Dashboards for Clinician Monitoring of Patients Through a Mobile Sensing Platform

描述（由申请人提供）：精神健康障碍在我国和世界各地造成非常高的个人、社会和经济成本，是一项重大的公共卫生挑战。临床医生和研究人员目前面临着通过自我报告和病史行为来推断患者就诊行为和治疗依从性的艰巨任务。Cogito的移动传感平台“Cogito Companion”通过手机传感器客观地测量行为模式，并将这些模式作为预测模型的输入，根据临床结果进行训练。这些模型预测心理状态，如抑郁、痛苦和焦虑的组成部分。然后，这些预测可以通过手机呈现给患者，通过临床仪表板呈现给临床医生。准实时监测、分析和可视化变化为临床医生了解患者行为提供了新的窗口。跨群体存储、聚合和分析这些新信号可以提供强大的、可推广的、人口水平的信息。该二期项目将包括一项临床试验，验证该技术在以患者为中心的医疗家中对患有合并症行为健康状况的患者的有效性。通过将这项技术应用到综合行为健康计划的工作流程中，将收集技术的有效性，并通过对提供者工作流程、治疗结果、患者结果、自助行为、临床研究和成本上升趋势的影响来评估。这一验证将导致该药物成功进入第三阶段商业化

DESCRIPTION (provided by applicant): Mental health disorders exact very high personal, social and economic costs in our country and around the world, presenting a significant public health challenge. Clinicians and researchers are currently faced with the difficult task of inferrig patient behavior and treatment adherence between clinic visits through self-report and historical behavior. Cogito's mobile sensing platform "Cogito Companion" objectively measures behavioral patterns via mobile phone sensors and uses these patterns as inputs to predictive models, trained against clinical outcomes. The models predict mental states, such as components of depression, distress, and anxiety. These predictions can then be presented to patients via their mobile phone and clinicians via a clinical dashboard. Monitoring, analyzing, and visualizing changes in quasi-real time allow clinicians a new window into understanding patient behavior. The storage, aggregation and analysis of these novel signals across groups allows for results providing powerful, generalizable, population-level information. This Phase II project will include a clinical trial validating the efficacy of the technology in a patient-centerd medical home with patients who have comorbid behavioral health conditions. Through implementation of this technology into the workflow of an integrated behavioral health program, results will be gathered on the efficacy of the technology as evaluated by the impact on provider workflow, treatment outcome, patient outcome, self-help behaviors, clinical research, and the upward trend in costs. This validation will lead to a successful Phase III commercialization of the technology.