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Real-Time Integration of Sensor and Self-Report Data for Clinical and Research Applications


Summary Wireless sensors, and mobile devices and applications are increasingly marketed for health monitoring or interventions in consumer and clinical settings for prevention or management of chronic disease. A rapidly expanding market segment of technologies are focused on objective measures of health related behaviors (e.g., physical activity, sleep, diet, medication adherence, etc.). These mobile health technologies offer the capability to collect tremendous volumes of high quality health data, with continuous monitoring or event recording functions, in near real time. The expanding use of behavioral monitoring technologies, applications and mobile messaging provides new opportunities within consumer health, clinical care, and research. However, meaningful interpretation of the high volume of data generated from monitoring technologies is a challenge for the patient, care team and the researcher. Further, health monitoring technologies are often criticized for lacking additional contextual data to facilitate their interpretation. Added to data from sensors and monitoring technology, self-reported measures can provide invaluable psychosocial, contextual, and environmental health-related information. Patient-reported outcomes in physical, mental or social health domains include physical abilities, fatigue, pain, depression, and social interactions. The expanded use of smartphone technologies lends itself to private, convenient, real-time data collection of self-reported measures. However, development or optimization of cross-platform mobile applications and scalable, efficient, cloud-based server platforms for rapid and real-time self-reporting and monitoring of these measures is needed. Real-time integration of objective and patient-reported data could improve understanding and clinical management of acute and time-varying symptoms such as fatigue, pain, or depression experienced by cancer and other chronic disease patients. The integrated collection of objective and self-reported data can stimulate innovation within clinical and research settings, including clinical trials, clinical care, case-management, interventions, surveillance, and epidemiologic studies. For example, temporal integration of medication monitoring technologies, such as smart pill cases and sensor-based activity and sleep data, with patient-reported measures of depression, fatigue, or pain could enhance pharmaceutical clinical trial results. However, efficient systems and platforms for the capture, storage, integration, visualization, and reporting of these data streams are extremely limited or non-existent. Project Goals This topic’s short-term goal is the development of innovative, secure, privacy-compliant mobile applications and paired analytic systems to control the collection, transfer, integration, analysis and reporting of objective and self-reported health-related measures. Longer term goals include the integration of these data systems and layers in health care and research settings to support customized monitoring and feedback loops, alerts, or alarms for consumers, patients, or members of the health care team. Responses to this topic are expected to address the development of efficient methods and platforms to: 1. Collect data from behavioral health monitoring technologies and self-reported behavioral, psychosocial, environmental, and contextual measures. 2. Demonstrate integration with various wireless sensors. 3. Appropriately secure data at each stage of collection, transfer, and storage. 4. Temporally integrate information from multiple data sources. 5. Visualize data using customizable tools. 6. Analyze and report on (patient identified or de-identified) individual or group level data using customizable tools and reporting systems. 7. Maintain compliance with HIPAA, privacy, and consent management protocols as required for platform specific applications. The resulting platform’s utility extends from consumer health to clinical care and research settings for behavioral monitoring and prevention or management of disease. This topic encourages development of innovative, secure, privacy compliant mobile applications and 2-way mobile messaging techniques to facilitate and control the collection and transport of temporal data inputs from behavioral health monitoring technologies, self-reported measures, and associated metadata. The data acquisition systems described above must be paired with efficient, scalable back-end systems for data importation, storage, integration, visualization, analyses, and output reporting. Data elements may include (but are not limited to) wireless physical activity or sleep sensors/monitors, physiologic sensors, adherence monitors, sensor-based measures of stress or fatigue, dietary intake measures, geospatial location tags or linkages, images, text based annotations, speech recording and recognition; and self-reports of behavioral, psychosocial, environmental, and contextual data. An essential task for each proposal is the development of transparent and customizable analytic tools for temporal data integration, visualization, and summary reporting of individual or group level measures. Recommended short term targets for system outputs are to provide reports to patients/participants, clinicians/researchers, and health systems; with longer term targets to provide reports directly to electronic medical records and public health surveillance systems. Recommended reports are consistent with current health outcomes policy priorities and objectives in the Meaningful Use Matrix for electronic health records established by the Health Information Technology Policy Committee (see Phase I Activities and Expected Deliverables • Establish a project team including proven expertise in: sensor technology for behavioral and physiological monitoring, wireless sensor integration with mobile devices (smartphones, tablets, etc.), self-reported and/or sensor-based psychosocial, environmental, and contextual measures, secure wireless transport of health data using standards based protocols, secure cloud-based computing models, data visualization, and systems architecture that will effectively address all objectives of the current topic • Provide a report including detailed description and/or technical documentation of the proposed: o Database structure for the proposed system’s self-reported and sensor-based data inputs and metadata requirements o Data standards for collection, transport, importation, and storage of self-reported and sensor-based data inputs o Data types for exchange of health-related behaviors such as physical activity, sleep, diet, and medication adherence between mobile platforms and secure servers o Data integration approaches to leverage multiple data input streams o Data visualization, feedback, and reporting systems for population or clinical monitoring and research applications o Expected sensor(s), mobile platform(s) and mobile device(s) compatibility matrix for front- end mobile application and back-end server systems to be developed • Develop a functional prototype system that includes: o Front-end mobile application(s) to facilitate and control the collection and transport of self-reported and sensor-based data inputs and any associated metadata used within the system o Integration with several wireless sensors including wireless physical activity monitors and other physiologic, geospatial, indoor location, proximity, environmental, or compliance related sensors o Automated data screening and importation protocols for data transferred from the mobile application to the back-end server systems o Software systems user interface (web- or computer-based) o Back-end user-interface controls for custom data integration and visualization for individual or group-level data • Provide a report detailing output reporting systems feasibility, proposed timelines, data standards, and communication architecture for reporting summary outputs to patients/subjects, clinicians/researchers, electronic medical records, and health surveillance systems • Finalize database formats and structure, data collection, transport, and importation methods for targeted data inputs • Include funds in budget to present Phase I findings and demonstrate the final prototype to an NCI evaluation panel Phase II Activities and Expected Deliverables • Beta-test and finalize front-end mobile applications developed in Phase I • Beta-test and finalize automated file transfer, screening, and database importation protocols and systems • Develop, beta-test, and finalize data integration and visualization tools developed in Phase I • Develop, beta-test, and finalize care team/researcher user-interface systems • Develop and beta-test output reporting systems capabilities for multiple system output targets listed above • Demonstrate system compatibility with sensor(s), mobile platform(s), and mobile device(s), included in the Phase I compatibility matrix • Perform regression testing for both front-end and back-end system functions • Conduct usability testing of consumer/patient-facing mobile applications and any associated web portals and care team/researcher-facing user interface features including system management, analyses, and reporting applications • Develop systems documentation where applicable • In the first year of the contract, provide the program and contract officers with a letter(s) of commercial interest • In the second year of the contract, provide the program and contract officers with a letter(s) of commercial commitment
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