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Original Contribution |

Use and Costs of Medical Care for Children and Adolescents With and Without Attention-Deficit/Hyperactivity Disorder FREE

Cynthia L. Leibson, PhD; Slavica K. Katusic, MD; William J. Barbaresi, MD; Jeanine Ransom, BS; Peter C. O'Brien, PhD
[+] Author Affiliations

Author Affiliations: Departments of Health Sciences Research (Drs Leibson, Katusic, and O'Brien, and Ms Ransom) and Pediatric and Adolescent Medicine (Dr Barbaresi), Mayo Clinic, Rochester, Minn.


JAMA. 2001;285(1):60-66. doi:10.1001/jama.285.1.60.
Text Size: A A A
Published online

Context A shortage of data exists on medical care use by persons with attention-deficit/hyperactivity disorder (ADHD).

Objective To compare medical care use and costs among persons with and without ADHD.

Design and Setting Population-based cohort study conducted in Rochester, Minn.

Subjects All children born in 1976-1982 were followed up through 1995, using school and medical records to identify those with ADHD. The 4880 birth cohort members (mean age, 7.3 years) still residing in Rochester in 1987 were followed up in medical facility–linked billing databases until death, emigration, or December 31, 1995.

Main Outcome Measures Clinical diagnoses, likelihood and frequency of inpatient and outpatient hospitalizations, emergency department (ED) visits, and total medical costs (including ambulatory care), compared among individuals with and without ADHD.

Results Among the 4119 birth cohort members who remained in the area through 1995 (mean age, 15.3 years), 7.5% (n = 309) had met criteria for ADHD. Compared with persons without ADHD, those with ADHD were more likely to have diagnoses in multiple categories, including major injuries (59% vs 49%; P<.001) and asthma (22% vs 13%; P<.001). The proportion with any hospital inpatient, hospital outpatient, or ED admission was higher for persons with ADHD vs those without ADHD (26% vs 18% [P<.001], 41% vs 33% [P = .006], and 81% vs 74% [P = .005], respectively). The 9-year median costs for persons with ADHD compared with those without ADHD were more than double ($4306 vs $1944; P<.001), even for the subset with no hospital or ED admissions (eg, median 1987 costs, $128 vs $65; P<.001). The differences between individuals with and without ADHD were similar for males and females and across all age groups.

Conclusion In our cohort, compared with persons without ADHD, those with ADHD exhibited substantially greater use of medical care in multiple care delivery settings.

Figures in this Article

Attention-deficit/hyperactivity disorder (ADHD) is a relatively common behavioral disorder of childhood, with important consequences for affected individuals, their families, and society.1,2 The financial burden of ADHD, however, has not been well described.1 Individuals with ADHD have been shown to exhibit increased use of mental health, social, and special education services,3,4 but there is a paucity of information on the use and costs of medical care.

The present study took advantage of the previous application of standardized research criteria for ADHD among members of a large population-based birth cohort.5,6 Members were followed up in a medical facility–linked billing data system over a 9-year period from a minimum of age 5 years to a maximum of age 19 years. Members with and without ADHD were compared for comorbid clinical diagnoses, the likelihood and frequency of emergency department (ED) visits, inpatient and outpatient hospitalizations, and total medical (including ambulatory care) costs.

Sample Description

All children born January 1, 1976, through December 31, 1982, to mothers residing in Rochester, Minn, townships that comprise Independent School District 535 (N = 8548) were previously identified using Minnesota Department of Health computerized birth certificate information.6 Each birth cohort member was retrospectively followed up using his/her medical and school records for evidence of ADHD until the earliest event of emigration, death, or December 31, 1995.5 Because formal diagnostic criteria for ADHD are typically met after children enter the school system, the review was limited to the 5718 cohort members who had not died or emigrated before age 5 years. The identification of ADHD among birth cohort members was facilitated because Rochester is geographically isolated and home to the Mayo Clinic, one of the world's largest referral centers. Therefore, local residents receive medical services from a limited number of providers, primarily Mayo Clinic and Olmsted Medical Center, another group practice, and their affiliated hospitals. Since 1907, information from every Mayo encounter has been contained within a patient-based medical record. Under the auspices of the Rochester Epidemiology Project,7 access to the medical records was expanded to include other medical facilities in and around Rochester, including Olmsted Medical Center and the area's few private medical practitioners. The medical records contain complete (hospital inpatient, hospital outpatient, ED, physician's office, and specialty clinic encounters) and detailed information (all clinicians' notes; psychiatric and neurological examinations, surveys, and questionnaires; all other diagnostic and laboratory results; and correspondence) from essentially all providers of care to local residents.

Permission was also obtained to access the resources of Independent School District 535, including the complete school records of all birth cohort members ever registered at any of the district's public, parochial, or private schools, plus those cohort members who were home schooled. The school records include medical reports, medication records, private tutoring or evaluation reports, individual and group-administered ability and achievement tests, and notations from teacher, parent, or other person related to any type of school performance difficulty. The district uses a standardized protocol for referrals for any type of difficulty in school performance, learning, or other potentially handicapping condition. A referral form is filled out and depending on the type and extent of the difficulty, an individual educational assessment report is filed, a meeting is held that includes both parents and teachers, and an individual education program is developed. Copies of all reports, meeting minutes, assessments, and periodic reassessments and reviews are maintained in the record and were included in the review for ADHD.

The medical and school records were reviewed by a trained abstractor, under the supervision of a developmental behavioral pediatrician (W.J.B.). The records were reviewed for (1) clinical diagnoses of ADHD or ADHD-like conditions, (2) parent or teacher questionnaires that assess ADHD symptoms, with scores that were at least 1 SD above the mean (t score ≥60) defined as positive, and (3) diagnostic criteria for ADHD as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV).8 Review for the latter was facilitated with an extensive dictionary of words/terms consistent with ADHD symptoms as specified in DSM-IV that was developed and pilot tested as part of the ADHD incidence study.5 Data on date, setting (home or school), and informant (teacher, parent, physician, or psychologist) were also abstracted.

Information obtained from the medical and school records was used to categorize each of the 5718 individuals as either having (1) definite ADHD, which consisted of a clinical diagnosis plus supporting documentation (ie, positive questionnaire results or problems consistent with DSM-IV criteria or both); (2) probable ADHD, which consisted of either a clinical diagnosis, but no supporting documentation or no clinical diagnosis, but both types of supporting documentation; or (3) neither definite nor probable ADHD.5,9 In this report, ADHD case status included both definite and probable cases.

Use and Cost Data

Studies of medical care use by Rochester residents are facilitated by the geographical isolation and small number of providers. More than 95% of all hospitalizations among residents occur at the 3 area hospitals affiliated with the 2 practice groups, Mayo Clinic and Olmsted Medical Center (1988 MEDPAR file, Health Care Financing Administration). Since 1987, use and billing data from these institutions are electronically linked; individuals are identified across institutions and over time. Therefore, the capacity exists to capture information on all hospital and ambulatory care delivered by these providers to area residents from January 1, 1987, through the present.1013 The files serve as a major source of financial information and include line-item detail on date, type, frequency, and billed charge for every good or service provided.

This study assigned a standardized, inflation-adjusted cost to each line item using a recently developed unit-costing algorithm.14 The algorithm differs depending on whether an item is covered under Medicare Part A or Part B. The distinction is methodological and does not imply that the database covers only Medicare patients. Costs for Medicare Part A items (ie, primarily hospital-billed items provided to inpatients [eg, room and board, radiology, physical therapy, supplies, etc]) are assigned using Medicare cost reports. These reports include the total costs allocated to each revenue-generating cost center within the hospital and the total charges billed by each cost center, thus affording calculation of a cost-to-charge ratio for each cost center at each of the 3 local hospitals for each year. Because the line-item detail includes a designated cost center and a billed charge for each item, a cost for each item can be calculated by multiplying the billed charge by the cost-center–specific cost-to-charge ratio for the year in which the service was delivered. The algorithm applies an inflation adjuster,15 and adjusts for geographical wage differences16 to express the costs for each year in 1995 national average dollars.

Medicare Part B items consist primarily of those billed by physicians (eg, examinations and consultations, diagnostic and therapeutic procedures), irrespective of the site of care. Part B also covers services (eg, laboratory, radiology, physical therapy, etc) provided to persons other than hospital inpatients. Part B items are identified using the Health Care Financing Administration Common Procedure Coding system. The costing algorithm uses Medicare national fee schedules that provide a published allowed fee for each item coded by the Health Care Financing Administration Common Procedure Coding system. A cost is assigned to each item by applying the code-specific 1995 Medicare national average allowed fee, therefore no inflation or geographical adjustment is required.

Because 1987 was the first year complete data were available, the analyses of cost and use were limited to the 5151 members of the birth cohort who had not died or emigrated prior to 1987. Following identification of these individuals, a Minnesota State statute was instituted that required patient authorization for use of medical records for research.17 The 271 individuals who refused authorization were excluded from review. After receiving institutional review board approvals, we reviewed the records of each of the remaining 4880 individuals from January 1, 1987, until the earliest event of emigration, death, or December 31, 1995, for data on total costs, inpatient and outpatient hospitalizations, inpatient days, and ED visits.

The billing data also afforded characterization of birth cohort members with respect to comorbid clinical diagnoses. The Johns Hopkins Ambulatory Care Group case mix system software18 was used to categorize every International Classification of Diseases, Ninth Revision diagnosis code assigned to each person into 1 of 32 mutually exclusive diagnostic morbidity clusters known as an ambulatory diagnostic group (ADG). The assignment is based on clinical similarity; the likelihood of persistence or recurrence of the diagnosis, disability, and/or mortality; the expected need for return visits, continued treatment, specialist services, and/or hospitalization; and the expected need for and cost of diagnostic and therapeutic procedures.18,19 The ADG categorization scheme was particularly appropriate for the present study because it was derived from a sample that included children and adolescents and was developed for the purpose of examining differences in use.

Statistical Analysis

Analyses of use and cost were performed for each calendar year and during all 9 years; the latter were limited to persons residing in the area in 1995 (ie, who remained during the full period of follow-up). Between-group differences in the likelihood of admission were tested using the χ2 statistic. For persons with at least 1 admission, between-group differences in the number of admissions were analyzed using the Wilcoxon rank sum test. To test whether differences between persons with and without ADHD varied by age, the dollar costs (log transformation) in each year of age were regressed against age for each individual. Regression coefficients for persons with and without ADHD were compared using the t test. To test whether ADHD-associated costs varied by sex, the predicted (log-transformed) costs for each individual at ages 7, 12, and 17 years served as dependent variables in 3 separate regression analyses that included ADHD, sex, and an interaction term as predictor variables. The sample sizes afforded more than 90% power to detect a 22% increase in costs between individuals with and without ADHD.

There were 4880 members of the original 1976-1982 birth cohort residing in the area in 1987 (mean age, 7.3 years); 350 met criteria for definite (n = 284) or probable (n = 66) ADHD between the age of 5 years and the earliest date of emigration, death, or December 31, 1995. In this study, birth cohort members who met research criteria for an ADHD incidence case were defined as having the condition throughout the study period (ie, both before and after the date they met the criteria). The 350 ADHD individuals constituted 7.2% (5.8% definite, 1.4% probable) of the cohort in 1987; the mean (SD) age for individuals with and without ADHD was 7.2 (1.9) and 7.3 (2.1) years, respectively; males constituted 75% of individuals with ADHD and 50% of individuals without ADHD.

By 1995, 4119 members of the birth cohort were residing in the area; individuals with ADHD constituted 7.5% (6.1% definite, 1.4% probable); the mean (SD) age for individuals with and without ADHD was 15.2 (2.0) and 15.3 (2.0) years, respectively. The diagnoses assigned to these individuals since 1987 were categorized into ADG clusters. For each of the 32 ADG clusters, the proportions of individuals assigned at least 1 diagnosis in that cluster are provided in Table 1. Males and females with ADHD were more likely than their non-ADHD counterparts to have been assigned a diagnosis in almost every cluster. The differences reached significance for both males and females in the psychosocial clusters. Significant differences between ADHD and non-ADHD males were observed in a number of other clusters, including signs/symptoms, asthma, and major injuries. There were fewer clusters for which the differences reached significance for females, probably due in part to the smaller numbers of female ADHD cases. Females with ADHD were significantly more likely to have received a diagnosis of signs/symptoms and asthma than their non-ADHD counterparts.

Table Graphic Jump LocationTable. Ambulatory Diagnostic Group Clusters With and Without Attention-Deficit/Hyperactivity Disorder (ADHD)*

Data on the proportion of individuals with 1 or more medical encounters are provided by encounter type for individuals with and without ADHD for each of the years 1987-1995 in Figure 1. The annual likelihood of a hospital inpatient admission was small and was similar for individuals with and without ADHD in every year but 1992; among those admitted, the number of inpatient days was similar for individuals with and without ADHD in every year but 1994 (median, 8 vs 3 for ADHD and non-ADHD, respectively; P = .04). The likelihood of a hospital outpatient admission was greater for individuals with than without ADHD in 4 of the 9 years. Among those admitted, the median number of admissions was 1 for both groups in each year (P>.99 in 1987; P = .93 in 1988; P = .33 in 1989; P = .79 in 1990; P = .66 in 1991; P = .74 in 1992; P = .13 in 1993; P = .91 in 1994; and P = .60 in 1995). The likelihood of an ED admission was significantly increased for individuals with ADHD compared with individuals without ADHD in 8 of the 9 years; among those admitted, individuals with ADHD experienced significantly more admissions than individuals without ADHD in 5 of the 9 years (P = .02 in 1988; P = .002 in 1989 and 1990; and P = .04 in 1994 and 1995). An apparent decline in the proportion admitted to the ED after 1989 was likely due to a shift from ED to urgent care use following the opening of an urgent care facility in 1990.

Figure 1. Percentage of Individuals With 1 or More Admissions per Year, by Encounter Type and Attention-Deficit/Hyperactivity Disorder (ADHD) Case Status
Graphic Jump Location
Individuals were resident members of the 1976-1982 Rochester birth cohort in years 1987-1995. Asterisk indicates that differences between groups were statistically significant at P<.05; dagger, P<.01; and double dagger, P<.001.

In each year, the proportions of birth cohort members who were billed for any medical care services or procedures ranged from 84% to 91% for individuals with ADHD and 76% to 81% for individuals without ADHD. Medical care costs were higher for individuals with ADHD compared with those without ADHD in every year; comparisons of Part A (hospital-billed) and Part B (physician-billed) dollars revealed that the differences were greatest for Part B costs (Figure 2).

Figure 2. Annual Median Medical Care Costs for Individuals With and Without Attention-Deficit/Hyperactivity Disorder (ADHD)
Graphic Jump Location
Individuals were resident members of the 1976-1982 Rochester birth cohort who incurred costs in years 1987-1995. Data are provided for costs assigned to Medicare Part A or to Medicare Part B separately and are expressed in 1995 national average dollars. Asterisk indicates differences between groups for Medicare Part A were statistically significant at P<.01. Differences between groups for Medicare Part B were statistically significant at P<.001 in each year.

In addition to comparisons between individuals with and without ADHD for each year of follow-up, analyses were performed at the level of the individual during the full 9 years of follow-up. The analyses were limited to the 309 individuals with ADHD and 3810 without ADHD who were residing in the area in 1995. Whether between-group comparisons for these 4119 individuals were representative of the entire cohort was addressed by testing for a significant effect of ADHD, adjusted for age and sex, on the likelihood of remaining in the area to 1995. Individuals with ADHD were more likely to remain than were individuals without ADHD (odds ratio [OR], 1.13; 95% confidence interval [CI], 1.05-2.07; P = .02). The likelihood did not vary as a function of sex (P = .20); individuals who were older in 1987 were more likely to remain than those who were younger (P<.001). There were no interactions between ADHD and age or sex; thus the effects of age and sex on loss to follow-up were similar for individuals with and without ADHD.

Over the full 9 years, the likelihood of at least 1 admission was significantly increased for individuals with ADHD compared with individuals without ADHD for each encounter type: hospital inpatient (26% vs 18%; P<.001), hospital outpatient (41% vs 33%; P = .006), and ED visit (81% vs 74%; P = .005). Compared with their non-ADHD counterparts, individuals with ADHD who were admitted experienced similar numbers of inpatient days (median, 3 vs 2; P = .30) and outpatient admissions (median, 2 vs 2; P = .10), but more frequent ED visits (median, 4 vs 3; P<.001). Median costs for all episodes of care during the 9 years of follow-up for individuals with ADHD were more than double those for individuals without ADHD ($4306 vs $1944; P<.001). To assess the effect of age on costs, the log-transformed dollar costs in each year of age were regressed against year of age for each of the 4119 individuals. The regression coefficients differed from zero for both groups (ADHD, mean [SD], 0.06 [0.35]; P = .001; non-ADHD, 0.07 [0.32]; P<.001), and did not differ between groups (P = .70 using the t test). These findings suggest that costs increased with increasing age and that the age-associated increases were similar for individuals with and without ADHD. Three regression analyses, with predicted log-transformed costs at ages 7, 12, and 17 years as dependent variables and ADHD and sex as predictor variables, revealed costs were unaffected by sex at age 7 years (P = .70), but were higher for females than males at ages 12 (P<.001) and 17 years (P<.001). There was a significant association between ADHD and costs (P<.001) in all 3 models. Tests for interactions between sex and ADHD were insignificant, suggesting that the contribution of ADHD to medical costs was similar for males and females.

This population-based historical cohort study followed up 4880 individuals from 1987 (age range, 5-11 years) through 1995 (age range, 13-19 years) to compare individuals with and without ADHD for medical care use and costs. During the 9-year period, individuals with ADHD compared with those without ADHD exhibited a significantly increased likelihood of hospital inpatient, hospital outpatient, and ED admissions. Among those admitted, the numbers of inpatient days and outpatient admissions were similar for individuals with and without ADHD; individuals with ADHD experienced more ED admissions than did individuals without ADHD.

Median costs (including ambulatory costs) for individuals with ADHD were greater than double the costs for individuals without ADHD. The differences between individuals with and without ADHD were similar for males and females and were consistent over all ages. The differences were greatest for Medicare Part B (physician-billed) costs. The increases remained significant in analyses limited to individuals who experienced some costs but did not experience any hospital inpatient, hospital outpatient, or ED admissions (eg, median 1987 costs were $128 vs $65 for individuals with and without ADHD, respectively; P<.001). These findings suggest that non-ED, nonhospital care may account for a substantial proportion of the excess costs associated with ADHD.

These findings and those from Table 1 are consistent with multiple reports that individuals with ADHD exhibit more psychosocial comorbidity, chronic health conditions, and adverse medical outcomes (eg, substance abuse, automobile collisions, poisoning, and fractures).4,2022 There are few studies comparing individuals with and without ADHD for medical care use. An Ontario Child Health Study survey found no difference between children with and without ADHD in the likelihood of any ambulatory care encounter in the prior 6 months.4,23 The power to detect a difference in the Ontario Child Health Study was limited by the relatively few cases (n = 147) and short observation period. A large national health interview survey asked parents whether their child had a disabling chronic mental health condition, and if yes, to identify the condition.24 Parents were asked to recall the number of physician contacts and hospitalizations by their child in the prior year; compared with children with no condition, those with ADHD experienced significantly more physician contacts but no increased risk of hospitalization.24 Interpretation of these findings is problematic because the parent-reported prevalence of disabling ADHD was 0.5%,24,25 a rate substantially lower than other estimates based on more generally accepted criteria.2,2629

The present study consisted of 350 ADHD cases followed up for up to 9 years. The presence of ADHD was established by applying comprehensive, standardized research criteria with retrospective review of complete medical and school records from age 5 to a maximum of 19 years among members of a population-based birth cohort.5 The present study was also advantaged in that the types and frequency of encounters were specified, and it afforded comparison between individuals with and without ADHD for medical care costs. The costs were adjusted for inflation and normalized to average national estimates. To our knowledge, no other such comparisons exist.

The present study has a number of limitations. The compilation of costs did not include those for services provided by the few private psychologists and psychiatrists practicing in the area. The impact of these missing costs is likely to be small; a list of birth cohort members ever seen at the largest of these practices revealed less than 3% were seen for any condition. Costs for outpatient drugs were also not included. Because individuals with ADHD are frequently treated with medication on an outpatient basis over extended periods, the cost differences observed here are likely an underestimate of the differences that would be observed if outpatient drug costs were included. The generalizability of study findings to the US population is limited by the fact that more than 95% of Rochester residents are white and both the proportion of the working population employed in the health care industry and the education level are higher compared with the entire US white population.7 The generalizability of study findings is also limited by marked differences in ADHD case ascertainment and detection over time and across geographic regions.30,31 In the present study, the determination of case status was based on retrospective record review by a single trained abstractor in close consultation with a developmental behavioral pediatrician (W.J.B.). The cumulative incidence of ADHD in this birth cohort from age 5 up to age 19 years is consistent with point prevalence estimates from a majority of population-based studies that used DSM criteria.2,2629 It is important to recognize, however, that evidence of DSM-IV criteria was not necessary to qualify an individual as a case in this study. Individuals could qualify as a definite case on the basis of both a clinical diagnosis and positive results from either a parent or teacher questionnaire, and they could qualify as a probable case on the basis of a clinical diagnosis alone. Neither was evidence of DSM-IV criteria sufficient. Subjects with information in the records that was consistent with DSM-IV criteria also had to have either a clinical diagnosis of ADHD or positive results from standardized parent and/or teacher questionnaires. To investigate the robustness of our study findings, we reanalyzed the data limiting the definition of ADHD cases to individuals with information in the records consistent with DSM-IV criteria (n = 221). Sixteen of these individuals did not qualify as having either definite or probable ADHD using our research definition. Median costs during the full 9 years of follow-up were $4829 (interquartile range, $2535-$8230) for members who met DSM-IV criteria compared with $4306 (interquartile range, $2222-$7150) using our definition. Both were significantly higher (P<.001) than the respective median costs for the remaining birth cohort members ($1945 vs $1907). The data were also analyzed with definite cases categorized as ADHD (median costs, $4317; interquartile range, $2331-$7092) and probable cases categorized as non-ADHD (median costs, $1926; interquartile range, $847-$4124; P<.001). Thus, despite the fact that alternative criteria identified different sets of individuals, the results were similar.

In conclusion, this study provides unique population-based longitudinal estimates of health care use and costs for individuals with and without ADHD. The findings have important clinical and public policy implications. They suggest that the burden of ADHD extends beyond the recognized social, behavioral, and academic outcomes3,4 to include markedly increased use of medical care. Dramatic differences in cost were observed for both sexes and at every age; the differences were not attributable to a few high-cost individuals but were broadly based.

National Institutes of Health, Centers for Disease Control and Prevention.  Diagnosis and Treatment of Attention Deficit Hyperactivity Disorder: NIH Consensus StatementBethesda, Md: National Institutes of Health, Centers for Disease Control and Prevention; 1998:1-37.
Anderson J, Werry JS. Emotional and behavioral problems. In: Pless IB, ed. The Epidemiology of Childhood Disorders. New York, NY: Oxford University Press; 1994:304-338.
Hansen C, Weiss D, Last CG. ADHD boys in young adulthood: psychosocial adjustment.  J Am Acad Child Adolesc Psychiatry.1999;38:165-171.
Szatmari P, Offord DR, Boyle MH. Correlates, associated impairments and patterns of service utilization of children with attention deficit disorder.  J Child Psychol Psychiatry.1989;30:205-217.
Barbaresi WJ, Katusic SK, Colligan RC.  et al.  The cumulative incidence of diagnosed and documented AD/HD in a population-based birth cohort.  Pediatr Res.2000;47:22A.
Katusic SK, Colligan RC, Barbaresi WJ, Schaid DJ, Jacobsen SJ. Potential influence of migration bias in birth cohort studies.  Mayo Clin Proc.1998;73:1053-1061.
Melton III LJ. History of the Rochester Epidemiology Project.  Mayo Clin Proc.1996;71:266-274.
American Psychiatric Association.  Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Washington, DC: American Psychiatric Association; 1994.
Barbaresi WJ. Primary care approach to the diagnosis and management of attention-deficit hyperactivity disorder.  Mayo Clin Proc.1996;71:463-471.
Campion ME, Naessens JM, Leibson CL.  et al.  The Olmsted County Benchmark Project.  Mayo Clin Proc.1992;67:5-14.
Leibson C, Naessens JM, Krishan I.  et al.  Disposition at discharge and 60-day mortality among elderly people following shorter hospital stays.  Gerontologist.1990;30:316-322.
Leibson CL, Naessens JM, Campion ME.  et al.  Trends in elderly hospitalization and readmission rates for a geographically-defined population.  J Am Geriatr Soc.1991;39:895-904.
Leibson CL, Hu T, Brown RD.  et al.  Utilization of acute care services in the year before and after first stroke.  Neurology.1996;46:861-869.
Wagner JL, Alberts SR, Sloan JA.  et al.  Incremental costs of enrolling cancer patients in clinical trials.  J Natl Cancer Inst.1999;91:847-853.
Prospective Payment Assessment Commission.  Medicare and the American Health Care System: Report to Congress. Washington, DC: Prospective Payment Assessment Commission; 1997.
 Health Care Financing Administration medical program: changes to the hospital inpatient prospective payment systems and fiscal year 1998 rates.  62 Federal Register.460 (1997).
Melton III LJ. The threat to medical-records research.  N Engl J Med.1997;337:1466-1470.
ACG Case-Mix Development Team.  Clinician's Guide: The Johns Hopkins University ACG Case-Mix Adjustment System. Version 4.1. Baltimore, Md: Johns Hopkins University; 1998:E.1-E.61.
Starfield B, Weiner J, Mumford L, Steinwachs D. Ambulatory care groups.  Health Serv Res.1991;26:53-74.
Barkley RA, Murphy KR, Kwasnik D. Motor vehicle driving competencies and risks in teens and young adults with attention deficit hyperactivity disorder.  Pediatrics.1996;98:1089-1095.
Barkley RA, Guevremont DC, Anastopoulos AD.  et al.  Driving-related risks and outcomes of attention deficit hyperactivity disorder in adolescents and young adults.  Pediatrics.1993;92:212-218.
Barkley RA, Fischer M, Edelbrock CS, Smallish L. The adolescent outcome of hyperactive children diagnosed by research criteria.  J Am Acad Child Adolesc Psychiatry.1990;29:546-547.
Offord DR, Boyle MH, Fleming JE, Blum HM, Grant NIR. Ontario Child Health Study: summary of selected results.  Can J Psychiatry.1989;34:483-491.
Halfon N, Newacheck PW. Prevalence and impact of parent-reported disabling mental health conditions among US children.  J Am Acad Child Adolesc Psychiatry.1999;38:600-609.
Costello EJ. Commentary on prevalence and impact of parent-reported disabling mental health conditions among US children.  J Am Acad Child Adolesc Psychiatry.1999;38:610-613.
Wolraich ML, Hannah JN, Pinnock TY.  et al.  Comparison of diagnostic criteria for attention-deficit hyperactivity disorder in a county-wide sample.  J Am Acad Child Adolesc Psychiatry.1996;35:319-324.
Baumgartel A, Wolraich ML, Dietrich M. Comparison of diagnostic criteria for attention deficit disorders in a German elementary school sample.  J Am Acad Child Adolesc Psychiatry.1995;34:629-638.
Pelham WE, Gnagy EM, Greenslade KE, Milich R. Teacher ratings of DSM-III-R symptoms for the disruptive behavior disorders.  J Am Acad Child Adolesc Psychiatry.1992;31:210-218.
Szatmari P, Offord DR, Boyle MH. Ontario Child Health Study.  J Child Psychol Psychiatry.1989;30:219-230.
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Figures

Figure 1. Percentage of Individuals With 1 or More Admissions per Year, by Encounter Type and Attention-Deficit/Hyperactivity Disorder (ADHD) Case Status
Graphic Jump Location
Individuals were resident members of the 1976-1982 Rochester birth cohort in years 1987-1995. Asterisk indicates that differences between groups were statistically significant at P<.05; dagger, P<.01; and double dagger, P<.001.
Figure 2. Annual Median Medical Care Costs for Individuals With and Without Attention-Deficit/Hyperactivity Disorder (ADHD)
Graphic Jump Location
Individuals were resident members of the 1976-1982 Rochester birth cohort who incurred costs in years 1987-1995. Data are provided for costs assigned to Medicare Part A or to Medicare Part B separately and are expressed in 1995 national average dollars. Asterisk indicates differences between groups for Medicare Part A were statistically significant at P<.01. Differences between groups for Medicare Part B were statistically significant at P<.001 in each year.

Tables

Table Graphic Jump LocationTable. Ambulatory Diagnostic Group Clusters With and Without Attention-Deficit/Hyperactivity Disorder (ADHD)*

References

National Institutes of Health, Centers for Disease Control and Prevention.  Diagnosis and Treatment of Attention Deficit Hyperactivity Disorder: NIH Consensus StatementBethesda, Md: National Institutes of Health, Centers for Disease Control and Prevention; 1998:1-37.
Anderson J, Werry JS. Emotional and behavioral problems. In: Pless IB, ed. The Epidemiology of Childhood Disorders. New York, NY: Oxford University Press; 1994:304-338.
Hansen C, Weiss D, Last CG. ADHD boys in young adulthood: psychosocial adjustment.  J Am Acad Child Adolesc Psychiatry.1999;38:165-171.
Szatmari P, Offord DR, Boyle MH. Correlates, associated impairments and patterns of service utilization of children with attention deficit disorder.  J Child Psychol Psychiatry.1989;30:205-217.
Barbaresi WJ, Katusic SK, Colligan RC.  et al.  The cumulative incidence of diagnosed and documented AD/HD in a population-based birth cohort.  Pediatr Res.2000;47:22A.
Katusic SK, Colligan RC, Barbaresi WJ, Schaid DJ, Jacobsen SJ. Potential influence of migration bias in birth cohort studies.  Mayo Clin Proc.1998;73:1053-1061.
Melton III LJ. History of the Rochester Epidemiology Project.  Mayo Clin Proc.1996;71:266-274.
American Psychiatric Association.  Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Washington, DC: American Psychiatric Association; 1994.
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