Opioid overdose deaths and potentially inappropriate opioid prescribing practices (PIP): A spatial epidemiological study.


Journal

The International journal on drug policy
ISSN: 1873-4758
Titre abrégé: Int J Drug Policy
Pays: Netherlands
ID NLM: 9014759

Informations de publication

Date de publication:
06 2019
Historique:
received: 12 07 2018
revised: 09 01 2019
accepted: 02 03 2019
pubmed: 14 4 2019
medline: 24 3 2020
entrez: 14 4 2019
Statut: ppublish

Résumé

Opioid overdose deaths quintupled in Massachusetts between 2000 and 2016. Potentially inappropriate opioid prescribing practices (PIP) are associated with increases in overdoses. The purpose of this study was to conduct spatial epidemiological analyses of novel comprehensively linked data to identify overdose and PIP hotspots. Sixteen administrative datasets, including prescription monitoring, medical claims, vital statistics, and medical examiner data, covering >98% of Massachusetts residents between 2011-2015, were linked in 2017 to better investigate the opioid epidemic. PIP was defined by six measures: ≥100 morphine milligram equivalents (MMEs), co-prescription of benzodiazepines and opioids, cash purchases of opioid prescriptions, opioid prescriptions without a recorded pain diagnosis, and opioid prescriptions through multiple prescribers or pharmacies. Using spatial autocorrelation and cluster analyses, overdose and PIP hotspots were identified among 538 ZIP codes. More than half of the adult population (n = 3,143,817, ages 18 and older) were prescribed opioids. Nearly all ZIP codes showed increasing rates of overdose over time. Overdose clusters were identified in Worcester, Northampton, Lee/Tyringham, Wareham/Bourne, Lynn, and Revere/Chelsea (Getis-Ord Gi*; p < 0.05). Large PIP clusters for ≥100 MMEs and prescription without pain diagnosis were identified in Western Massachusetts; and smaller clusters for multiple prescribers in Nantucket, Berkshire, and Hampden Counties (p < 0.05). Co-prescriptions and cash payment clusters were localized and nearly identical (p < 0.05). Overlap in PIP and overdose clusters was identified in Cape Cod and Berkshire County. However, we also found contradictory patterns in overdose and PIP hotspots. Overdose and PIP hotspots were identified, as well as regions where the two overlapped, and where they diverged. Results indicate that PIP clustering alone does not explain overdose clustering patterns. Our findings can inform public health policy decisions at the local level, which include a focus on PIP and misuse of heroin and fentanyl that aim to curb opioid overdoses.

Identifiants

pubmed: 30981166
pii: S0955-3959(19)30090-8
doi: 10.1016/j.drugpo.2019.03.024
pmc: PMC6685426
mid: NIHMS1526783
pii:
doi:

Substances chimiques

Analgesics, Opioid 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

37-45

Subventions

Organisme : NIDA NIH HHS
ID : K23 DA042168
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001064
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR002544
Pays : United States

Informations de copyright

Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

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Auteurs

Thomas J Stopka (TJ)

Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States. Electronic address: thomas.stopka@tufts.edu.

Harsha Amaravadi (H)

Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.

Anna R Kaplan (AR)

Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.

Rachel Hoh (R)

Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.

Dana Bernson (D)

Massachusetts Department of Public Health, Boston, MA, United States.

Kenneth K H Chui (KKH)

Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.

Thomas Land (T)

University of Massachusetts Medical School, Division of Clinical Informatics, Worcester, MA, United States (T. Land).

Alexander Y Walley (AY)

Massachusetts Department of Public Health, Boston, MA, United States; Boston University School of Medicine/Boston Medical Center, Boston, MA, United States.

Marc R LaRochelle (MR)

Boston University School of Medicine/Boston Medical Center, Boston, MA, United States.

Adam J Rose (AJ)

Boston University School of Medicine/Boston Medical Center, Boston, MA, United States; RAND Corporation, Boston, MA, United States.

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