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. 2018 May 16;16(1):69.
doi: 10.1186/s12916-018-1058-y.

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

Hsien-Yen Chang  1   2   3 , Hadi Kharrazi  1   3 , Dave Bodycombe  1   3 , Jonathan P Weiner  1   3 , G Caleb Alexander  4   5   6
Affiliations

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

Hsien-Yen Chang et al. BMC Med. .

Abstract

Background: Previous 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.

Methods: This 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.

Results: Of 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.

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

Keywords: Chronic high-dose opioid users; Concomitant users of opioid and benzodiazepine; Healthcare costs; Opioid shoppers; Resource utilization.

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Conflict of interest statement

Ethics approval and consent to participate

The data source included de-identified information, and this project was deemed not to be human subject research by the institutional review board of the Johns Hopkins Bloomberg School of Public Health; ethics review board approval for such studies is not required.

Consent for publication

All authors have approved this manuscript for publication.

Competing interests

Dr. Alexander serves as the Chair of the FDA’s Peripheral and Central Nervous System Advisory Committee, serves as a paid consultant and Chairs a QuintilesIMS Advisory Board, serves on the Advisory Board of MesaRx Innovations, and is a member of OptumRx’s National P&T Committee. This arrangement has been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. In addition, this study applies the ACG case-mix/risk adjustment methodology, developed at Johns Hopkins Bloomberg School of Public Health. Although ACGs are an important aspect of the paper, the goal of this paper is not to directly assess or evaluate the methodology. The Johns Hopkins University receives royalties for non-academic use of software based on the ACG methodology. Dr. Chang, Dr. Kharrazi, Dr. Bodycombe and Dr. Weiner receive a portion of their salary support from this revenue.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

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