TY  - JOUR
PY  - 2022//
TI  - The prevalence of opioid use disorder in Kentucky's counties: a two-year multi-sample capture-recapture analysis
JO  - Drug and alcohol dependence
A1  - Thompson, Katherine
A1  - Barocas, Joshua A.
A1  - Delcher, Chris
A1  - Bae, Jungjun
A1  - Hammerslag, Lindsey
A1  - Wang, Jianing
A1  - Chandler, Redonna
A1  - Villani, Jennifer
A1  - Walsh, Sharon
A1  - Talbert, Jeffery
SP  - e109710
EP  - e109710
VL  - 242
IS  - 
N2  - BACKGROUND: Kentucky has one of the highest opioid overdose mortality rates in the United States. Accurate estimates of people with opioid use disorder (OUD) are critical to plan for the scope of interventions required to reduce overdose and opioid misuse. Commonly used household surveys are known to underestimate OUD at the state-level and do not provide county-level estimates. <br><br>METHODS: We performed a multi-sample capture-recapture analysis to estimate OUD prevalence in Kentucky in 2018 and 2019. We utilized four statewide datasets that were linked at the individual level: 1) Registry of Vital Statistics, 2) Emergency Medical Services (EMS), 3) Kentucky's Prescription Drug Monitoring Program (PDMP), and 4) Kentucky Medicaid. We included persons aged 18-64 years who resided in Kentucky between 2018 and 2019. We identified individuals with administrative data consistent with OUD in each of the datasets, including a fatal opioid-involved overdose (Vital Statistics), EMS runs for suspected opioid overdose, receipt of buprenorphine for OUD treatment (PDMP), or Medicaid claims for OUD. Observed and estimated counts of OUD cases and prevalence of OUD among the adult population in Kentucky. <br><br>RESULTS: The estimated statewide OUD prevalence was 5.5 % and 5.9 % for 2018 and 2019, respectively, ranging from 1.3 % to 17.7 % across Kentucky counties. As expected, counties with the highest OUD rates were Appalachian counties (eastern area) of the state. <br><br>CONCLUSIONS: Our analysis reveals a substantially larger proportion of KY residents have OUD than previously estimated. Our approach offers a model for states needing county-level estimates of OUD.<p />  <p>Language: en</p>
LA  - en
SN  - 0376-8716
UR  - http://dx.doi.org/10.1016/j.drugalcdep.2022.109710
ID  - ref1
ER  -