Abstract Objective To describe the age-specific and lifetime incremental societal costs of autism in the United States. Design Estimates of use and costs of direct medical and nonmedical care were obtained from a literature review and database analysis. A human capital approach was used to estimate lost productivity. These costs were projected across the life span, and discounted incremental age-specific costs were computed. Setting United States. Participants Hypothetical incident autism cohort born in 2000 and diagnosed in 2003. Main Outcome Measures Discounted per capita incremental societal costs. Results The lifetime per capita incremental societal cost of autism is $3.2 million. Lost productivity and adult care are the largest components of costs. The distribution of costs over the life span varies by cost category. Conclusions Although autism is typically thought of as a disorder of childhood, its costs can be felt well into adulthood. The substantial costs resulting from adult care and lost productivity of both individuals with autism and their parents have important implications for those aging members of the baby boom generation approaching retirement, including large financial burdens affecting not only those families but also potentially society in general. These results may imply that physicians and other care professionals should consider recommending that parents of children with autism seek financial counseling to help plan for the transition into adulthood. Autism is a very expensive disorder costing our society upwards of $35 billion in direct (both medical and nonmedical) and indirect costs to care for all individuals diagnosed each year over their lifetimes.1 Given the financial and nonfinancial costs we face and given increasingly more options for treatment and possibly for prevention, information on the distribution of costs is needed to help us decide on how to best allocate scarce resources to support individuals with autism and their families. Because the complementary (or competing) treatment and prevention strategies currently available, or yet to be developed, vary in effectiveness or implementation costs, understanding how total costs due to autism are distributed across the life cycle is important to make better decisions. Relatively little is known about the societal costs of autism, in total and at different points across the life cycle. In earlier work, the per capita and total societal costs for individuals with autism were described.1 Although the per capita and societal costs were described overall and across 17 components of direct medical, direct nonmedical, and indirect costs, age-specific costs were not. Because certain categories are more relevant and more costly and because these costs are borne by different parties at different ages, presenting the age distribution of the costs of autism can provide policy makers information that is helpful for cost-utility analyses and for current and future resource planning activities. The focus of this study is to present estimates of the costs of autism along with some detail on how the estimates were constructed. Although no clinical data are presented, these data should be useful to health care professionals, families, and agencies in planning for future care, especially with respect to nonmedical costs. Methods A detailed description of the sources of data and computational methods used to compile the costs of autism has been presented elsewhere.1 Briefly, cross-sectional cost data from different age groups were used to create prevalence-based cost estimates that approximate incidence-based estimates (ie, those constructed by longitudinally tracking an incident cohort over time). A prevalence-based cohort, also known as a synthetic, or hypothetical, cohort,2 allows us to approximate the lifetime experiences of a single incident cohort by using the prevalence-based cost patterns as if they were observed longitudinally from an incident cohort. Although an incidence-based cost-of-illness approach is more appropriate because it captures the full experience of autism, including any comorbid conditions, formidable data requirements preclude it.3 The total costs of autism equal the sum of its direct and indirect costs. Direct costs measure the value of goods and services used and indirect costs measure the value of lost productivity due to autism. These direct and indirect costs represent the value of other activities that these resources could have purchased (ie, opportunity costs).4,5 Physician and other professional services, hospital and emergency department services, drugs, equipment and other supplies, and medically related travel and time costs are typical components of direct medical costs. Direct medical costs were obtained either from the literature or from an analysis of the Medical Expenditure Panel Survey (MEPS)6 and the National Health Interview Survey (NHIS).7 Special education, transportation, child care and babysitting, respite care, out-of-home placement, home and vehicle modifications, and supported employment services are typical components of direct nonmedical costs. Nonmedical costs were obtained from the literature. Multiple cost estimates within categories were averaged to obtain a single cost estimate for each category. Indirect costs are the value of lost or impaired work time (income), benefits, and household services of individuals with autism and their caregivers because of missed time at work, reduced work hours, switching to a lower-paying but more flexible job, or leaving the workforce. Indirect costs were computed using a human capital approach3,8 that combines average earnings, benefits, and household services with information on average work-life expectancies and labor force participation rates for men and women at different ages. In the analyses that follow, the incremental costs of autism are presented, which are defined as those additional costs that are due exclusively to autism. For example, costs due to use of medical services for periodic well-child preventive care or care related to the common cold are not considered herein because those costs are common to children with and without autism; however, costs specifically due to autism are considered herein. When incremental costs were not available or otherwise specifically presented in the source materials, they were computed by subtracting national average costs calculated from the MEPS from the costs reported in the source documents. For example, if a source document presented an average cost of $X for all children with autism and the national average for all children for that same category was $Y, then the incremental cost was computed as $(Y−X). Because of the broad impact of autism on families, insurers, taxpayers, and society and because of the considerable public autism funding, a societal perspective was used, as recommended by the Panel on Cost-effectiveness in Health and Medicine.8 The Harvard School of Public Health Human Subjects Committee had previously exempted this study from institutional approval. Direct costs Literature Review An in-depth targeted literature review concentrating on US-based studies was conducted to obtain data on use and costs. British and Canadian studies were also used when data were otherwise unavailable. Data on physician, outpatient, clinic services, dental care,9 prescription medications,9-11 complementary and alternative therapies,12-18 behavioral therapies,19-22 hospital and emergency services,9,23 allied health, equipment and supplies, home health,9 and medically related travel9 were classified as direct medical. Data on child care,9,19 adult care,19,20 respite and family care,9,19,20 home and care modifications,9,24 special education,19,20,25-27 supported employment,20,28-34 and other costs9,24 were classified as direct nonmedical. Although some dimensions of care may be misclassified between direct medical and direct nonmedical (for example, many special education programs provide behavioral therapies), because the degree of misclassification is not known, no corrections were made. Costs, as reported in the source materials, were inflated to 2003 US dollars using the all-item consumer price index.35 State-specific costs were transformed to national averages36 and foreign costs were converted to US costs using the latest available Federal Reserve exchange rates.37 Use measures were translated to costs by multiplying the use measures by age group–specific survey-adjusted average costs from the MEPS.6 More in-depth information on how the cost estimates were constructed from these sources is available elsewhere1 and in a technical appendix available on request. Survey Analysis Data from the NHIS7 and the MEPS6 were also used to supplement data on costs of autism and to also compute average costs for use in deriving the incremental costs of autism. Because confidentiality concerns constrain the MEPS to only report the first 3 digits of diagnosis codes, individuals with an International Classification of Diseases, Ninth Revision (ICD-9) diagnosis code of 299, which includes autism diagnoses (299.0x) as well as disintegrative psychoses (299.1x) and early childhood psychoses (299.8x/299.9x), were used as proxies for individuals with autism. Specific autism questions were available in the NHIS during 1997-2000. Information from those questions was combined with an ICD-9 diagnosis code of 299 in the NHIS and was linked to the MEPS to increase the number of usable cases. Survey-adjusted means for expenditures were then computed as described earlier. Further information is available elsewhere1 and from the technical appendix. Indirect costs Productivity losses for people with autism were estimated by combining standard average work-life expectancies for all men and women taken from the economics literature (ages 23-57 years for men and 23-53 years for women),34 with average income and benefits (from Tables 696 and 628 of the Statistical Abstract of the United States36) and estimates of age- and sex-specific labor force participation rates.38 Average incomes are projected for future years based on estimated productivity growth rates35 to estimate average total earnings and benefits at each age. These estimates are adjusted for the fact that while some adults with autism are unable to work, others are (35% of adults with lower levels of disability and 10% of adults with higher levels of disability work in supported work environments). Finally, the lost value of sex-specific household services is added.3,39 These estimates do not account for the effects of taxes or lost leisure time. Similar methods were used to estimate productivity for parents. Fathers of children with lower levels of disability were assumed to be unemployed 10% of the time (and working full-time during the remaining 90%) and mothers were assumed to be unemployed 55% of time (and were working half-time 25% of the time and full-time, 20%).40,41 Fathers of children with higher levels of disability were assumed to be unemployed 20% of the time and mothers were assumed to be unemployed 60% of time (and were working half-time 30% of the time and full-time, 10%). These assumptions were combined with the same average earnings, benefits, productivity growth, labor force participation rates as used for individuals with autism, and the appropriate work-life expectances. These estimates assumed households in which both a mother and a father care for 1 child with autism. These estimates will differ based on different family configurations. Calculating costs To the extent possible, cost estimates were derived for higher- and lower-functioning individuals as they were presented in the literature. Semidependent, independent, or those individuals described as having high-functioning autism were classified in the higher-functioning category. Dependent individuals or those not described as having high-functioning autism were classified in the lower-functioning category. Based on data presented in Fombonne,42 the prevalence of higher-functioning autism is assumed to be 54%. The male-female ratio is assumed to be 4:1. Weighted average per capita costs were computed based on the assumed distribution of lower- and higher-functioning status and the male-female ratio. Age 3 years was considered to be the baseline age (age at diagnosis) and 2003 was the baseline year. Because there is some evidence that people with autism have reduced life expectancies,43-46 costs were tabulated through age 66 years for males and through age 65 years for females. Costs were discounted to present value (to age 3 years) using a discount rate of 3% as recommended by the Panel on Cost-effectiveness in Health and Medicine.8 Costs in future years were discounted, or deflated, to reflect the time value of money: a dollar today is worth more than a dollar in the future. In doing so, all costs were adjusted for the different periods in which they were incurred. In other words, dollars at different ages become comparable. Because health care resource investments, such as in the case of autism research and treatment budgets, incur costs in the present and potentially realize the benefits in the future, it is common to discount future flows of costs (and benefits) to present value. Although 3% is the currently used standard for a discount rate, this rate is varied in the sensitivity analyses described in the next subsection. Sensitivity analyses In previous work, the robustness of the overall cost estimates was assessed using 1-way sensitivity analyses and conclusions were mostly robust to changes in many key parameters.1 However, the total costs were found to be most sensitive to changes in the discount rate and to changes in the assumed level of indirect costs. Because variations in indirect costs will not substantially change the pattern of costs over the life cycle, herein focus is placed on the discount rate.8 The discount rate is varied between 2% and 5% as suggested by Gold et al.8 Definition of autism Many of the sources of data simply used the term autism and did not differentiate between the different autism spectrum disorders. Reflecting the literature, the term autism herein is used in an inclusive manner to mean all disorders in the spectrum. Given the nature of many of the nonmedical and indirect costs, it is likely that those costs are more representative of more disabled individuals. Older sources9 may have only included lower-functioning children and individuals in their definitions of autism. However, varying the proportions of lower- and higher-functioning individuals does not substantially change conclusions about overall lifetime costs.1 Results In the Tables that follow, the average per capita costs by category are presented in 5-year intervals (the full Tables are available as eTable 1, eTable 2, eTable 3, and eTable 4). Table 1 and Figure 1 display the incremental societal direct medical, direct nonmedical, and indirect costs. Direct medical costs are quite high for the first 5 years of life (average of around $35 000), start to decline substantially by age 8 years (around $6000), and continue to decline through the end of life to around $1000. Direct nonmedical costs vary around $10 000 to approximately $16 000 during the first 20 years of life, peak in the 23- to 27-year age range (around $27 500), and then steadily decline to the end of life to around $8000 in the last age group. Indirect costs also display a similar pattern, decreasing from around $43 000 in early life, peaking at ages 23 to 27 years (around $52 000), and declining through the end of life to $0. Figure 1. View LargeDownload Age distribution of incremental societal costs of autism (present value). eTable 1. View LargeDownload Age-Specific and Lifetime Incremental Societal Costs of Autism* eTable 2. View LargeDownload Age-Specific and Lifetime Incremental Societal Direct Medical Costs of Autism* eTable 3. View LargeDownload Age-Specific and Lifetime Incremental Societal Direct Nonmedical Costs of Autism* eTable 4. View LargeDownload Age-Specific and Lifetime Incremental Societal Indirect Costs of Autism* Table 1. View LargeDownload Age-Specific and Lifetime per Capita Incremental Societal Costs of Autism* Table 2 displays the individual components of the incremental societal direct medical costs. Considered over the entire life span, direct medical costs make up 9.7% of total discounted lifetime costs. Behavioral therapies, which are the largest component of direct medical costs, make up 6.5% of total discounted lifetime costs.1 However, behavioral therapies, as presented herein, are only relevant for children 19 years or younger. The large direct medical costs early in life are driven primarily by behavioral therapies that cost around $32 000 during the first 5-year age group and decline from about $4000 in the 8- to 12-year age group to around $1250 for the 18- to 22-year age group. Physician and dental costs are initially high, then decrease, but increase again in later life. Prescription drugs, complementary and alternative therapies, and hospital and emergency services are also relatively high initially but steadily decline. Some costs decline less smoothly than others because of different availability of cost-by-age estimates in the literature. Table 2. View LargeDownload Age-Specific and Lifetime per Capita Incremental Societal Direct Costs of Autism* Table 3 displays the individual components of the incremental societal direct nonmedical costs. Nonmedical costs, except during ages 3 to 7 years, are more expensive than direct medical costs and make up 31% of total discounted lifetime costs.1 Different costs become relevant at different ages, which contributes to the dips and spikes in the direct nonmedical line in Figure 1. Child care and respite costs, which average about $5700 in early ages to around $3600 at ages 18 to 22 years, contribute far less (3% of total discounted lifetime costs) than adult care costs (21% of total discounted lifetime costs), which range from around $25 000 at ages 23 to 27 years to around $7400 at ages 63 to 66 years. Special education costs, which make up 4.8% of total discounted lifetime costs, range from around $12 000 at age 6 years (costs for ages 3-5 years are assumed to be zero) to around $6200 at ages 18 to 22 years, and supported employment costs range from around $800 at ages 23 to 37 years to around $300 at ages 53 to 57 years (age 57 years is the assumed end of working life). Table 3. View LargeDownload Age-Specific and Lifetime per Capita Incremental Societal Direct Nonmedical Costs of Autism* Table 4 displays the components of the incremental societal indirect costs. Indirect costs are by far the largest component of the total incremental societal costs of autism (59.3% of total discounted lifetime costs).1 Own indirect costs, which make up 30.7% of total discounted lifetime costs, range from around $33 000 at ages 23 to 27 years to around $18 000 at ages 53 to 57 years. Not own (assumed herein to be parents’) indirect costs, which make up 28.6% of total discounted lifetime costs, range from around $43 000 at ages 3 to 7 years, when parents are assumed to be about 33 to 37 years of age, to around $19 000 at ages 23 to 27 years, when parents are assumed to be 53 to 57 years of age, to around $3000 per year for the next 5 years until the end of the average work life. Although total indirect costs spike at ages 23 to 27 years, because of the overlapping own and not own indirect costs, as Figure 2 indicates, at any given time from age 3 years through age 57 years, there is a substantial and smoothly declining level of indirect costs. Figure 2 also dramatically illustrates, at least for this model, the transition from exclusive parental lost productivity almost immediately to lost own productivity. Figure 2. View LargeDownload Age distribution of own and not own indirect incremental costs (present value). Table 4. View LargeDownload Age-Specific and Lifetime per Capita Incremental Societal Indirect Costs of Autism* Sensitivity analyses Sensitivity analyses using 2% and 5%, which are common upper and lower bounds, reveal that the patterns of age-specific expenditures are similarly shaped. Figure 3 displays total costs using 2%, 3%, and 5% as the discount rates. There is an inverse relationship between the discount rate and the weight placed on future costs: lower discount rates place greater weight on future costs and higher rates place less weight on future costs. As a result, total present value costs will be larger the smaller the discount rate. The maximum difference in total costs between the 5% scenario and the 2% scenario (about $53 000) occurs at age 24 years and the average difference in costs between the 5% and 2% scenarios is about $31 000. Figure 3. View LargeDownload Age distribution of total incremental societal costs of autism computed at different discount rates. Comment This article presents the first description, to my knowledge, of the societal costs of autism in the United States across all ages of the life span and contributes not only to the literature on the costs of autism but also to the literature on age-specific health care costs in general. As was previously reported, the total annual societal per capita cost of caring for and treating a person with autism in the United States was estimated to be $3.2 million and about $35 billion for an entire birth cohort of people with autism.1 Sensitivity analyses revealed that these lifetime costs could range from $13 billion to $76 billion depending on the underlying assumptions of the model. Although those estimates are highly conservative because they exclude a number of important elements (such as legal costs that families incur to secure services47,48; lost productivity of those other than parents; the costs of genetic testing; the full costs of alternative therapies, including diets; the costs of adverse outcomes of potentially dangerous treatment modalities; and costs associated with immunization-avoidance behaviors48), they are valuable because they add information to a relatively underdeveloped literature. As treatment and, perhaps prevention, strategies are developed, knowledge of when costs are incurred relative to when benefits are expected is important for clinical decision-making and cost-effectiveness analysis efforts. Knowledge about age-specific per capita incremental societal costs is particularly important because, as opposed to the summary lifetime data presented previously,1,25,47 age-specific data illuminate the relative magnitudes of different types of costs at different ages. Given that at different ages different segments of society are responsible for absorbing these costs, this detailed disaggregation of costs can provide even more valuable information to planners, policy makers, and even to families making decisions that can affect current and future financial health, especially as they consider the fact that at various points in the life cycle different costs are more germane than others. Although autism is typically thought of as a disorder of childhood, its costs can be felt well into adulthood. Adult care, which has the largest lifetime cost of all direct costs, is typically more than 5 times larger than the next 3 largest costs, which include care incurred during childhood (behavioral therapies, child/respite care, and special education). Alemayehu and Warner49 reported that the typical American spends about $317 000 over his or her lifetime in direct medical costs, incurring 60% of those costs after age 65 years. In contrast, people with autism incur about $306 000 in incremental direct medical costs, implying that people with autism spend twice as much as the typical American over their lifetimes and spend 60% of those incremental direct medical costs after age 21 years. These results, especially on the substantial costs resulting from lost productivity of both individuals with autism and their parents and from rather large adult care costs, have important implications for those aging members of the baby boom generation approaching retirement. As those individuals retire, many of their adult children with autism will be transitioning into adult care settings. Those costs, combined with very limited to nonexistent income for their adult children with autism combined with potentially lower levels of savings because of decreased income and benefits while employed, may create a large financial burden affecting not only those families but potentially society in general. Perhaps physicians and other care professionals should consider recommending that parents of children with autism seek financial counseling to help plan for the transition into adulthood. Although this study is limited by a number of factors, it is the first of its kind, to my knowledge, and can shed insight into the lifetime distribution of autism costs and also motivate future, more rigorous studies. The cost model presented herein is based on a number of simplifying assumptions and relies on sometimes incomplete and old information. These caveats should be kept in mind when using these estimates for policy or practice decision making. The results presented herein for direct medical costs are consistent with recently published data on health care use and costs for children with autism. Gurney et al50 reported that, relative to children without autism, children with autism, as reported by their parents, experience a significantly higher number of preventive visits and emergency and nonemergency hospital visits. Croen et al51 reported, based on administrative data from the Northern California Kaiser Permanente Medical Care program, that children with autism incurred 2.5 times as much outpatient costs, 2.9 times as much inpatient costs, and 7.6 times as much medication costs as randomly selected children without autism. Pursuing a research agenda of both carefully and systematically documenting the costs of autism in the United States can be helpful in improving these estimates. Prospectively tracking the life experiences of individuals with autism and their families and obtaining a wide variety of data on the different sources of services for people with autism can provide this more complete picture. Prospectively collected clinical and quality-of-life data combined with cost data will be even more useful for understanding the societal costs, both financial and nonfinancial, of caring for those members of our society with autism at every age of the life course. Correspondence: Michael L. Ganz, MS, PhD, Abt Associates Inc, 181 Spring St, Lexington, MA 02421 (email@example.com). Accepted for Publication: November 16, 2006. Financial Disclosure: None reported. Additional Information:eTable 1, eTable 2, eTable 3, and eTable 4 are available. References 1. Ganz MLMoldin SOedRubenstein JLRed The costs of autism. Understanding Autism: From Basic Neuroscience to Treatment. Boca Raton, Fla Taylor and Francis Group2006;Google Scholar 2. National Center for Health Statistics, NCHS definitions: synthetic cohort. December16 2004;http://www.cdc.gov/nchs/datawh/nchsdefs/syntheticcohort.htmAccessed January 5, 2005 3. Waitzman NJScheffler RMRomano PS The Costs of Birth Defects: Estimates of the Value of Prevention. Lanham, Md University Press of America, Inc1996; 4. Pindyck RSRubinfeld DL Microeconomics. 5th ed. Upper Saddle River, NJ Prentice Hall2000; 5. Rice DPHodgson TAKopstein AN The economic costs of illness: a replication and update. Health Care Financ Rev 1985;761- 80PubMedGoogle Scholar 6. Agency for Healthcare Research and Quality, The Medical Expenditure Panel Survey. http://www.ahrq.gov/data/mepsix.htmAccessed January 3, 2005 7. Centers for Disease Control and Prevention, The National Health Interview Survey. December16 2004;http://www.cdc.gov/nchs/nhis.htmAccessed January 3, 2005 8. Gold MRedSiegel JEedRussell LBedWeinstein MCed Cost-Effectiveness in Health and Medicine. New York, NY Oxford University Press1996; 9. Birenbaum AGuyot DCohen HJ Health Care Financing for Severe Developmental Disabilities. Washington, DC American Association on Mental Retardation1990; 10. Aman MGVan Bourgondien MEWolford PLSarphare G Psychotropic and anticonvulsant drugs in subjects with autism: prevalence and patterns of use. J Am Acad Child Adolesc Psychiatry 1995;341672- 1681PubMedGoogle ScholarCrossref 11. Martin AScahill LKlin AVolkmar FR Higher-functioning pervasive developmental disorders: rates and patterns of psychotropic drug use. J Am Acad Child Adolesc Psychiatry 1999;38923- 931PubMedGoogle ScholarCrossref 12. Aman MGLam KSCollier-Crespin A Prevalence and patterns of use of psychoactive medicines among individuals with autism in the Autism Society of Ohio. J Autism Dev Disord 2003;33527- 534PubMedGoogle ScholarCrossref 13. Eisenberg DMKessler RCFoster CNorlock FECalkins DRDelbanco TL Unconventional medicine in the United States: prevalence, costs, and patterns of use. N Engl J Med 1993;328246- 252PubMedGoogle ScholarCrossref 14. Green VAPituch KAItchon JChoi AO'Reilly MSigafoos J Internet survey of treatments used by parents of children with autism. Res Dev Disabil 2006;2770- 84PubMedGoogle ScholarCrossref 15. Langworthy-Lam KSAman MGVan Bourgondien ME Prevalence and patterns of use of psychoactive medicines in individuals with autism in the Autism Society of North Carolina. J Child Adolesc Psychopharmacol 2002;12311- 321PubMedGoogle ScholarCrossref 16. Levy SEMandell DSMerhar SIttenbach RFPinto-Martin JA Use of complementary and alternative medicine among children recently diagnosed with autistic spectrum disorder. J Dev Behav Pediatr 2003;24418- 423PubMedGoogle ScholarCrossref 17. Nickel RE Controversial therapies for young children with developmental disabilities. Infants Young Child 1996;829- 40Google ScholarCrossref 18. Yussman SMRyan SAAuinger PWeitzman M Visits to complementary and alternative medicine providers by children and adolescents in the United States. Ambul Pediatr 2004;4429- 435PubMedGoogle ScholarCrossref 19. Hildebrand DG Cost-Benefit Analysis of Lovaas Treatment for Autism and Autism Spectrum Disorder (ASD). Vancouver, British Columbia Columbia Pacific Consulting1999; 20. Jacobson JWMulick JAGreen G Cost-benefit estimates for early intensive behavioral intervention for young children with autism—general model and single state case. Behav Intervent 1998;13201- 226Google ScholarCrossref 21. Lovaas OI Behavioral treatment and normal educational and intellectual functioning in young autistic children. J Consult Clin Psychol 1987;553- 9PubMedGoogle ScholarCrossref 22. McEachin JJSmith TLovaas OI Long-term outcome for children with autism who received early intensive behavioral treatment. Am J Ment Retard 1993;97359- 372PubMedGoogle Scholar 23. Walsh KKKastner TCriscione T Characteristics of hospitalizations for people with developmental disabilities: utilization, costs, and impact of care coordination. Am J Ment Retard 1997;101505- 520PubMedGoogle Scholar 24. Fujiura GTRoccoforte JABraddock D Costs of family care for adults with mental retardation and related developmental disabilities. Am J Ment Retard 1994;99250- 261PubMedGoogle Scholar 25. Järbrink KKnapp M The economic impact of autism in Britain. Autism 2001;57- 22PubMedGoogle ScholarCrossref 26. Parrish THarr JWolman JAnthony JMerickel AEsra P State Special Education Finance Systems, 1999–2000. Part II: Special Education Revenues and Expenditures. Palo Alto, Calif Center for Special Education Finance2004; 27. Yeargin-Allsopp MRice CKarapurkar TDoernberg NBoyle CMurphy C Prevalence of autism in a US metropolitan area. JAMA 2003;28949- 55PubMedGoogle ScholarCrossref 28. Bureau of Labor Statistics, Occupational Outlook Handbook, 2004-05 Edition. Washington, DC US Dept of Labor2004; 29. Capo LC Autism, employment, and the role of occupational therapy. Work 2001;16201- 207PubMedGoogle Scholar 30. Heal LWMcCaughrin WBTines JJ Methodological nuances and pitfalls of benefit-cost analysis: a critique. Res Dev Disabil 1989;10201- 212PubMedGoogle ScholarCrossref 31. Keel JHMesibov GBWoods AV TEACCH-supported employment program. J Autism Dev Disord 1997;273- 9PubMedGoogle ScholarCrossref 32. Mawhood LHowlin P The outcome of a supported employment scheme for high functioning adults with autism or Asperger syndrome. Autism 1999;3229- 254Google ScholarCrossref 33. Rusch FRConley RWMcCaughrin B Benefit-cost analysis of supported employment in Illinois: a statewide evaluation. Am J Ment Retard 1990;9544- 54PubMedGoogle Scholar 34. Skoog GRCiecka JE The Markov (increment-decrement) model of labor force activity: extended tables of central tendency, variation, and probability intervals. J Legal Econ 2001;11;23- 87Google Scholar 35. Congressional Budget Office, The budget and economic outlook: an update. August2003;http://www.cbo.gov/showdoc.cfm?index=4493&sequence=3Accessed January 4, 2005 36. US Department of Commerce, Statistical Abstract of the United States. Washington, DC Bureau of the Census2004; 37. Board of Governors of the Federal Reserve System, Foreign Exchange Rates Historical Data Series H.10. http://www.federalreserve.gov/releases/H10/hist/Accessed January 4, 2005 38. Congressional Budget Office, CBO's projections of the labor force. September2004;http://www.cbo.gov/showdoc.cfm?index=5803&sequence=0Accessed January 4, 2005 39. American Academy of Pediatrics, The pediatrician's role in the diagnosis and management of autistic spectrum disorder in children. Pediatrics 2001;1071221- 1226PubMedGoogle ScholarCrossref 40. Butter EMWynn JMulick JA Early intervention critical to autism treatment. Pediatr Ann 2003;32677- 684PubMedGoogle ScholarCrossref 41. Population Division, Annual Estimates of the Population by Sex and Five-Year Age Groups for the United States: April 1, 2000 to July 1, 2003. Washington, DC US Census Bureau2004;http://www.census.gov/popest/archives/Accessed January 4, 2005 42. Fombonne E Epidemiological surveys of autism and other pervasive developmental disorders: an update. J Autism Dev Disord 2003;33365- 382PubMedGoogle ScholarCrossref 43. Fombonne E The life expectancy of children diagnosed with a pervasive developmental disorder. J Autism Dev Disord 2003;33361PubMedGoogle ScholarCrossref 44. Gillberg C Outcome in autism and autistic-like conditions. J Am Acad Child Adolesc Psychiatry 1991;30375- 382PubMedGoogle ScholarCrossref 45. Shavelle RMStrauss D Comparative mortality of persons with autism in California, 1980-1996. J Insur Med 1998;30220- 225PubMedGoogle Scholar 46. Shavelle RMStrauss DJPickett J Causes of death in autism. J Autism Dev Disord 2001;31569- 576PubMedGoogle ScholarCrossref 47. Maltby J The costs of autism: more than meets the eye. Advocate 2000;33 (6) 12- 16http://www.autisminfo.com/Advocate.pdfAccessed December 24, 2004Google Scholar 48. Folstein SERosen-Sheidley B Genetics of autism: complex aetiology for a heterogeneous disorder. Nat Rev Genet 2001;2943- 955PubMedGoogle ScholarCrossref 49. Alemayehu BWarner KE The lifetime distribution of health care costs. Health Serv Res 2004;39627- 642PubMedGoogle ScholarCrossref 50. Gurney JGMcPheeters MLDavis MM Parental report of health conditions and health care use among children with and without autism: National Survey of Children's Health. Arch Pediatr Adolesc Med 2006;160825- 830PubMedGoogle ScholarCrossref 51. Croen LANajjar DVRay GTLotspeich LBernal P A comparison of health care utilization and costs of children with and without autism spectrum disorders in a large group-model health plan. Pediatrics 2006;118e1203- e1211http://pediatrics.aappublications.org/cgi/content/full/118/4/e1203PubMedGoogle ScholarCrossref
Archives of Pediatrics & Adolescent Medicine – American Medical Association
Published: Apr 1, 2007
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera