SBIR Phase I: A software product that empowers healthcare teams with community resource information and facilitates post-treatment care coordination.

SBIR 第一阶段：一款软件产品，为医疗团队提供社区资源信息并促进治疗后护理协调。

• 批准号: 1746170
• 负责人: Tom Lee
• 金额: $ 22.49万
• 依托单位: Medical Innovators Company, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1746170&HistoricalAwards=false
• 关键词: SBIR; Phase; software; product; empowers

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to develop and test feasibility of a web-based software and machine learning technology that is able to empower healthcare teams with community resource information as well as facilitate coordination of post-treatment care. Lack of access to community resources such as housing, food and transportation (also known as social determinants of health) has been associated with negative health outcomes such as unplanned hospital readmissions and emergency room visits. This leads to high healthcare costs. Therefore, healthcare teams (i.e. social workers, case managers and discharge planners) spend a significant amount of time to locate appropriate community resources for their patients. Our innovation will leverage a community of healthcare professionals and the resource providers to ultimately find community resources for patients in a faster and less costly manner. The machine learning technology supported by this award will connect healthcare professionals with relevant community resources that ultimately reduces the cost and time associated with this process. A successful implementation of this technology will lead to improved post-treatment care outcomes for the patients and reduced cost of care. The proposed project will develop and test the feasibility of a web-based software platform to empower healthcare professionals to share community resources. Novel machine learning technology will be developed to facilitate appropriate and efficient exchange of community resources. Healthcare professionals using the platform will be able to get onto the platform as well as search and share resources. The machine learning algorithm leverages the relationships of healthcare professionals and resource providers to coordinate community resource sharing. A successful implementation of this algorithm will provide substantial improvements on the ability to acquire timely community resources as compared current methods. The goal of this research is to validate whether the machine learning technology is able to help healthcare professionals identify appropriate community resources.

该小企业创新研究 (SBIR) 第一阶段项目的更广泛影响/商业潜力将是开发和测试基于网络的软件和机器学习技术的可行性，该技术能够为医疗团队提供社区资源信息，并促进治疗后护理的协调。缺乏获得住房、食物和交通等社区资源（也称为健康的社会决定因素）与意外的再入院和急诊室就诊等负面健康结果有关。这导致高昂的医疗费用。因此，医疗团队（即社会工作者、个案经理和出院计划人员）花费大量时间为患者寻找合适的社区资源。我们的创新将利用医疗保健专业人员和资源提供者的社区，最终以更快、更低成本的方式为患者找到社区资源。该奖项支持的机器学习技术将医疗保健专业人员与相关社区资源联系起来，最终降低与此过程相关的成本和时间。该技术的成功实施将改善患者的治疗后护理结果并降低护理成本。 拟议的项目将开发并测试基于网络的软件平台的可行性，以使医疗保健专业人员能够共享社区资源。将开发新颖的机器学习技术，以促进社区资源的适当和有效的交换。使用该平台的医疗保健专业人员将能够进入该平台并搜索和共享资源。机器学习算法利用医疗保健专业人员和资源提供者的关系来协调社区资源共享。与现有方法相比，该算法的成功实施将大大提高及时获取社区资源的能力。这项研究的目的是验证机器学习技术是否能够帮助医疗保健专业人员识别适当的社区资源。