Penn Behavioral Economics Research Team Wins $600,000 Donaghue Grant
A behavioral economics research team led by Penn Medicine's Amol Navathe and Mitesh Patel has received a $600,000 grant from the Donaghue Foundation to conduct studies evaluating two different potential ways to reduce physicians' opioid prescribing.
The large project will involve 50 emergency departments and urgent care centers affiliated with 24 hospitals operated by the Sutter Health System throughout northern California.
Called "The REDUCE Trial," the three-year project will test if electronic health records default options can be used to effectively decrease the number of opioid pills physicians prescribe, and, if monthly reports comparing each physician's opioid prescribing patterns with those of his or her peers could nudge doctors toward lower levels of such prescribing. "REDUCE" is an acronym for "Randomized trial of EHR Defaults and Using social Comparison Feedback to Effectively decrease opioid prescription pill burden."
Many physicians don’t know their prescribing patterns or how well they perform compared to their peers, so we're bringing some social norming to bear here.
Dose and duration
"The Centers for Disease Control (CDC) has put out good evidence that suggests when physicians, in their good intentions, start patients on opioids, a non-trivial proportion of those patients end up becoming dependent and that this is related to both the dose and duration of the opioid prescription," explained Navathe, MD, PhD, an Assistant Professor at Penn's Perelman School of Medicine and an LDI Senior Fellow.
"There's also a suggestion of wide variation in practice patterns around opioid prescribing in emergency departments, primary care and other offices," Navathe continued. "Our goal is identify interventions that include education and behavioral economics techniques that can move physicians toward prescribing lower doses of lower duration and substitute non-opioids when appropriate."
'A lot of promise'
"We think the default approach has a lot of promise here," said Patel. "We previously tested how defaults can influence physician prescribing for both generic medications in primary care practices and opioids in the emergency room. This REDUCE Trial goes the next step by implementing this strategy more broadly across a large health system."
Patel, MD, MBA, MS also an Assistant Professor of Medicine at Perelman and an LDI Senior Fellow, is co-primary investigator with Navathe.
The grant is part of the Donaghue Foundation's Greater Value Portfolio that funds research aimed at identifying practical solutions for specific health care problems.
EHR systems' default capabilities
Navathe explained that generally, most EHR systems don't have a default for opioid prescriptions. "So, when you prescribe somebody 30 days of opioids that should be taken on an 'as needed' basis every four hours," said Navathe, "that comes to six pills a day. You may intend for them to have 30 pills used only "as needed" throughout 30 days but some EHR systems automatically calculate 6 pills a day for thirty days or 180 pills."
He emphasized that the study is not focusing on patients involved in a chronic opioid therapy but rather ER patients seeking treatment for low acuity conditions like low back pain or ankle sprains.
"One idea is that we could default physicians to something like no more than 10 or 20 pills, although we still have to work out some of the details," Navathe said.
Monthly personal feedback
In the other arm of the study -- the prescribing comparison -- physicians will receive monthly personal feedback about where their opioid prescribing levels rank in relation to peers in the same hospital system or the nearby geographic area.
"Many physicians don’t know their prescribing patterns or how well they perform compared to their peers," said Navathe. "So, we're bringing some social norming to bear here. That's a powerful behavioral economics mechanism that we're testing, especially for the outliers. We want to use this to both educate and nudge physicians to practice in an evidence-based way."