Evidence map›Paper›PMID 30471102›Full record

ArticleJournal of the American Geriatrics Society2019

Effect of Age on Opioid Prescribing, Overdose, and Mortality in Massachusetts, 2011 to 2015.

Adam J Rose, Ryan McBain, Megan S Schuler, Marc R LaRochelle, David A Ganz, Vikram Kilambi, Bradley D Stein, Dana Bernson, Kenneth Kwan Ho Chui, Thomas Land and 2 more

Abstract readEvaluation Study
In one paragraph

Article in Journal of the American Geriatrics Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
6.9field-weighted citation impact, top 3% 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

23 citing papers in PubMed, 59 citations in OpenAlex.

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  7. 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
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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

12 authors at 5 institutions in 1 country.

Adam J RoseRAND Corporation, Boston, Massachusetts.ORCID 0000-0001-8681-6155
Ryan McBainRAND Corporation, Boston, Massachusetts.
Megan S SchulerRAND Corporation, Boston, Massachusetts.
Marc R LaRochelleSection of General Internal Medicine, School of Medicine, Boston University, Boston, Massachusetts.
David A GanzRAND Corporation, Santa Monica, California.
Vikram KilambiRAND Corporation, Boston, Massachusetts.
Bradley D SteinRAND Corporation, Pittsburgh, Pennsylvania.
Dana BernsonMassachusetts Department of Public Health, Boston, Massachusetts.
Kenneth Kwan Ho ChuiSchool of Medicine, Tufts University, Boston, Massachusetts.
Thomas LandSchool of Medicine, University of Massachusetts, Worcester, Massachusetts.
Alexander Y WalleySection of General Internal Medicine, School of Medicine, Boston University, Boston, Massachusetts.
Thomas J StopkaSchool of Medicine, Tufts University, Boston, Massachusetts.
RAND Corporation · USBoston University · USTufts University · USMassachusetts Department of Public Health · USUniversity of Massachusetts Chan Medical School · US

Funding

Project-005UL1TR001430 · NCATS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BAIR-MERRITT, MEGAN H, CENTER, DAVID M. · 2015 to 2024
$52.3M
Optimal Methods for Estimating Policy Effect Heterogeneity in Opioid Policy ResearchP50DA046351 · NIDA · RAND CORPORATION · PI BRADLEY D STEIN · 2018 to 2026
$20.8M
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 TR001430NIDA NIH HHS K23 DA042168NIDA NIH HHS P50 DA046351
6 · The paper itself

Abstract

objectivesTo examine the effect of age on the likelihood of PIP of opioids and the effect of PIP on adverse outcomes.

designRetrospective cohort study.

settingData from multiple state agencies in Massachusetts from 2011 to 2015.

participantsAdult Massachusetts residents (N=3,078,163) who received at least one prescription opioid during the study period; approximately half (1,589,365) aged 50 and older. MEASUREMENTS: We measured exposure to 5 types of PIP: high-dose opioids, coprescription with benzodiazepines, multiple opioid prescribers, multiple opioid pharmacies, and continuous opioid therapy without a pain diagnosis. We examined 3 adverse outcomes: nonfatal opioid overdose, fatal opioid overdose, and all-cause mortality.

resultsThe rate of any PIP increased with age, from 2% of individuals age 18 to 29 to 14% of those aged 50 and older. Older adults also had higher rates of exposure to 2 or more different types of PIP (40-49, 2.5%; 50-69, 5%; ≥70, 4%). Of covariates assessed, older age was the greatest predictor of PIP. In analyses stratified according to age, any PIP and specific types of PIP were associated with nonfatal overdose, fatal overdose, and all-cause mortality in younger and older adults.

conclusionOlder adults are more likely to be exposed to PIP, which increases their risk of adverse events. Strategies to reduce exposure to PIP and to improve outcomes in those already exposed will be instrumental to addressing the opioid crisis in older adults. J Am Geriatr Soc 67:128-132, 2019.

Indexed as

Age FactorsAgedAged, 80 and overAnalgesics, OpioidDrug OverdoseFemaleHumansMaleMassachusettsMiddle AgedOpioid-Related DisordersPainPractice Patterns, Physicians'Retrospective StudiesAnalgesics, Opioidagedmortalityopioid overdosepotentially inappropriate prescribing

Identifiers

PMID30471102
PMCPMC6448572
OpenAlexW2901750597

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.