SBIR-STTR Award

Dashboards for Clinician Monitoring of Patients Through a Mobile Sensing Platform
Award last edited on: 6/14/17

Sponsored Program
SBIR
Awarding Agency
NIH : NIMH
Total Award Amount
$2,131,823
Award Phase
2
Solicitation Topic Code
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Principal Investigator
Skyler Place

Company Information

Cogito Corporation (AKA: Cogito Health Inc)

100 High Street 7th Floor
Boston, MA 02110
   (617) 580-3101
   info@cogitocorp.com
   www.cogitocorp.com
Location: Single
Congr. District: 08
County: Suffolk

Phase I

Contract Number: 1R43MH100748-01
Start Date: 4/1/13    Completed: 3/31/14
Phase I year
2013
Phase I Amount
$336,770
Mental health disorders exact very high personal, social and economic costs in our country and around the world, presenting a significant public health challenge. Cogito has developed and deployed technology that listens to natural conversation and produces predictive accuracies of 70-90% with respect to various outcomes such as depression (Azarbayejani, Feast, Zhang, & Massey, 2011; Azarbayejani, Feast, & Pentland, 2010; Chu, 2009). This software tool has been recently augmented and extended to mobile telephones. Cogito's new software suite, the Mobile Sensing Platform, objectively measures behavioral indicators (including motion, communication, location, and voice) and allows patients to more easily monitor their symptoms over time for depression, anxiety, and PTSD. The primary focus of this Phase I application is to develop a new tool - a dashboard - that will extend the mobile platform to researchers and clinicians, thus providing a means of readily visualizing and analyzing these complex patient behavioral data patterns. Extending Cogito's Mobile Sensing Platform to include a new clinician dashboard will enhance greatly the usability and value of the rich data streams collected via our mobile sensing software. Researchers will be able to monitor and quantify the effect of treatments on different patients in quasi-real time, at both the individual and group level. Specific aims of this Phase I proposal are to design and develop a dashboard visualization tool and to establish that the data presented to clinicians and researchers via the dashboard are valid, valuable and useful. Clinical researchers are currently faced with the difficult task of inferring patient behavior and treatment compliance between visits through self-report and historical behavior. Using passively gathered behavioral signals through a smart phone application allows for symptom assessment models to be built from actual behavior instead of reported behavior. Monitoring, analyzing, and visualizing changes in quasi-real time allow clinicians a new window into understanding patient behavior. The Cogito Mobile Sensing Platform would provide such a service, allowing for improvements in patient care through measurement of treatment efficacy, adjustments of medication, and rapid assessments of behavioral change. Cogito is currently involved in clinical trials using our platform to monitor mental illness in US military personnel. We will use this dataset to illustrate prototypical symptom clusters. These longitudinal symptom sets will form the basis for building the dashboard visualization tool. Focus groups with clinical researchers will align the data presentation and usability with the needs of practicing medical professionals.

Public Health Relevance Statement:


Public Health Relevance:
Mental health disorders exact very high personal, social and economic costs in our country and around the world, presenting a great public health challenge. Cogito is developing a dashboard for our mobile software platform that objectively measures behavioral symptoms of anxiety and mood disorders, allowing clinicians to more easily monitor patients' mental health status over time and thereby facilitating research, diagnosis, treatment and monitoring. These improvements will allow for better more efficient patient care while providing quantitative measures of treatment success and quasi-real time risk assessment.

Project Terms:
Adverse reactions; Anxiety; Anxiety Disorders; base; Behavior; Behavior assessment; behavior measurement; Behavior Therapy; Behavioral; behavioral health; Behavioral Symptoms; Car Phone; Caring; Clinical; Clinical Trials; Communication; Complex; Compliance behavior; Computer software; Country; Data; Data Set; design; Detection; Development; Diagnosis; Disease; economic cost; Effectiveness of Interventions; Enrollment; Feedback; flexibility; Focus Groups; Health Status; Hospitals; Imagery; improved; Individual; Lead; Location; Measurement; Measures; Medical; Mental Depression; Mental disorders; Mental Health; Military Personnel; Modeling; Monitor; Mood Disorders; Motion; Outcome; Outpatients; Patient Care; Patient Monitoring; Patient Self-Report; Patient-Centered Care; Patients; Pattern; Pharmaceutical Preparations; Phase; Population; Post-Traumatic Stress Disorders; Privacy; Process; public health medicine (field); public health relevance; Reporting; Research; Research Personnel; Risk; Risk Assessment; screening; Services; Signal Transduction; social; Software Tools; Stream; success; Symptoms; System; Tablets; Technology; Telephone; Testing; Time; tool; treatment effect; Treatment Efficacy; usability; Veterans; Visit; Voice; web site; Work

Phase II

Contract Number: 2R44MH100748-02
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
2014
(last award dollars: 2016)
Phase II Amount
$1,795,053

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 thetechnology.

Thesaurus Terms:
Anxiety;Behavior;Behavior Measurement;Behavior Therapy;Behavioral;Behavioral Health;Car Phone;Caring;Clinic;Clinic Visits;Clinical;Clinical Assessments;Clinical Research;Clinical Trial Protocol Document;Clinical Trials;Commercialization;Companions;Computer Simulation;Consultations;Cost;Country;Data;Data Analyses;Data Collection;Design;Detection;Development;Diagnosis;Disease;Distress;Economic Cost;Engineering Design;Enrollment;Feedback;Flexibility;Funding;Future;Health;Health Personnel;Health Services Research;Health Status;Healthcare;Helping Behavior;Home Environment;Hospitals;Improved;Institutional Review Boards;Lead;Marketing;Measures;Medical;Mental Depression;Mental Disorders;Mental Health;Mental State;Modeling;Monitor;Novel;Outcome;Patient Monitoring;Patient Oriented;Patient Self-Report;Patients;Pattern;Phase;Pilot Projects;Population;Predictive Modeling;Preparation;Primary Health Care;Privacy;Programs;Protocols Documentation;Provider;Public Health Medicine (Field);Public Health Relevance;Recommendation;Research;Research Personnel;Running;Self Help;Sensor;Signal Transduction;Social;Stream;Success;System;Technology;Time;Tool;Training;Treatment Adherence;Treatment Outcome;Trend;Validation;Woman;