SBIR Phase I: Autonomous Integration of EMR Information for Patient-Centric Open API Access

SBIR 第一阶段：自主集成 EMR 信息以实现以患者为中心的开放 API 访问

• 批准号: 1345813
• 负责人: Anil Sethi
• 金额: $ 14.98万
• 依托单位: Gliimpse LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-01-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1345813&HistoricalAwards=false
• 关键词: SBIR; Phase; Autonomous; Integration; EMR

This Small Business Innovation Research (SBIR) Phase I project proposes to develop a tool for autonomous capture, translation, and integration of proprietary clinical information from Electronic Medical records into a standard public format. The project addresses ongoing healthcare regulations such as the PPACA which require doctors to provide patient access to medical data through electronic means, as well as efficiently share with other providers. Due to the nature of existing Electronic Medical Record systems, data sharing is difficult and discouraged. . Further an Open API will be provided to allow authorized third parties to access such data. Research will focus on data capture, parsing, and machine learning techniques to ensure accuracy and performance. It is expected that multiple methods will be evaluated and at least one method will be implemented in a prototype system. The broader impact/commercial potential of this project will enhance the capability of patients to control their own medical data, its sharing, who has access, and analysis by hospitals and research institutions for ongoing medical research. By placing control of the patient?s data in the hands of the patient, they can choose to keep or share any or all medical data to any provider, or for research purposes. The rapid extraction and integration of data from multiple sources and provision of an open API will remove medical data from the control of vendors with no economic incentive to ensure data sharing. By allowing a single platform for integration, interrogation, and sharing, research and other software platforms can be built on top of the API to enhance medical research, patient awareness, and physician awareness of all data sources, including hospitals, other doctors, third party applications, and the growing use of ?Quantified Self? measurement devices. Significant increases in efficiency for provider use and reduced expenditures on custom coded EMR solutions are anticipated, eliminating the requirement for millions of dollars of consulting, and improved patient care through efficient use of doctor time and provision of relevant information.

这个小企业创新研究（SBIR）第一阶段项目建议开发一种工具，用于自动捕获、翻译和集成来自电子医疗记录的专有临床信息到标准的公共格式。该项目涉及现行的医疗保健法规，如PPACA，这些法规要求医生通过电子手段向患者提供医疗数据，并有效地与其他提供者共享。由于现有电子病历系统的性质，数据共享是困难的和不鼓励的。此外，将提供开放API，以允许授权第三方访问这些数据。研究将集中在数据捕获、解析和机器学习技术上，以确保准确性和性能。预计将评估多种方法，并且至少有一种方法将在原型系统中实现。该项目的更广泛影响/商业潜力将增强患者控制自己的医疗数据、共享数据、访问数据的人员以及医院和研究机构为正在进行的医学研究进行分析的能力。通过控制病人？当数据掌握在患者手中时，他们可以选择将任何或所有医疗数据保留或共享给任何提供者，或用于研究目的。从多个来源快速提取和集成数据以及提供开放API将使医疗数据摆脱供应商的控制，而没有经济激励来确保数据共享。通过允许单一平台进行集成、询问和共享，可以在API之上构建研究和其他软件平台，以增强医学研究、患者意识和医生对所有数据源的认识，包括医院、其他医生、第三方应用程序和越来越多的使用？量化自我?测量设备。预计将显著提高供应商的使用效率，减少定制编码EMR解决方案的支出，消除数百万美元的咨询需求，并通过有效利用医生时间和提供相关信息改善患者护理。