Factors associated with non-attendance at pediatric subspecialty asthma clinics.
BACKGROUND
Children with Medicaid insurance are less likely to receive subspecialty asthma care than non-Medicaid patients. However, it is not clear if such disparities are due to non-attendance at scheduled visits by patients.


OBJECTIVE
To determine factors associated with non-attendance at scheduled visits for pediatric subspecialty asthma care.


METHODS
We conducted a cross-sectional study of children with scheduled visits at three asthma clinics during a 12-month period. Our outcome of interest was patient non-attendance for a scheduled visit, controlling for age, gender, new patient status, type of insurance, severity of illness, distance to clinic, clinic site, month, and weekday of scheduled visit. We used logistic regression for multivariate comparisons and controlled for clustering effects for children with multiple scheduled visits.


RESULTS
There were 1236 scheduled visits for 857 unique patients. Median age: 7 years (IQR 3-11); median distance traveled: 24 miles (IQR 13-41); 20% had Medicaid insurance. The non-attendance rate was 8%. In multivariate analysis, Medicaid insurance (OR 2.33, 95% CI 1.45-3.74) and visits scheduled in September-December (3.26, 2.08-5.11) were associated with non-attendance.


CONCLUSIONS
Children with Medicaid insurance are less likely to attend scheduled visits for subspecialty asthma care, controlling for seasonal variation. Programs designed to address disparities in pediatric asthma outcomes regarding subspecialist care may improve their effectiveness by addressing barriers to attendance and anticipating poor attendance in the fall season.
Yoon
Esther Y
EY
Division of General Pediatrics, University of Michigan, Ann Arbor, Michigan 48109-0456, USA. est@med.umich.edu
Davis
Matthew M
MM
Van Cleave
Jeanne
J
Maheshwari
Sudha
S
Cabana
Michael D
MD
D001071:Appointments and Schedules; D001249:Asthma / Q000453:epidemiology*; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008484:Medicaid / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D010352:Patient Dropouts / Q000706:statistics & numerical data*; D010372:Pediatrics / Q000706:statistics & numerical data*; D012307:Risk Factors; D012621:Seasons; D013038:Specialization / Q000706:statistics & numerical data*; D014481:United States