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Wei YJ, Chen C, Sarayani A, Winterstein AG. Performance of the Centers for Medicare & Medicaid Services’ Opioid Overutilization Criteria for Classifying Opioid Use Disorder or Overdose. JAMA. 2019;321(6):609–611. doi:10.1001/jama.2018.20404
To address the growing problem of opioid overuse and abuse in the Medicare population, the Centers for Medicare & Medicaid Services (CMS) launched an Overutilization Monitoring System in 2013, requiring its Part D plan sponsors to identify beneficiaries who are at high risk of opioid-related adverse events based on opioid overutilization criteria and to implement interventions.1 Whether the criteria, which depend on prescription-dispensing data, are accurate as a clinical marker for classifying beneficiaries with opioid use disorder (OUD) or overdose is unknown.
We used the 5% Medicare sample from 2011 through 2014 to estimate the sensitivity, specificity, and positive predictive value of the CMS opioid overutilization criteria in correctly identifying prescription opioid users at risk of OUD or overdose in three 6-month cycles (ie, January 1–June 30, April 1–September 30, and July 1–December 31) in each calendar year. We studied the performance measures over time, hypothesizing that accuracy might change with increasing efforts to combat the opioid crisis.2 Concordant with the most recent (2017) reporting requirements for Part D plans, we used 3 overlapping 6-month cycles per year.1
In each 6-month cycle, eligible patients were required to have at least 1 prescription opioid filled; be continuously enrolled in Parts A, B, and D; and have no cancer nor be receiving hospice care.1 We identified eligible beneficiaries who met CMS criteria as opioid overutilizers (ie, receiving prescription opioids with a mean daily morphine equivalent dose ≥90 mg and from >3 prescribers and >3 pharmacists or receiving a prescription of opioids with a mean daily morphine equivalent dose of ≥90 mg by >4 prescribers)1 and those who had a diagnosis of OUD or overdose3 in the same 6 months plus the subsequent 12 months to account for delays in OUD diagnoses. Linear regression was used to determine trends over time (SAS version 9.4; SAS Institute Inc). Statistical significance was defined as a 2-sided P<.05. This study was approved by the University of Florida Institutional Review Board with a waiver of informed consent.
We identified between 142 036 and 190 320 eligible beneficiaries prescribed opioids across the 6-month measurement cycles from 2011 through 2014. The proportion of beneficiaries who met CMS overutilization criteria during any 6-month cycle ranged from 0.37% to 0.58%. The proportion who had a diagnosis of OUD or overdose during the 18-month follow-up increased from 3.91% in the first cycle to 7.55% in the last. We observed low sensitivity of the criteria, ranging from 4.96% (95% CI, 4.42%-5.58%) at the beginning of the study period to 2.52% (95% CI, 2.26%-2.81%) at the end (P for trend <.001) and positive predictive values ranged from 35.20% (95% CI, 32.14%-38.38%) to 50.94% (95% CI, 47.00%-54.86%; P for trend <.001). Specificity was greater than 99% in all cycles (Table).
Although the CMS criteria may target patients at true risk of OUD or overdose, they missed the majority of patients with OUD or overdose and flagged more than half of opioid prescription users as high risk who were not diagnosed as having OUD or overdose. The small positive predictive value is attributable partly to the low OUD prevalence in the Medicare sample.
For identified high-risk beneficiaries, CMS requires its Part D plan sponsors to implement patient-specific utilization review, case management, and dose-dependent safety alerts or reimbursement rejections at the time of opioid dispensing.1,4 The Substance Use-Disorder Prevention That Promotes Opioid Recovery and Treatment (SUPPORT) for Patients and Communities Act, which was signed into law on October 24, 2018, allows CMS to refuse payment for opioids prescribed to beneficiaries who are identified as high risk unless their prescriptions are issued by a designated clinician.5 Based on this study, the CMS criteria’s low sensitivity suggests different approaches are needed to identify high-risk patients and prevent or treat OUD.
The mechanisms explaining the present findings likely include reliance on prescription opioid data and failure to capture illicit opioid use, which is surpassing prescription opioids in their contribution to opioid overdoses.6 Because the CMS criteria are confined to patients who received opioid prescriptions, these results do not extend to patients with OUD or overdose who solely used illicit opioid sources; thus, reported incidence rates and sensitivity results are likely underestimated.
Accepted for Publication: November 29, 2018.
Corresponding Author: Yu-Jung Jenny Wei, PhD, Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, 1225 Center Dr, Health Professions Nursing Pharmacy Bldg, Room 3321, Gainesville, FL 32610 (firstname.lastname@example.org).
Author Contributions: Drs Wei and Winterstein had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Wei, Chen, Winterstein.
Acquisition, analysis, or interpretation of data: Wei, Chen, Sarayani.
Drafting of the manuscript: Wei.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: All authors.
Obtained funding: Wei.
Administrative, technical, or material support: Wei, Chen, Winterstein.
Conflict of Interest Disclosures: None reported.
Funding/Support: This project had no direct funding. Dr Wei is supported in part by a Mentored Research Scientist Award (K01AG054764) from the National Institute on Aging.
Role of the Funder/Sponsor: The National Institute on Aging had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
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