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Health IT's Role in the Opioid Epidemic? Get the Right Data to Providers At the Right Time


40 people die every day as a result of overdose from prescription opioids. Here's how can the health IT community can help curb overdose and abuse.

opioid epidemic

was the worst thing to ever happen to American medicine. It meant that many patient-physician interactions began and ended with opioids, from the 0-10 pain scale at presentation to a prescription at discharge.

From that point, incentives to prescribe opioids grew quickly. By 2001, a California jury had already convicted a physician of elder abuse for under treating his patient’s pain. What followed was an intense ramping up of opioid prescribing that’s led to the nationwide epidemic we’re experiencing today.

“There’s probably nobody here who’s from a jurisdiction that’s unaffected,” said Kurt Hegmann, MD, MPH, said in a presentation at HIMSS 2018 in Las Vegas, Nevada.

Gauging the Possibilities

Hegmann and Kaiser Permanente’s Roman Kownacki, MD, have been working to figure out how the health IT community can leverage its tools — from big data and analytics to electronic medical records (EMR) – to help curb abuse and overdose deaths. What they’ve discovered is that giving physicians the right information at the right time can make all the difference.

In a study of treatments offered to 7840 patients who’d undergone carpal tunnel surgery, Hegmann found that 70% of patients filled a postoperative opioid prescription, but nearly 30% received a prescription contrary to guidelines set forth by the American College of Occupational and Environmental Medicine (ACOEM). 15% were prescribed an opioid prescription that lasted longer than 5 days, and about 17% were prescribed a high dose of opioids with more than 50 morphine mg equivalents per day. Additionally, 0.3% were prescribed a long-acting or extended release opioid.

If these same physicians had followed ACOEM prescribing guidelines, Hegmann found that when controlling for confounders and holding all covariates constant at their average values, there would be a decrease in disability durations of 2 days, or a 5% drop.

“Those who are in the [chief financial officer] CFO suite know that 2 days of productivity is very expensive. You’re talking about the person’s hourly rate plus their benefits, et cetera,” he said.

Additionally, guideline adherence would have decreased medical costs by $422 per patient. Amplified across the population, it would equate to $102 million annual savings—and that’s just for a simple carpal tunnel surgery.

Learning Curves

When Kownacki ran a report on his hospital’s opioid prescribing patterns, he found that some of the doctors were prescribing opioids to more than half of their patients. “I have to tell you, I was embarrassed and astounded,” he said. “We really felt like we had to do something about it.”

Kownacki sent a physician out to Massachusetts General Hospital to learn how to effectively communicate with his hospital’s working clinicians, and inform them about prescribing guidelines and best practices. When the physician came back, the hospital’s leadership implemented mandatory trainings for the 110 doctors who handle worker’s compensation.

“A year later, we checked the data. It was exactly the same. No change whatsoever,” Kownacki said. “We had to do a little soul searching.”

Kownacki and the leadership team turned to the data. “You need to measure what you’re doing, pull the easy data and integrate it with the clinical tools that you mandate your physicians to use,” he said.

That prescription and clinical data was fragmented, so the hospital leadership pulled it together to understand how often opioids were being prescribed, and what clinical decision making was leading to those prescriptions. Then, they presented that data to physicians in a simple, manageable interface via the hospital’s EMR.

Physicians suddenly had easy access to the ACOEM’s prescribing guidelines, applicable screening tools and patient questionnaires. They integrated the EMR with the California state Prescription Drug Monitoring Program (PDMP), so doctors could see where and when their patients were receiving and filling opioid prescriptions. Then, they monitored when patients would drop off the list of those who were receiving and filling prescriptions.

“Because of the real time clinical decision support, we had about a 75% drop in the number of new opiate prescriptions. When we first started this in 2008, about 14% of patients were getting opiates. Now we’re down to about 3%,” Kownacki said. Data showed that there were no adverse outcomes in terms of cases being prolonged, and case durations were shorter, too.

“It’s all about pulling data and bringing it to physicians in real time. When the docs enter the diagnosis in, there’s a tab that shows the minimal medically necessary days off. It’s pushed out into their screen and helps them with their clinical decision making. That’s where we want to go with the guidelines, too,” Kownacki said.

Overcoming Resistance

Even with all of the advantages Kownacki’s integrated EMR can confer, there’s still adoption resistance among clinicians, in part because of too many broken promises and overhyped expectations, Hegmann said.

“The number of times I’ve heard, ‘X is great, it saves time, it’s easier to find things,’ is fascinating. Because you’ll need an extra person in the room to put in all this info, won’t you? We have to overcome this,” Hegmann said.

The best way to do that is to clear a path between the provider and the information they need to make the best clinical decisions. That can, in turn, produce the best clinical outcomes. Once those tools are available, Hegmann predicted a decrease in adoption resistance.

“Physicians and health care providers want good outcomes more than anything. That’s what they’re driven by—they want to help people.” Hegmann said. “We need to get the right data into the lap of the provider. We need to get it right in front of them.”

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