26652
Delay of Diagnosis in ASD

Poster Presentation
Thursday, May 10, 2018: 5:30 PM-7:00 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
L. Verhoeven1, D. van Dijk2, P. van Deurzen3 and W. G. Staal4,5, (1)Dr Leo Kannerhuis, Doorwerth, Netherlands, (2)Research, Development & Innovation, Dr Leo Kannerhuis, Doorwerth, Netherlands, (3)Karakter, NIjmegen, Netherlands, (4)Radboud University Medical Center Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Nijmegen, Netherlands, (5)Institute for Brain and Cognition, Leiden University, Leiden, Netherlands
Background:

Timely diagnosis of autism spectrum disorders (ASD) is of major interest for public health, patients and caregivers. So far, the majority of studies have focused on age of ASD diagnosis. However, the diagnostic process is an important factor to consider when trying to establish an early age of diagnosis. The few studies on this subject indicate a rather long diagnostic process.

Objectives:

The present study emphasizes on the duration of the diagnostic process, the diagnostic delay. The studies aimed to assess the mean diagnostic delay as well as to identify factors associated with this potential delay (predictors).

Methods:

For this purpose a cohort study with retrospective data collection was conducted among a population of individuals with ASD who were referred for diagnosis or care to mental health care centers specialized in ASD in the Netherlands. A random sample of 814 individuals with ASD referred in the period between May 2013 – April 2014 was included.

Eight potential factors (predictors) that could influence the diagnostic process were assed: age at first contact with mental healthcare/welfare, age of ASD diagnosis, gender, intellectual disability, current psychiatric comorbidity, prior diagnosis, year of first contact with mental healthcare/welfare, and the amount of previous mental healthcare/welfare tracks.

Analysis regarding diagnostic delay included expression of the mean, median, and standard deviation and illustrated by a Kaplan Meier curve. Second, the relationships between diagnostic delay and the included predictors of delay were tested. Pearson correlation coefficients were conducted between diagnostic delay and our continuous predictors (number of mental healthcare/welfare tracks, age at first contact with mental healthcare/welfare, age of ASD diagnosis, and year of first contact with mental healthcare/welfare). Student’s t-test were conducted to asses potential differences in delay regarding the categorical predictors (gender, intellectual disability, the presence of prior diagnosis, and the presence of comorbid diagnosis). As a final step, a linear multiple regression analysis was performed including all predictors.

Results:

Results showed that diagnostic delay ranged from 0 to 366 months with a median of 19 months and a mean of 35.7 months (three years). Of all individuals with ASD, 25% received the ASD diagnosis within 2 months and the last 25 % ‘waited’ for longer than 4.2 years. A longer diagnostic delay was associated with several factors including a higher number of previous mental healthcare/welfare tracks, an earlier year of first contact with mental healthcare/welfare, an older age of ASD diagnosis, more prior diagnosis, and more comorbidity. Gender and intellectual disability were not related to diagnostic delay.

Conclusions:

Although findings indicated that the diagnostic delay for ASD has been reduced for individuals encountering welfare/mental health care in more recent years, the majority of individuals still show a considerable diagnostic delay. This observed diagnostic delay shows spacious room for improvement in the diagnostic process.