Background/Objectives: This retrospective cohort study compared well-child visits (WCVs) and immunization encounters from birth to age three among rural and urban South Carolina (SC) Medicaid-enrolled children with neonatal opioid withdrawal syndrome (NOWS). Methods: We applied logistic and Poisson regression models to examine associations between rural status and the number of WCVs, WCV adherence, and immunization encounters. Results: The sample included 833 urban and 161 rural children with NOWS born between 2006 and 2014. Significant differences existed between groups in the number of WCVs and immunization encounters each year from birth to age three (p = < 0.01 for all the comparisons). After covariate adjustment, rural compared to urban status was associated with decreased WCVs from birth to 11 months (incidence rate ratio (IRR): 0.85; 95% CI: 0.77–0.93) and 12 to 23 months (IRR: 0.80; 95% CI: 0.69–0.93). Rural status was not significantly associated with decreased WCVs from 24 to 35 months (IRR: 0.81; 95% CI: 0.63–1.03). Rural compared to urban status was associated with a 34% lower odds of WCV adherence from 12 to 23 months (odds ratio (OR): 0.66; 95% CI: 0.44–0.99). Furthermore, rural compared to urban status was associated with decreased immunization encounters from birth to 11 months (IRR: 0.60; 95% CI: 0.52–0.69), 12 to 23 months (IRR: 0.61; 95% CI: 0.50–0.71), and 24 to 35 months (IRR: 0.55; 95% CI: 0.40–0.76). Conclusions: Rurality was associated with decreased WCVs and immunization encounters among children with a history of NOWS residing in SC. Policy interventions, including telehealth services and expanded Medicaid access, could improve WCV and immunization rates among these children.

Background: To predict areas with a high concentration of long-term uninsured (LTU) and Emergency Department (ED) usage by uninsured patients in South Carolina. Methods: American Community Survey data was used to predict the concentration of LTU at the ZIP Code Tabulation Area (ZCTA) level. In a multivariate regression model, the LTU concentration was then modeled to predict ED visits by uninsured patients. ED data came from the restricted South Carolina Patient Encounter data with patients’ billing zip codes. A simulation was conducted to predict changes in the ED visit numbers and rates by uninsured patients if the LTU concentration was reduced to a lower level. Results: Overall, there was a positive relationship between ED visit rates by the uninsured patients and areas with higher concentrations of LTU. Our simulation model predicted that if the LTU concentration for each ZCTA was reduced to the lowest quintile, the ED visit rates by the uninsured would decrease significantly. The greatest reduction in the number of ED visits by the uninsured over a two-year period was for the following primary diagnoses: abdominal pain (15,751 visits), cellulitis and abscess (11,260 visits) and diseases for the teeth and supporting structures (10,525 visits). Conclusions: The provision of primary healthcare services to the LTU could help cut back inappropriate uses of ED resources and healthcare costs.