• Lauren M Scarpati, Noam Y Kirson, Miriam L Zichlin, Zitong B Jia, Howard G Birnbaum, and Jaren C Howard.
• Analysis Group, Inc, 111 Huntington Ave, 14th Floor, Boston, MA 02199. E-mail: lauren.scarpati@analysisgroup.com.
• Am J Manag Care. 2017 May 1; 23 (5): 276-282.

ObjectivesTo replicate and extend a recently published analysis of the drivers of excess costs of opioid abuse.Study DesignRetrospective data analysis using de-identified claims data from the Truven MarketScan Commercial Claims and Encounter database.MethodsMedical and prescription drug claims from beneficiaries covered by large self-insured US companies were used to select patients with incident diagnoses of opioid abuse between 2012 and 2015. Two cohorts, abusers and nonabusers, were matched using propensity score methods. Excess healthcare costs were estimated over a 6-month baseline period and 12-month follow-up period. Cost drivers were assessed by diagnosis (3-digit International Classification of Diseases, Ninth Revision, Clinical Modification groupings) and place of service.ResultsThe analysis included 73,714 matched pairs of abusers and nonabusers. Relative to nonabusers, abusers had considerably higher annual healthcare costs of $10,989 per patient, or $1.98 per member per month. Excess costs were similar, yet lower, than the previous analysis using another commercial claims database. In both analyses, a ramp-up in excess costs was observed prior to the incident abuse diagnosis, followed by a decline post diagnosis, although not to baseline levels. Key drivers of excess costs in the 2 studies included opioid use disorders, nonopioid substance misuse, and painful and mental health conditions. From 2010 to 2014, the prevalence of diagnosed opioid abuse doubled, with incidence rates exhibiting an increasing, though flatter, trend than earlier in the period.ConclusionsOpioid abuse imposes a considerable economic burden on payers. Many abusers have complex healthcare needs and may require care beyond that which is required to treat opioid abuse. These results are robust and consistent across different data sources.

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