SBIR Phase I: Autonomous Integration of EMR Information for Patient-Centric Open API Access
SBIR Phase I: Autonomous Integration of EMR Information for Patient-Centric Open API Access
批准号:
1345813
负责人:
Anil Sethi
金额:
$14.98万
依托单位:
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
项目状态:
已结题
起止时间:
2014-01-01 至 2014-06-30
中文摘要
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英文摘要
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.
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