Opioid overdose deaths and potentially inappropriate opioid prescribing practices (PIP): A spatial epidemiological study
Name:
Publisher version
View Source
Access full-text PDFOpen Access
View Source
Check access options
Check access options
Authors
Stopka, Thomas J.Amaravadi, Harsha
Kaplan, Anna R.
Hoh, Rachel
Bernson, Dana
Chui, Kenneth K.H.
Land, Thomas
Walley, Alexander Y.
LaRochelle, Marc R.
Rose, Adam J.
UMass Chan Affiliations
Prevention Research CenterDepartment of Medicine, Division of Preventive and Behavioral Medicine
Division of Clinical Informatics
Document Type
Journal ArticlePublication Date
2019-06-01Keywords
ClustersGeographic information systems (GIS)
Getis-Ord Gi*
Hotspots
Massachusetts
Opioid overdose
Prescription opioids
Clinical Epidemiology
Community Health and Preventive Medicine
Epidemiology
Geographic Information Sciences
Health Policy
Health Services Administration
Health Services Research
Pharmaceutical Preparations
Substance Abuse and Addiction
Therapeutics
Metadata
Show full item recordAbstract
INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.Source
Int J Drug Policy. 2019 Jun;68:37-45. doi: 10.1016/j.drugpo.2019.03.024. Epub 2019 Apr 11. Link to article on publisher's site
DOI
10.1016/j.drugpo.2019.03.024Permanent Link to this Item
http://hdl.handle.net/20.500.14038/41034PubMed ID
30981166Related Resources
Rights
© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).Distribution License
http://creativecommons.org/licenses/by-nc-nd/4.0/ae974a485f413a2113503eed53cd6c53
10.1016/j.drugpo.2019.03.024
Scopus Count
Except where otherwise noted, this item's license is described as © 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).