Evidence map›Paper›PMID 30981166›Full record

ArticleThe International journal on drug policy2019

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

Thomas J Stopka, Harsha Amaravadi, Anna R Kaplan, Rachel Hoh, Dana Bernson, Kenneth K H Chui, Thomas Land, Alexander Y Walley, Marc R LaRochelle, Adam J Rose

Open access · hybridAbstract read
In one paragraph

Article in The International journal on drug policy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
7.8field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.

  1. Pooled it
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  11. Use of Big Data and Ethical Issues for Populations With Substance Use Disorder.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2023
    Article
  12. Article
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  14. Review
  15. Fatal overdose: Predicting to prevent.The International journal on drug policy · 2022
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Thomas J StopkaDepartment of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States. Electronic address: thomas.stopka@tufts.edu.
Harsha AmaravadiDepartment of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.
Anna R KaplanDepartment of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.
Rachel HohDepartment of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.
Dana BernsonMassachusetts Department of Public Health, Boston, MA, United States.
Kenneth K H ChuiDepartment of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA, United States.
Thomas LandUniversity of Massachusetts Medical School, Division of Clinical Informatics, Worcester, MA, United States (T. Land).
Alexander Y WalleyMassachusetts Department of Public Health, Boston, MA, United States; Boston University School of Medicine/Boston Medical Center, Boston, MA, United States.
Marc R LaRochelleBoston University School of Medicine/Boston Medical Center, Boston, MA, United States.
Adam J RoseBoston University School of Medicine/Boston Medical Center, Boston, MA, United States; RAND Corporation, Boston, MA, United States.
Tufts University · USBoston University · USMassachusetts Department of Public Health · USUniversity of Massachusetts Chan Medical School · US

Funding

Tufts Clinical and Translational Science Institute (Pilot Supplement)UL1TR002544 · NCATS · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2018 to 2022
$50.2M
Tufts Clinical and Translational Research InstituteUL1TR001064 · NCATS · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2013 to 2017
$26.4M
Improving urine drug test utility to mitigate prescription opioid riskK23DA042168 · NIDA · BOSTON MEDICAL CENTER · PI LAROCHELLE, MARC · 2017 to 2021
$956k
NCATS NIH HHS UL1 TR001064NCATS NIH HHS UL1 TR002544NIDA NIH HHS K23 DA042168
6 · The paper itself

Abstract

introductionOpioid 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.

methodsSixteen 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.

resultsMore 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.

conclusionsOverdose 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.

Indexed as

AdultAnalgesics, OpioidDatabases, FactualDrug OverdoseFemaleGeography, MedicalHumansInappropriate PrescribingMaleMassachusettsPractice Patterns, Physicians'Young AdultAnalgesics, OpioidClustersGeographic information systems (GIS)Getis-Ord Gi*HotspotsMassachusettsOpioid overdosePrescription opioids

Identifiers

PMID30981166
PMCPMC6685426
OpenAlexW2939153368

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.