The impact of automatic physician review of prescription drug monitoring program data on opioid prescribing in a Maryland statewide hospital system

Autor: Benoit Stryckman, MA, Anna Schoenbaum, DNP, Joel Klein, MD, Rose Chasm, MD, Eberechukwu Onukwugha, PhD, Zachary DW Dezman, MD
Rok vydání: 2022
Předmět:
Zdroj: Journal of Opioid Management. 18:547-556
ISSN: 1551-7489
DOI: 10.5055/jom.2022.0750
Popis: Background and aims: Prescription drug monitoring programs (PDMPs) were implemented to decrease dangerous opioid prescribing but have had variable results. This report details how automatic PDMP review changed opioid prescribing across a statewide medical system.Design: An observational study.Setting: Fourteen hospital networks in the United States.Cases: Healthcare encountered from July 1, 2016 to June 30, 2019.Intervention: Starting from July 1, 2018, the patient’s PDMP data would be displayed automatically to providers in the unified electronic medical record (EMR) whenever the provider began to write for an opioid prescription.Measurements: Outcomes were prescriptions per encounter (PPE) and the morphine milligram equivalents (MME) per prescription. Outcomes were stratified by practice location, medication prescribed, and diagnosis. All data, including whether the prompt was triggered for a given encounter and whether a prescription was given, were extracted from the EMR. An interrupted time-series analysis was used to determine how PPE and MME changed in response to the implementation of automatic PDMP review.Findings: Of the 624,488 encounters examined, 18.37 percent (n = 114,710) were in emergency departments, 56.79 percent were admissions (n = 354,634), and 24.84 percent (n = 155,144) were outpatient visits. Opioid prescriptions were started and then canceled 24 percent of the time after the PDMP was shown. There was a decline in MME (βOverall + Policy Trends = –3.17, p =
Databáze: OpenAIRE