Estimating Cumulative Health Care Costs of Childhood and Adolescence Autism Spectrum Disorder in Ontario, Canada: A Population-Based Incident Cohort Study

We undertook a retrospective, population-based, incident cohort study of children and adolescents aged 0–19 years old diagnosed with ASD to estimate total cumulative health care costs to the health care system, using data from Ontario, Canada’s most populous province (2019 population 14.6 million).

We employed health records obtained through the administration of Ontario’s health insurance system and made available at ICES, an independent, non-profit research institute in Toronto, Ontario. The ICES data repository contains individual-level linkable and longitudinal data on most publicly funded health care services for all legal residents of Ontario. The following health services databases were used in this analysis: Discharge Abstract Database, Ontario Mental Health Reporting System, Continuing Care Reporting System, National Rehabilitation Reporting System, National Ambulatory Care Reporting System, Ontario Health Insurance Plan claims database, Ontario Drug Benefit Program database, and Home Care Database. In addition, the Registered Persons Database, a population-based registry, which contains data on individuals who contacted the health care system, was used to obtain patients’ date of birth, sex, eligibility for universal health care and status changes, and postal code of residence, while the 2011 and 2016 Census data were employed to obtain neighbourhood-level data, such as household income expressed in quintiles, and level of rurality of residence. A full description of each database can be found in Appendix Table A1 (see electronic supplementary material [ESM]). All databases were linked using unique encoded identifiers and analysed at ICES, in compliance with Ontario privacy legislation. The use of these data was authorised under section 45 of Ontario’s Personal Health Information Protection Act, which does not require review by a Research Ethics Board.

All children and adolescents (ages 0–19 years old) with a valid health card number, residing in Ontario and diagnosed with ASD were included in the analysis. This age range was chosen based on a meta-analysis, which found a mean age at diagnosis of 60.48 months (i.e., 5 years) (95% CI 50.12–70.83) with a range of 30.90–234.57 months (i.e., 2.6–19.5 years old) [6]. To identify all incident cases of children and adolescents with ASD, a previously validated algorithm [7] was employed, where individuals were selected into the cohort if they had an ASD diagnostic code (ICD-9 code 299.x/ICD-10 code F84.x [autism, atypical autism, Asperger’s syndrome, other pervasive developmental disorders, pervasive developmental disorders unspecified], any diagnosis) for a single hospital discharge, emergency department visit or outpatient surgery, or three ASD physician billing codes (ICD-9 code 299 – child psychoses) within 3 years since birth. To ensure an incident cohort was obtained, all health records for each individual since database inception or date of birth, whichever came first when looking back, were examined. Incident cases were estimated from 2010 to 2019, for the total sample and by sex.

Incident cases of children and adolescents with ASD were characterised in terms of their socio-demographic characteristics—sex, age, neighbourhood income quintile and rural residence—and presence of chronic physical, mental and behavioural health conditions and intellectual disabilities common among children and adolescents with and without ASD—asthma, cancer, diabetes mellitus, ADHD, mood and/or anxiety disorders, learning and developmental disorders, Down syndrome, and Prader-Willi syndrome—ascertained either through disease registries (the Pediatric Oncology Group of Ontario Networked Information System and the Ontario Cancer Registry), validated algorithms or algorithms defined elsewhere [8‐13].

The number of days alive (and eligible for public health insurance) were estimated from diagnosis until the end of the observation period (i.e., December 31, 2020) for each child/adolescent. The sample was then divided into two groups: (i) censored (i.e., those who were alive during the entire observation period and whose death was not observed) and (ii) non-censored (i.e., those who died, moved out of the province, or who lost eligibility for public health insurance before the end of the observation period and for whom death or end of observation window was observed). See Appendix Table A3 in the ESM for the number of censored and non-censored groups of patients each year.

A costing algorithm was used to estimate total direct patient-level health care costs of children and adolescents with ASD borne by the public third-party payers, the Ontario Ministries of Health and Long-term Care [14]. The algorithm’s costing methodology uses a bottom-up/micro-costing approach to cost services at the patient level, which identifies individual episodes of care or utilisation in the health care system and respective prices, or costs paid. Given Ontario’s public health insurance system, providers in a private marketplace rarely set prices; therefore, costs or amounts paid by the third-party payer were used. Where individual unit costs were not available (e.g., long-term care), a top-down approach, which allocates corporate aggregate costs to individual visits or cases/episodes of care, was employed. For hospital/institution-based care, such as hospitalisations and emergency departments, a measure of utilisation (which accounts for resource intensity using appropriate weights) was multiplied by a unit cost (e.g., cost per standard hospital stay, cost per Comprehensive Ambulatory Classification System weighted case). For other services, such as physician visits and outpatient prescription drugs, utilisation (i.e., number of visits, units) was multiplied by a unit cost (i.e., fee paid) obtained from Ontario Health Insurance Plan and Ontario Drug Benefit Program claims data, respectively, while for home care, utilisation was multiplied by a unit cost (i.e., cost per visit) obtained from the Ontario Ministry of Health [14]. Costs captured by the algorithm account for over 90% of all government-paid health care services, given the availability of relevant databases at ICES, and include costs directly related to ASD as well as other non-ASD related costs [14]. Further details on the costing methodology can be found elsewhere [14]. Costs were categorised into several health service categories—psychiatric hospitalisations, medical hospitalisations, other hospital/institution-based care (i.e., complex continuing care, inpatient rehabilitation and long-term care), hospital outpatient clinic visits, emergency department visits, other ambulatory care (i.e., same-day surgery, dialysis clinic visits and cancer clinic visits), physician services, outpatient prescription drug covered under the public provincial drug plan and home care—and reported in 2021 Canadian dollars (CAD, where 1 CAD = 0.7978 USD in 2021).

One way to estimate mean cumulative health care costs when censoring is present is to reweight each case so that it represents not only itself but also some number of incomplete/censored cases [15]. Several estimators have been proposed to estimate cumulative mean health care costs [15]. Bang and Tsiatis proposed a consistent estimator based on the inverse probability weighting technique, which can be used to estimate cumulative costs [16]. The total cost of children and adolescents who died or were lost to attrition and those with complete cost information during the analysis period was weighted by one over the Kaplan-Meier (i.e., 1/KM) survival probability estimator, with reverse censoring (where deaths/attritors are denoted as 0 and censored cases as 1). The weighted costs were then summed and divided by the total study sample size to determine the mean total cost estimate in the presence of censoring. However, when the patient’s cost history is available, the Bang and Tsiatis estimator is not efficient since it does not use the cost information from censored observations. A more efficient (but also consistent) estimator is the one proposed by Zhao and Tian [17]. Given that we are estimating costs of children and adolescents, who typically do not have a long history of health care costs, and among whom death is rare, the estimator proposed by Zhao and Tian did not seem appropriate. Therefore, cumulative health care costs from diagnosis to death or end of observation period were estimated using the Bang and Tsiatis estimator, which employed data on observation time and health care costs incurred by the public third-party payers. Total mean cumulative health care costs for the first year after diagnosis, including date of diagnosis (i.e., 1-year costs), and respective 95% confidence intervals (CIs) were estimated for the full sample as well as by health service, sex and age group at diagnosis. In addition, total mean cumulative health care costs, undiscounted and discounted at 1.5% (in line with the Canadian Agency for Drugs and Technologies in Health recommendations [18]), were estimated for the 5- and 10-year periods, for the full sample, by sex and by age group at diagnosis. As a sensitivity analysis, we also estimated cumulative costs using the Zhao and Tian estimator as well as cumulative costs for the fully observed observations to assess the robustness of our findings.

In 2010, there were 2867 diagnosed cases of ASD; in 2019, the number of incident cases had risen to 6072, a 2-fold increase (see Appendix Table A2 in the ESM). There were substantially more males diagnosed with ASD (76%–81%) than females (19%–24%) for all years; however, while the number of males doubled from 2010 to 2019 (from 2329 to 4648), it more than doubled for females (538 to 1424).The mean age at diagnosis was 6.93, with about two-fifths (40.6%) of the sample diagnosed between the ages of 4 and 8 (Table 1). For females, the mean follow-up time (in days) was 1850.75, while for males it was 1936.85. There were slightly more children and adolescents in the lowest neighbourhood income quintile (24.4%); most children and adolescents with ASD lived in urban settings (94.6%). Regarding clinical characteristics, a large percentage of children and adolescents with ASD had mood and/or anxiety disorders (46.4%) and learning and developmental disorders (40.6%) at diagnosis; 19.4% had asthma. Males and females did not look different on socio-demographic and clinical characteristics, as evidenced by the standardised mean difference (SMD) ≤0.10, except for age at diagnosis where females were slightly older than males (7.32 vs 6.82, respectively; SMD = 0.11).

Mean cumulative health care costs for children and adolescents with ASD in the first year post-diagnosis was $4710.18 CAD (95% CI 4560.28–4860.08) (Table 2). Costs of physician services made up the largest proportion of total costs in the first year post-diagnosis (30%); other relevant costs included those for hospitalisations (17.9% and 15.4% for psychiatric and medical hospitalisations, respectively). The top diagnoses for psychiatric and medical hospitalisations included ASD, adjustment disorders and ADHD, and cancer treatment, epilepsy and pneumonia, respectively (not shown). Females had higher health care costs than males, overall ($6271.62 CAD [95% CI 5825.72–6717.52] vs $4281.40 CAD [95% CI 4135.06–4427.74]) and for most cost categories. Mean health care costs also differed by age group at diagnosis, with older individuals incurring higher costs (e.g., $10,975.24 CAD [95% CI 8905.29–13,045.20] for those aged 18–19 years vs $3169.43 CAD [95% CI 2985.55–3353.32] for 0- to 3-year-olds) (Table 3). For several health services, such as psychiatric hospitalisations, other hospital/institution-based care, physician services and outpatient prescription drugs, mean cumulative health care costs also increased with age at diagnosis.

Total mean cumulative 5- and 10-year discounted costs were $16,025.95 CAD (95% CI 15,371.64–16,680.26) and $32,635.76 CAD (95% CI 28,906.94–36,364.58), respectively (Table 4); 10-year costs were roughly two times the amount of 5-year costs, suggesting that, after the first year of diagnosis, cumulative costs increased at a constant rate. Cumulative costs were almost 50% higher for females than males for both 5 and 10 years ($21,090.61 CAD [95% CI 19,192.38–22,988.85] and $44,227.73 CAD [95% CI 35,964.85–52,490.61] vs $14,735.91 CAD [95% CI 14,073.66–15,398.17] and $29,881.73 CAD [95% CI 25,713.65–34,049.81]). Moreover, mean cumulative costs increased with age at diagnosis, where 18- to 19-year-olds had total mean cumulative 5- and 10-year discounted costs of $33,620.30 CAD (95% CI 25,838.98–41,401.63) and $65,419.36 CAD (95% CI 33,875.40–96,963.32), while 0- to 3-year-olds had total cumulative 5- and 10-year discounted costs of $11,410.36 CAD (95% CI 10,668.92–12,151.80) and $23,413.14 CAD (95% CI 18,902.54–27,923.74), respectively (Table 5). In the sensitivity analysis, it was found that the estimates of cumulative costs using the Zhao and Tian estimator and for the fully observed sample did not differ substantially from those obtained in the main analysis (though the latter values were more similar)—5-year discounted costs of $15,394.39 CAD (95% CI 14,875.11–15,913.66) and $15,963.32 CAD (95% CI 15,305.56–16,621.08) and 10-year discounted costs of $27,976.72 CAD (95% CI 27,129.99–28,823.44) and $32,938.07 CAD (95% CI 29,069.42–36,806.72), respectively (see Appendix Table A4 in the ESM for discounted costs by sex).

Nonetheless, this study has some limitations. We were unable to include the costs of mental health care provided in community-based agencies; these data are not currently available for research purposes at ICES, the data provider. Thus, our cost estimates are likely an underestimate of the total cumulative costs incurred by children and adolescents with ASD, though these costs are likely a small portion of the overall burden to the health care system. Previous work has estimated lifetime costs. We estimated 10-year cumulative costs for incident cases between the ages of 0 and 19 years. After 10 years, these individuals were between the ages of 10 and 29 years and thus our 10-year cumulative cost estimates represent cumulative costs incurred from childhood to early adulthood, which are only a fraction of an individual’s lifetime. Future work should seek to follow incident cases of ASD over a longer period of time to obtain cumulative costs of longer duration. Moreover, other relevant costs of caring for individuals with ASD include therapeutic costs, (special) education costs, costs of lost productivity for adults with ASD, costs of informal care and lost productivity for family/caregivers, costs of accommodation and respite care, and out-of-pocket expenses. Future research should also consider estimating the cumulative costs of these components. Finally, while determining the costs associated with ASD is important, determining the incremental costs of ASD is also an important avenue of future research. Notwithstanding, these estimates will still be relevant for decision makers who require this information for resource allocation purposes as well as researchers undertaking ASD-related economic evaluations.