Socioeconomic disparities are negatively associated with pediatric emergency department aftercare compliance.
OBJECTIVE
This study sought to identify demographic, socioeconomic, and clinical predictors of aftercare noncompliance by pediatric emergency department (ED) patients.


METHODS
The authors conducted a prospective, observational study of pediatric patients presenting to a university teaching hospital ED from July 1, 2002, through August 31, 2002. Demographic and clinical information was obtained from guardians during the ED visit. Guardians were contacted after discharge to determine compliance with ED aftercare instructions. Subjects were excluded if they were admitted or if guardians were unavailable or unwilling to consent. Data were analyzed using multivariable logistic regression to identify predictors of noncompliance from a list of predetermined variables.


RESULTS
Of the 409 patients enrolled in the study, 111 were prescribed medications and 364 were given specific follow-up instructions. Subtypes of the variable "insurance status" were significantly associated with medication noncompliance in multivariable regression analysis. "Insurance status" and "low-acuity discharge diagnoses" were significantly associated with follow-up noncompliance.


CONCLUSIONS
Disparity in health insurance has been shown to be a predictor of poor aftercare compliance for pediatric ED patients within the patient population.
Wang
N Ewen
NE
Division of Emergency Medicine, Stanford University School of Medicine, Palo Alto, CA 94304, USA. ewen@stanford.edu
Gisondi
Michael A
MA
Golzari
Mana
M
van der Vlugt
Theresa M
TM
Tuuli
Methodius
M
D000293:Adolescent; D000328:Adult; D000359:Aftercare / Q000706:statistics & numerical data*; D002140:California; D017028:Caregivers; D002648:Child; D002675:Child, Preschool; D004522:Educational Status; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007348:Insurance, Health; D016015:Logistic Models; D008297:Male; D011446:Prospective Studies; D012923:Social Class; D016312:Treatment Refusal / Q000706:statistics & numerical data*