Abstract
Objective: Missed patient appointments have a substantial negative impact on patient care, child health and well-being, and clinic functioning. This study aims to identify health system interface and child/family demographic characteristics as potential predictors of appointment attendance in a pediatric outpatient neuropsychology clinic. Method: Pediatric patients (N = 6,976 across 13,362 scheduled appointments) who attended versus missed scheduled appointments at a large, urban assessment clinic were compared on a broad array of factors extracted from the medical record, and the cumulative impact of significant risk factors was examined. Results: In the final multivariate logistic regression model, health system interface factors that significantly predicted more missed appointments included a higher percentage of previous missed appointments within the broader medical center, missing pre-visit intake paperwork, assessment/testing appointment type, and visit timing relative to the COVID-19 pandemic (i.e. more missed appointments prior to the pandemic). Demographic characteristics that significantly predicted more missed appointments in the final model included Medicaid (medical assistance) insurance and greater neighborhood disadvantage per the Area Deprivation Index (ADI). Waitlist length, referral source, season, format (telehealth vs. in-person), need for interpreter, language, and age were not predictive of appointment attendance. Taken together, 7.75% of patients with zero risk factors missed their appointment, while 22.30% of patients with five risk factors missed their appointment. Conclusions: Pediatric neuropsychology clinics have a unique array of factors that impact successful attendance, and identification of these factors can help inform policies, clinic procedures, and strategies to decrease barriers, and thus increase appointment attendance, in similar settings.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 As expected, patients’ race/ethnicity was strongly associated with indicators of socioeconomic disparities between our two largest groups (e.g., White families lived in areas with significantly more neighborhood advantage than Black families; White families were approximately three times more likely than Black families to have commercial insurance), and this disparity is consistent with considerable prior literature on health and racial inequities in the United States. Given this substantial overlap, and consistent with prior research (Dennis et al., Citation2022; Taylor et al., Citation2020), we opted to omit patients’ race/ethnicity in inferential analyses. It is important to note, however, that understanding race-related experiences that contribute to missed appointments (e.g., distrust of medical systems given prior exploitation and medical discrimination, e.g., Brandon et al., Citation2005; Wells & Gowda, Citation2020) is critically important, and future studies that can directly explore patient experiences are needed.