Identification of factors associated with opioid-related and hepatitis C virus-related hospitalisations at the ZIP code area level in the USA: an ecological and modelling study.

BACKGROUND: Opioid overdose and related diseases remain a growing public health crisis in the USA. Identifying sociostructural and other contextual factors associated with adverse health outcomes is needed to improve prediction models to inform policy and interventions. We aimed to identify high-risk communities for targeted delivery of screening and prevention interventions for opioid use disorder and hepatitis C virus (HCV). METHODS: In this ecological and modelling study, we fit mixed-effects negative binomial regression models to identify factors associated with, and predict, opioid-related and HCV-related hospitalisations for ZIP code tabulation areas (ZCTAs) in South Carolina, USA. All individuals aged 18 years or older living in South Carolina from Jan 1, 2016, to Dec 31, 2021, were included. Data on opioid-related and HCV-related hospitalisations, as well as data on additional individual-level variables, were collected from medical claims records, which were obtained from the South Carolina Revenue and Fiscal Affairs Office. Demographic and socioeconomic variables were obtained from the United States Census Bureau (American Community Survey, 2021) with additional structural health-care barrier data obtained from South Carolina's Center for Rural and Primary Health Care, and the American Hospital Directory. FINDINGS: Between Jan 1, 2016, and Dec 31, 2021, 41 691 individuals were hospitalised for opioid misuse and 26 860 were hospitalised for HCV. There were a median of 80 (IQR 24-213) opioid-related hospitalisations and 61 (21-196) HCV-related hospitalisations per ZCTA. A standard deviation increase in ZCTA-level uninsured rate (relative risk 1·24 [95% CI 1·17-1·31]), poverty rate (1·24 [1·17-1·31]), mortality (1·18 [1·12-1·25]), and social vulnerability index (1·17 [1·10-1·24]) was significantly associated with increased combined opioid-related and HCV-related hospitalisation rates. A standard deviation increase in ZCTA-level income (0·79 [0·75-0·84]) and unemployment rate (0·87 [0·82-0·93]) was significantly associated with decreased combined opioid-related and HCV-related hospitalisations. Using 2016-20 hospitalisations as training data, our models predicted ZCTA-level opioid-related hospitalisations in 2021 with a median of 80·4% (IQR 66·8-91·1) accuracy and HCV-related hospitalisations in 2021 with a median of 75·2% (61·2-87·7) accuracy. Several underserved high-risk ZCTAs were identified for delivery of targeted interventions. INTERPRETATION: Our results suggest that individuals from economically disadvantaged and medically under-resourced communities are more likely to have an opioid-related or HCV-related hospitalisation. In conjunction with hospitalisation forecasts, our results could be used to identify and prioritise high-risk, underserved communities for delivery of field-level interventions. FUNDING: South Carolina Center for Rural and Primary Healthcare, National Institute on Drug Abuse, and National Library of Medicine.

Implementation of a mobile health clinic framework for Hepatitis C virus screening and treatment: a descriptive study.

Background: Although treatment for Hepatitis C Virus (HCV) is effective, individuals face access barriers. The utility of mobile health clinics (MHC), effective mechanisms for providing healthcare to underserved populations, is understudied for HCV-related interventions. We aimed to describe implementation of, and factors associated with, screening and treatment via MHCs. Methods: Clemson Rural Health implemented a novel MHC program to reach and treat populations at-risk for HCV with a focus on care for uninsured individuals. We examined HCV screening and treatment initiation/completion indicators between May 2021 and January 2023. Findings: Among 607 individuals screened across 31 locations, 94 (15.5%) tested positive via antibody and viral load testing. Treatment initiation and completion rates were 49.6% and 86.0%, respectively. Among those screened, the majority were male (57.5%), White (61.3%; Black/Hispanic: 28.2%/7.7%), and without personal vehicle as primary transportation mode (54.4%). Injection drug use (IDU) was 27.2% and uninsured rate was 42.8%. Compared to HCV-negative, those infected included more individuals aged 30-44 (52.1% vs. 36.4%, p = 0.023), male (70.2% vs. 55.2%, p = 0.009), White (78.5% vs. 60.2%, p < 0.0001), without personal vehicle (58.5% vs. 43.5%, p = 0.028), IDU (83.7% vs. 21.0%, p < 0.0001), and uninsured (61.2% vs. 48.8%, p = 0.050). Uninsured rates were higher among those initiating compared to not initiating treatment (74.5% vs. 45.3%, p = 0.004). Interpretation: The MHC framework successfully reaching its target population: at-risk individuals with access barriers to healthcare. The high HCV screening and treatment initiation/completion rates demonstrate the utility of MHCs as effective and acceptable intervention settings among historically difficult-to-treat populations. Funding: Gilead Sciences, Inc., and SC Center for Rural and Primary Healthcare.