. Deaths from synthetic opioids—primarily Fentanyl—multiplied more than six times from 2013 to 2016 alone. (Opioids in this chart include synthetic opioids, heroin, natural and semi-synthetic opioids, and methadone.)
This explosion in opioid deaths has even contributed to a decrease in U.S. life expectancy.
"This is really a fast-moving epidemic that's getting worse," said Dr. Anne Schuchat, acting director of the CDC.
The overdose cases and deaths only tell part of the story. This risk among the population speaks to our challenges in turning these bleak trends around. According to the American Society of Addiction Medicine, almost 2.6 million Americans have a substance abuse disorder involving prescription pain killers or heroin. More than 75 percent involve misuse of prescription pain killers.
This epidemic raises special challenges and complications for physicians. They have a duty to treat patients compassionately and manage their pain, but also must mitigate the risk of opioid addiction. It creates complex conflicts, as evidenced by the recent opposition by doctors to proposed Medicare rules that would allow insurers to restrict or deny filling legitimate prescriptions for certain pain medications. How do doctors appropriately heal patients while recognizing and treating abuse risks?
Technology, in the form of Jvion's AI-enabled prescriptive analytics, stands to provide breakthrough understanding, visibility and direction to help physicians target and treat patients at risk of opioid abuse. It’s built with remarkable intelligence that can absorb clinical and socioeconomic data for entire patient communities and provide crisp, clear, comprehensive profiles of risk and recommended treatments. Symptoms that in isolation might not raise a risk flag for doctors become part of a comprehensive patient “biography.” Using this clinical intelligence asset as a foundation, Jvion collaborates with healthcare organizations to apply specific “vectors” that comprehend risk profiles for an endless number of illnesses and conditions—including opioid abuse and other behavioral health conditions.

Jvion’s Opioid Abuse Vector effectively and efficiently identifies individuals at increased likelihood of abusing opioids within the next year—regardless of their current prescribed opioid use. The machine accounts for all patients within a population to recognize risk regardless of whether a patient’s addiction started with heroin or prescription pain killers. Clinicians see patient-level risk outputs that include contributing clinical and socioeconomic factors. The machine also recommends personalized clinical actions most effective at reducing risk.

The technology may seem complex—the machine makes more than a quadrillion clinical and non-clinical considerations for each patient. But the Jvion Machine works elegantly and quickly, providing clinicians with clear risk profiles and guidance within weeks of setup. Once it’s running it provides details and treatment guidance for patients in real time, using technology called Eigen spheres to continuously learn, interpret and communicate risk and treatment at all stages.

Most importantly, technology is not the end unto itself—it’s about how it can help us prevent harm and heal. AI-enabled prescriptive analytics represents a promising, hopeful frontier in addressing the vexing human tragedy of the growing opioid epidemic.
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