Psychiatric comorbidities in children with conduct disorder: a descriptive analysis of real-world data

The literature on the prevalence of mental disorders affecting children and adolescents has expanded significantly over the last three decades around the world. Despite the field having matured significantly, there has been no meta-analysis to calculate a worldwide-pooled prevalence and to empirically assess the sources of heterogeneity of estimates.

To examine the effects of varying diagnostic and pharmaceutical criteria on the performance of claims-based algorithms for identifying beneficiaries with hypertension, heart failure, chronic lung disease, arthritis, glaucoma, and diabetes. Secondary 1999-2000 data from two Medicare+Choice health plans. Retrospective analysis of algorithm specificity and sensitivity. Physician, facility, and pharmacy claims data were extracted from electronic records for a sample of 3,633 continuously enrolled beneficiaries who responded to an independent survey that included questions about chronic diseases. Compared to an algorithm that required a single medical claim in a one-year period that listed the diagnosis, either requiring that the diagnosis be listed on two separate claims or that the diagnosis to be listed on one claim for a face-to-face encounter with a health care provider significantly increased specificity for the conditions studied by 0.03 to 0.11. Specificity of algorithms was significantly improved by 0.03 to 0.17 when both a medical claim with a diagnosis and a pharmacy claim for a medication commonly used to treat the condition were required. Sensitivity improved significantly by 0.01 to 0.20 when the algorithm relied on a medical claim with a diagnosis or a pharmacy claim, and by 0.05 to 0.17 when two years rather than one year of claims data were analyzed. Algorithms that had specificity more than 0.95 were found for all six conditions. Sensitivity above 0.90 was not achieved all conditions. Varying claims criteria improved the performance of case-finding algorithms for six chronic conditions. Highly specific, and sometimes sensitive, algorithms for identifying members of health plans with several chronic conditions can be developed using claims data.

Substance use and substance use disorders are highly prevalent among youth under juvenile justice (JJ) supervision, and related to delinquency, psychopathology, social problems, risky sex and sexually transmitted infections, and health problems. However, numerous gaps exist in the identification of behavioral health (BH) problems and in the subsequent referral, initiation and retention in treatment for youth in community justice settings. This reflects both organizational and systems factors, including coordination between justice and BH agencies.