BACKGROUND: Despite increasing reliance on prescription drug monitoring programs (PDMPs) as a response to the opioid epidemic, the relationship between aberrant drug-related behaviors captured by the PDMP and opioid use disorder is incompletely understood. How PDMP data should guide emergency department (ED) assessment has not been studied. OBJECTIVES: The objective was to evaluate a relationship between PDMP opioid prescription records and self-reported nonmedical opioid use of prescription opioids in a cohort of opioid-dependent ED patients enrolled in a treatment trial. METHODS: PDMP opioid prescription records during 1 year prior to study enrollment on 329 adults meeting Diagnostic and Statistical Manual IV criteria for opioid dependence entering a randomized clinical trial in a large, urban ED were cross-tabulated with data on 30-day nonmedical prescription opioid use self-report. The association among these two types of data was assessed by the Goodman and Kruskal's gamma; a logistic regression was used to explore characteristics of participants who had PDMP record of opioid prescriptions. RESULTS: During 1 year prior to study enrollment, 118 of 329 (36%) patients had at least one opioid prescription (range = 1-51) in our states' PDMP. Patients who reported ≥15 of 30 days of nonmedical prescription opioid use were more likely to have at least four PDMP opioid prescriptions (20/38; 53%) than patients reporting 1 to 14 days (14/38, 37%) or zero days of nonmedical prescription opioid use (4/38, 11%; p = 0.002). Female sex and having health insurance were significantly more represented in the PDMP (p < 0.05 for both). CONCLUSION:PDMPs may be helpful in identifying patients with certain aberrant drug-related behavior, but are unable to detect many patients with opioid use disorder. The majority of ED patients with opioid use disorder were not captured by the PDMP, highlighting the importance of using additional methods such as screening and clinical history to identify opioid use disorders in ED patients and the limitations of PDMPs to detect opioid use disorders.
RCT Entities:
BACKGROUND: Despite increasing reliance on prescription drug monitoring programs (PDMPs) as a response to the opioid epidemic, the relationship between aberrant drug-related behaviors captured by the PDMP and opioid use disorder is incompletely understood. How PDMP data should guide emergency department (ED) assessment has not been studied. OBJECTIVES: The objective was to evaluate a relationship between PDMP opioid prescription records and self-reported nonmedical opioid use of prescription opioids in a cohort of opioid-dependent ED patients enrolled in a treatment trial. METHODS:PDMP opioid prescription records during 1 year prior to study enrollment on 329 adults meeting Diagnostic and Statistical Manual IV criteria for opioid dependence entering a randomized clinical trial in a large, urban ED were cross-tabulated with data on 30-day nonmedical prescription opioid use self-report. The association among these two types of data was assessed by the Goodman and Kruskal's gamma; a logistic regression was used to explore characteristics of participants who had PDMP record of opioid prescriptions. RESULTS: During 1 year prior to study enrollment, 118 of 329 (36%) patients had at least one opioid prescription (range = 1-51) in our states' PDMP. Patients who reported ≥15 of 30 days of nonmedical prescription opioid use were more likely to have at least four PDMP opioid prescriptions (20/38; 53%) than patients reporting 1 to 14 days (14/38, 37%) or zero days of nonmedical prescription opioid use (4/38, 11%; p = 0.002). Female sex and having health insurance were significantly more represented in the PDMP (p < 0.05 for both). CONCLUSION: PDMPs may be helpful in identifying patients with certain aberrant drug-related behavior, but are unable to detect many patients with opioid use disorder. The majority of ED patients with opioid use disorder were not captured by the PDMP, highlighting the importance of using additional methods such as screening and clinical history to identify opioid use disorders in ED patients and the limitations of PDMPs to detect opioid use disorders.
Authors: Peter W Kreiner; Gail K Strickler; Eduardo A Undurraga; Maria E Torres; Ruslan V Nikitin; Anne Rogers Journal: Drug Alcohol Depend Date: 2017-04-01 Impact factor: 4.492
Authors: Joseph A Boscarino; Margaret R Rukstalis; Stuart N Hoffman; John J Han; Porat M Erlich; Stephen Ross; Glenn S Gerhard; Walter F Stewart Journal: J Addict Dis Date: 2011 Jul-Sep
Authors: R Kathryn McHugh; Elise E Devito; Dorian Dodd; Kathleen M Carroll; Jennifer Sharpe Potter; Shelly F Greenfield; Hilary Smith Connery; Roger D Weiss Journal: J Subst Abuse Treat Date: 2013-01-11
Authors: Scott G Weiner; Christopher A Griggs; Patricia M Mitchell; Breanne K Langlois; Franklin D Friedman; Rebecca L Moore; Shuo Cheng Lin; Kerrie P Nelson; James A Feldman Journal: Ann Emerg Med Date: 2013-07-09 Impact factor: 5.721
Authors: Herbert C Duber; Isabel A Barata; Eric Cioè-Peña; Stephen Y Liang; Eric Ketcham; Wendy Macias-Konstantopoulos; Shawn A Ryan; Mark Stavros; Lauren K Whiteside Journal: Ann Emerg Med Date: 2018-06-05 Impact factor: 5.721
Authors: Fady Y Hijji; Tyler Sanda; Scott D Huff; Andrew W Froehle; Joseph D Henningsen; Andrew D Schneider; Joseph G Lyons; Humza M Mian; Jennifer Jerele; Indresh Venkatarayappa Journal: Eur J Orthop Surg Traumatol Date: 2022-01-04
Authors: Aaron D Dora-Laskey; Jason E Goldstick; Brooke J Arterberry; Suni Jo Roberts; Rebecca L Haffajee; Amy S B Bohnert; Rebecca M Cunningham; Patrick M Carter Journal: West J Emerg Med Date: 2020-06-19