Autism spectrum disorder/Takiwātanga: An Integrated Data Infrastructure-based approach to autism spectrum disorder research in New Zealand. (November 2020)

• Record Type: Journal Article
• Authors: Bowden, Nicholas; Thabrew, Hiran; Kokaua, Jesse; Audas, Richard; Milne, Barry; Smiler, Kirsten; Stace, Hilary; Taylor, Barry; Gibb, Sheree
• Is Part Of: Autism. Volume 24:Number 8(2020)
• Page Start: 2213
• Page End: 2227
• Publication Date: 2020-11
• Subjects: autism spectrum disorder -- big data -- case identification -- Integrated Data Infrastructure -- mental health; Autism -- Periodicals; Autism in children -- Periodicals; 616.85882005
• DOI: 10.1177/1362361320939329
• Languages: English
• ISSNs: 1362-3613

Abstract

New Zealand has few estimates of the prevalence of autism spectrum disorder and no national registry. The use of administrative data sources is expanding and could be useful in autism spectrum disorder research. However, the extent to which autism spectrum disorder can be captured in these data sources is unknown. In this study, we utilised three linked administrative health data sources from the Integrated Data Infrastructure to identify cases of autism spectrum disorder among New Zealand children and young people. We then investigated the extent to which a range of mental health, neurodevelopmental and related problems co-occur with autism spectrum disorder. In total, 9555 unique individuals aged 0–24 with autism spectrum disorder were identified. The identification rate for 8-year-olds was 1 in 102. Co-occurring mental health or related problems were noted in 68% of the autism spectrum disorder group. The most common co-occurring conditions were intellectual disability, disruptive behaviours and emotional problems. Although data from the Integrated Data Infrastructure may currently undercount cases of autism spectrum disorder, they could be useful for monitoring service and treatment-related trends, types of co-occurring conditions and for examining social outcomes. With further refinement, the Integrated Data Infrastructure could prove valuable for informing the national incidence and prevalence of autism spectrum disorder and the long-term effectiveness of clinical guidelines and interventions for this group. Lay abstract: New Zealand has few estimates of the prevalence autism spectrum disorder and no national registry or data set to identify and track cases. This hinders the ability to make informed, evidence-based decisions relating to autism spectrum disorder. In this study, we utilised linked health and non-health data to develop a method for identifying cases of autism spectrum disorder among children and young people in New Zealand. In addition, we examined rates of co-occurring mental health, neurodevelopmental and related conditions among this cohort and compared these to the general population. The method identified almost 10, 000 children and young people with autism spectrum disorder in New Zealand. Co-occurring mental health or related problems were found in over 68% of this group (nearly seven times higher than the general population), and around half were identified with multiple co-occurring conditions. The most frequently identified conditions were intellectual disability, disruptive behaviours and emotional problems. We have developed a useful method for monitoring service and treatment-related trends, number and types of co-occurring conditions and examining social outcomes among individuals with autism spectrum disorder. While the method may underestimate the prevalence of autism spectrum disorder in New Zealand, it provides a significant step towards establishing a more comprehensive evidence base to inform autism spectrum disorder–related policy.