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National Cancer Institute

Smart and Connected Health

Overview

The Smart and Connected Health program aims to accelerate the development and use of innovative approaches that partner technology-based solutions with biobehavioral health research. The end-goal is a health care system that is proactive, person-centered, and focused on well-being, rather than reactive, hospital-centered, and disease-focused. This interagency program aims to develop next-generation health care solutions by funding high-risk, high-reward efforts in a variety of areas, including information science, technology, behavior, cognition, sensors, robotics, bioimaging, and engineering.

Due to recent technological advances (e.g. high-throughput computing), medicine is on the threshold of a sector-wide transformation. These innovations have the potential to accelerate discovery, facilitate the delivery of high-quality healthcare, improve patient outcomes, decrease costs, and address the complexity of challenging health problems such as cancer, heart disease, and diabetes. Realizing the promise of disruptive transformation in health and health care will require well-coordinated, multidisciplinary approaches that draw from social, behavioral, economic, and computer science disciplines, as well as engineering, medicine, and biology. The Smart and Connected Health initiative is therefore designed to encourage multidisciplinary approaches and greater collaboration between academic, industry, and nonprofit sectors. It also aims to establish better linkages between fundamental science, clinical practice and technology development, and deployment and use.

There are currently three Smart and Connected Health projects in the HCIRB portfolio:

  • “Improving early detection and intervention of lymphedema through machine learning and sensor-based movement analysis” (Yao Wang/Mei Fu, NYU)

    This project will use machine learning to understand the association between personal and clinical factors and the presence of breast-cancer related lymphedema, in order to develop a web-based self-assessment platform that will enable patients to assess their risk for lymphedema. The platform will serve as a decision support tool for both clinician and patient and will facilitate patient-centered, evidence-based intervention decision-making. The project will also develop a Kinect-enhanced intervention training system to provide instant audio-visual feedback to patients when they perform a series of exercises that have the potential to reduce the risk of chronic lymphedema. The system will track relevant body joints using Kinect sensor data and evaluate their conformance with prescribed trajectories.
  • “Intelligent Information Sharing: Advancing Teamwork in Complex Care” (Barbara Grosz, Harvard University)

    The aim of this project is to identify appropriate vocabularies for patient-provider communication about care goals and to create a prototype multi-agent communication system that will reduce discontinuities in communication and improve the effectiveness of care for children with cancer and other complex conditions. The “GoalKeeper” system being developed as part of this project provides technological support for care coordination by 1) monitoring the treatment goals associated with the needs of patients with complex pathologies, 2) monitoring the communication and information flows necessary for supporting those goals, and 3) sending prompts and reminders to members of the treatment team to keep the communication and information flow intact.
  • “Creating Interactive Models of Healthcare Journeys to Improve Patient-Centered Care and Patient Engagement” (Elizabeth D Mynatt/Thad Starner, Georgia Institute of Technology)

    The aim of this project is to develop, deploy, and assess novel technologies that can support breast cancer patients with health information management throughout their entire cancer journey, both in and out of the health care system. The patient-centered health tool developed as part of this project, which presents customized, dynamic content based on both temporal data (e.g. a patient’s phase of care in the cancer journey) and continuous user input, can provide patients with tailored and personalized support throughout treatment and survivorship; assist patients in meeting their information, social, economic and logistical needs; and allow health care providers to more effectively monitor patients and assess their well-being.
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