RAPID: Bridging the Health Care Skill Gap

RAPID：缩小医疗保健技能差距

• 批准号: 2029590
• 负责人: Robert Robson
• 金额: $ 19.91万
• 依托单位: Eduworks Corporation
• 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: 2020-06-01 至 2022-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029590&HistoricalAwards=false
• 关键词: RAPID; Bridging; Health; Care; Skill

The project aims to serve the national need of increasing the capacity to have more qualified healthcare providers to address the challenge of the Coronavirus Disease 2019 (COVID-19). By developing and deploying web-based tools that individuals and employers can use to explore healthcare-related competency frameworks, self-identify skill gaps, and find credentials and training, this project seeks to fill gaps in the healthcare workforce. These tools will help individuals identify healthcare areas where they have adjacent skill sets and will also help companies identify employees who are candidates for upskilling into healthcare. Once individual skills are inventoried, the tool will help users identify where they can obtain the requisite healthcare skills and credentials. The tool will be usable on desktop and mobile devices which broadens the reach of this project. The project seeks to address the COVID-19 crisis by providing end users with the ability to compare their own skills with those required for available healthcare roles and credentials and, in some cases, find ways to fill gaps. The frameworks and related credentials will come from the Credential Engine and additional data will come from the Open Syllabus Project. This project will apply artificial intelligence (AI), specifically natural language understanding (NLU), to (a) crosswalk competency frameworks associated with these credentials, (b) compare skills entered by users to those required to earn those credentials, (c) generate an "alignment score" that measures and quantifies the gap between the two skill sets, and (d) suggest courses and credential programs with the potential to close those gaps. This will contribute to research into applications of NLU to competency-based credentialing and training and will provide data in a concrete domain (healthcare). Including validation and sharing of the underlying competency framework translation and alignment score services via an open data infrastructure will improve our nation’s healthcare talent pipeline.This RAPID award is made by the Convergence Accelerator program in the Office of Integrative Activities and is associated with the Convergence Accelerator Track B: Future of Work and the Human-Technology Frontier.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.

该项目旨在满足国家的需求，增加更多合格医疗服务提供者的能力，以应对2019冠状病毒病（COVID-19）的挑战。通过开发和部署基于网络的工具，个人和雇主可以用来探索医疗保健相关的能力框架，自我识别技能差距，并找到证书和培训，该项目旨在填补医疗保健劳动力的差距。这些工具将帮助个人识别他们拥有相邻技能的医疗保健领域，也将帮助公司识别谁是医疗保健技能提升的候选人。一旦个人技能被清点，该工具将帮助用户确定他们可以在哪里获得必要的医疗保健技能和证书。该工具将在桌面和移动的设备上使用，这扩大了该项目的范围。该项目旨在通过为最终用户提供将其自身技能与现有医疗保健角色和证书所需技能进行比较的能力来应对COVID-19危机，并在某些情况下找到填补空白的方法。框架和相关证书将来自证书引擎，其他数据将来自开放教学大纲项目。该项目将应用人工智能（AI），特别是自然语言理解（NLU），以（a）与这些证书相关的人行横道能力框架，（B）将用户输入的技能与获得这些证书所需的技能进行比较，（c）生成一个“对齐分数”，用于测量和量化两个技能集之间的差距，以及（d）建议有可能缩小这些差距的课程和证书项目。这将有助于研究NLU在基于能力的认证和培训中的应用，并将提供具体领域（医疗保健）的数据。通过开放式数据基础设施验证和共享基础能力框架翻译和对齐评分服务将改善我们国家的医疗保健人才管道。该RAPID奖由整合活动办公室的融合加速器计划颁发，与融合加速器轨道B相关：工作的未来和人类技术前沿。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。