Direct Costs of Opioid Abuse in an Insured Population in the United States.

J Manag Care Spec Pharm

vice president, medical affairs and pain research, Inflexxion, Inc., Newton, Massachusetts.

Published: October 2020


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Article Abstract

Objective: To (a) describe the demographics of opioid abusers; (b) compare the prevalence rates of selected comorbidities and the medical and drug utilization patterns of opioid abusers with patients from a control group, for the period from 1998 to 2002; and (c) calculate the mean annual per-patient total health care costs (e.g., inpatient, outpatient, emergency room, drug, other) from the perspective of a private payer.

Methods: An administrative database of medical and pharmacy claims from 1998 to 2002 of 16 self-insured employer health plans with approximately 2 million lives was used to identify "opioid abusers"-patients with claims associated with ICD-9-CM () codes for opioid abuse (304.0, 304.7, 305.5, and 965.0 [excluding 965.01]). A control group of nonabusers was selected using a matched sample (by age, gender, employment status, and census region) in a 3:1 ratio. Per-patient annual health care costs (mean total medical and drug costs) were measured in 2003 U.S. dollars. Multivariate regression techniques were also used to control for comorbidities and to compare costs with a benchmark of depressed patients.

Results: 740 patients were identified as opioid abusers, a prevalence of 8 in 10,000 persons aged 12 to 64 years continuously enrolled in health care plans for whom 12 months of data were available for calculating costs. Opioid abusers, compared with nonabusers, had significantly higher prevalence rates for a number of specific comorbidities, including nonopioid poisoning, hepatitis (A, B, or C), psychiatric illnesses, and pancreatitis, which were approximately 78, 36, 9, and 21 (<0.01) times higher, respectively, compared with nonabusers. Opioid abusers also had higher levels of medical and prescription drug utilization. Almost 60% of opioid abusers had prescription drug claims for opioids compared with approximately 20% for nonabusers. Prevalence rates for hospital inpatient visits for opioid abusers were more than 12 times higher compared with nonabusers (<0.01). Mean annual direct health care costs for opioid abusers were more than 8 times higher than for nonabusers ($15,884 versus $1,830, respectively, < 0.01). Hospital inpatient and physician-outpatient costs accounted for 46% ($7,239) and 31% ($5,000) of opioid abusers' health care costs, compared with 17% ($310) and 50% ($906), respectively, for nonabusers. Mean drug costs for opioid abusers were more than 5 times higher than costs for nonabusers ($2,034 vs. $386, respectively, <0.01), driven by higher drug utilization (including opioids) for opioid abusers. Even when controlling for comorbidities using a multivariate regression model of a matched control of depressed patients, the average health care costs of opioid abusers were 1.8 times higher than the average health care costs of depressed patients.

Conclusion: The high costs of opioid abuse were driven primarily by high prevalence rates of costly comorbidites and high utilization rates of medical services and prescription drugs.

Disclosures: Funding for this research was provided by an unrestricted grant from Janssen Medical Affairs, L.L.C. and was obtained by authors Susan Vallow and Jeff Schein, who are employed by Janssen Medical Affairs, L.L.C. Nathaniel Katz is a consultant to Janssen and numerous other pharmaceutical companies that manufacture branded opioid products and nonopioid analgesics; authors Alan G. White, Howard G. Birnbaum, Milena N. Mareva, and Maham Daher disclose no potential bias or conflict of interest relating to this article. White served as principal author of the study. Study concept and design were contributed primarily by White, Vallow, Schein, and Katz. Analysis and interpretation of data were contributed by all authors. Drafting of the manuscript was primarily the work of White, and its critical revision was the work of White and Vallow. Statistical expertise was contributed by White, Birnbaum, and Daher, and administrative, technical, and/or material support was provided by Analysis Group, Inc., Boston, MA.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391027PMC
http://dx.doi.org/10.18553/jmcp.2020.26.10.1188DOI Listing

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