Abstract / Summary
Background: Despite the benefits of the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), many eligible children remain unenrolled.
Objective: This study evaluated responses to an electronic health record (EHR)-embedded federal nutrition program (FNP) participation screening and WIC referral tool implemented within 8 clinics during well-child visits for children younger than 5 years of age.
Methods: Structured EHR data from July 2020 to October 2023 were extracted to summarize screening, referral acceptance, WIC enrollment outcomes, and patient demographics. Multivariable logistic regression was used to examine patient-level predictors of WIC nonenrollment at the first screening, referral acceptance, and enrollment among those accepting a referral, with analyses stratified by clinic type.
Results: Among 5385 children, 51.8% (n=2785) were newborn-aged, 36.6% (n=1969) were Hispanic, and 87.8% (n=4726) were Medicaid-insured. The mean age at the initial screening was 10.7 (SD 14.2) months. Among screened patients (n=3606), 34% (n=1235) were not enrolled in WIC at the first screening. Medicaid coverage, an academic clinic setting, non-Hispanic Black or Hispanic race, and ethnicity were associated with lower odds of WIC nonenrollment. Among those not enrolled with a documented response to referral (n=819), 59% (n=488) accepted the referral. Acceptance was higher among non-Hispanic Black and Hispanic patients, newborn-aged patients, those with Medicaid coverage, and those seen in academic clinics. Among referral acceptors with follow-up (n=438), 61% (n=265) were enrolled at the last screening, with higher odds among newborn-aged patients and those in academic clinics.
Conclusions: An EHR-based automated intervention can facilitate screening and referral to WIC. WIC participation at the first screening, referral acceptance, and enrollment after referral varied by sociodemographic characteristics, suggesting opportunities to improve equitable access through health care system-based approaches.