Literature DB >> 30146997

The Impact of Prescription Drug Monitoring Programs on U.S. Opioid Prescriptions.

Ian Ayres1, Amen Jalal1.   

Abstract

This paper seeks to understand the treatment effect of Prescription Drug Monitoring Programs (PDMPs) on opioid prescription rates. Using county-level panel data on all opioid prescriptions in the U.S. between 2006 and 2015, we investigate whether state interventions like PDMPs have heterogeneous treatment effects at the sub-state level, based on regional and temporal variations in policy design, extent of urbanization, race, and income. Our models comprehensively control for a set of county and time fixed effects, countyspecific and time-varying demographic controls, potentially endogenous time-series trends in prescription rates, and other state-level opioid interventions such as Naloxone Access and Good Samaritan laws, Medicaid expansion, and the provision of Methadone Assistance Treatment. We find that PDMPs are only effective in reducing prescription rates if they obligate doctors to check for patients' history prior to filling out a prescription, but the frequency at which a state requires its PDMP to be updated is irrelevant to its effectiveness. Moreover, the significant treatment effects of PDMPs are almost exclusively driven by urban and predominantly white counties, with the relatively more affluent regions showing greater responsiveness than their less affluent counterparts.

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Year:  2018        PMID: 30146997     DOI: 10.1177/1073110518782948

Source DB:  PubMed          Journal:  J Law Med Ethics        ISSN: 1073-1105            Impact factor:   1.718


  8 in total

1.  Methodological Challenges and Proposed Solutions for Evaluating Opioid Policy Effectiveness.

Authors:  Megan S Schuler; Beth Ann Griffin; Magdalena Cerdá; Emma E McGinty; Elizabeth A Stuart
Journal:  Health Serv Outcomes Res Methodol       Date:  2020-11-12

2.  "Nobody Knows How You're Supposed to Interpret it:" End-user Perspectives on Prescription Drug Monitoring Program in Massachusetts.

Authors:  Mina Hong; Sarah Seymour; Thomas J Stopka; Lane Bandanza; Erin Crocker; Allison Morgan; Leo Beletsky
Journal:  J Addict Med       Date:  2022 May-Jun 01       Impact factor: 4.647

3.  Dynamic prediction of work status for workers with occupational injuries: assessing the value of longitudinal observations.

Authors:  Erkin Ötleş; Jon Seymour; Haozhu Wang; Brian T Denton
Journal:  J Am Med Inform Assoc       Date:  2022-10-07       Impact factor: 7.942

4.  Kratom Use in the US: Both a Regional Phenomenon and a White Middle-Class Phenomenon? Evidence From NSDUH 2019 and an Online Convenience Sample.

Authors:  Jeffrey M Rogers; Kirsten E Smith; Justin C Strickland; David H Epstein
Journal:  Front Pharmacol       Date:  2021-12-20       Impact factor: 5.810

Review 5.  The state of the science in opioid policy research.

Authors:  Megan S Schuler; Sara E Heins; Rosanna Smart; Beth Ann Griffin; David Powell; Elizabeth A Stuart; Bryce Pardo; Sierra Smucker; Stephen W Patrick; Rosalie Liccardo Pacula; Bradley D Stein
Journal:  Drug Alcohol Depend       Date:  2020-06-27       Impact factor: 4.492

6.  Advances in prescription drug monitoring program research: a literature synthesis (June 2018 to December 2019).

Authors:  Chris Delcher; Nathan Pauly; Patience Moyo
Journal:  Curr Opin Psychiatry       Date:  2020-07       Impact factor: 4.787

7.  Urban scaling of opioid overdose deaths in the USA: a cross-sectional study in three periods between 2005 and 2017.

Authors:  Pricila H Mullachery; Stephen Lankenau; Ana V Diez Roux; Ran Li; Rosie Mae Henson; Usama Bilal
Journal:  BMJ Open       Date:  2022-03-03       Impact factor: 2.692

8.  Co-prescription network reveals social dynamics of opioid doctor shopping.

Authors:  Brea L Perry; Kai Cheng Yang; Patrick Kaminski; Meltem Odabas; Jaehyuk Park; Michelle Martel; Carrie B Oser; Patricia R Freeman; Yong-Yeol Ahn; Jeffery Talbert
Journal:  PLoS One       Date:  2019-10-25       Impact factor: 3.240

  8 in total

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