MENTAL RETARDATION AND DEVELOPMENTAL DISABILITIES RESEARCH REVIEWS 13: 129 – 135 (2007) ISSUES RELATED TO THE DIAGNOSIS AND TREATMENT OF AUTISM SPECTRUM DISORDERS Paul T. Shattuck1* and Scott D. Grosse2 1 Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin 2 National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia This paper explores issues and implications for diagnosis and treatment, stemming from the growing number of children identified with autism spectrum disorders (ASDs). Recent developments and innovations in special education and Medicaid programs are emphasized. Eligibility determination policies, innovations in diagnostic practices, the cost and financing of assessment, variability among programs in diagnostic criteria, and racial/ethnic disparities in the timing of diagnosis all influence the capacity of service systems to provide diagnoses in a timely, coordinated, accurate, economical, and equitable manner. There are several barriers to the more widespread provision of intensive intervention for children with ASDs, including lack of strong evidence of effectiveness in scaled-up public programs, uncertainty about the extent of obligations to provide services under the Individuals with Disabilities Education Act, high cost of intervention, and variability among states in their willingness to fund intensive intervention via Medicaid. Innovative policy experiments with respect to financing intensive intervention through schools and Medicaid are being conducted in a number of states. ' 2007 Wiley-Liss, Inc. MRDD Research Reviews 2007;13:129–135. Key Words: autism; policy; developmental screening; special education; early intervention T hirty years ago, the word ‘‘autism’’ was used to describe a severe developmental disorder believed to occur in *2–4 in 10,000 children [American Psychiatric Association (APA), 1980]. In recent decades, the diagnostic criteria for autism have changed, with a lower threshold for obtaining the most severe diagnosis on the autism spectrum and with additional diagnostic categories now available [Gernsbacher et al., 2005]. The most recent epidemiological estimates place the prevalence of all autism spectrum disorders (ASDs; autistic disorder, Asperger’s disorder, and pervasive developmental disorder—not otherwise specified) combined at around 50–60 per 10,000 school-age children [Chakrabarti and Fombonne, 2005; Fombonne, 2005; Schieve et al., 2006]. Changes in many factors, including diagnostic criteria, service eligibility regulations, understanding about intervention, political advocacy, and estimates of prevalence, have combined to place new and growing demands on publicly funded systems that serve children with ASDs. This paper explores selected implications of recent research on ASD diagnosis and intensive behavioral intervention. These two topics were chosen because of their central importance for improving the lives of individuals with ASDs and ' 2007 Wiley -Liss, Inc. because they are particularly fraught with controversy. Our focus is on children in the United States, and we emphasize issues related to special education and Medicaid—the two publicly funded service systems that serve the largest number of children nationwide and that spend the most on services for this population. Omitted from review are the topics of personnel preparation, adult services, economic studies, and health services, partly because the corresponding research base is sparse and underdeveloped compared with that for identification and intervention, and partly because we wanted to develop an in-depth review of two topics rather than a cursory review of many. After a brief background review of changing program enrollment trends, we review issues related to identification, assessment, and diagnosis followed by a review of issues related to comprehensive intensive intervention. Trends in special education enrollments provide an example of how growing numbers of children in publicly funded programs are being labeled with ASDs. Schools were required to use a new autism reporting category beginning in 1992, but they were not required to use a particular set of diagnostic criteria (for instance, DSM-IV). Before this time, there was no separate enrollment category for autism. Despite the lack of standardized criteria, recent surveillance research in the United States suggests that virtually all children reported in the special education autism category also meet surveillance case criteria for ASDs [Bertrand et al., 2001; Yeargin-Allsopp et al., 2003]. On the other hand, not all children with ASDs who receive special education services are classified and counted in the autism category. The special education data only report counts of primary classifications. In 1996, only 41% of children aged 3–10 years, who met case criteria for ASDs in metropolitan Atlanta, Disclaimer: The findings and conclusions are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention. Grant sponsor: National Institute of Child Health and Human Development; Grant number: T32 HD07489. *Correspondence to: Paul T. Shattuck, 533 Waisman Center, University of Wisconsin-Madison, 1500 Highland Ave., Madison, WI 53705. E-mail: [email protected] Received 3 January 2007; Accepted 5 January 2007 Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/mrdd.20143 received special education services under the autism eligibility category [Yeargin-Allsopp et al., 2003]. Thus, the growing enrollment prevalence of autism could be the result of a growing proportion of children with ASDs being classified as such and not necessarily an increase in the prevalence of children with ASDs receiving special education services or an increase in the population prevalence [Shattuck, 2006]. The total number of students aged 6–21 years identified in the ASD reporting category in U.S. special education grew from 18,540 in the 1993–1994 school year to 165,552 in the 2004–2005 school year [U.S. Department of Education, 1995; IDEAdata.org, 2005]. The 2004–2005 count of younger children aged 6–11 years was 109,869 [IDEAdata.org, 2005], yielding a national enrollment prevalence (the proportion of all children in a given age group enrolled in the autism classification category) of 46/ 10,000 for children aged 6–11, using the 2005 Census data in the denominator [U.S. Census Bureau, 2005]. Enrollment prevalence varies widely by geography. For instance, the enrollment prevalence of ASDs among children aged 6–11 in special education in 2003 ranged from a low of 10/10,000 in New Mexico to a high of 68/10,000 in Minnesota, nearly a sevenfold difference [Shattuck, 2006]. The degree to which this range reflects variability in identification rules and practices or variability in true population prevalence is not known. States with enrollment counts well below the expected population count will likely continue to see growing enrollment in the ASD category, whereas the aggregate national rate of growing enrollment will likely taper and plateau as enrollment prevalence more closely approaches estimates of the population prevalence. Enrollment of children labeled with ASDs has also increased dramatically in the past 15 years in other public programs, including Medicaid [Ruble et al., 2005] and state service systems [Croen et al., 2002]. These trends represent significant challenges for service providers and policy makers. One fundamental challenge is developing best practices for identification, assessment, and diagnosis, so that appropriate intervention can begin as early as possible. For programs that decide to offer carve-out benefits available only to children with autism, the issue of eligibility determination can be problematic insofar as assessment can be expensive, and diagnostic 130 reliability among clinicians is imperfect. After determining which children actually have an ASD, the next major challenge for public programs is determining which interventions to fund and how to pay for them. We begin our review with a look at issues related to identification, assessment, and diagnosis. et al., 1999; American Academy of Pediatrics, 2001], there are several indicators of problems in the diagnostic capacity of service systems, including waiting lists up to several years at some specialty diagnostic clinics [Yale Developmental Disabilities Clinic] and some evidence of racial disparities in the timing of diagnosis [Mandell et al., 2002]. We will examine several issues related to the diagnostic capacity of service systems, including eligibility determination, innovations in diagnostic practices, the cost and financing of assessment, variability among programs in diagnostic criteria, and racial/ethnic disparities in the timing of diagnosis. We will also look briefly at recent initiatives to improve the timing and accuracy of autism diagnosis. Whether program eligibility hinges on a diagnosis of autism can significantly influence the capacity of service systems to accurately determine who has autism. Several states have established carve-out benefits that are available only for children with an ASD diagnosis. For instance, Maryland has a Medicaid Home and Community Based Services (HCBS) waiver for children with ASDs, which covers respite care, intensive intervention, residential habilitation, supported employment, environmental adaptations, and service coordination for children up to age 21 [Maryland Department of Health and Mental Hygiene, 2002]. In another example, Ohio has an ASD scholarship program that gives families a lump sum to pay for therapeutic intervention outside the public special education system [Ohio Department of Education]. Research has found that programs that use an ASD diagnosis to determine eligibility for funding or services can influence clinical diagnostic conclusions. A recent Australian survey of child psychiatrists and developmental pediatricians found that 58% of clinicians reported ‘‘upgrading’’ the diagnosis of children with ambiguous or uncertain autistic symptoms to an official medical diagnosis of ASD, and so those children could qualify for additional services that were contingent on having an ASD diagnosis [Skellern et al., 2005]. This particular finding with respect to ASD diagnostic practices has not been studied in the United States. However, prior U.S. research confirms that pediatricians and child psychiatrists are generally willing to adjust diagnostic coding to influence their patients’ eligibility for services, and that the use of such alternate coding practices is more likely in behavioral and mental health disorders [Rushton et al., 2002]. The Wisconsin HCBS waiver for IDENTIFICATION, ASSESSMENT, AND DIAGNOSIS The central policy issue considered in this section is the capacity of service systems to provide diagnoses in a timely, coordinated, accurate, economical, and equitable manner. Early and accurate diagnosis of ASDs is important because it facilitates timely entry into appropriate treatment, thereby ‘‘We will examine several issues related to the diagnostic capacity of service systems, including eligibility determination, innovations in diagnostic practices, the cost and financing of assessment, variability among programs in diagnostic criteria, and racial/ethnic disparities in the timing of diagnosis.’’ improving outcomes; it enables families to learn about their child’s developmental challenges, so that they can more quickly adapt to new role demands and better advocate for their child’s needs; and it opens the opportunity for genetic counseling in light of the increased risk of occurrence in subsequent siblings [Mandell et al., 2002]. Autistic disorder can be diagnosed reliably around 2 years of age by an experienced clinician, whereas pervasive developmental disorder—not otherwise specified and Asperger’s disorder cannot generally be diagnosed reliably until a later age [Lord and Spence, 2006]. Although there is an emerging professional consensus about what constitutes best practices for conducting comprehensive diagnostic assessments [Filipek MRDD Research Reviews DOI 10.1002/mrdd AUTISM ISSUES SHATTUCK AND GROSSE children with ASDs has coped with this issue by requiring for eligibility both an ASD diagnosis from a qualified clinician and a score on a standardized functional screening instrument above a cutoff, indicating the level of care needed for Medicaid programs has been met and that is administered by a state employee [Wisconsin Department of Health and Family Services]. Recent innovations in clinical tools and methods for screening for and diagnosing ASDs can improve the diagnostic capacity of service and health systems. Reliable Level 2 screening tools (those used to briefly asses the possibility of an ASD diagnosis after a child has been flagged by an initial general developmental screen) are now available for use in routine clinical settings [Eaves et al., 2006; Robins and DumontMathieu, 2006]. Standardized diagnostic tools, such as the Autism Diagnostic Observation Schedule [Lord et al., 2000] and the Autism Diagnostic Interview–Revised [Lord et al., 1994], are also widely available. The extent to which these innovations have diffused into general practice is not known, but should be considered as a measurable outcome for policies aimed at improving the diagnostic capacity of service and health systems. One potential impediment to timely autism diagnosis is the cost of screening and assessment along with challenges in obtaining reimbursement. Clinicians’ concerns about getting reimbursed for developmental screening are often cited as a barrier to its inclusion in primary care visits [Halfon et al., 2001]. However, a brief series of structured general questions about development administered during a well-child visit can be completed for an estimated $2–$4 in staff time cost [Glascoe, 2005]. Well-child visits reimbursed by state Medicaid programs under Early and Periodic Screening, Diagnosis, and Treatment (EPSDT) are supposed to include developmental screens, although the adequacy of EPSDT reimbursement rates has been challenged [Rosenberg and Cohen, 2006]. Reimbursement for formal developmental screens and assessments is likely to be less of a barrier than in the past, because of the recent availability of specific procedure codes and because of the relative values for these codes established by the Center for Medicare and Medicaid Services (CMS) for reimbursement purposes in 2005. Developmental screening using a validated formal screening tool was assigned a relative value of $13.64 [American Academy of Pediatrics, 2005], although the average private insurance reimbursement in 2004 for this billing code was $27 [Campbell and Lollar, 2006]. A developmental assessment using standardized instruments, which can take an hour or more to administer and evaluate [American Academy of Pediatrics, 2005], was assigned a relative value of $145.15 [American Academy of Pediatrics, 2005], similar to the average private insurance reimbursement in 2004 of $144 [Campbell and Lollar, 2006]. Cost and reimbursement issues are likely to present more of a barrier to access for comprehensive developmental assessments. Such an assessment performed by a single practitioner is estimated to cost *$1,000 [Glascoe, 2005]. This far exceeds the prevailing reimbursement rates for developmental assessments as noted earlier. Moreover, the charge for a multidisciplinary assessment performed at a specialized center, aimed at informing intervention for a child with an ASD, can amount to $4,000 or more. The diagnostic odyssey for any given child with an ASD can take years to navigate and cost thousands of dollars. The cost of specialized autism assessment is not covered by all health plans, even though no research exists that estimates the proportion of plans with this coverage. At least three states (Connecticut, Maine, and New Hampshire) have included ASDs in mental health parity legislation, mandating improved coverage for services, including diagnosis [Sing et al., 1998]. More research is needed to document the range of variability in reimbursement policies among private and public insurance programs and to examine the impact of this variability on the timing of diagnosis and on family financial burden. A major impediment to coordinated and economical identification and diagnosis is that autism diagnoses can be provided by different professionals (e.g., physicians, psychologists, educators) through different service systems (e.g., health plans, schools) and for different purposes (e.g., eligibility determination, treatment planning). Diagnostic criteria vary across professions, systems, and purposes. Resulting diagnoses are not always recognized by other systems or professions. For instance, a school diagnosis of ASD may not be recognized by a child’s health plan and vice versa. Thus, most children with ASDs receive multiple diagnostic evaluations [YearginAllsopp et al., 2003], which diminishes efficiency and increases costs. Also, MRDD Research Reviews DOI 10.1002/mrdd AUTISM ISSUES there can be surprisingly little overlap among children who are recognized by each system as having ASDs. In particular, the health care system often misses children who are only identified through their involvement in special education. For instance, in metropolitan Atlanta in 1996, 40% of all children meeting ASD case criteria were identified only through school systems [Yeargin-Allsopp et al., 2003]. The degree to which such discrepancies are due to differences in service use or lack of agreement in diagnostic criteria between health care and school settings has not been established. Racial/ethnic disparities in the timing of diagnosis indicate inequities in the overall system of identification and diagnosis. In a study of 406 Pennsylvania children who received Medicaid-funded services under a diagnostic code of autistic disorder in 1999, age of diagnosis was significantly younger for white children (6.3 years) than for black children (7.9 years) [Mandell et al., 2002]. Two more recent studies did not find racial differences in age of diagnosis [Mandell et al., 2005; Wiggins et al., 2006]. We do not currently have representative national or state estimates that would allow us to reliably test for disparities in the timing of diagnosis in the general population, which is an important area for further research. To the extent that disparities in ASD diagnosis occur, they may reflect broader issues of disparities in access to and use of health services [Mandell et al., 2002; Smedley et al., 2003] or in the availability of culturally competent assessments that are sensitive to cultural variations in the presenting symptoms of ASDs and related family expectations for treatment [Mandell and Novak, 2005]. Whether policy interventions to increase the proportion of all children receiving routine developmental screening [Pinto-Martin et al., 2005] has a measurable spillover effect in reducing disparities in ASD diagnosis remains to be examined. There is mixed evidence about racial/ethnic disparities in the overall prevalence of ASDs. For instance, a recent study based on the Center for Disease Control and Prevention’s (CDC) Metropolitan Atlanta Developmental Disabilities Surveillance Program found that the adjusted odds ratio for having autism and intellectual disability was 3.6 (95% CI 2.4, 5.6) among children of black mothers when compared with children of white mothers, whereas the same adjusted odds ratio was not significant for having autism without intellec- SHATTUCK AND GROSSE 131 tual disability [Bhasin and Schendel, in press]. However, no significant blackwhite differences in the prevalence of autism were found in two recent national health surveys [Schieve et al., 2006]. Disparities in overall prevalence estimates might be due to disparities in identification practices or to true population differences. Professional organizations have responded to the growing concern about the number of children diagnosed with ASDs by recommending and promoting screening, diagnostic, and management guidelines [American Academy of Pediatrics, 2001]. Additionally, two federal initiatives are aimed at improving the quality and timing of ASD identification and diagnosis. ‘‘Learn the Signs. Act Early.’’ is an awareness-building campaign initiated by CDC and conducted in partnership with other groups [Centers for Disease Control and Prevention, 2006]. The campaign is targeted at parents and health care providers. Information and printed materials about development and screening (including some in Spanish) can be downloaded from the associated website and used in clinic settings to promote awareness about child development, in general, and ASD symptoms, in particular. The National Medical Home Autism Initiative, a project funded by the Maternal and Child Health Bureau of the Health Resources and Services Administration, promotes health care professionals’ application of the medical home concept to children with ASDs [Waisman Center, 2006]. Publicly funded campaigns to raise awareness among health professionals and the public are likely to improve the timing of identification and reduce the number of children with ASDs who are not diagnosed until after school entry. However, increasing efforts to screen for ASDs without a corresponding investment of resources to increase the availability of and reimbursement for specialist assessment and intervention services will likely result in continued growth of waiting lists for diagnosis and treatment. INTERVENTION Children with ASDs typically need a variety of therapeutic and supportive services [National Research Council, 2001]. Comprehensive intensive interventions developed specifically for treating autism are the focus of this section because of their high cost and specificity to ASDs, and because of policy and legal controversy surrounding publicly funded provision. This section 132 ment in response to intensive intervention (e.g., [Maurice, 1993]). Demand for public funding of intensive intervention has also been fueled by the historical trend toward family-centered care, whereby parents increasingly expect that their choice of intervention method should prevail in the development of education and service plans for their child [Feinberg and Vacca, 2000]. One of the major barriers to the broader provision of intensive intervention is the lack of unequivocal evidence of effectiveness. Most research to date has focused on efficacy in small samples under tightly controlled clinical conditions, where individual treatment outcomes vary widely (for useful reviews, see National Research Council, 2001; Rogers and Ozonoff, 2006]. To plan programs and justify the allocation of resources, policy makers need to know whether intervention is effective, once scaled up for delivery in real-world service system settings, what proportion of children can be expected to respond to treatment in real-world settings, whether home-based or more inclusive environments are more conducive to positive outcomes, and how decisions are made on when to discontinue intervention for individual children, either because maximum benefit has been reached or because no significant effect has been observed. Research evidence answering these questions directly and conclusively is not available. The indeterminate nature of the research evidence creates a dilemma for policy makers who face growing demand for this type of intervention. Making decisions on health issues in the absence of unequivocal research evidence is not uncommon; policy makers in this area could benefit from exploring how these matters have been addressed in other health issues [Atkins et al., 2005; Lomas et al., 2005]. General recommendations from this literature suggest the importance of developing deliberative processes that include a wide variety of stakeholders, which are tightly focused on specific policy questions, directly confront the value dimensions of the decisions at hand, and make room for consideration of both scientific and colloquial evidence. The comprehensive review of extant literature on autism intervention conducted by the National Research Council [National Research Council, 2001] and the formation of state task forces on autism services [Maine Administrators of Services for Children with Disabilities, 2000; Pennsylvania Department of Public Welfare, explores barriers to the provision of effective, affordable, and equitable intensive intervention. Programs funded by the Individuals with Disabilities Education Act (IDEA) and Medicaid are featured, because controversies over public provision of intensive intervention have occurred mainly in relation to these two programs. We first consider the state of evidence regarding the effectiveness of intensive intervention for autism in real-world settings and the need to consider heterogeneity in ASD symptomatology with regard to the need for, and response to, intervention. Then we examine issues specific to IDEA and Medicaid. ‘‘Comprehensive intensive interventions developed specifically for treating autism are the focus of this section because of their high cost and specificity to ASDs, and because of policy and legal controversy surrounding publicly funded provision.’’ Comprehensive intensive interventions are defined here as small-group or one-on-one behavioral and educational interventions that are delivered for at least 10–15 hr per week. They include well-known treatment models such as the UCLA Young Autism Project, Treatment and Education of Autistic and Related Communication Handicapped Children, and the Denver Model (see National Research Council, 2001 for an overview of comprehensive programs). As autism enrollment numbers have risen, there has been a corresponding increase in parent demand for public provision of intensive intervention in schools and for public assistance with the high cost of intensive interventions delivered by private providers. This demand is partly fueled by the widely known promising results of some clinical research [Lovaas, 1987; McEachin et al., 1993] and widely read family anecdotes of dramatic improve- MRDD Research Reviews DOI 10.1002/mrdd AUTISM ISSUES SHATTUCK AND GROSSE 2004] are examples of how such deliberative processes have been applied to the questions raised here. Another impediment to wider availability of intensive intervention is the tremendous heterogeneity in development, symptomatology, and comorbidity among children with ASDs, and a lack of evidence of how these differences affect needs for, and responses to, intervention. While there is consensus that the symptoms and developmental delays associated with ASDs can be reduced or alleviated by exposure to intensive intervention in many cases [National Research Council, 2001; Rogers and Ozonoff, 2006], there is little specificity in terms of recommendations about which interventions are optimal for different groups of children. In particular, it is not known whether every child on the autism spectrum needs or would benefit from intensive intervention, as most of the intensive intervention research to date has focused on treating those with autistic disorder. Whether children with less-severe ASDs need or benefit from intensive intervention is an important question for future research, especially since this group represents the majority of children on the autism spectrum [Fombonne, 2005]. The ability to define and forecast the different kinds and amounts of intervention public programs would have to supply to match the needs of this population is hampered by the lack of detail about both the distribution of this population’s needs and how to best match needs and interventions for each individual. Most population-based studies of ASD prevalence characterize the distribution of severity by reporting the proportion meeting criteria for intellectual disability, and this proportion has varied widely in recent reports [Fombonne, 2005]. In addition to reducing the imprecision of these estimates, future research must characterize the distribution of severity and the intervention needs of this population in greater detail, to assist policy makers and program administrators. Several specific barriers exist to the provision of intensive intervention through programs mandated by the Individuals with Disabilities Education Act (early intervention and special education), including the high cost of intensive intervention and uncertainty over the legal obligation of these programs to provide or fund intensive intervention or both. A growing number of administrative and court rulings have attempted to address the extent of programs’ treatment obligations for children with ASDs, especially in cases where parents want the program to provide or pay for intensive intervention [Mandlawitz, 2002; Zirkel, 2002; Nelson and Huefner, 2003]. Three issues have dominated these cases: the type of intervention to be provided, the intensity and duration of intervention, and the setting (at home, a private school, inclusive public classroom, segregated public classroom) [Mandlawitz, 2002]. The IDEA requires schools to provide a ‘‘free appropriate public education.’’ Parents have the right to administrative and judicial appeals to contest the package of services the district offers their child. In Board of Education of the Hendrick Hudson Central School District v. Rowley, 458 U.S. 76 [1982], the Supreme Court ruled that services provided under the IDEA need to provide some educational benefit but do not need to provide optimal or maximal benefit. The decision established a twopart test for reviewing the adequacy of school district programming for students in special education. First, it must be established that the school followed all required procedures set forth in IDEA with respect to assessment and program development. Second, the child’s individualized education program must be ‘‘reasonably calculated to enable the child to receive meaningful benefit’’ [Board of Education of the Hendrick Hudson Central School District v. Rowley, 1982; p. 206]. Cases about the type of intervention methodology to be used, level of prescribed intensity, and setting often become a competition between expert witnesses. Rulings to date have favored schools in a narrow majority of cases [Zirkel, 2002; Nelson and Huefner, 2003]. Cases ruled in favor of parents have typically hinged on a demonstration of district failure to adequately comply with the procedural safeguards set forth by IDEA or failure to meet the Rowley test, rather than by successfully arguing the superiority of one intervention method over another. This balance may change, as a growing number of private schools for children with ASDs team up with specialist attorneys to help families sue districts to pay for placement at the private school, using well-honed strategies that leverage precedent rulings [Katz, 2006]. The cost of serving children with ASDs in special education is another barrier in making intensive intervention more widely available. Intensive intervention can be very expensive, averag- MRDD Research Reviews DOI 10.1002/mrdd AUTISM ISSUES ing about $40,000 per child per year for a full-time program [Ganz, 2006]. The cost can be even higher for center-based programs. There are no nationally representative estimates of how many children enrolled in the autism special education category are being provided intensive intervention, but we do know the overall average spending on children in different categories. A national study calculated that during the 1999–2000 school year, total spending on students receiving special education services in the autism category averaged $18,790, compared with average expenditures of $6,556 per child for children not receiving special education services [Chambers et al., 2003]. Thus, each child placed in the autism category was associated with an increase of $12,234 per year in education expenditures above and beyond the average per pupil expenditure for regular education students. Adjusting this per pupil expenditure estimate for inflation and multiplying by the total enrollment in the 2004–2005 school year, the cost to America’s schools of serving students in the autism category was *$2.3 billion in 2004–2005. The total educational cost of autism is actually higher, because an unknown number of students with autism are classified in other enrollment categories. Policy makers caught between political demands for more widespread funding of intensive intervention through the schools and tight school funding overall have begun to experiment with alternative funding mechanisms. Some states have created a pooled risk mechanism that gives extra state aid to school districts with a disproportionate share of high-cost students [Rawe and Healy, 2006]. Others have created carve-out benefits available only to children with ASDs. For instance, OH has piloted an autism scholarship program through the state department of education. Under this program, families of children aged 3–21, identified in the special education autism category, are eligible for a cash allowance of up to $15,000 per year, which can be used for private intervention services (including in-home intensive intervention) or private school tuition [Ohio Legislative Office of Education Oversight, 2005]. Funding comes out of existing state and local budgets, as no additional appropriation accompanied the new program. There were 178 students participating as of the start of the 2004–2005 school year. Surveyed parents indicated a high level of satisfaction with the program, though no SHATTUCK AND GROSSE 133 effectiveness evaluations have been conducted. School district officials have voiced concerns that the program could generate a negative financial impact, including the need to reduce services to other children in special education. A proposed bill to introduce a scholarship program in Wisconsin was defeated in 2006 because of similar concerns. The politically charged atmosphere surrounding school funding issues, where providing services for one group is often framed as being at the expense of providing service for others, has prompted some states to look for other ways to finance intensive intervention for children with ASDs that do not involve school funds. Another potential mechanism for public funding of intensive intervention services is the Medicaid HCBS waiver. Waivers allow states to use Medicaid funds to pay for services to support individuals in the community, who might otherwise be at risk for institutional placement (for an overview of HCBS waivers, see [Duckett and Guy, 2000]. States must formally apply to the CMS to implement a waiver. Once approved, a waiver must be operated and monitored as a discrete program, and permission to continue operating must be renewed every 3–5 years. HCBS waivers can be targeted to specific groups, based on type of disability, such as autism, and enrollment can be capped. An example of an HCBS waiver that pays for intensive intervention is one started in 2004 in Wisconsin that had served more than 700 families as of November 2006 (Diana Adamski, Wisconsin Department of Health and Family Services, personal communication, November 6, 2006). This autism carveout benefit is nested within a broader HCBS waiver for children with developmental disabilities (Wisconsin Department of Health and Family Services). Eligibility criteria include having an ASD diagnosis from a qualified professional, meeting level-of-care criteria using a standardized screening tool developed by the state, and being under the age of 8. The maximum intensity is 35 hr per week, length of enrollment is capped at 3 years, families and clinicians can draw from an eclectic array of methodologies when devising individualized treatment plans, and there is a sliding scale for family copayments. The 3-year limit was a compromise, balancing a desire to maximize therapeutic impact with a desire to ensure turnover in the number of slots available for future cohorts. Despite this built-in turnover, the waiting list had grown to 134 more than 200 as of November 2006. There are no reports detailing the number of states with autism waivers or comparing the characteristics of waivers across states. Furthermore, no evaluations have been conducted to examine the clinical effectiveness, cost effectiveness, or equity of Medicaid-funded carve-out benefits. These are important topics for future research. The Deficit Reduction Act (DRA), signed into law in 2006, contains several provisions that will affect the provision of Medicaid benefits for children with developmental disabilities, including those with ASDs, starting in 2007 [Crowley, 2006]. Most relevant to the present discussion of intensive intervention, under the DRA, states can offer HCBS as part of their state Medicaid plan (i.e., without a waiver) for families with income below 150% of the federal poverty level. Eligibility will not have to depend on meeting the institutional level-of-care test required by most waivers. States can cap enrollment and restrict availability to selected geographic areas. Whether some states will take advantage of these provisions to expand availability of funding for intensive intervention remains to be seen. improve services for all people with disabilities, regardless of diagnosis. Historically in the field of social welfare policy, entitlements granted to one group can sometimes provide leverage for other groups in obtaining an expansion of entitlements for themselves. However, this outcome is not guaranteed, and carveout entitlements may actually sow division among groups that could achieve more political gain by working together. Future research on autism policy that directly considers the qualitative and ethical dimensions of some of these issues could aid decision making, which in the policy arena always involves questions of values and power in addition to consideration of scientific evidence. REFERENCES American Academy of Pediatrics. 2001. The pediatrician’s role in the diagnosis and management of autistic spectrum disorder in children. Pediatrics 107:1221–1226. American Academy of Pediatrics. 2005. Developmental screening/testing coding fact sheet for primary care practitioners. Available at http://www.cdc.gov/ncbddd/child/documents/ AAP Coding Fact Sheet for Primary Care. pdf. Accessed October 28, 2006. APA. 1980. Diagnostic and Statistical Manual of Mental Disorders, 3rd ed. Washington, DC: APA. Atkins D, Siegel J, Slutsky J. 2005. Making policy when the evidence is in dispute. Health Aff 24:102–113. Bertrand J, Boyle C, Yeargin-Allsopp M, et al. 2001. Prevalence of autism in a United States population: The Brick Township, New Jersey, Investigation. Pediatrics 108:1155–1162. Bhasin TK, Schendel D. Sociodemographic risk factors for autism in a US metropolitan area. J Autism Dev Disord (in press). Board of Education of the Hendrick Hudson Central School District v. Rowley, 458 US 176 (1982). Campbell KP, Lollar D. 2006. Child development evidence-statement: Screening. In: Campbell KP, Lanza A, Dixon R, et al., editors. A purchaser’s guide to clinical preventive services: moving science into coverage. Washington, DC: National Business Group on Health. Centers for Disease Control and Prevention. 2006. Learn the signs. Act early. Early identification of children with autism or other developmental disorders awareness campaign. Available at http://www.cdc.gov/ncbddd/ autism/actearly/. Accessed May 16, 2006. Chakrabarti S, Fombonne E. 2005. Pervasive developmental disorders in preschool children: confirmation of high prevalence. Am J Psychiatry 162:1133–1141. Chambers JG, Shkolnik J, Perez M. 2003. Total expenditures for students with disabilities, 1999–2000: Spending variation by disability (No. 5). Palo Alto, CA: American Institutes for Research. Croen LA, Grether JK, Hoogstrate J, et al. 2002. The changing prevalence of autism in California. J Autism Dev Disord 32:207–215. Crowley JS. 2006. Medicaid long-term services reforms in the Deficit Reduction Act. Available at http://www.kff.org/medicaid/upload/ 7486.pdf. Accessed October 30, 2006. CONCLUSION The growing number of children diagnosed with an ASD and the efforts of well-organized advocacy groups have increased pressure on policy makers and service systems to improve and expand diagnostic and treatment services. Such changes face many obstacles as we have discussed. While a number of policy experiments are under way to improve identification and intervention in realworld settings, the ability to generalize conclusions from these experiments is limited by the lack of scientifically rigorous evaluations. Funding mechanisms for scientific research on intervention are generally designed to support experimental clinical research, the standards of which can rarely be met in policy evaluation studies [McCall and Green, 2004]. To facilitate progress in this area, it is important to develop new ways to fund rigorous evaluations of policy innovations in applied settings. An overarching policy issue that advocates and decision makers’ need to address is the extent to which policies and services should be specific to certain conditions. At one end of the continuum is the creation of carve-out programs, where diagnosis on the autism spectrum is part of the eligibility criteria. At the other end are efforts to create and MRDD Research Reviews DOI 10.1002/mrdd AUTISM ISSUES SHATTUCK AND GROSSE Duckett MJ, Guy MR. 2000. Home and community-based services waivers. Health Care Financ Rev 22:123–125. Eaves LC, Wingert HD, Ho HH, et al. 2006. Screening for autism spectrum disorders with the Social Communication Questionnaire. Dev Behav Pediatr 27:s95–s103. Feinberg E, Vacca J. 2000. The drama and trauma of creating policies on autism: critical issues to consider in the new millennium. Focus Autism Other Dev Disabil 15:130–137. Filipek PA, Accardo PJ, Baranek GT, et al. 1999. The screening and diagnosis of autistic spectrum disorders. J Autism Dev Disord 29:439–484. Fombonne E. 2005. The changing epidemiology of autism. J Appl Res Intellect Disabil 18: 281–294. Ganz ML. 2006. The costs of autism. In: Moldin SO, Rubenstein JLR, editors. Understanding autism: from basic neuroscience to treatment. New York: CRC Taylor and Francis. p 475–502. Gernsbacher M, Dawson M, Goldsmith HH. 2005. Three reasons not to believe in an autism epidemic. Curr Dir Psychol Sci 14:55–58. Glascoe FP. 2005. Screening for developmental and behavioral problems. Ment Retard Dev Disabil Res Rev 11:173–179. Halfon N, Hochstein M, Harvinder S, et al. 2001. Barriers to the provision of developmental assessments during pediatric health supervision. Paper presented at the American Academy of Pediatrics, Pediatric Academic Societies Annual Meeting. IDEAdata.org. 2005. Annual report tables. Available at http://www.ideadata.org/PartBdata. asp. Accessed February 17, 2005. Katz A. 2006. The autism clause: A handful of new schools charge up to $140,000 a year to educate an autistic child. Who can pay that much? Anyone with the right lawyer. New York Mag 39:50–132. Lomas JL, Culyer T, McCutcheon C, et al. 2005. Conceptualizing and combining evidence for health system guidance. Ottawa: Canadian Health Services Research Foundation. Lord C, Risi S, Lambrecht L, et al. 2000. The autism diagnostic observations schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord 30:205–223. Lord C, Rutter M, Le Couteur A. 1994. Autism diagnostic interview-revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord 24:659–685. Lord C, Spence S. 2006. Autism spectrum disorders: Phenotype and diagnosis. In: Moldin SO, Rubenstein JLR, editors. Understanding autism: from basic neuroscience to treatment. New York: CRC Taylor and Francis. p 1–23. Lovaas IO. 1987. Behavioral treatment and normal educational and intellectual functioning in young autistic children. J Consult Clin Psychol 55:3–9. Maine Administrators of Services for Children with Disabilities. 2000. Report of MADSEC Autism Task Force. Available at http://www. madsec.org/docs/ATFReport.pdf. Accessed December 12, 2006. Mandell DS, Listerud J, Levy SE, et al. 2002. Race differences in the age at diagnosis among Medicaid-eligible children with autism. J Am Acad Child Adolesc Psychiatry 41:1447–1453. Mandell DS, Novak MM. 2005. The role of culture in families’ treatment decisions for children with autism spectrum disorders. Ment Retard Dev Disabil Res Rev 11:110– 115. Mandell DS, Novak MM, Zubritsky CD. 2005. Factors associated with age of diagnosis among children with autism spectrum disorders. Pediatrics 116:1480–1486. Mandlawitz MR. 2002. The impact of the legal system on educational programming for young children with autism spectrum disorder. J Autism Dev Disord 3:495–508. Maryland Department of Health and Mental Hygiene. 2002. Medicaid Home and Community-Based Services waiver for children with autism spectrum disorder fact sheet. Available at http://www.dhmh.state.md.us/ mma/waiverprograms/html/Autism Waiver Fact Sheet.htm. Accessed July 8, 2006. Maurice C. 1993. Let me hear your voice: a family’s triumph over autism. New York: Ballantine Books. McCall RB, Green BL. 2004. Beyond the methodological gold standards of behavioral research: considerations for practice and policy. Soc Policy Rep 18:3–19. McEachin JJ, Smith T, Lovaas IO. 1993. Longterm outcome for children with autism who received early intensive behavioral treatment. Am J Ment Retard 97:359–372. National Research Council. 2001. Educating children with autism. Washington, DC: National Academy Press. Nelson C, Huefner DS. 2003. Young children with autism: judicial responses to the Lovaas and discrete trial training debates. J Early Interv 26:1–19. Ohio Department of Education. Autism scholarship program. Available at http://www. ode.state.oh.us/GD/Templates/Pages/ODE/ ODEDetail.aspx?Page¼3&TopicRelationID¼ 967&Content¼18137. Accessed October 19, 2006. Ohio Legislative Office of Education Oversight. 2005. Formative evaluation of Ohio’s autism scholarship program. Columbus: Ohio Legislative Office of Education Oversight. Pennsylvania Department of Public Welfare. 2004. Autism task force: Final report. Available at http://www.dpw.state.pa.us/General/AboutDPW/ SecretaryPublicWelfare/AutismTaskForce/. Accessed December 12, 2006. Pinto-Martin JA, Dunkle M, Earls M, et al. 2005. Developmental stages of developmental screening: steps to implementation of a successful program. Am J Clin Nutr 95:6–10. Rawe J, Healy R. 2006. Who pays for special ed? Time 168:62–63. Robins DL, Dumont-Mathieu TM. 2006. Early screening for autism spectrum disorders: update on the modified checklist for autism in toddlers and other measures. Dev Behav Pediatr 27:s111–s119. Rogers SJ, Ozonoff S. 2006. Behavioral, educational, and developmental treatments for autism. In: Moldin SO, Rubenstein JLR, editors. Understanding autism: from basic neu- MRDD Research Reviews DOI 10.1002/mrdd AUTISM ISSUES roscience to treatment. Boca Raton, FL: CRC Taylor and Francis. p 443–473. Rosenberg M, Cohen F. 2006. Medicaid and physician reimbursement. Pediatrics 118:808–809. Ruble LA, Heflinger CA, Renfrew JW, et al. 2005. Access and service use by children with autism spectrum disorders in Medicaid managed care. J Autism Dev Disord 35: 3–13. Rushton JL, Felt BT, Roberts MW. 2002. Coding of pediatric behavioral and mental disorders. Pediatrics 110:e8. Schieve LA, Rice C, Boyle C. 2006. Parental report of diagnosed autism in children aged 4–17 years—United States, 2003–2004. MMWR Morb Mortal Wkly Rep 55:481–486. Shattuck P. 2006. The contribution of diagnostic substitution to the growing administrative prevalence of autism in U.S. special education. Pediatrics 117:1028–1037. Sing M, Hill S, Smolkin S, et al. 1998. The costs and effects of parity for mental health and substance abuse insurance benefits. Available at http://mentalhealth.samhsa.gov/publications/ allpubs/Mc99-80/Prtyfnix.asp. Accessed December 12, 2006. Skellern C, Schluter P, McDowell M. 2005. From complexity to category: responding to diagnostic uncertainties of autistic spectrum disorders. Disabil Rehabil Child Health 41: 407–412. Smedley BD, Stith AY, Nelson AR, editors. 2003. Unequal treatment: confronting racial and ethnic disparities in health care. Washington, DC: National Academies Press. U.S. Census Bureau. 2005. State single year of age and sex population estimates: April 1, 2000 to July 1, 2005—Resident. Available at http://www.census.gov/popest/datasets.html. Accessed October 25, 2006. US Department of Education. 1995. Seventeenth Annual Report to Congress on the Implementation of the Individuals with Disabilities Education Act. Washington DC: US Department of Education. Waisman Center. 2006. National medical home autism initiative. Available at http://www. waisman.wisc.edu/cedd/NMHAI/DESCRIPTION.HTML. Accessed May 16, 2006. Wiggins LD, Baio J, Rice C. 2006. Examination of the time between first evaluation and first autism spectrum diagnosis in a population-based sample. Dev Behav Pediatr 27: s79–s87. Wisconsin Department of Health and Family Services. Information for families, providers and county staff about autism services and the children’s waivers under Wisconsin Medicaid. Available at http://dhfs.wisconsin.gov/ bdds/clts/autism/index.htm. Accessed October 19, 2006. Yale Developmental Disabilities Clinic. Clinic Information. Available at http://info.med.yale.edu/chldstdy/autism/clinic.html. Accessed June 7, 2006. Yeargin-Allsopp M, Rice C, Karapurkar T, et al. 2003. Prevalence of autism in a US metropolitan area. JAMA 289:49–55. Zirkel PA. 2002. The autism case law: Administrative and judicial hearings. Focus Autism Other Dev Disabil 17:84–93. SHATTUCK AND GROSSE 135
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