SBIR Phase II: Implementation of a Digital Health Platform to Enable Behavioral Health Integration in Multiple Care Settings

SBIR 第二阶段：实施数字健康平台以实现多种护理环境中的行为健康整合

• 批准号: 1951062
• 负责人: Adam Pardes
• 金额: $ 74.94万
• 依托单位: NeuroFlow, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1951062&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Implementation; Digital

The broader/commercial impact of this SBIR Phase II project aims to enable behavioral health access and engagement across the continuum of care by improving outcomes, overall wellness, and cost of care by combining integrated care, evidence-based tools, and data science. Approximately 1 in 5 adults in the U.S. experience mental illness in a given year, which costs an estimated $752 billion in healthcare expenditures annually. The proposed work will use artificial intelligence and data science capabilities to create personalized patient experiences outside of clinical settings to improve health outcomes, care team efficiency, and resource utilization. This SBIR Phase II project will use artificial intelligence and data science capabilities to create personalized patient experiences outside of clinical settings. This project will: 1) advance a system with EHR interoperability managing a bi-directional flow of discrete data; 2) automate components of the platform’s comprehensive content and assignment library; and 3) use artificial intelligence, specifically real-time natural language processing, to identify and support patients that are potentially in crisis.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.

该SBIR第二阶段项目的更广泛/商业影响旨在通过结合综合护理，循证工具和数据科学来改善结果，整体健康和护理成本，从而实现整个护理过程中的行为健康访问和参与。在美国，每年大约有五分之一的成年人患有精神疾病，每年的医疗支出估计为7520亿美元。拟议的工作将利用人工智能和数据科学能力，在临床环境之外创建个性化的患者体验，以改善健康结果、护理团队效率和资源利用率。SBIR第二阶段项目将使用人工智能和数据科学能力，在临床环境之外创建个性化的患者体验。该项目将：1）推进具有EHR互操作性的系统，管理离散数据的双向流; 2）自动化平台的综合内容和任务库的组件;以及3）使用人工智能，特别是实时自然语言处理，该奖项反映了NSF的法定使命，并通过使用基金会的学术价值和更广泛的影响审查标准。