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中文摘要
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描述(由申请人提供):在医院和医生办公室采用电子健康记录(EHR)已被广泛推广为各种医疗保健问题的单一解决方案。然而,美国84%的中小企业(SMB)医生实践尚未采用EHR系统。介入动力公司(IDC)进行了200多个初级保健医生的采访,发现采用的主要障碍是工作流程延迟和费用。降低工作流速度的最大因素是数据输入过程。IDC提出的项目有这样一个具体目标:利用创新的语音输入技术和开源代码系统开发一个低成本的自动化解决方案,使初级保健医生能够在病人检查过程中完成初级保健记录。将以上下文敏感、领域受限的方式分析叙述性语音输入,以生成结构化的临床数据,这些数据可以轻松集成到符合标准的电子病历中。通过使用直接转换为相关EHR条目的语音输入,医生可以提高其笔记的准确性,消除第三方转录错误并避免工作流程延迟。项目方法将包括: 进一步测试和最终开发DocTalk,这是IDC正在申请专利的语音系统,可以对结构化医疗信息进行准确的自然语言处理;开发概念验证数据系统,使用领域增强的开放源代码将医生的语音输入从语音转换为文本,再转换为结构化文本,再转换为电子健康记录数据;针对传统EHR输入方法评估概念验证系统的有效性,目标如下:制图时间减少50%或更多,输出准确率达到90%或更高,主观指标得分超过4分,包括可学习性,工作流适应性,可用性和整体满意度。拟议计划的成功完成将为IDC提供一个可行的技术平台,该平台可以立即用于初级保健医生生成结构化文档,用于其当前的EHR平台。此外,在该计划中开发和完善的技术可以以多种方式扩展。 公共卫生相关性:IDC技术旨在规避中小型企业市场采用的正常障碍,并允许以最低的价格快速提高工作流程和患者护理质量。IDC将为目前使用笔和纸的医生提供一种更自然、更快的方式来输入临床数据,消除在键盘输入或复杂的EHR屏幕导航上花费的时间。该系统将生成结构化的临床数据,使健康信息的交换,患者记录的便携性,计费,数据分析(本地实践和公共卫生),营销和其他好处,从而降低整体医疗保健成本。
英文摘要
DESCRIPTION (provided by applicant): The adoption of electronic health records (EHR) in hospitals and physician offices has been widely promoted as a single solution to a wide variety of health care issues. Yet 84% of small and medium business (SMB) physician practices in the US have not adopted EHR systems. Interventional Dynamics Corporation (IDC) has conducted more than 200 primary care physician interviews, finding that the major disincentives to adoption are workflow delay and expense. The single greatest factor in the reduction of workflow speed is the data input process. IDC's proposed project has this specific aim: Utilize an innovative voice entry technique and open source code systems to develop a low-cost, automated solution to allow primary care physicians to complete a primary care note entirely during the patient examination process. The narrative speech input will be analyzed in a context-sensitive, domain-restricted manner to produce structured clinical data that can be readily integrated into standards-compliant electronic medical records. By using speech inputs that are converted directly to relevant EHR entries, physicians can increase the accuracy of their notes, eliminate third party transcription errors and avoid workflow delays. The project approach will include: Further testing and final development of DocTalk, the IDC patent pending speech system that allows accurate natural language processing of structured medical information; Development of a proof-of-concept data system that converts physician voice input from voice to text to structured text to EHR data using domain enhanced open source code; The evaluation of the effectiveness of the proof-of-concept system against traditional EHR input methods with the following goals: Achieve 50% or more reduction in charting time, achieve 90% or more accuracy in output, and score greater than 4 of 5 on subjective metrics including learnability, workflow fit, usability, and overall satisfaction. Successful completion of the proposed program will provide IDC with a viable technology platform that can immediately be useful to primary care physicians in generating structured documents for use with their current EHR platforms. Furthermore, the technology developed and refined within this program can be expanded in multiple ways. PUBLIC HEALTH RELEVANCE: The IDC technology is designed to circumvent the normal barriers to adoption in the SMB market and allow for quick increases in workflow and quality of patient care at a minimal price point. IDC will provide physicians who currently use pen and paper a more natural and faster way to input clinical data, eliminating time spent on hunt-and-peck keyboard entry or complicated EHR screen navigation. The system will generate structured clinical data that enables the exchange of health information, the portability of patient records, billing, data analytics (both local practice and public health), marketing, and other benefits, resulting in the reduction of overall healthcare costs.
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Transforming Real-world evidence with Unstructured and Structured data to advance Tailored therapy (TRUST)
  • 批准号:
    10450726
  • 项目类别:
  • 资助金额:
    $189.54万
  • 财政年份:
    2020
  • 负责人:
    Daniel Jay Riskin
  • 依托单位:
Transforming Real-world evidence with Unstructured and Structured data to advance Tailored therapy (TRUST)
  • 批准号:
    10256676
  • 项目类别:
  • 资助金额:
    $189.54万
  • 财政年份:
    2020
  • 负责人:
    Daniel Jay Riskin
  • 依托单位:
Transforming Real-world evidence with Unstructured and Structured data to advance Tailored therapy (TRUST)
  • 批准号:
    10180783
  • 项目类别:
  • 资助金额:
    $189.54万
  • 财政年份:
    2020
  • 负责人:
    Daniel Jay Riskin
  • 依托单位:
Enabling value-based healthcare through automating risk assessment for episode-based care
  • 批准号:
    9464424
  • 项目类别:
  • 资助金额:
    $22.26万
  • 财政年份:
    2017
  • 负责人:
    Daniel Jay Riskin
  • 依托单位:
海外基金