I R D T

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: shattuck@waisman.wisc.edu
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