Opioid overdose deaths and potentially inappropriate opioid prescribing practices (PIP): A spatial epidemiological study.
Adult
Analgesics, Opioid
/ adverse effects
Databases, Factual
/ statistics & numerical data
Drug Overdose
/ epidemiology
Female
Geography, Medical
/ statistics & numerical data
Humans
Inappropriate Prescribing
/ mortality
Male
Massachusetts
/ epidemiology
Practice Patterns, Physicians'
/ statistics & numerical data
Young Adult
Clusters
Geographic information systems (GIS)
Getis-Ord Gi*
Hotspots
Massachusetts
Opioid overdose
Prescription opioids
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
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
37-45Subventions
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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