Assessing the validity of administrative health data for the identification of children and youth with autism spectrum disorder in Ontario

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

BACKGROUND

Few studies have estimated cumulative health care costs post-diagnosis for individuals with autism spectrum disorder (ASD).

OBJECTIVES

Using an incidence-based approach, the objective of this analysis was to estimate cumulative costs of ASD to the Ontario health care system of children and adolescents.

METHODS

Using administrative health records from Ontario, Canada's most populous province, a retrospective, population-based, incident cohort study of children and adolescents aged 0-19 years old diagnosed with ASD was undertaken to estimate cumulative health care costs of ASD to the health care system from 2010 to 2019. Cumulative health care costs in 2021 Canadian dollars (CAD) from diagnosis to death or end of observation period were estimated using a consistent estimator based on the inverse probability weighting technique. Cumulative health care costs (and respective 95% confidence intervals [CI]) were estimated for 1, 5 and 10 years post-diagnosis by sex, age group and health service.

RESULTS

In 2010, there were 2867 diagnosed cases of ASD; in 2019, the number of incident cases had risen to 6072. The first year (i.e., 1-year) post-diagnosis cost of ASD was $4710.18 CAD (95% CI 4560.28-4860.08); just under a third of costs were for physician services. Total cumulative 5- and 10-year discounted costs were $16,025.95 CAD (15,371.64-16,680.26) and $32,635.76 CAD (28,906.94-36,364.58), respectively. Mean costs were higher for females and older age groups.

CONCLUSIONS

These results suggest that costs of ASD are high in the year of diagnosis and then increase at a steady rate thereafter. This information will help with future resource planning within the health care sector to ensure individuals with ASD are supported once their diagnosis is established.

Neurological and psychiatric disorders among autistic adults: a population healthcare record study

BACKGROUND

Co-occurring psychiatric disorders are common in autism, with previous studies suggesting 54-94% of autistic individuals develop a mental health condition in their lifetime. Most studies have looked at clinically-recruited cohorts, or paediatric cohorts followed into adulthood, with less known about the autistic community at a population level. We therefore studied the prevalence of co-occurring psychiatric and neurological conditions in autistic individuals in a national sample.

METHODS

This retrospective case-control study utilised the SAIL Databank to examine anonymised whole population electronic health record data from 2001 to 2016 in Wales, UK (N = 3.6 million). We investigated the prevalence of co-occurring psychiatric and selected neurological diagnoses in autistic adults' records during the study period using International Classification of Diseases-10 and Read v2 clinical codes compared to general population controls matched for age, sex and deprivation.

RESULTS

All psychiatric conditions examined were more common amongst adults with autism after adjusting for age, sex and deprivation. Prevalence of attention-deficit hyperactivity disorder (7.00%), bipolar disorder (2.50%), obsessive-compulsive disorder (3.02%), psychosis (18.30%) and schizophrenia (5.20%) were markedly elevated in those with autism, with corresponding odds ratios 8.24-10.74 times the general population. Depression (25.90%) and anxiety (22.40%) were also more prevalent, with epilepsy 9.21 times more common in autism.

CONCLUSIONS

We found that a range of psychiatric conditions were more frequently recorded in autistic individuals. We add to understanding of under-reporting and diagnostic overshadowing in autism. With increasing awareness of autism, services should be cognisant of the psychiatric conditions that frequently co-occur in this population.

Accuracy of administrative database algorithms for autism spectrum disorder, attention-deficit/hyperactivity disorder and fetal alcohol spectrum disorder case ascertainment: a systematic review

INTRODUCTION

The purpose of this study was to perform a systematic review to assess the validity of administrative database algorithms used to identify cases of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) and fetal alcohol spectrum disorder (FASD).

METHODS

MEDLINE, Embase, Global Health and PsycInfo were searched for studies that validated algorithms for the identification of ASD, ADHD and FASD in administrative databases published between 1995 and 2021 in English or French. The grey literature and reference lists of included studies were also searched. Two reviewers independently screened the literature, extracted relevant information, conducted reporting quality, risk of bias and applicability assessments, and synthesized the evidence qualitatively. PROSPERO CRD42019146941.

RESULTS

Out of 48 articles assessed at full-text level, 14 were included in the review. No studies were found for FASD. Despite potential sources of bias and significant between-study heterogeneity, results suggested that increasing the number of ASD diagnostic codes required from a single data source increased specificity and positive predictive value at the expense of sensitivity. The best-performing algorithms for the identification of ASD were based on a combination of data sources, with physician claims database being the single best source. One study found that education data might improve the identification of ASD (i.e. higher sensitivity) in school-aged children when combined with physician claims data; however, additional studies including cases without ASD are required to fully evaluate the diagnostic accuracy of such algorithms. For ADHD, there was not enough information to assess the impact of number of diagnostic codes or additional data sources on algorithm accuracy.

CONCLUSION

There is some evidence to suggest that cases of ASD and ADHD can be identified using administrative data; however, studies that assessed the ability of algorithms to discriminate reliably between cases with and without the condition of interest were lacking. No evidence exists for FASD. Methodologically higher-quality studies are needed to understand the full potential of using administrative data for the identification of these conditions.

Evidence of increasing recorded diagnosis of autism spectrum disorders in Wales, UK: An e-cohort study

LAY ABSTRACT

Autism spectrum disorders (autism) are thought to be relatively common, with analyses estimating 1% in the population could meet diagnostic criteria. New services for adult diagnosis have been set up in Wales, UK; however, no studies have examined for the proportion of adults with autism in Wales. In this study, we take anonymised healthcare record data from more than 3.6 million people to produce a national estimate of recorded autism diagnoses. We found the overall prevalence rate of autism in healthcare records was 0.51%. The number of new-recorded cases of autism increased from 0.188 per 1000 person-years in 2001 to 0.644 per 1000 person-years in 2016. The estimate of 0.51% prevalence in the population is lower than suggested by population survey and cohort studies, but comparable to other administrative records. From 2001 to 2016, the number of autism services for adults has increased, and autism is more widely known in society, while concurrently in healthcare records, there was a >150% increase autism diagnoses in the years 2008-2016. An increasing number of diagnoses were among women and those aged over 35 years. This study suggests that while the number of people being diagnosed with autism is increasing, many are still unrecognised by healthcare services.

Premature mortality in a population-based cohort of autistic adults in Canada

Research from different countries suggests that autistic adults are more likely to die prematurely than non-autistic adults, but these studies do not always investigate male and female individuals separately and do not consider whether this pattern is unique to autistic people or is also an issue for people with other developmental disabilities. We examined premature mortality in autistic males and females (assigned at birth) in a population-based cohort, compared to males and females with and without other developmental disabilities. Using linked administrative health and social services population data from Ontario, Canada, age-matched males and females aged 19-65 years were followed between 2010 and 2016, and causes of death were determined. Over the 6-year observation period, 330 of 42,607 persons (0.77%) in the group without developmental disabilities had died compared to 259 of 10,646 persons (2.43%) in the autism group and 419 of 10,615 persons (3.95%) in the other developmental disabilities group. Autistic males and females were more likely to die than non-autistic males (adjusted risk ratio, RR 3.13, 95%CI 2.58-3.79) and non-autistic females (adjusted RR 3.12, 95%CI 2.35-4.13) without developmental disabilities, but were less likely to die than adults with other developmental disabilities (males: adjusted RR 0.66, 95%CI 0.55-0.79; females: adjusted RR 0.55, 95%CI 0.43-0.71). Most common causes of death varied depending on a person's sex and diagnosis. Given the greater likelihood of premature mortality in adults with developmental disabilities including autism, greater attention and resources directed toward their health and social care are needed, tailored to their sex and diagnosis-informed needs. LAY SUMMARY: This study looked at how many autistic men and women died over 6 years (2010-2016), along with how they died, and compared this to adults who did not have autism living in Ontario, Canada. It found that autistic men and women were more than three times as likely to die as people of the same age who did not have a developmental disability. However, adults with other developmental disabilities besides autism were even more likely to die than autistic adults. This means that we have to pay more attention and invest in better social and health care for autistic people, along with people who have other types of developmental disabilities.

Assessing the validity of administrative health data for the identification of children and youth with autism spectrum disorder in Ontario

Population‐level identification of children and youth with ASD is essential for surveillance and planning for required services. The objective of this study was to develop and validate an algorithm for the identification of children and youth with ASD using administrative health data. In this retrospective validation study, we linked an electronic medical record (EMR)‐based reference standard, consisting 10,000 individuals aged 1–24 years, including 112 confirmed ASD cases to Ontario administrative health data, for the testing of multiple case‐finding algorithms. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and corresponding 95% confidence intervals (CI) were calculated for each algorithm. The optimal algorithm was validated in three external cohorts representing family practice, education, and specialized clinical settings. The optimal algorithm included an ASD diagnostic code for a single hospital discharge or emergency department visit or outpatient surgery, or three ASD physician billing codes in 3 years. This algorithm's sensitivity was 50.0% (95%CI 40.7–88.7%), specificity 99.6% (99.4–99.7), PPV 56.6% (46.8–66.3), and NPV 99.4% (99.3–99.6). The results of this study illustrate limitations and need for cautious interpretation when using administrative health data alone for the identification of children and youth with ASD.

Lay Summary

We tested algorithms (set of rules) to identify young people with ASD using routinely collected administrative health data. Even the best algorithm misses more than half of those in Ontario with ASD. To understand this better, we tested how well the algorithm worked in different settings (family practice, education, and specialized clinics). The identification of individuals with ASD at a population level is essential for planning for support services and the allocation of resources. Autism Res 2021, 14: 1037–1045. © 2021 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC.