Evidence map›Paper›PMID 29764482›Full record

ArticleBMC medicine2018

Healthcare costs and utilization associated with high-risk prescription opioid use: a retrospective cohort study.

Hsien-Yen Chang, Hadi Kharrazi, Dave Bodycombe, Jonathan P Weiner, G Caleb Alexander

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 2 pooled it
9.6field-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

52 citing papers in PubMed, 2 syntheses or guidelines pooled it, 121 citations in OpenAlex.

  1. Pooled it
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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

5 authors at 1 institution in 1 country.

Hsien-Yen ChangDepartment of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Hadi KharraziDepartment of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Dave BodycombeDepartment of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Jonathan P WeinerDepartment of Health Policy & Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
G Caleb AlexanderCenter for Drug Safety and Effectiveness, Johns Hopkins University, Baltimore, MD, USA. galexand@jhsph.edu.
Johns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevious studies on high-risk opioid use have only focused on patients diagnosed with an opioid disorder. This study evaluates the impact of various high-risk prescription opioid use groups on healthcare costs and utilization.

methodsThis is a retrospective cohort study using QuintilesIMS health plan claims with independent variables from 2012 and outcomes from 2013. We included a population-based sample of 191,405 non-elderly adults with known sex, one or more opioid prescriptions, and continuous enrollment in 2012 and 2013. Three high-risk opioid use groups were identified in 2012 as (1) persons with 100+ morphine milligram equivalents per day for 90+ consecutive days (chronic users); (2) persons with 30+ days of concomitant opioid and benzodiazepine use (concomitant users); and (3) individuals diagnosed with an opioid use disorder. The length of time that a person had been characterized as a high-risk user was measured. Three healthcare costs (total, medical, and pharmacy costs) and four binary utilization indicators (the top 5% total cost users, the top 5% pharmacy cost users, any hospitalization, and any emergency department visit) derived from 2013 were outcomes. We applied a generalized linear model (GLM) with a log-link function and gamma distribution for costs while logistic regression was employed for utilization indicators. We also adopted propensity score weighting to control for the baseline differences between high-risk and non-high-risk opioid users.

resultsOf individuals with one or more opioid prescription, 1.45% were chronic users, 4.81% were concomitant users, and 0.94% were diagnosed as having an opioid use disorder. After adjustment and propensity score weighting, chronic users had statistically significant higher prospective total (40%), medical (3%), and pharmacy (172%) costs. The increases in total, medical, and pharmacy costs associated with concomitant users were 13%, 7%, and 41%, and 28%, 21% and 63% for users with a diagnosed opioid use disorder. Both total and pharmacy costs increased with the length of time characterized as high-risk users, with the increase being statistically significant. Only concomitant users were associated with a higher odds of hospitalization or emergency department use.

conclusionsIndividuals with high-risk prescription opioid use have significantly higher healthcare costs and utilization than their counterparts, especially those with chronic high-dose opioid use.

Indexed as

Analgesics, OpioidCohort StudiesFemaleHealth Care CostsHumansMaleMiddle AgedRetrospective StudiesAnalgesics, OpioidChronic high-dose opioid usersConcomitant users of opioid and benzodiazepineHealthcare costsOpioid shoppersResource utilization

Identifiers

PMID29764482
PMCPMC5954462
OpenAlexW2804283237

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.