Authors: Sean G Young*, University of Arkansas for Medical Sciences, Corey J Hayes, University of Arkansas for Medical Sciences, Jonathan Aram, University of Maryland, Mark Tait, University of Arkansas for Medical Sciences
Topics: Medical and Health Geography, Spatial Analysis & Modeling
Keywords: Medical Geography, Opioids, Travel Patterns, GIS
Session Type: Paper
Start / End Time: 3:05 PM / 4:45 PM
Room: Tyler, Marriott, Mezzanine Level
Presentation File: No File Uploaded
The US Opioid Epidemic continues to be a major health crisis, with tens of thousands of deaths each year. Non-medical use of prescription opioids often precedes the use of illicit opioids like heroin. Certain high-risk uses of prescription opioids are associated with increased addiction and overdoses, including prescriptions for more than 90 milligrams of morphine equivalents per day and overlapping prescriptions for opioids and benzodiazepines or skeletal muscle relaxants. Nearly a quarter of prescription opioid recipients in Arkansas engaged in one or more of these high-risk uses at least once in 2015-2016. Safer prescribing practices and early detection of risky behaviors involving prescription opioids are key to bringing the epidemic to an end. Most risk prediction algorithms are a-spatial, such as doctor shopping, which considers the number of prescribers and pharmacies visited, but not their locations or spatial relationships. We contrast this approach with spatial analyses of patient travel, including doctor hopping, which evaluates how many prescribers are bypassed (aka hopped) in order to reach the chosen prescriber. We compare doctor shopping and doctor hopping in relation to high-risk opioid use behaviors using data from the Arkansas Prescription Drug Monitoring Program. We also discuss ways in which results from these analyses could be used by prescribers in a clinical setting.