National Science Foundation – National Institutes of Health NSF-NIH Interagency Initiative: Smart and Connected Health

March 9, 2018 by School of Medicine Webmaster

Institutes and Centers of the National Institutes of Health (NIH) and the National Science Foundation (NSF) have identified Smart and Connected Health as a program focus. The purpose of this interagency program solicitation is the development of technologies, analytics and models supporting next generation health and medical research through high-risk, high-reward advances in computer and information science, engineering and technology, behavior, cognition, robotics and imaging. Collaborations between academic, industry, and other organizations are strongly encouraged to establish better linkages between fundamental science, medicine and healthcare practice and technology development, deployment and use. This solicitation is aligned with previous reports by the President’s Council of Advisors on Science and Technology and others calling for new partnerships to facilitate major changes in health and medicine, as well as healthcare delivery and is aimed at the fundamental research to enable these changes. Realizing the promise of disruptive transformation in health, medicine and healthcare will require well-coordinated, multi-disciplinary approaches that draw from the computer and information sciences, engineering, social, behavioral, and economic sciences, medical and health research and biology.

The following will be considered in response to NSF’s solicitation NSF-18-541:

  • Integrative Projects: Multi-disciplinary teams spanning 2 to 4 years and may receive NIH support from $300,000 total costs per year.

Scientists and engineers from all disciplines are encouraged to participate.

Application submission is through the National Science Foundation via solicitation NSF-18-541. Following a jointly conducted initial peer review of these applications, likely NIH awardees applications will be forwarded for NIH processing. The general interests of the participating NIH Institute organizations are outlined below:
National Cancer Institute (NCI)
NCI is interested in funding research centered on the use smart and connected health technologies to facilitate the efficient and effective collection, flow, and use of health information to improve cancer outcomes. Two governing documents are especially relevant to guide research endeavors in the area. First is a report produced by the President’s Cancer Panel, a legislatively mandated oversight committee, titled: “Improving Cancer-Related Outcomes with Connected Health: A Report to the President of the United States from the President’s Cancer Panel.” Second is the NCI’s Cancer Moonshot SM Blue Ribbon Panel Report on priorities for accomplishing in five years what might otherwise have taken ten. From these two reports, the following priorities are relevant to the SCH initiative:

  • Improve understanding of how connected health technologies can optimize team performance through better support for distributed cognition between all members of the patient’s virtual care team (inclusive of the patient and patient’s caregivers) as co-producers of positive health outcomes across the continuum of care from prevention, early detection, treatment, survivorship, and end-of-life.
  • Identify strategies to enhance individuals’ engagement in their healthcare through smart and connected support structures, including the ability to manage symptoms and adverse events during treatment.
  • Develop approaches for using data from connected devices – including biosensors, home monitoring devices, smartphones, and wearable technologies – in meaningful ways to enhance clinical care and to support faster cures.
  • Create the building blocks of a national data ecosystem for sharing and analyzing cancer data so that researchers, clinicians, and patients will be able to contribute data and benefit from actionable data analytics.
  • Develop intelligent data mining tools for predicting patients’ responses to treatment based on a retrospective analysis of patients’ clinical, specimen, and genomic data.
  • Utilize health information technologies to enhance cancer surveillance for the benefit of local, regional, and national efforts to improve health outcomes equitably across populations.

National Human Genome Research Institute of (NHGRI).  NHGRI encourages research related to genomic medicine. Such research may include, but not be limited to:

  • methods and algorithms for aggregation of multi-scale clinical and genomic data about a patient in electronic health records (EHRs) and personal health records (PHRs)
  • decision support tools to facilitate optimized patient-centered, evidence-based decisions utilizing genomic data
  • human-computer interfaces for clinician, patient, and family access to genomic information in EHRs and PHRs.

National Institute on Aging (NIA).  NIA is specifically interested in applications which improve quality of life and health of individuals with Alzheimer’s Disease (AD) and Alzheimer’s Disease and Related Dementia (ADRD) and/or their family care providers, with a special focus on diverse and underrepresented populations, including older adults living alone. Additionally, efforts to address how the SCH program might begin to address prediction of cognitive or other decline in everyday function that may predict or detect the earliest indicators of dementia will be of interest.

National Institute on Alcohol Abuse and Alcoholism (NIAAA).  Use technology (e.g. EMA, brain imaging, biosensors) and innovative statistical methods (e.g., machine learning, systems science dynamic models) appropriate for analysis of “big data” (i.e., time intensive, multisource data) to inform our understanding of mechanisms underlying problematic alcohol use.

  • Development or improvement of a portable, affordable, inconspicuous, and user-friendly device/technique to enhance medication adherence.
  • Develop, improve, and validate ecological momentary assessment (EMA) methods for capturing, integrating and analyzing real-time multi-source data related to alcohol use including sensor integration and modeling behavioral processes.
  • Devise novel methods (e.g., Web-mining software of social networking sites) that capture social network information among groups at risk for alcohol use disorder and high-risk drinking.

National Institute of Biomedical Imaging and Bioengineering (NIBIB). The mission of NIBIB is to improve health by leading the development and accelerating the application of biomedical technologies. NIBIB has broad interests in the development of biomedical technologies to improve human health and address health disparities. Program areas of particular relevance include: health information technologies, telehealth, mHealth, point-of-care technologies, rehabilitation engineering, robotics, and next generation predictive models. The Institute is interested in the development of novel technologies and in advances that enable effective utilization of new or existing technologies.

National Institute of Neurological Disorders and Stroke (NINDS).  Within the goals of this FOA, NINDS is particularly interested in research that advances technologies and systems with the potential to decrease the burden of neurological disorders and stroke. Examples of areas of interest include the development and validation of invasive and non-invasive devices, diagnostic/monitoring tools, advanced imaging techniques, computational models, tissue engineering, and other innovative methods.

National Library of Medicine (NLM).  NLM is interested in the development of technologies, analytics and models that utilize novel informatics and data science approaches to help individuals gather, manage and use data and information about their personal health. To bring the benefits of big data research to consumers and patients, new biomedical informatics and data science approaches are needed, shaped to meet the needs of consumers and patients, whose health literacy, language skills, technical sophistication, education and cultural traditions affect how they find, understand and use personal health information. Novel data science approaches are needed to help individuals at every step, from harvesting to storing to using data and information in a personal health library. These approaches should support FAIR (Findable, Accessible, Interoperable, Reusable) principles of data management.

National Institute of Mental Health (NIMH).  NIMH is interested in supporting the development of novel technologies to improve the understanding and treatment of mental illness. NIMH encourages research consistent with the NAMHC workgroup report “Opportunities and Challenges of Developing Information Technologies on Behavioral and Social Science Clinical Research” to improve early detection of mental illness and improve access, continuity, quality, equity, and value of care. NIMH priorities include:

Deep phenotyping through the development of technologies to capture and analyze fine-grained, multimodal data from individuals with mental disorders and healthy controls, for the purpose of identifying novel biological and behavioral patterns that can (1) add to our understanding of specific mental health constructs and domains of function; (2) reveal causal links between environmental factors and mental functions; (3) uncover developmental trajectories; (4) better predict outcomes; and (5) improve the specificity and timeliness of clinical interventions. Technologies of interest to NIMH include, but are not limited to:

  • Sensors tailored to infer subjective mental states (e.g. mood, thought process, risk of self-harm, abnormal perceptions) from objectively observable behaviors (e.g. speech, movement, social interactions).
  • Sensors adapted to monitor mental health related outcomes across the lifespan, in special populations, and within diverse settings (e.g. young children, geriatric populations, nonverbal individuals, assisted living environments).
  • Platforms for the delivery of nonpharmacological interventions (e.g. cognitive behavioral, psychosocial, stimulation-based) in real-world settings.
  • Technology allowing simultaneous, temporally synchronized neurophysiology measurements and quantification of behavior, with high spatial and temporal precision, using either invasive or noninvasive methods, toward the long-term goal of closing the loop between real-time behavioral measurements and delivery of targeted interventions in real-world settings.
  • Sensors to measure outcomes of mental health interventions, including demonstrations of sensitivity to change and correspondence to conventional clinical assessments.

Technologies targeting improvements in mental health care delivery systems, including:

  • Methods to harmonize and analyze electronic health record (EHR) data across multiple systems, especially for low base-rate events/conditions that are difficult to identify, treat, and/or manage (e.g., suicide).
  • Application of ‘big data’ analytics and/or algorithm development to EHRs to inform real-time clinical decision making and measurement-based care associated with the delivery of mental health services.
  • Technology platforms that include real-time use of disease registries, measurement-based care, feedback systems, and quality improvement processes as part of a continuously learning healthcare system.
  • Research to improve designs, measures, and statistical approaches to support testing of system improvement efforts, including information and communication technologies.

Technology platforms which can be utilized across a range of systems (e.g., primary care, schools, criminal justice system, child welfare agencies) to optimize the delivery of effective mental health interventions.

  • Development of innovative technologies to facilitate adoption, implementation, sustainability, and scalability of best practices, or conversely, technologies to de-implement low value mental health services.

Deadlines:  May 22, 2018; December 11, 2018 and annually thereafter


Filed Under: Funding Opportunities