课题基金 / 基金详情

Co-Development of Telehealth, Remote Patient Monitoring, and AI-based Tools for Inclusive Technology-Facilitated Healthcare Work of the Future

Co-Development of Telehealth, Remote Patient Monitoring, and AI-based Tools for Inclusive Technology-Facilitated Healthcare Work of the Future
共同开发远程医疗、远程患者监护和基于人工智能的工具,以实现包容性技术促进未来的医疗保健工作
批准号:
2129076
负责人:
Oded Nov
金额:
$250.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-10-15 至 2026-09-30

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中文摘要
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英文摘要
As the use of digital health technologies grows, gaps between the potential of new technologies, existing healthcare practices, and workers’ preparedness for new technologies limit the potential of digital health to achieve acceptance and effective utilization at scale. This transition to scale research project views inclusion as a key driver of scale in future technology-facilitated healthcare work. Inclusive technology for healthcare work will enable workers in diverse roles and skills to leverage increasing access to data-driven technologies. The project focuses on the growth of Data-Intensive Technologies (DIT), which include telehealth and AI-based tools. The project’s approach to transition to scale centers on alleviating existing misalignment between current healthcare work and data-intensive technologies in three ways. First is through the co-development of tools and generalizable design principles with users that lower the barrier to technology integration for healthcare workers. Second is by empowering individuals within healthcare systems who have diverse roles to adopt and use the tools and improve their skills. Third is to enable patient-centered healthcare that promotes autonomy and strengthens clinician-patient concordance. The project represents a multi-institutional commitment to transitioning innovative healthcare to scale, through DIT facilitated inclusion of diverse workers in healthcare systems across the U.S., which together encompass over 1000 care sites in U.S. 24 states, multiple work roles, and different levels of training and hierarchy.This project brings together several scientific fields, including human-computer interaction, health informatics, artificial intelligence (AI), sensing, medicine, organizational behavior, and research on diversity and inclusion. The investigator team is structured to achieve multiple convergent goals such as quantifying the impacts of scaling DIT on inclusive healthcare work and modelling prescription and adoption of DIT towards inclusive deployment at scale. Additionally, the investigators seek to identify generalizable DIT design principles for inclusive healthcare work at scale, and to develop theory and tools to facilitate at-scale inclusion through DIT-based patient-provider concordance. Finally, the project expects to develop tools and practices for lowering barriers to comprehension of and engagement with DIT by diverse healthcare workers; to create AI-based team-focused tools; and to analyze the opportunities and challenges in using AI for diverse healthcare teams’ work. This project has been funded by the NSF Future of Work at the Human-Technology Frontier cross-directorate program to promote deeper basic understanding of the interdependent human-technology partnership in work contexts by advancing design of intelligent work technologies that operate in harmony with human workers.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.
期刊论文(13)
专著(0)
科研奖励(0)
会议论文
The Algorithmic Transparency Playbook: A Stakeholder-first Approach to Creating Transparency for Your Organization’s Algorithms
算法透明度手册:为组织的算法创造透明度的利益相关者优先的方法
DOI: 10.1145/3544549.3574169
发表时间: 2023
期刊: 2023 CHI Conference on Human Factors in Computing Systems
影响因子: --
作者: [Bell, Andrew, Nov, Oded, Stoyanovich, Julia]
通讯作者: Stoyanovich, Julia
AI model transferability in healthcare: a sociotechnical perspective
医疗保健中的人工智能模型可转移性:社会技术视角
DOI: 10.1038/s42256-022-00544-x
发表时间: 2022
期刊: Nature Machine Intelligence
影响因子: 23.8
作者: [Wiesenfeld, Batia Mishan, Aphinyanaphongs, Yin, Nov, Oded]
通讯作者: Nov, Oded
DOI: 10.1145/3555622
发表时间: 2022-11
期刊: Proceedings of the ACM on Human-Computer Interaction
影响因子: --
作者: [G. Dove;Adelle Fernando;Kim Hertz;Jin Kim;J. Rizzo;W. Seiple;O. Nov]
通讯作者: G. Dove;Adelle Fernando;Kim Hertz;Jin Kim;J. Rizzo;W. Seiple;O. Nov
DOI: 10.1017/dap.2023.8
发表时间: 2023
期刊: Data & Policy
影响因子: --
作者: [Bell, Andrew, Nov, Oded, Stoyanovich, Julia]
通讯作者: Stoyanovich, Julia
Learning Data Science Through Civic Engagement With Open Data
  • 批准号:
    2005890
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2020
  • 负责人:
    Oded Nov
  • 依托单位:
FW-HTF-RL: Collaborative Research: Future expert work in the age of "black box", data-intensive, and algorithmically augmented healthcare
  • 批准号:
    1928614
  • 项目类别:
    Standard Grant
  • 资助金额:
    $150.0万
  • 财政年份:
    2019
  • 负责人:
    Oded Nov
  • 依托单位:
CHS: Small: Collaborative Research: Ubiqomics: HCI for augmenting our world with pervasive personal and environmental omic data
  • 批准号:
    1814932
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $24.99万
  • 财政年份:
    2018
  • 负责人:
    Oded Nov
  • 依托单位:
EAGER: Exploring Spear-Phishing: A Socio-Technical Experimental Framework
  • 批准号:
    1359601
  • 项目类别:
    Standard Grant
  • 资助金额:
    $20.36万
  • 财政年份:
    2014
  • 负责人:
    Oded Nov
  • 依托单位:
国内基金
海外基金
水稻边界发育缺陷突变体abnormal boundary development(abd)的基因克隆与功能分析
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: