Clinical Decision Support Systems for Child Neuropsychiatric Disorders: The Time Has Come?

Abstract

Great advances in molecular biology, genetics and imaging serve to enhance the desire to develop multi-level and multi-scale models for "personalized medicine" but they remain very challenging for high prevalence, high impact childhood onset neuropsychiatric disorders. We currently have the capacity to develop innovative, effective and efficient clinical decision support models, while also creating the opportunities for rapidly incorporating multi-scale, multi-level data as they become available in the very near future. Sensitive to these complex issues, this paper discusses how these existing resources can be used to develop state-of-the-art clinical decision support models that will improve patient care and reduce costs in primary care and specialist settings in the present while creating a mechanism for adding biomarker and other data as it emerges. The new clinical decision support system for child and adolescent mental disorders needs to integrate existing heterogeneous, geographically distinct, current and historical patient-specific and population-specific data in order to generate new information and models for clinic decision support at the level of the individual patient, using the already available informatics frameworks.