The Association Between Local Economic Conditions and Opioid Prescriptions Among Disabled Medicare Beneficiaries

Datos Bibliográficos

ID9101255
AutoresChao Zhou (0009-0001-7966-2044, Health Care Cost Institute, Washington, DC, autor de correspondencia), Ning Neil Yu (0000-0002-0044-028X, Nanjing Audit University, Nanjing, China), Jan L Losby (0000-0001-6875-0746, Stanford University, Stanford, CA)
Año2018
Volumen56
Número1
Páginas62-68
Fecha de publicación2018-01-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaMedical Care (JOURNAL)
Identificadores de la revistaISSN: 0025-7079 • E-ISSN: 1537-1948
EditorialOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0000000000000841
PMID29227444
OpenAlexW2772590780
IdiomaEN
Citas recibidas7
Referencias citadas27

BACKGROUND: This paper concerns public health crises today-the problem of opioid prescription access and related abuse. Inspired by Case and Deaton's seminal work on increasing mortality among white Americans with lower education, this paper explores the relationship between opioid prescribing and local economic factors. OBJECTIVE: We examined the association between county-level socioeconomic factors (median household income, unemployment rate, Gini index) and opioid prescribing. SUBJECTS: We used the complete 2014 Medicare enrollment and part D drug prescription data from the Center for Medicare and Medicaid Services to study opioid prescriptions of disabled Medicare beneficiaries without record of cancer treatment, palliative care, or end-of-life care. MEASURES AND RESEARCH DESIGN: We summarized the demographic and geographic variation, and investigated how the local economic environment, measured by county median household income, unemployment rate, Gini index, and urban-rural classification correlated with various measures of individual opioid prescriptions. Measures included number of filled opioid prescriptions, total days' supply, average morphine milligram equivalent (MME)/day, and annual total MME dosage. To assess the robustness of the results, we controlled for individual and other county characteristics, used multiple estimation methods including linear least squares, logistic regression, and Tobit regression. RESULTS AND CONCLUSIONS: Lower county median household income, higher unemployment rates, and less income inequality were consistently associated with more and higher MME opioid prescriptions among disabled Medicare beneficiaries. Geographically, we found that the urban-rural divide was not gradual and that beneficiaries in large central metro counties were less likely to have an opioid prescription than those living in other areas

Economic growth · Economics · Environmental health · Geography · Health care · Household income · Logistic regression · Medicaid · Medical prescription · Population · Socioeconomic status · Unemployment · Demography · Healthcare Policy and Management · Medication Adherence and Compliance · Medicine · Opioid Use Disorder Treatment