Abstract
Autism is associated with a range of costs. This paper reviews the literature on estimating the economic costs of autism spectrum disorder (ASD). More or less 50 papers covering multiple countries (US, UK, Australia, Canada, Sweden, the Netherlands, etc.) were analysed. Six types of costs are discussed in depth: (i) medical and healthcare service costs, (ii) therapeutic costs, (iii) (special) education costs, (iv) costs of production loss for adults with ASD, (v) costs of informal care and lost productivity for family/caregivers, and (vi) costs of accommodation, respite care, and out-of-pocket expenses. A general finding is that individuals with ASD and families with children with ASD have higher costs. Education costs appear to be a major cost component for parents with children with ASD.
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Notes
Alternatively, one could opt to include the individual diagnostic labels [autistic disorder, childhood disintegrative disorder, pervasive developmental disorder-not otherwise specified (PDD-NOS), and Asperger syndrome] in the search process.
In the transformation of the cost figures, reported cost figures were first inflated to the year 2018. Subsequently, inflated cost figures were all converted to US $ thereby adopting the conversion rate as on 1 January 2018 (£1.00 = $1.3491 US, €1.00 = $1.20 US, $1.00 Canadian = $0.800961 US, $1.00 Australian = $0.788955 US).
For North America, Payakachat et al. (2018) found an increase in the use of treatment services for individuals with ASD, with the top three of the most frequently received services including speech therapy (67%), occupational therapy (50%) and behavioural therapies/services (28%) such as ABA, Lovaas therapy, (Early Start) Denver Model, and Discrete Trial Training (DTT).
In a sensitivity analysis carried out to address uncertainty and lack of good evidence for IBI efficacy, Motiwala et al. (2006) also tested more optimistic and pessimistic efficacy rates for IBI. Based on these parameter settings, Motiwala et al. (2006) obtained estimates of savings that are lower than the figures reported by Chasson et al. (2007) (i.e., between 34.479 and 53.720 Canadian $ per individual vs. 208,500 US $ per child as in Chasson et al. 2007).
It is discussed in the literature (e.g., Garber and Phelps 1997) that ICERs can be useful as a decision rule in resource allocation particularly for making decision about (relatively new) intervention and/or therapy programmes that are costly but generate improved effects over time. ICERs can be compared with an a priori established cost-effectiveness threshold (i.e., willingness-to-pay value per unit of effect) in order to decide whether the new intervention is an efficient use of resources.
Amendah et al. (2011) found that residential schools are more common for children with ASD in Sweden compared to children with ASD in the US.
Lavelle et al. (2014) provided detailed estimations of ASD-related education costs by distinguishing between eleven mutually exclusive school placement categories for children with ASD based on type of school (public, private day, residential, home and other), type of classroom (special or general education) and age [preschool age (3- to 4-year olds) or school age (5- to 17-year olds)]. The (regression-based) analysis revealed large different estimates of education costs for children with ASD depending on the type of school placement category the child with ASD attended. Based on the cost estimates, Lavelle et al. (2014) concluded that education was the biggest cost category in the total cost for children with ASD.
It is important to note that Ganz (2007) assumed that the cost of lost productivity for individuals with ASD and additional learning disabilities was assumed to be zero. The authors emphasized that this cost figure of zero did not correspond to the real cost figure but was merely due to a lack of available information.
Based on findings of previous studies, Järbrink and Knapp (2001) assumed that individuals with high functioning ASD work in low-skilled, low-paid jobs, often despite a high level of education. For this group, the cost of lost productivity was estimated based on gross wages according to the human capital method (Järbrink and Knapp 2001, p. 9).
Similar time loss figures were found by Järbrink (2007) for Sweden, with parents reporting that they spend on average 977 h per year on caring for their child with ASD.
In another cost estimation study for the UK, Knapp et al. (2009) reported similar percentages, i.e. a higher percentage of adults with ASD and intellectual disabilities living in supported living accommodation (7% vs. 5%), in residential care (52% vs. 16%), and in a hospital (6% vs. 0%) as compared to adults with ASD, yet, without intellectual disabilities (Knapp et al. 2009, p. 320).
Another possible reason for the cross-country differences in ASD-related costs are the differences in ethno-racial and demographical diversity across countries. For instance, Shattuck et al. (2012) provided empirical evidence which suggests the presence of racial and/or demographical disparities in access to health services across a wide range of health conditions and service systems.
With efficiency we refer to the link between inputs and outputs of ASD services (e.g., how do the resources invested in the organization and implementation of EIBI programmes relate to the number of young children with ASD effectively being able to enter in such programmes), whereas with effectiveness we refer to the link between the outputs and the outcomes of ASD services [e.g., how does the number of people being provided with the organized EIBI programme relate to the total number of dependency-free life years (DFLYs) generated by this programme].
A linear regression analysis revealed that the cross-state variation in the administrative prevalence of ASD relate to characteristics of the education and health system with the administrative prevalence of ASD being positively associated with education-related spending as well as the number of paediatricians and the number of school-based health centers in the state.
As a possible explanation for this higher cost figure, Cimera and Cowan (2009) pointed out that the proportion of individuals with ASD is small (0.55% in 2006) in the overall vocational rehabilitation population. Vocational rehabilitation counsellors might thus be unfamiliar with the ASD population and their unique needs. This could result in a ‘trial and error’ method of providing services” (Cimera and Cowan 2009, p. 298), which increases the cost of vocational rehabilitation.
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The search and the filtering of the papers for the review article was performed by JJ (under supervision and with help from NR). JJ performed the abstraction of the data from the papers. Both NR and JJ worked on the writing of the paper manuscript. JJ mainly worked on the writing of the first draft. NR considerably reworked this draft and designed the tables for the figure. The revision of the paper was done by NR.
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Rogge, N., Janssen, J. The Economic Costs of Autism Spectrum Disorder: A Literature Review. J Autism Dev Disord 49, 2873–2900 (2019). https://doi.org/10.1007/s10803-019-04014-z
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DOI: https://doi.org/10.1007/s10803-019-04014-z