A Bayesian Spatio-temporal Model to Optimize Allocation of Buprenorphine in North Carolina
نویسندگان
چکیده
The opioid epidemic is an ongoing public health crisis. In North Carolina, overdose deaths due to illicit have sharply increased over the last 5-7 years. Buprenorphine a U.S. Food and Drug Administration approved medication for treatment of use disorder obtained by prescription. Prior January 2023, providers had obtain waiver were limited in number patients that they could prescribe buprenorphine. Thus, identifying counties where increasing buprenorphine would yield greatest overall reduction death can help policymakers target certain geographical regions inform effective response. We propose Bayesian spatio-temporal model relates yearly, county-level changes rates prescriptions. our forecast statewide count rate future years, we nonlinear constrained optimization identify optimal increase each county under set constraints on available resources. Our estimates negative relationship between after accounting other covariates, identified single-year allocation strategy estimated reduce 5%
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ژورنال
عنوان ژورنال: Statistics and public policy
سال: 2023
ISSN: ['2330-443X']
DOI: https://doi.org/10.1080/2330443x.2023.2218448