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J Dev Behav Pediatr. 2012 Nov-Dec;33(9):685-97. doi: 10.1097/DBP.0b013e31826c66ef.

Determinants of appointment absenteeism at an outpatient pediatric autism clinic.

Author information

1
Center for Autism and Related Disorders, Kennedy Krieger Institute, Baltimore, MD, USA. kalb@kennedykrieger.org

Abstract

OBJECTIVE:

Two widely discussed yet highly understudied factors that obstruct timely diagnosis and intervention among children with an autism spectrum disorder (ASD) are missed scheduled appointments and wait time for outpatient services. Research surrounding outpatient appointment no-show and cancellation rates as well as predictors of such would shed light on the barriers to community-based clinical care.

METHODS:

In this study, data from 8049 children and adolescents (mean = 6.97 years, SD = 4.81) with scheduled appointments at a multidisciplinary pediatric outpatient autism center were examined. A total of 43,504 appointments, scheduled between June 2003 and April 2012, were analyzed. Random and fixed effects multinomial logistic regression models were employed to explore the child-, clinician-, and appointment-related determinants of no-show and cancellation for initial and follow-up appointments.

RESULTS:

A no-show rate of 9% and 15%, and a cancellation rate of 11% and 10% was observed for initial (n = 8049) and follow-up (n = 35,455) appointments, respectively. Different predictors were found for both no-show and cancellation at the initial and follow-up appointments. In the multivariate analyses, the most consistent and robust predictors of no-show were African-American child race, medical assistance, provider type and appointment type, and evening appointments. For cancellation, these included increased wait time and provider type. Importantly, cancellation and no-show at the initial evaluation increased the risk for these same outcomes at follow-up.

CONCLUSION:

As ASD prevalence figures continue to increase in the United States, findings surrounding wait time, appointment absenteeism, and clinical models of care are important to improving public health.

PMID:
23095496
DOI:
10.1097/DBP.0b013e31826c66ef
[Indexed for MEDLINE]
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