Adolescent ADD/ADHD 0
Adolescent ADD/ADHD and Risky Behavior: Prevalence, Odds,
and Health-Care Costs
Lise Youngblade, PhD
Florida Center for Medicaid & the Uninsured
College of Public Health and Health Professions
University of Florida
352/273-5059
Sponsored by
The Agency for Health Care Administration
Florida Center for Medicaid and the Uninsured
Shapig. n g Hearhcae Policr
June, 2004
Adolescent ADD/ADHD 1
Background
Attention deficit/hyperactivity disorder (ADD/ADHD) is a commonly diagnosed childhood
behavioral disorder, estimated to affect 3 to 5 percent of school-age children and leading to
numerous pathological outcomes including higher rates of injury, problems in school, family and
societal disruptions.1 Less is known about ADD/ADHD during adolescence, in part because all
major diagnostic criteria have been developed on younger children.1 Longitudinal population-
based cohort estimates of adolescent ADD/ADHD in individuals who were diagnosed during
childhood suggest that about 5 to 7 percent of adolescents are affected by ADD/ADHD,
depending on whether probable or definite diagnoses are made.2 Other estimates of adolescent
ADD/ADHD vary more broadly based on whether school-based or community-based samples
are drawn.3 ADD/ADHD is thought to develop early and, contrary to previous beliefs, often
persists into adolescence and adulthood.4
As children with ADD/ADHD grow older, they become at increased risk for substance
abuse, teenage pregnancy, delinquent and antisocial behavior, and injuries of all sorts,
particularly if the condition remains untreated.5'6'7'8 A previous study revealed that healthcare
costs are substantially higher for low-income adolescents engaging in risky behavior versus
those that do not, and that these adolescents have a higher proportion of health care in
Emergency Department (ED) settings than adolescents who do not engage in risky behavior.9
Because of demonstrated links between ADD/ADHD and risky behavior,5'6'7'8 analyses in the
current paper investigate the probability of engaging in risky behavior for adolescents diagnosed
with ADD/ADHD compared to those who are not, and examine the concomitant healthcare costs
associated with ADD/ADHD and risky behavior.
Interestingly, while the increased use of mental health, social and special education
services for children with ADD/ADHD have been well documented,5'10 as have the social,
behavioral, and academic consequences of ADD/ADHD,10,11 with few exceptions, the use and
Adolescent ADD/ADHD 2
costs of medical care for individuals with ADD/ADHD remains overlooked.2'8 Adolescents,
particularly those engaging in risk-taking behaviors and those with special health care needs
such as ADD/ADHD, require an array of preventive care, diagnostic, and treatment services.
Thus, analyses of healthcare use and costs are greatly needed in order to ensure that adequate
financing, provider network and service delivery systems are developed to best meet the needs
of the adolescent population, especially those at risk for high-cost health care.
The goals of the present study were to investigate: (a) the prevalence of ADD/ADHD in
a general pool of low-income adolescents enrolled in Medicaid; (b) the probability of risky
behavior and of inpatient and ED use, based on ADD/ADHD diagnosis; and (c) the concomitant
health-care charges for those engaging in risky behavior.
Method
Data Sources
Study participants were adolescents (aged 11.5 to 19 years of age) enrolled in the Florida
Medicaid Program during FY 2002 and FY 2003, who had at least one encounter with the
medical system. The Florida Agency for Health Care Administration provided person-level
enrollment, claims, and encounter data for use in these analyses. The enrollment files
contained the adolescents' age, gender, and number of months enrolled in the program. The
claims and encounter files contained International Classification of Diseases 9th Revision
Clinical Modification (ICD-9-CM) codes, Physician's Current Procedural Terminology (CPT)
codes, inpatient hospitalization codes, and dates that the health care services were provided.
Description of Variables Used
Identification of Adolescents with ADD/ADHD and Risky Behaviors
Adolescents who had at least one contact with the medical system during the time
period were included in this study. Adolescents with ADD/ADHD were identified by searching
Adolescent ADD/ADHD 3
the claims and encounter data for at least two independent occurrences of the ICD-9-CM code
(314.0) for ADD/ADHD. Two occurrences were imposed to guard against rule-out visits.
Adolescents engaging in risky behaviors were identified using ICD-9-CM codes found in
the claims and encounter data.9 A panel of three physicians at the University of Florida
developed a list of ICD-9-CM codes that might be indicative of risky behavior, such as alcohol or
drug treatment, injuries, and sexually transmitted infections. It should be noted that there is a
fair degree of controversy about whether normal pregnancy should be indicative of a "risky
behavior" or not. On the one hand, it is a prevalent diagnosis for older adolescents; on the other
hand, given the well documented maladaptive outcomes of teenage pregnancy, particularly for
single mothers, it can be considered a risky behavior. In this study, given the prevalence of
pregnancy, especially in later adolescence, we chose not to include it in the list of diagnoses
indicative of risky behavior. As a check, however, we re-ran all multivariate analyses both ways,
and the direction of effects was identical whether pregnancy was included or not, although the
descriptive information and magnitude of effects differed somewhat. Thus, in this study, risky
behavior identification does not include pregnancy.
The list was reviewed by an expert at the National Association of Children's Hospitals
and Related Institutions (NACHRI) and further refined. The final list contained 2,199 diagnostic
codes indicative of risk-taking behaviors. Single diagnostic codes were used to define risky
behaviors. Mental health and substance abuse services were included as risky behavior
diagnoses, although mental health services linked to mental disorder (such as schizophrenia)
were considered a special health care need rather than a risky behavior and were therefore not
included as risky behaviors. In addition, to avoid a potential tautology owing to the fact that
mental health services are part of ongoing treatment for many with ADD/ADHD, mental health
visits that contained an ICD-9-CM code of ADD/ADHD were not considered as indicative of risky
behavior.
Adolescent ADD/ADHD 4
Health Care Charges
Monthly health care charge rates were developed for each adolescent using the claims
and encounter data. Outpatient encounters included all preventive and acute care services in
office, clinic, and hospital settings. Physical, occupational, and speech therapies, as well as
home health, mental health and substance abuse services were included in both outpatient and
inpatient settings. Emergency department (ED) and inpatient charge rates were developed
using the presence of an ED code or a hospital admission date in the records.
Health care charge data were calculated using the Medicaid fee schedule. Per person
charge variables were expressed as dollars per adolescent per month (i.e., monthly per person
inpatient, outpatient, ED, and total charges).
Analysis Plan
Charge variables were expressed as dollars per adolescent per month. Monthly rates
were computed because of variability in enrollment. These rates were compared using
Wilcoxon rank sum tests between adolescents with no ADD/ADHD or risky behavior condition
and adolescents with ADD/ADHD, adolescents with risky behavior, and adolescents with both
ADD/ADHD and risky behavior. Odds of risky behavior and of hospital inpatient and Emergency
Department visits were calculated using logistic regression.
Results
Table 1 presents sample characteristics for adolescents with ADD/ADHD, adolescents
engaging in risky behaviors, adolescents with both diagnoses, and adolescents with neither
diagnosis. From the population of adolescents enrolled during FY 2002 and FY 2003 in the
Florida Medicaid Program who had at least one contact with the medical system (n= 284,882),
11,262 (3.95%) adolescents were identified as having ADD/ADHD. Males were over-
represented in the ADD/ADHD group, as compared to the group with no ADD/ADHD diagnosis.
Adolescent ADD/ADHD 5
Overall, 32.14% of the total pool (n=91,569) was identified as engaging in risky behavior.
Females were more likely to be identified as engaging in risky behavior than males. When
separated by whether or not adolescents had ADD/ADHD, 40.45% of those with ADD/ADHD
had risky-behavior diagnoses, as compared to 31.80% of those without ADD/ADHD.
Odds of Engaging in Risky Behavior
Logistic regression was used to predict the odds of engaging in risky behavior based on
ADD/ADHD diagnosis, after controlling for age, gender, and months enrolled in the program. As
seen in Table 2, after controlling for age, gender, and enrollment months, adolescents with
ADD/ADHD were about twice as likely to engage in risky behavior as those who did not have a
diagnosis of ADD/ADHD.
Table 1. Study Population Characteristics
Characteristic Adolescents with ADD/ADHD Adolescents with No ADD/ADHD
Risky Behavior No Risky Risky Behavior No Risky Behavior
Behavior
N 4,555 6,707 87,014 186,606
(%) (40.45%) (59.55%) (31.80%) (68.20%)
Gender: Female 1,305 1,320 61,541 99,585
(28.65%) (19.68%) (70.73%) (53.37%)
Male 3,250 5,387 25,473 87,016
(71.35%) (80.32%) (29.27%) (46.63%)
Mean Age in 13.33 12.97 15.27 14.29
Years (1.68) (1.62) (2.09) (2.17)
(Std. Dev.)
Mean Months 22.10 20.48 18.00 15.14
Enrolled (4.13) (5.64) (6.89) (7.64)
(Std. Dev.)
Adolescent ADD/ADHD 6
Table 2. Odds Of Risky Behavior Based On ADD/ADHD Diagnosis
Effect Point Estimate Confidence Intervals Significance
Age 1.250 1.245, 1.255 .0001
Gender 0.523 0.514, 0.533 .0001
Months Enrolled 1.069 1.068, 1.070 .0001
ADD/ADHD 1.950 1.871, 2.032 .0001
Notes. Age and months enrolled are continuous variables. Gender is coded 1= male,
0=female. ADD/ADHD is coded 1=ADD/ADHD, 0= no ADD/ADHD.
Odds of Inpatient and ED Use
Since inpatient use and emergency room visits are relatively rare events in the
adolescent population, the odds that adolescents with ADD/ADHD, especially those engaging in
risky behavior, would use these categories of service were computed. Logistic regression was
used to predict the odds of having an Emergency Department (ED) visit (Table 3) or inpatient
stay (Table 4) based on age, gender, risky behavior and diagnosis of ADD/ADHD. As seen in
Table 3, having a diagnosis of ADD/ADHD slightly increased the odds of an ED visit. Those
with risky behavior were more than four times as likely as those without risky behavior to have
an ED visit. The odds of an ED visit were highest for those adolescents with ADD/ADHD and
engaging in risky behavior: more than 6 times as likely to have an ED visit as all others.
With respect to inpatient utilization, those with ADD/ADHD were somewhat more likely to
have an inpatient stay than those without ADD/ADHD. The odds of an inpatient stay were about
two times higher for those engaging in risky behavior as compared to those who were not, and
the odds of inpatient utilization for those with ADD/ADHD and engaging in risky behavior were
about twice those of all others (see Table 4).
Adolescent ADD/ADHD 7
Table 3. Odds of Emergency Department Visit Based on ADD/ADHD and Risky Behavior
Effect Point Estimate Confidence Intervals Significance
Age 1.023 1.019, 1.027 .0001
Gender 1.175 1.154, 1.977 .0001
Months Enrolled 1.048 1.047, 1.049 .0001
ADD/ADHD 1.094 1.034, 1.158 .01
Risky Behavior 4.439 4.358, 4.523 .0001
ADD/ADHD and Risky 6.655 6.239, 7.099 .0001
Behavior__
Notes. Age and months enrolled are continuous variables. Gender is coded 1= male,
0=female. ADD/ADHD is coded 1=ADD/ADHD, 0= no ADD/ADHD. Risky Behavior is coded
1=risky behavior, 0=no risky behavior. ADD/ADHD and Risky Behavior is coded 1=both
diagnoses, 0=everyone else.
Table 4. Odds of an Inpatient Stay Based on ADD/ADHD and Risky Behavior
Effect Point Estimate Confidence Intervals Significance
Age 1.152 1.147, 1.156 .0001
Gender 0.751 0.738, 0.764 .0001
Months Enrolled 1.010 1.009, 1.011 .0001
ADD/ADHD 1.282 1.211, 1.357 .0001
Risky Behavior 2.041 2.005, 2.078 .0001
ADD/ADHD and Risky 1.995 1.875, 2.123 .0001
Behavior__
Notes. Age and months enrolled are continuous variables. Gender is coded 1= male,
0=female. ADD/ADHD is coded 1=ADD/ADHD, 0= no ADD/ADHD. Risky Behavior is coded
1=risky behavior, 0=no risky behavior. ADD/ADHD and Risky Behavior is coded 1=both
diagnoses, 0=everyone else.
Adolescent ADD/ADHD 8
Health Care Charges
The next set of analyses examined the average monthly health care charges (outpatient,
inpatient, and emergency department charges, and their total) of adolescents with and without
ADD/ADHD and, further, between those who engaged in risky behavior and those who did not.
As seen in Table 5, the average monthly per person total health-care charges were highest for
adolescents with ADD/ADHD who were engaging in risky behavior. However, the highest ED
and inpatient charges were for those who were engaging in risky behavior; however, there was
no difference in ED and inpatient charges for those engaging in risky behavior based on
ADD/ADHD diagnosis.
Table 5. Monthly Per Person Charges Associated with ADD/ADHD and Risky Behavior
Dollars/person/month: Adolescents with ADD/ADHD Adolescents with no
Mean ADD/ADHD
(Std. Dev.) Risky No Risky Risky No Risky
Behavior Behavior Behavior Behavior
Outpatient $198.45 $135.59 $95.04 $56.47
($214.10) ($179.42) ($158.18) ($143.41)
Inpatient $86.77 $26.17 $95.65 $48.42
($201.92) ($147.18) ($379.43) ($334.96)
Emergency Department $3.88 $1.06 $3.91 $1.36
($4.38) ($2.62) ($7.16) ($5.34)
Total $289.10 $159.82 $194.6 $106.25
($330.24) ($249.22) ($458.59) ($407.62)
Notes. Using Wilcoxon rank sum tests, all pairwise comparisons to the group with no
ADD/ADHD and no risky behavior were significant at p < .05.
Moderation by Medication
The purpose of the last set of analyses was to examine medication use in this
population, both descriptively and as a moderator of the effect of ADD/ADHD on the odds of
risky behavior. Of the adolescents with ADD/ADHD, about 69.93% (n=7,876) had prescriptions
for at least one medication for ADD/ADHD. Table 7 provides a descriptive summary of the type
of medication prescribed for ADD/ADHD. The majority of those receiving medication were
receiving stimulants (75.08%). About 9% received anti-depressants, and about 16% received
Adolescent ADD/ADHD 9
prescriptions for both. Considering the total number of prescriptions for ADD/ADHD, stimulants
accounted for about 80% of filled prescriptions. Average per capital costs for ADD/ADHD
medication were $21.05 (sd=$27.93) per month.
Table 7. Medications Prescribed for Treatment of ADD/ADHD
Medication Number (%) Adolescents % of All Prescriptions for
with ADD/ADHD Receiving ADD/ADHD
this Drug
Stimulants 5,914 81.07%
(75.08%)
Anti-Depressants 688 18.93%
(8.74%)
Both 1,274
(16.18%)
Next, we examined the probability of engaging in risky behavior for adolescents
diagnosed with ADHD on medication compared to those with ADHD who are not on medication.
Accordingly, a logistic regression was run using the sample of those adolescents who were
diagnosed with ADD/ADHD. The outcome variable was the odds of risky behavior. The
predictors were age, gender, months enrolled, and whether they were on medication or not. As
seen in Table 8, contrary to expectations, medication use did not cut the odds of engaging in
risky behavior for those with ADD/ADHD. Instead, medication use was associated with a higher
likelihood of being identified as engaging in risky behavior.
Because this was an unexpected finding, we also considered the medication type
(stimulant, anti-depressant, or both) and re-ran the analysis using medication type as a
predictor. As seen in Table 9, when compared to non-medicated adolescents with ADD/ADHD,
those on medication have higher odds of risky behavior, with the highest odds associated with
the use of anti-depressants. These two analyses may indicate that adolescents with more
severe symptomatology may be placed on medication for their ADD/ADHD. However, because
Adolescent ADD/ADHD 10
this is a correlational study, we have no way of ascertaining the direction of effects. Clearly, this
is an area that requires further study.
Table 8. Odds of Risky Behavior Diagnosis for Adolescents with ADD/ADHD
Effect Point Estimate Confidence Significance
Intervals
Age 1.165 1.138, 1.193 .0001
Gender 0.607 0.555, 0.664 .0001
Months Enrolled 1.070 1.061, 1.079 .0001
Medication Use 1.240 1.138, 1.352 .0001
Notes. Age and months enrolled are continuous variables. Gender is coded 1= male,
0=female. Medication use is coded 1=yes, 0=no.
Table 9. Odds of Risky Behavior Diagnosis for Adolescents with ADD/ADHD by
Specific Medication Class
Effect Point Estimate Confidence Significance
Intervals
Age 1.161 1.134, 1.189 .0001
Gender 0.612 0.559, 0.670 .0001
Months Enrolled 1.069 1.060, 1.078 .0001
Anti-Depressants 1.676 1.415, 1.986 .0001
Stimulants 1.136 1.038, 1.244 .01
Both 1.557 1.361, 1.781 .0001
Notes. Age and months enrolled are continuous variables. Gender is coded 1= male,
0=female. Medication use is coded: Stimulants 1=yes, 0=no; Anti-depressants 1=yes,
0=no; both 1=yes, 0=no; the referent medication group is "none".
Adolescent ADD/ADHD 11
The last analysis compared the costs of ADD/ADHD and risky behavior based on
whether the adolescent was receiving medication for ADD/ADHD or not. As seen in Table 10,
the mean total charges (sum of inpatient, outpatient, and ED) for those with ADD/ADHD and
who were treated with medication were less than those who were not receiving medication,
although this was not a statistically significant difference. For those with ADD/ADHD who were
engaging in risky behavior, the same pattern held, but was a statistically significant difference
(t=5.19, p < .0001). Thus, even though medication use did not reduce the odds of risky
behavior, it did reduce the costs of risky behavior. This perhaps suggests that, if it is the case
that the more severe adolescents are placed on medication, the significance of their
symptomatology and the severity of their risky behavior is reduced. Again, this needs further
study.
Table 10. Costs of ADD/ADHD and Risky Behavior, by Drug Use
Mean Total Charges
On Medication No Medication
Adolescents with ADD/ADHD $206.69 $224.70
($273.62) ($329.78)
Adolescents with ADD/ADHD and Risky Behavior $274.39 $327.98
($313.33) ($367.67)
Conclusions
The purpose of this study was to investigate: (a) the prevalence of ADD/ADHD in a
general pool of low-income adolescents enrolled in Medicaid; (b) the probability of risky
behavior and of inpatient and ED use, based on ADD/ADHD diagnosis; and (c) the concomitant
health-care charges for those engaging in risky behavior. The results of this study underscore
links between ADD/ADHD, risky behavior, and health-care costs.
Using data from the Florida Medicaid program, these analyses documented that roughly
four per cent of the adolescents using health care services had ADD/ADHD. This prevalence
Adolescent ADD/ADHD 12
rate is close to, but slightly less than, that generally reported for children and adolescents.1'2
Prevalence comparisons across studies are complicated, however, due to a number of factors.
Some of the differences are due to different sampling strategies and populations studied. In
addition, differences emerge because of variations in the methodology for identifying individuals
with ADD/ADHD claims and encounter versus parent report versus standardized clinical
protocols. Further, there is currently no diagnostic "gold standard" specific to adolescents and
adults; diagnostic criteria are extrapolated from those developed for children. This, too,
contributes to the inconsistency among prevalence reports.
Two additional factors specific to our methodology may also deflate the prevalence rate,
relative to other population based studies. First, our analyses were restricted to health-care
users; thus, adolescents who were enrolled in the program but had no contact with the health-
care system during the study period are not represented in this estimate. Second, we relied on
submitted claims and encounter data. This methodology allows for the study of large pools of
individuals. However, the validity of the data is only as good as what is originally coded for
reimbursement. Thus, diagnoses that appear in charts but are not coded for reimbursement are
not represented in this estimate.
The second and third goals of this study were to examine the odds of risky behavior and
the odds of infrequently used but high cost categories of service for individuals with and
without ADD/ADHD, and their concomitant charges. This study showed that adolescents
diagnosed with ADD/ADHD were at heightened risk for engaging in risky behavior,
demonstrating two-fold odds of risky behavior compared to adolescents who did not have
ADD/ADHD. Moreover, the health-care charges attributable to ADD/ADHD, especially in
combination with risky behavior, were substantially higher when compared to those with out
ADD/ADHD and not engaging in risky behavior.
Three previous studies have examined the health-care use and costs patterns for
children and adolescents with ADD/ADHD compared to those without, with mixed results. One
Adolescent ADD/ADHD 13
study found no differences in the likelihood of ambulatory care visits during the prior six months
between children with and without ADD/ADHD.12 A second study, using data from a large
national survey, found that children with ADD/ADHD had more physician visits than non-ADHD
children, but there were no differences in hospitalizations between those with and without
ADD/ADHD.6 The third, and most comprehensive, of these studies was a large population-
based cohort study of 4,880 children followed during a 9-year period.2 These researchers found
by searching medical billing records that individuals with ADD/ADHD had a higher likelihood of
hospital inpatient, hospital outpatient, and ED admissions, and median costs were more than
double the costs of individuals without ADD/ADHD. The differences were similar for males and
females, and across all age groups, including adolescents. The results of the current study
build on this work. Using claims and encounter methodology similar to that used by Leibson et
al.,2 our analyses show higher odds of and charges associated with inpatient and ED use for
adolescents with ADD/ADHD, but further, that the odds and costs associated with ADD/ADHD
are exacerbated by its link with risky behavior.
Notably, in this paper, risky behavior is considered a broad-band composite, reflecting
many different specific risky behaviors. This is not to argue that a focus on specific risky
behaviors is not useful, but rather that the experience of programs serving diverse, basically
healthy populations, is likely to reflect a broad sampling of risky behavior. Thus, this "non-
categorical," broad-band approach to defining risky behaviors should be of use to insurers,
practitioners and health plans, as well as policy-makers who design health care programs. At
the same time, however, a generalist approach to defining risky behaviors masks the relative
associations between ADD/ADHD and specific risky behaviors, and understanding the specific
risky behaviors associated with ADD/ADHD not only has implications for use and cost patterns,
but also has significant implications for prevention efforts. Thus, future research is needed to
stratify risky behaviors and their links with ADD/ADHD.
Adolescent ADD/ADHD 14
The current study has several limitations. First, we did not assess adolescents' unmet
health care needs. The benefit package for Medicaid is rich and provides inpatient, outpatient,
emergency room care, and mental health services. However, it is possible that adolescents did
not receive all needed health care services and thus our health care use and charge
calculations may underestimate their true needs. Second, adolescents were categorized as
"engaging in risky behaviors" based on particular diagnoses. Those at risk who have not yet
manifested a diagnostic outcome in the claims and encounter data are underrepresented in our
analysis. Furthermore, because little information is available on what the right rate of use or cost
is for this population, caution is warranted in drawing conclusions about anticipating future
costs. An important next step would be to compare use and charges to standards of care where
they exist in order to benchmark the magnitude of increased use and charges for adolescents
with special health care needs, such as ADD/ADHD, or risky behavior. Finally, several cautions
are needed regarding the use of claims and encounter data. Diagnostic codes in claims and
encounter data are subjective, leading to potential biases in defining use and charges.
However, despite these limitations, this study has a number of important strengths,
including the following: (1) This study is among few population-based studies of adolescent
ADD/ADHD and among the first to examine health care use and charges for adolescents with
ADD/ADHD who are enrolled in Medicaid. (2) As opposed to parent or adolescent report,
diagnostic criteria from claims and encounter data were used to define groups, and thus allowed
analysis of a large pool of individuals. (3) In addition to total use and charges, charges were
calculated by category of service (outpatient, inpatient, ED). (4) Finally, all health care charges
and utilization were examined, not just that related to ADD/ADHD or to risky behavior. Thus,
these analyses reflect a total health-care portrait, as opposed to a condition-specific analysis.
In summary, the purpose of this study was to examine health care use and charge
patterns for a pool of adolescents with and without ADD/ADHD who were enrolled in Medicaid
services. The data indicated that adolescents with ADD/ADHD manifested higher odds of and
Adolescent ADD/ADHD 15
charges associated with inpatient and ED use, but further, that the odds and costs associated
with ADD/ADHD were magnified by its link with risky behavior. This study underscores the
importance of considering the unique needs of adolescents, including specific diagnostic
conditions and their association with costly medically-related behaviors, to ensure that adequate
financing, provider network and service delivery systems are developed to best meet the needs
of the adolescent population.
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