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Laboratory / MedLab & Pharmaceuticals

Predictive models could save lives in rampant opioid crisis

Before Northeastern professor James Benneyan described his research, he gave a stark reminder of the opioid epidemic it aims to address.

Post date: Jan 06, 2020 | Virginia, US

Benneyan described this effect as "squeezing the balloon and it bubbles somewhere else," and said it illustrates the complexity of the opioid problem. And there are other ways the balloon phenomenon plays out. For example, after a massive legal effort to crack down on heroin trafficking in western Massachusetts, mortality actually spiked. Rather than cleaning up the streets, the drug sweep created a new market for an even deadlier substance—fentanyl.

"These are very complex dynamical systems," Benneyan said. That's where the approach comes in. "What we've learned by running our models is that one intervention alone isn't going to make much difference and probably is just going to squeeze the balloon and cause a problem elsewhere. There really needs to be a well-orchestrated, highly attuned set of interventions that constantly adapts."

Optimize, rather than overburden

Healthcare clinics are strapped for resources. They don't have the means to screen everyone who comes in seeking painkillers, which means many potential addicts will slip through the cracks. But Benneyan has built predictive models that can identify patients at high risk for abusing opioids. This would allow clinics to focus screening efforts where they're most needed.

Another significant problem is the availability of treatment. Many people who want to get help don't have a nearby option for care. By employing the same type of mathematical model a retail outlet like Wal-Mart uses to choose the site of a new store, Benneyan has developed access optimization models to inform where to locate short-term and long-term treatment facilities.

"There is this tragic percentage of people who want to get into care but can't. That's the heart-wrenching piece," Benneyan said. His found that simply redistributing where the clinics are located—without spending any additional money—would save lives.

There are also opportunities for optimization within the clinics themselves. Many are grassroots, not-for-profit organizations that have staffing, layout, and flow challenges, Benneyan said. He is building a team of graduate and undergraduate industrial engineers who will go "into the trenches" and work to make the clinics run more efficiently.

"The things that bring tears to your eyes are stories like the captain of the soccer team who died unable to find a treatment facility that could take her. That tragedy, which repeats itself nationally over and over, causes us to well up," Benneyan said. "This is affecting everybody's lives."

Source: medicalxpress.com

Source: medicalxpress.com
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Laboratory / MedLab & Pharmaceuticals:

Predictive models could save lives in rampant opioid crisis

Before Northeastern professor James Benneyan described his research, he gave a stark reminder of the opioid epidemic it aims to address.

Post date: Jan 06, 2020 | Virginia, US

Benneyan described this effect as "squeezing the balloon and it bubbles somewhere else," and said it illustrates the complexity of the opioid problem. And there are other ways the balloon phenomenon plays out. For example, after a massive legal effort to crack down on heroin trafficking in western Massachusetts, mortality actually spiked. Rather than cleaning up the streets, the drug sweep created a new market for an even deadlier substance—fentanyl.

"These are very complex dynamical systems," Benneyan said. That's where the approach comes in. "What we've learned by running our models is that one intervention alone isn't going to make much difference and probably is just going to squeeze the balloon and cause a problem elsewhere. There really needs to be a well-orchestrated, highly attuned set of interventions that constantly adapts."

Optimize, rather than overburden

Healthcare clinics are strapped for resources. They don't have the means to screen everyone who comes in seeking painkillers, which means many potential addicts will slip through the cracks. But Benneyan has built predictive models that can identify patients at high risk for abusing opioids. This would allow clinics to focus screening efforts where they're most needed.

Another significant problem is the availability of treatment. Many people who want to get help don't have a nearby option for care. By employing the same type of mathematical model a retail outlet like Wal-Mart uses to choose the site of a new store, Benneyan has developed access optimization models to inform where to locate short-term and long-term treatment facilities.

"There is this tragic percentage of people who want to get into care but can't. That's the heart-wrenching piece," Benneyan said. His found that simply redistributing where the clinics are located—without spending any additional money—would save lives.

There are also opportunities for optimization within the clinics themselves. Many are grassroots, not-for-profit organizations that have staffing, layout, and flow challenges, Benneyan said. He is building a team of graduate and undergraduate industrial engineers who will go "into the trenches" and work to make the clinics run more efficiently.

"The things that bring tears to your eyes are stories like the captain of the soccer team who died unable to find a treatment facility that could take her. That tragedy, which repeats itself nationally over and over, causes us to well up," Benneyan said. "This is affecting everybody's lives."

Source: medicalxpress.com

Source: medicalxpress.com

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