SBIR Phase I: eLearning system that enables patient-centered, team-based care and reduces physician shortages in medically underserved areas

SBIR 第一阶段：电子学习系统，实现以患者为中心、基于团队的护理，并减少医疗服务不足地区的医生短缺

• 批准号: 1746007
• 负责人: Maria Levis
• 金额: $ 22.5万
• 依托单位: Impactivo 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 2019-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1746007&HistoricalAwards=false
• 关键词: SBIR; Phase; eLearning; system; enables

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to significantly reduce primary care physician shortages and improve quality of care for low income patients in the United States by developing a tool that analyzes clinical care team performance data at federally qualified health centers (FQHCs) to automatically deploy individually tailored eLearning support for staff members that enables patient centered team based care. FQHCs are funded by the U.S. Department of Health and Human Services to serve 22 million low income patients living in more than 10,000 of the poorest communities across the Nation. Well-implemented patient centered team-based care has the potential to significantly reduce physician shortages and burden of chronic disease which disproportionately affects low income communities. However, efforts to move and sustain FQHCs participation in this model have had limited success with only 66% attaining patient centered medical home (PCMH) recognition in 2016. Various public initiatives, including the Health Resources and Service Administration Quality Improvement Award and Medicare Access and CHIP Reauthorization Act (MACRA), are providing additional financial incentives to move primary care practices towards PCMH Recognition. However, current approaches to practice transformation are cumbersome and difficult to sustain.The proposed project seeks to disrupt continued health professional education at FQHCs by assessing the feasibility of developing a tool that leverages electronic health record data to identify gaps in patient centered team based care for diabetic patients and deploys tailored asynchronous individualized e-learning nudge type support to each member of the care team based on their performance. The research objectives of this SBIR Phase 1 are to establish the feasibility of using EHR data through an API to trigger individual user and team level flags for variation from a specific set of PCMH standards and diabetes clinical protocols; to develop algorithms that generate an individualized learner user profile and teams level reports; to generate data to design algorithms that learn from user preferences, impacts on flags and patient outcomes; to design user interphase for reward and recognition and to evaluate end user acceptance of eLearning tools. The research will be approached using user centric design, behavioral economics and adult learning principles to gather specific requirements and develop a minimum viable product focused on a subset of between five to 10 indicators.

这项小型企业创新研究（SBIR）I阶段项目的更广泛的影响/商业潜力是，通过开发一种分析联邦合格的健康中心（FQHC）的临床护理团队绩效数据的工具，可以显着减少初级保健医师短缺，并改善美国低收入患者的护理质量，以自动为员工抚养员工抚养员工，从而为员工提供服务，从而为员工提供服务。 FQHC由美国卫生和公共服务部资助，为全国最贫穷社区中有10,000多个社区中的2200万低收入患者提供服务。 以良好的为中心的基于患者的护理有可能显着减少医师短缺和慢性病负担，从而对低收入社区产生不成比例的影响。但是，2016年仅获得以患者为中心的医疗院（PCMH）认可的66％的成功措施，搬迁和维持FQHC的努力取得了有限的成功。各种公共计划，包括健康资源和服务管理质量改进奖以及Medicare Access and Medicare Access and Medicare Recast and Chipra化法案（MACRA），可为PCMH提供其他资金侵害。 However, current approaches to practice transformation are cumbersome and difficult to sustain.The proposed project seeks to disrupt continued health professional education at FQHCs by assessing the feasibility of developing a tool that leverages electronic health record data to identify gaps in patient centered team based care for diabetic patients and deploys tailored asynchronous individualized e-learning nudge type support to each member of the care team based on their performance. 该SBIR第1阶段的研究目标是建立通过API使用EHR数据来触发单个用户和团队级别标志的可行性，从而从一组特定的PCMH标准和糖尿病临床方案中进行了变化；开发生成个性化学习者用户资料和团队级别报告的算法；要生成数据以设计从用户偏好中学习的算法，对标志和患者结果的影响；设计用户中间的奖励和识别，并评估最终用户对电子学习工具的接受。 将使用以用户为中心的设计，行为经济学和成人学习原则进行研究，以收集特定的要求，并开发最低可行的产品，重点介于5到10个指标之间。