ResearchPublications

Sensitivity of Medicaid claims data for identifying opioid use disorder in patients admitted to 6 New York City public hospitals
Abstract

OBJECTIVES: Behavioral health diagnoses are frequently underreported in administrative health data. For a pragmatic trial of a hospital addiction consult program, we sought to determine the sensitivity of Medicaid claims data for identifying patients with opioid use disorder (OUD).

METHODS: A structured review of electronic health record (EHR) data was conducted to identify patients with OUD in 6 New York City public hospitals. Cases selected for review were adults admitted to medical/surgical inpatient units who received methadone or sublingual buprenorphine in the hospital. For cases with OUD based on EHR review, we searched for the hospitalization in Medicaid claims data and examined International Classification of Diseases, Tenth Revision discharge diagnosis codes to identify opioid diagnoses (OUD, opioid poisoning, or opioid-related adverse events). Sensitivity of Medicaid claims data for capturing OUD hospitalizations was calculated using EHR review findings as the reference standard measure.

RESULTS: Among 552 cases with OUD based on EHR review, 465 (84.2%) were found in the Medicaid claims data, of which 418 (89.9%) had an opioid discharge diagnosis. Opioid diagnoses were the primary diagnosis in 49 cases (11.7%), whereas in the remainder, they were secondary diagnoses.

CONCLUSION: In this sample of hospitalized patients receiving OUD medications, Medicaid claims seem to have good sensitivity for capturing opioid diagnoses. Although the sensitivity of claims data may vary, it can potentially be a valuable source of information about OUD patients.

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Full citation:
McNeely J, Gallagher SD, Mazumdar M, Appleton N, Fernando J, Owens E, Bone E, Krawczyk N, Dolle J, Marcello RK, Billings J, Wang S (2023).
Sensitivity of Medicaid claims data for identifying opioid use disorder in patients admitted to 6 New York City public hospitals
Journal of Addiction Medicine, 17 (3), 339-341. doi: 10.1097/ADM.0000000000001097. PMCID: PMC10110762.