Chat with us, powered by LiveChat Week 2-Access to Healthcare in Developmental Disabilities Based on your review of the articles assigned thus far, please discuss whether the h | EssayAbode

Week 2-Access to Healthcare in Developmental Disabilities Based on your review of the articles assigned thus far, please discuss whether the h

 

Week 2-Access to Healthcare in Developmental Disabilities

  • Based on your review of the articles assigned thus far, please discuss whether the healthcare issues of individuals with developmental disabilities are being met and provide support for your conclusions based on the readings and information found in other sources. Also, discuss potential barriers to effective care within this population.

O R I G I N A L P A P E R

Access to Care for Autism-Related Services

Kathleen C. Thomas Æ Alan R. Ellis Æ Carolyn McLaurin Æ Julie Daniels Æ Joseph P. Morrissey

Published online: 19 March 2007 � Springer Science+Business Media, LLC 2007

Abstract This paper identifies family characteristics

associated with use of autism-related services. A

telephone or in-person survey was completed during

2003–2005 by 383 North Carolina families with a child

11 years old or younger with ASD. Access to care is

limited for racial and ethnic minority families, with low

parental education, living in nonmetropolitan areas,

and not following a major treatment approach. Service

use is more likely when parents have higher stress.

Families use a broad array of services; the mix varies

with child ASD diagnosis and age group. Disparities in

service use associated with race, residence and educa-

tion point to the need to develop policy, practice and

family-level interventions that can address barriers to

services for children with ASD.

Keywords Autism � Services � Access

Children with autism spectrum disorder (ASD) have a

heterogeneous set of skills and deficits. A successful

treatment protocol must take into account the individ-

ual characteristics of the child and that child’s family in

order to define meaningful treatment goals and strat-

egies to move toward them (Hurth, Shaw, Izeman,

Whaley, & Rogers, 1999; Rogers, 1998; Dawson &

Osterling, 1997). Families are aware that ‘one size does

not fit all,’ and they commonly express interest in a

broad array of treatments in their search for the

one(s) right for their child (Green, Pituch, Itochon,

Choi, & Sigafoos, 2005; Carey, 2004; Gross, 2004;

Bodfish, 2004; Smith & Antolovich, 2000; Levy,

Mandell, Merher, Ittenbach, & Pinto-Martin, 2003).

Several studies have found that families with a child

with ASD experience difficulties accessing services

(Ruble, Heflinger, Renfrew, & Saunders, 2005; Kraus,

Gulley, Sciegaii, & Wells, 2003; Kohler, 2000). How-

ever, studies of child and family characteristics associ-

ated with use of services for ASD have been limited.

Children with ASD of minority race and ethnicity have

been found to receive services at a later age and

receive a different mix of services from white children

(Mandell, Listerus, Levy, & Pinto-Martin, 2002; Levy

et al., 2003). Younger children have been found to use

more services, and families were less likely to express

difficulties accessing care when children were covered

by public or private insurance (Green et al., 2005;

Kraus et al., 2003). Families with higher education,

with more than one child with special health care

needs, and those not following a major treatment

approach for ASD (e.g. TEACCH: Marcus, Garfinkle,

& Wolery, 2001; Lovaas: McEachin, Smith, & Lovaas,

1993; Floortime: Wieder & Greenspan, 2003) have

been found to express problems accessing care or use

K. C. Thomas (&) � A. R. Ellis � C. McLaurin � J. P. Morrissey Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, 725 Martin Luther King Jr. Blvd. CB#7590, Chapel Hill, NC 27599- 7590, USA e-mail: [email protected]

J. Daniels Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

J. P. Morrissey Department of Health Policy and Administration, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

J Autism Dev Disord (2007) 37:1902–1912

DOI 10.1007/s10803-006-0323-7

123

fewer services (Thomas, Morrissey, & McLaurin, 2006;

Kraus et al., 2003). Specific relationships between

service use and child and parent behavioral health

needs have not been consistently demonstrated

(Luther, Canham & Cureton, 2005; Green et al.,

2005; Hare, Pratt, Burton, Bromley, & Emerson,

2004; Kraus et al. 2003; Dunn, Burbine, Bowers, &

Tantleff-Dunn, 2001; Hastings & Johnson, 2001; Fac-

tor, Perry, & Freeman, 1990).

This study sought to expand the literature on access

to services for ASD by studying the characteristics of a

community sample of families and their child with ASD

that are associated with use of a wide range of autism-

related services. The classical Andersen and Aday

model of access to health care provided the framework

for identifying families who have limited access to care

for ASD. Family characteristics that impact service use

were divided into predisposing, enabling and need

factors (Aday, 1989; Aday & Andersen, 1975). A

number of different autism-related services were

examined in order to identify any differences in the

patterns of utilization across type of service.

Methods

Sample

The study was based on a community sample of 383

families with a child with ASD, aged 11 years or

younger, living in North Carolina. Although the sample

was based on a single state, North Carolina is widely

considered to have a comprehensive service system for

young children with ASD and can provide an under-

standing of what utilization looks like when families

have many choices. At the same time, there is variation

in service use in North Carolina (Thomas et al., 2006),

so it should provide a conservative view of the family

and child characteristics that account for variation.

The sample was recruited through a two-pronged

approach. Sixty percent of the sample was obtained

through a subject registry and the remainder through

direct recruitment. The study used the Neurodevelop-

mental Disorders Research Center Subject Registry at

the University of North Carolina at Chapel Hill (UNC).

The Subject Registry enrolls families served at Division

TEACCH (Treatment and Education of Autistic and

related Communication handicapped CHildren) regio-

nal centers who are interested in participating in

research on ASD. When a child is diagnosed, or

suspected of a diagnosis of ASD, either by a private

practitioner or by a state Children’s Developmental

Services Agency, the child can be referred to a

TEACCH Regional Center to confirm that diagnosis.

For those with confirmed diagnoses, TEACCH serves

as a source of training and referral for the family and for

teachers (Campbell, Schopler, Cueva, & Hallin, 1996).

The Registry sent a mailing to families; interested

families provided contact information to the study team

or gave consent to the Registry to do so. Participants

were also recruited directly through mailings to all

elementary school principals and directors of excep-

tional children’s divisions, TEACCH Regional Centers,

and state Children’s Developmental Services Agencies

within North Carolina. In addition, the Autism Society

of North Carolina and Families for Early Autism

Treatment of North Carolina (NCFEAT), two major

advocacy groups, assisted in recruitment by sharing

study information and an invitation to participate. The

referring agency provided potential participants with a

description of the study and contact information for the

study team, so that potential participants, rather than

the research team, initiated contact.

Families who expressed an interest in participating

in the study provided an address and were mailed and

returned written informed consent to participate. The

consent form was approved by the UNC Office of

Human Research Ethics. The majority (97 percent) of

respondents were mothers.

Data Collection

Interviews were conducted in two phases. Families of

children aged 8 and younger were interviewed by

telephone during the winter of 2003–2004 (Thomas

et al., 2006). Families of children aged 9–11 years were

interviewed in person during the winter of 2004–2005.

Each interview was conducted in two segments, with

the phone or in-person interview supplemented with a

self-administered segment. The self-administered seg-

ment was sent by mail to the families of younger

children. For families of older children, the respondent

was given the self-administered survey booklet during

a break in the in-person interview. These efforts

yielded a 91 percent response rate amongst families

who initially expressed an interest in participating.

Measures

All measures were derived from the survey and based

on parent’s recall and report. Thomas et al. (2006)

provides a description of instrument development.

A list of autism-related services was developed from

those described in the literature and listed on web sites

maintained by advocacy groups such as the Autism

123

J Autism Dev Disord (2007) 37:1902–1912 1903

Society of America as well as various state agencies

across the country. Service use was catalogued, regard-

less of the extent to which any given therapy might be

recommended by professionals or supported in the

literature. Services were listed in groups, beginning

with those in school and those outside of school

(including diet therapies, other autism-specific thera-

pies, and general therapies not specific to ASD). The

goal was to distinguish different sources of autism-

related service use. For example, a child might receive

speech/language therapy at school, and outside school,

targeted to children with ASD, or targeted to children

with a variety of diagnoses. The survey also catalogued

parent and sibling services, child care services, and

other special service providers. These sections served

to identify any additional service use that might be

more readily identified by the type of provider than by

the name of the service. For example, after receiving a

set of services in clinic settings, a family might have

a behavioral specialist come to their home to set up a

structured learning environment for the child which

could be maintained with the help of a therapeutic

support person. Brief descriptions of the services were

offered if requested. Medication and supplement use

was measured using a modified version of the Brief

Medication Questionnaire (BMQ; Svarstad, Chewning,

Sleath, & Claesson, 1999).

We used a measure we developed to identify the

major treatment approach for ASD used by the family

(Thomas et al., 2006). After piloting the instrument,

parents recommended that we distinguish between this

‘major treatment approach’ and routine autism-related

services. The major treatment approach was assessed

with a set of questions about approach utilization

(referred to by approach name(s) and acronym). The

survey asked about Applied Behavior Analysis (or

ABA, but not the Lovaas approach), Defeat Autism

Now (DAN), Floor Time (or Greenspan), the Denver

Model, Lovaas and TEACCH (or Treatment and

Education of Autistic and related Communication

handicapped CHildren). In this way, familiarity was

assessed based on name recognition.

Family stress was measured with the Questionnaire

on Resources and Stress (QRS), using the short form

developed by Friedrich and colleagues (Friedrich,

Greenberg, & Crnic, 1983). The survey contains the

subscale on Parent and Family Problems. This is an 18

item scale of true/false questions which provide a

summed score. The norm for children with mental

retardation is around 6. The short form of the QRS has

a high correlation (q = 0.997) with the long form and internal and external validity (Rousey, Best, & Blach-

er, 1992; Friedrich et al., 1983).

The instrument assessed health insurance coverage

of several different types: private, Medicaid, Health

Choice (North Carolina’s state children’s health insur-

ance plan), coverage from any other public program, or

none. Families were asked to code all that apply, so

that any secondary coverage could be noted.

ASD diagnosis was based on parent’s report of

Asperger syndrome, classical autism, or pervasive

developmental disorder not otherwise specified

(PDD-NOS). The instrument also asked about Rhett’s

and childhood disintegrative disorder, but responses

were too few to distinguish, so they were combined

with the classical autism category.

Racial and ethnic minority status was measured

from report of race (up to five separate races could be

identified) and Hispanic culture. All families who were

not white and all who were Hispanic were categorized

as racial and ethnic minority.

Nonmetropolitan residence is based on Rural-Urban

Continuum Code (RUCC) a classification scheme that

distinguishes metropolitan counties by the population

size of their metro area, and nonmetropolitan counties

by degree of urbanization and adjacency to a metro-

politan area (USDA, 2004). RUCC codes are devel-

oped at the zip code level and applied to each family

based on address of residence. (USDA, 2004)

Statistical Methods

Chi square tests (df = 1) were used to measure the

difference in sample demographic characteristics and

use of major treatment approach by age group of the

child with ASD (4 years or less, 5–8 years, and 9–

11 years). Logit models were used to measure the

predisposing, enabling and need characteristics associ-

ated with use of each autism-related service obtained

outside school. This allowed us to see variation in the

factors associated with use of each type of service.

Findings are presented only for those services used by

at least 10 percent of families (n = 38) and models that

produced a significant fit (according to a change in the

likelihood ratio statistic, a = 0.05) in order to assure their robustness.

Results

Sample Characteristics

Table 1 presents characteristics of sample families and

their child with ASD. In comparison to North Carolina

and national populations, the sample was slightly less

likely to be of minority race or ethnicity, had slightly

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1904 J Autism Dev Disord (2007) 37:1902–1912

higher education and income, and was more likely to

have health insurance. In North Carolina, 21.6 percent

of families are African American and 4.7 percent are

Hispanic (U.S. Census, 2001). Seventy-eight percent of

individuals aged 25 or over in North Carolina have a

high school degree or higher (U.S. Census, 2000). The

state median income in 2003 was $46,000 (U.S. Census,

2003). Among children, age 18 or younger in the

general population, 56 percent have private health

insurance, 23 percent have Medicaid, and 7 percent

have no insurance (national estimates from the Med-

ical Expenditure Panel Survey in 2002; Rhoades &

Cohen, 2004).

The older elementary children (9–11 years) were

more likely to have a diagnosis of Asperger syndrome

or mental retardation, compared to younger children.

Studies of the rates of classical autism compared to

Asperger syndrome are sparse, but Fombonne suggests

a mean ratio of classical autism to Asperger syndrome

of roughly 4:1 (Fombonne, 2003). The rate was 3.5:1 in

the study sample. However, this rate was higher (5.5:1)

among younger children (4 years old or less), but much

lower (1.1:1) for older children. The sample prevalence

of mental retardation was much lower than the median

prevalence of 70 percent reported in a review of the

literature (Fombonne, 2002).

The study sample appears similar to those of other

epidemiological studies of ASD with respect to gender.

The proportion of boys in the sample was very close to

the mean ratio of boys to girls with ASD of 4.3 to 1 (or

86 percent boys) reported in a review of epidemiolog-

ical studies (Fombonne, 2003).

Major Treatment Approach for ASD

Three quarters of the families of the youngest (4 or

younger) children and two thirds of remaining families

reported using one or more of the listed major

treatment approaches for ASD (Table 2). No families

reported using the Denver model, so it was dropped

from the analysis. Thirty percent of the families of the

youngest children were using more than one approach;

use of multiple approaches diminished to 11 percent of

the older children. Just over half (55–62 percent) of

families used a TEACCH approach. One quarter to

one third of families said that they did not use any of

the listed major treatment approaches for ASD.

Service Use

Families were using a broad array of services. Table 3

lists the 56 services included in the survey instrument,

grouped by whether they are received in school or

outside school, and by category of service. The table

gives the percentage of families who were currently

using each service at the time of the survey by age of

the child (4 years or less, 5–8, or 9–11 years old).

Altogether, families were using 46 of the 56 services

listed. Families with children in the middle age group

(5–8 years old) were using a wider range of services (44

out of 56) compared to those with older (9–11 years

old) children (35 out of 56) or younger (4 years old or

less) children (31 out of 56). Cells with fewer than 3

families are reported as zero.

Predictors of Service Use

Table 4 shows logit models of any use for 16

different services that families use outside school.

Table 1 Sample characteristics: Child with ASD and family

Characteristic Percent Mean (SD)

Child characteristics: Age in years – 7 (2.4)

Age 4 years or less 26 Age 5–8 years 52 Age 9–11 years 22

Male 87 Race

White 76 African American 16 Other race 5

Hispanic 4 Autism diagnosis

Asperger syndrome 21 Classical autism 71 Pervasive developmental

disorder not otherwise specified 8

Mental retardation 20 Insurance coverage

Private insurance only 58 Medicaid but no private insurance 21 Medicaid and private insurance 8 Public insurance

(other than Medicaid) only 7

No major treatment approach 32

Family characteristics: Household composition

Two-parent household 77 Single parent household 22 Extended family household 9 Siblings – 1 (0.8)

Education Less than high school 1 High school degree 37 College degree 35 Graduate degree 27

Annual household income Less than $35,000 28 $35,000–$49,999 20 $50,000–$74,999 26 $75,000 or above 26

Well-being Family stress score – 10 (5.5)

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J Autism Dev Disord (2007) 37:1902–1912 1905

Each model had a significant fit according to a

likelihood ratio test (a = 0.05). Table 4 omits models for 4 services (after school care, psychiatrist, parent

support groups, and occupational therapy) used

outside school by over 10 percent of the sample

because the overall fit was not significant or the

model did not converge.

Predisposing Characteristics

Racial and ethnic minority families had half the odds

(OR = 0.48) of using a case manager, and only a

quarter the odds of using a psychologist (OR = 27),

developmental pediatrician (OR = 28), and sensory

integration (OR = 25). When parents had a college or

graduate degree, families had 2 to nearly 4 times the

odds of using a neurologist, the Picture Exchange

Communication System (PECS) and hippotherapy/

therapeutic horseback riding. When parents had higher

levels of stress, families had slightly higher odds

(OR = 1.1) of using a number of services: summer

camp or respite care, a case manager, medication and

supplements, PECS and hippotherapy/therapeutic

horseback riding. When families did not identify any

major treatment approach for ASD, they had between

one half and one fifth the odds of using care from

family or friends, PECS, parent training classes, sen-

sory integration and casein/gluten free diets. When

families were living in nonmetropolitan areas, they had

lower odds of using summer camp (OR = 0.33) and

respite care (OR = 0.21).

Enabling Characteristics

When children were covered by Medicaid or other

public insurance, families had from 2 to 11 times the

odds of using services that could be considered

medically necessary (medication) as well as therapeutic

support services (respite care, case manager, PECS,

speech/language therapy) compared to families whose

children were covered by private insurance. Con-

versely, when children were covered by Medicaid or

other public insurance, families had only one quarter

the odds of using supplements. When children did not

have health insurance, families had much higher odds

of using a case manager (OR = 4.94) and a develop-

mental pediatrician (OR = 16.60). When children did

not have health insurance, families did not have lower

odds of using any other services. Families that had an

annual income above $50,000 had higher odds of using

a developmental pediatrician and speech/language

therapy.

Need Characteristics

Families of children with Asperger syndrome had twice

the odds of those of children with classical autism of

using medication and one third or less the odds of using

PECS or casein/gluten free diets. Families of children

with mental retardation had twice the odds of using

respite care, a case manager, and sensory integration

therapy, and one quarter the odds of using a psychol-

ogist. Families of children 4 years old or less had at

least twice the odds of families whose children were

5–8 years old of using services that help define a

diagnosis and plan of treatment (case manager, devel-

opmental pediatrician), that help with communication

(PECS, speech/language therapy), as well as supple-

ments. They had half the odds or less of using services

for school-age children (special summer camp) a

psychologist, medications, and social skills training.

Families whose children were 9–11 years old had over

twice the odds of using respite care and a third or less

the odds of using PECS and sensory integration.

Table 2 Major treatment approaches for ASD

Age group:

£4 years 5–8 years 9–11 years

Approach Percent usinga: Anyc Alonec Any Alone Anyc Alonec

TEACCH 55 36 59 44 62 51 Applied Behavioral Analysis (ABA)b 22 5 16 3 9 4 Floor Time 17* 5* 7 0 5 0 Defeat Autism Now (DAN) 13 0 7 0 5 0 Lovaas 11 0 5 0 0 0 None of the above 24 na 35 na 33 na

a Percents do not add to 100 because families may use more than one approach; cells with fewer than 5 families coded as zero b Any approach based on ABA other than the Lovaas approach c v2 test of difference in percent of 5–8 yr olds using given approach compared to younger and older groups, df = 1, * significant difference a = 0.01

123

1906 J Autism Dev Disord (2007) 37:1902–1912

Discussion

In sum, families and their children with ASD used a

broad array of services; the breadth of services used was

highest for children aged 5–8 years. Access to care was

limited for racial and ethnic minority families, those with

low levels of education, those who were not using a

major treatment approach, and those living in nonme-

tropolitan areas. Family use of a major treatment

approach or multiple approaches for ASD was lower

for older age groups of children, although the majority of

families of children in the older age group (9–11 years

old) still used one approach. When parents had higher

levels of stress, the odds of service use were higher.

Medicaid and more family income also increased the

odds of use. When children did not have any health

Table 3 Autism-related service use: In school and outside school by age group

Age in years Age in years

Service Percent using b : £4 5–8 9–11 Service Percent usingb: £4 5–8 9–11

In school a

Speech/language therapy 91 79 65 Occupational therapy 60 66 42 Social skills training 29 28 46 Physical therapy 9 11 6 Adaptive physical education 4 13 16 Music therapy 6 8 6 Audiologist 0 2 0

Outside school Child care services Social therapies

Care from family or friends 64 58 55 Social skills training 6 16 24 Special summer camp 6 16 24 Hippotherapy/therapeutic riding 7 13 7 Respite care 14 10 22 Play therapy 16 7 6 After school care 0 12 13 Music therapy 8 6 0 Day care 12 3 0 Holding therapy 0 2 0 Residential placement 0 0 0 Dog therapy 0 2 0

Dolphin therapy 0 0 0 Other specialist providers Aversive 0 0 0

Case manager 41 24 35 Neurologist 15 18 16 Sensory/motor therapies Developmental pediatrician 20 10 9 Sensory integration therapy 22 22 12 Psychologist 5 13 23 Occupational therapy 21 11 11 Psychiatrist 0 14 24 Auditory integration 0 3 4 Behavioral specialist 9 8 5 Physical therapy 4 0 0 Therapeutic Support Person 0 6 9 Craniosacral trt, myofacial release 0 0 0 Personal Care Assistant 0 4 18 Squeeze machine 0 0 0 Audiologist 0 2 0

CAM therapies Medications & supplements Casein free diet 19 9 6

Medication 36 52 68 Gluten free diet 18 7 6 Supplements 26 13 15 Feingold diet 6 2 0

Specialized eye glasses 0 3 5 Communication therapies/systems Enzyme potentiated desensitization 0 2 0

Picture exchange communication 35 18 10 Immune system therapy 0 0 0 Speech/language therapy 29 15 10 Secretin 0 0 0 Facilitated communication 0 2 0 Acupuncture 0 0 0 Fast for word computer program 0 2 0 Cranial electrical stimulation 0 0 0

Flexyx neurotherapy system 0 0 0 Family services

Parent support groups 36 29 31 Parent training classes 7 12 15 Family counseling 0 6 11 Sibling support groups 0 0 4

a n = 85, 186, 81 children in preschool or school ages £4, 5–8, 9–11 years respectively b Cells with fewer than three families rounded to 0

CAM = complementary and alternative medicine

123

J Autism Dev Disord (2007) 37:1902–1912 1907

insurance, the odds of their family receiving services that

facilitated entry into the system of care was increased.

The mix of services families use varied with the child’s

ASD diagnosis and age, and findings indicate a higher

rate of Asperger syndrome in older children. These

findings are consistent with prior work (Ruble et al.,

2005; Kraus et al., 2003; Birenbaum & Cohen, 1993;

Birenbaum, Guyot & Cohen, 1990), but expand the view

of access to incorporate a wide range of autism-related

services. Disparities in service use associated with race,

residence and education point to the need to develop

policy, practice and family-level interventions that can

address barriers to services for all children with ASD.

Generalizability

This study was based on a community sample of

families in North Carolina which is widely considered

to have a comprehensive service system for young

children with ASD. This service system is supported by

Division TEACCH which provides assessment and

referral services through nine regional centers across

the state. TEACCH also provides training for parents

and teachers. To the extent that TEACCH facilitates

access to ASD services, analysis of access to care in

North Carolina may hide certain barriers to care that

are important in non TEACCH environments. From

this perspective, this analysis provides a conservative

view of barriers to care for ASD. On the other hand, it

is important to note that about 40 percent of sample

families reported that they were not using TEACCH.

Some of these families were using other major treat-

ment approaches, but most were not using any

approach. Study recruitment with the help of schools

and state assessment agencies was effective in bringing

in families outside of TEACCH. Although these

families may have benefited from TEACCH influence

throughout the state, they provided variation in the

parent perspective on major treatment approach and

how that approach impacts decision-making about

patterns of service use.

It is important to keep in mind that these findings

were derived from a sample of families who volun-

teered to participate and were identified because of

their use of services or connection to ASD information

resources. These were families who had the time to

devote energy to completing a survey. Reports from a

treated sample are likely to overestimate the use of

services compared to the general ASD population.

This sample was likely to be missing families with few

disposable resources, families who might be unsure if

their child had ASD, who were not well-connected

Table 4 Factors associated with use of services, by service

Variable C a re

f ro

m F

a m

ily

o r

F ri e n d s

S p e ci

a l S

u m

m e r

C a m

p

R e sp

ite C

a re

C a se

M a n a g e r

N e u ro

lo g is

t

D e ve

lo p m

e n ta

l P

e d ia

tr ic

ia n

P sy

ch o lo

g is

t

M e d ic

a tio

n

S u p p le

m e n ts

P ic

tu re

E xc

h a n g e

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