Discussion

Results from this study indicated a consistent pattern of greater relative frequency of alcohol and drug counseling services for children with co-occurring MH and SU disorders. Higher rates of alcohol and drug counseling among the co-occurring group suggest that the SU disorders identified during the study’s assessments were appropriately reflected in the services obtained by these children. Nevertheless, in absolute terms, the penetration rate or the proportion of children who needed these services and received them was considerably lower than ideal. In the two 18-month periods that were concurrent with the assessments, less than half (i.e., 44% for Wave 1 and 30% for Wave 4) of those who could have benefited from such treatment received it. Perhaps, even more disturbing, during the entire 6-year study period, only slightly more than half (i.e., 54%) obtained at least one alcohol or drug counseling service. Arguably, in this case, the proverbial glass is half empty rather than half full.

The other consistent finding across the three selected time periods that reflects the need for more alcohol and drug counseling services was the increased contact with law enforcement among those with co-occurrence. Although the use of addictive substances and increased criminality is not a surprising finding and has been found by many other researchers, the immediate and long-term deleterious effects of such high rates of involvement with law enforcement underscores further the pressing need for additional addictive disorder treatment services.

Little support was found for the existence of systems-related barriers to services based on the assumption that these children were identified initially as having a MH disorder and, therefore, were being served in nonintegrated mental health or public educational systems, which were not co-coordinating a full array of services from the alcohol or drug treatment systems. Perhaps some support for system-based barriers may be interpreted from two of the findings during the 18-month period beginning at Wave 4. Reductions in needed services for children having co-occurrence were seen in one mental health (psychotropic medication) and one educational (special education classes) service consistent with a system-based service reduction. However, one limitation of the current study is that the existing database does not provide complete information on which service system and what service model provided the obtained services. Therefore, no firm conclusions can be drawn from these data with regard to service use from a specific system or delivery model. Moreover, alternative explanations of these data exist. For example, fewer special education classes and reduced use of psychotropic medication might just as easily be reflecting higher levels of criminal justice involvement rather than exclusionary policies of the alcohol or drug treatment system.

Another limitation of the current study is that the existing data were restricted to dichotomous indicators of service use (i.e., yes/no) with no information on service effectiveness. Although this exploratory study provided data on whether children ever received at least one episode of a service, no fine-grained frequency or duration measures of service use were available, which are important dimensions of service use. Potentially even more significant was the absence of service effectiveness measures, which provide data on the utility of receiving a service. Somewhat paradoxically, receiving more services may not indicate better services, as, at least theoretically, one episode of a highly effective service may provide more benefit than numerous episodes of ineffective treatment.

Future research should utilize databases that incorporate both more fine-grained measures of service use and outcome measures that are related to service effectiveness. Specifically, among existing databases, there are at least two types that have potential for providing more comprehensive comparisons of service use between adolescents with and without comorbidity. The first type are those databases that have been collected to compare children’s integrated systems or systems of care services to the more traditional stand-alone service systems model. The National Evaluation of the Comprehensive Community Mental Health Services for Children and Their Families Program conducted by Macro International (E. Wayne Holden, Principal Investigator) provides a good example of this type of database. Using a matched pairs longitudinal design, MACRO has paired five selected system of care demonstration sites with five matched (on community, child, and family variables) comparison sites. Each set of paired sites provides a quasi-experimental comparison of children with serious emotional disturbance under either an integrated or traditional service system. During a 24-month period, for each child, service data has been collected on type, duration, and costs. Additionally, diagnosis and outcome measures (e.g., children’s problems, functional behavior) have been collected. Therefore, it would be possible, by splitting the sample into those with and without comorbidity, to explore overall differences between these groups with regard to type, frequency, and costs of services. Moreover, any interactions with type of service system model (i.e., system of care/traditional) can be examined. Tests of these interactions would address directly the question of whether service use patterns for the comorbid are improved, unchanged, or recduced under an integrated service system.

The second type of databases are statewide administrative databases such as Medicaid eligibility and claims records, public behavioral health events, and HMO encounters. Typically, data are collected at the person-level and include information on diagnosis, eligibility status, type; location; and cost of service received, gender, and race/ethnicity. For example, in the State of Florida, children’s diagnoses, service use, and cost data are available for all children’s mental health, physical health, and substance use services received by Medicaid participants. Comparisons between the comorbid and those with only a MH disorder can be made using the Florida Medicaid Claims files and the statewide public behavioral health files. Recent analyses of these databases conducted at the de la Parte Florida Mental Health Institute, the archive facility for the State, examined the types of services, duration, access to care, and cost among various types of recipients (e.g., consumer characteristics such as managed care plan membership or being seen by a particular service provider). Similar analyses could be performed for adolescents with and without co-morbidity. Using either of these database types, future research could provide a more comprehensive assessment of how service use patterns differ, or not, between adolescents with co-occurrence versus their MH only peers.

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