| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 17, 2020 |
| Latest Amendment Date: | October 14, 2020 |
| Award Number: | 2026614 |
| Award Instrument: | Standard Grant |
| Program Manager: |
David Corman
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2020 |
| End Date: | September 30, 2022 (Estimated) |
| Total Intended Award Amount: | $149,932.00 |
| Total Awarded Amount to Date: | $149,932.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
160 ALDRICH HALL IRVINE CA US 92697-0001 (949)824-7295 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
141 Innovation Drive, Ste 250 Irvine CA US 92617-3213 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | FW-HTF Futr Wrk Hum-Tech Frntr |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Healthcare systems in the USA face challenges in developing organized and affordable platforms that increase the reach and services to communities. Existing community-centered care (CCC) models rely on caregivers to provide critical medical assistance in a community setting, particularly for elderly, disabled and vulnerable populations. These CCC models extend the reach of home-delivered services by employing community healthcare workers (CHWs) who provide the necessary care for the community. Since these CHWs are trained and supervised by registered nurses (RNs), this CCC model suffers from an inability to scale in a cost-effective manner while providing personalized and quality care for the community. This Future of Work at the Human Technology Frontier planning grant lays the foundation for a new digital health enabled community-centered care (D-CCC) model that will transform the manual, restricted, and unstructured state of the current community healthcare landscape into a scalable, digital, and automated space. The D-CCC model will improve: the future of work ? the nature of healthcare services delivered to home/community; the future of workers ? training and empowering RNs and CHWs to improve quality of serving capabilities; and the future of technology ? using AI-enabled cognitive Cyber-Physical System (CPS) models for novel and scalable healthcare services. The D-CCC model will achieve scalability by using technology to allow CHWs to serve an expanded patient population, including underserved, elderly, disabled and vulnerable groups.
The planning grant will fill several gaps for successful launch of the D-CCC research vision. In particular, the planning grant plans to: 1) better understand community needs to analyze the range of desired services; 2) engage a community advisory board (CAB) to assess the requirements of future workers ? CHWs and RNs ? to digitally empower them for effective delivery of community centric services in a scalable, yet personalized manner; 3) conduct focus groups to gain perspectives about the efficient implementation and integration model of the D-CCC model in the community, as well as identify barriers and issues of most concern for workers and individuals from key stakeholders across the community spectrum, including patients, CHWs, CHW leaders, RNs, medical centers, non-profit healthcare organizations, public/government advisors, and other community members; 4) conduct feasibility and needs assessment studies that bring together multiple stakeholders and bridge the gap between human-work-workers-technology frontiers; and 5) hold visioning workshops to lay a solid foundation for an actionable research agenda that will yield tangible results. This planning grant will formulate such a basis, assemble the requisite research team, identify key members of an initial CAB, and outline the roadmap for realizing research objectives that will be included in a future full FW-HTF proposal to address these problems
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
This planning grant addressed a crucial requirement at the national level -- facilitating increased access to health-related services for underserved communities and improving their knowledge, awareness, and education on healthcare and wellbeing. Healthcare services in the United States are expensive and poorly structured to serve disadvantaged communities. This creates the need for an organized and affordable model for providing healthcare services to underserved communities. Several states, including California, have adopted the Community Centered Care (CCC) model, in which community health workers (CHWs) are employed as alternative assistance to registered health providers to extend the reach of home-delivered services. CHWs are lay members of the community with deep cultural understanding and community-specific knowledge who expertly bridge the healthcare and social services gap. CHWs deliver community-specific healthcare-related services to clients, including health promotion and education, episodic monitoring, and occasional home visitations.
The current CCC model has shown success in delivering culturally sensitive health education and linking individuals with community resources. However, there are many shortcomings related to the sustainable health impact of the clients and their family caregivers, as well as the efficiency of the work of the community health workers and health providers. These problems include not always getting complete information about the people they help, not being aware of changes in their health, not being proactive in their approach to healthcare, poor communication, not involving the family caregivers, and not being connected to medical providers.
This planning grant initiated an effort to propose a novel model of care, the digital Community Centered Care (D-CCC) model. The goal of D-CCC is to change the way community health workers and health providers deliver care to people in underserved communities. Instead of providing care that is based on subjective information and only given when there is a problem, the goal is to offer care that is based on predicting and preventing health problems and is personalized for each individual. The D-CCC model helps community health workers and health providers work together more effectively, using technology to provide objective health assessments and proactive, preventive care. The model also involves the families of those receiving care as active participants, offering them guidance and support, which benefits both the families and the individuals receiving care. Finally, the platform makes it possible to share important health information with medical providers to improve overall care.
Over the course of this planning grant, we started an initiative to fill gaps in knowledge, build a strong team, engage key community stakeholders, conduct a pilot study, and create a detailed research roadmap to create a well-formed full research proposal. We assembled a strong multidisciplinary team (computer scientists, informatics experts, control engineers, community outreach experts, experts in geriatric medicine and nursing, behavioral psychologists, and partners from community-health organizations).
We formed a Community Advisory Board (CAB) with representation from a wide range of stakeholders, from insurance companies, public health specialists, and community organizations to registered providers, community health workers, and clients (older adults and their family caregivers). We held six CAB meetings. Through our CAB, we were introduced to and subsequently formed a strong partnership with the local community organization Meals on Wheels Orange County (MOW OC). We also conducted six focused group interviews among key stakeholders to identify potential barriers and issues of most concern among community health workers, supervisors, clients, and caregivers and also assess attitudes and feelings regarding technology acceptance among them. We shared the lessons learned through these meetings and sessions with the community and published them as scientific articles.
We also conducted a pilot study with a close partnership with MoW OC. 10 participants participated in this study from underserved Hispanic communities in OC. We implemented and deployed a subset of the monitoring system with the close collaboration of MoW?s Staff. The clients received a smart, blood pressure monitor, a smart scale (for weight, body composition, and vascular health monitoring), and a smart ring (for sleep, heart rate (HR), physical activity, HR variability, and stress monitoring), while the family caregivers received a smart ring (to monitor their wellbeing and mental health) and a custom mobile application for subjective measurements about the clients (e.g., fall, depression, food, fatigue, etc.). We also developed a smart dashboard for the MoW staff to monitor the participants continuously and remotely and also receive alerts. The feasibility of the devices was tested by measuring the daily usage or wear time during the 8-week study period. The study showed the high feasibility of using the BP monitor and smart ring in this population. We found that data empowered the community health workers and nurses in the caregiving process.
From a broader impact perspective, the planning grant involved Ph.D., MS, and undergraduate students (from computer science, informatics, and nursing science) at UCI who gained experience related to digital health technology.
Last Modified: 02/14/2023
Modified by: Amir Rahmani
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