Bipolar disorder is an inherently complex chronic illness characterized by recurrent, dramatic mood changes. Management of bipolar disorder typically consists of a combination of medication, therapy, and lifestyle adjustments. However, clinicians lack tools to select optimal treatments tailored to the individualized needs of the patient. The goal of this project is to develop and validate a novel computational tool to aid mental health researchers and providers in assessing trajectories of bipolar disorder. Based on concepts from nonlinear systems (chaos) theory, this computational tool will reveal underlying dynamic interactions that characterize bipolar disorder. This new knowledge will be used both as a research tool to assess the efficacy of treatment regimens, and as a decisional platform for mental health providers to identify individualized patterns of illness expression that can guide interventions and suggest evidence based treatment strategies. The development of this novel computational tool has the potential to have a profound impact on public health and achieve significant commercial success. This Phase I study has four Specific Aims: Specific Aim 1. Identify key medical and behavioral variables, parameters, and interactions Specific Aim 2. Use software to identify significant changes in bipolar patients Specific Aim 3. Enter expert advice into knowledge base Specific Aim 4. Establish user interface and test usability
Public Health Relevance: Bipolar disorder is associated with high levels of morbidity, disability, and premature mortality. Bipolar disorder is among the top ten leading causes of disability worldwide with a lifetime prevalence estimated to be 4.5% in the US. Bipolar disorder has a substantial effect on many aspects of a patient's life and is a source of significant economic burden, with US direct and indirect costs estimated to be about $70.6 billion annually. The development of computer software that could analyze bipolar disorder patient data to evaluate the effectiveness of treatments and provide guidance for interventions would have a significant impact on public health.
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