Capturing Patient-Provider Encounter through Text Speech and Dialogue Processing

通过文本语音和对话处理捕捉患者与提供者的相遇

• 批准号: 7934200
• 负责人: PETER SZOLOVITS
• 金额: $ 15.3万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-30 至 2010-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7934200
• 关键词: Address; Adopted; Arts; Beds; Biomedical Research; Boston; Child; Childhood; Clinic; Clinical; Clinical Data; Collaborations; Collection; Communication; Computer Systems; Computer Systems Development; Computer software; Computers; Conflict (Psychology); Data; Diagnosis; Discipline of Nursing; Disease; Documentation; Environment; Environmental Health; Evaluation; Feedback; Genetic Transcription; Goals; Health Personnel; Healthcare; Individual; Lead; Linguistics; Manuals; Medical; Medical Records; Medical Research; Memory; Methods; Modeling; Paper; Patients; Pediatric Hospitals; Pharmaceutical Preparations; Privacy; Process; Provider; Records; Research; Research Ethics Committees; Research Personnel; Resources; Rest; Running; Series; Signs and Symptoms; Speech; Stream; Structure; System; Techniques; Technology; Test Result; Testing; Text; Time; Transcript; Visit; Visual; Work; base; clinical care; clinically significant; design; electronic recording system; experience; improved; information organization; new technology; patient safety; prototype; research study; response; speech recognition; success; translational medicine

Project Summary Complete and accurate collection of clinical data in the course of health care is a long-standing goal that has not been achieved either by manual record-keeping or through electronic record systems. This proposed project addresses the problem from the beginning of the clinical process, by aiming to improve the capture of relevant medical facts during the face-to-face interaction between a patient and provider. Instead of relying on the provider's fallible memory to record facts after the visit, the proposed system will "listen" to the conversation, use automatic speech recognition to produce an (imperfect) record of what was said, and apply a variety of text analysis and extraction methods to create a draft record of the encounter. Further, it will provide an interface that should permit patients and providers to examine the facts that were recorded and to correct and complete them, also using speech as the primary interface. The projects aims are to develop and integrate the components needed to accomplish this goal, to create a testbed in collaboration with researchers at the environmental health clinic of a children's hos- pital in which experiments can guide system development and assess progress, and to conduct a series of evaluations that assess a series of objectives. First, the research will characterize the ability of the speech recognition, information extraction and information organization components to process the target conversations. Second, it will evaluate the hypothesis that this system can collect a more complete and accurate record than what is routinely collected. Subsequently, it will evaluate the time taken by clinicians to use the system, the extent to which the system is seen to disrupt the patient-provider encounter, the ability of patients to use the system to make additions and corrections to their records, and the subjective response of both patients and providers to use of the system. Success in this effort should lead to better clinical care that is based on more complete and accurate data. In addition, clinical data are also becoming an important resource in the conduct of translational medicine research, where improved data are obviously highly valuable. Project Narrative A well-organized, complete and accurate record of clinical encounters can form the bedrock of data on which both clinical care and clinical and biomedical research can rest. This project applies state of the art and novel technologies to "listen" to and interpret encounters between patients and health care providers to create such records. Its success should lead to better health care and greater possibilities for using clinical data in medical research.

项目概要 完整、准确地收集医疗保健过程中的临床数据是我们长期追求的目标 无论是通过手工记录保存还是通过电子记录系统都未能实现这一目标。这 拟议的项目从临床过程一开始就解决了问题，旨在改善 在患者和提供者之间面对面互动期间捕获相关的医疗事实。 所提议的系统不再依赖提供者的错误记忆来记录访问后的事实 将“聆听”对话，使用自动语音识别来生成（不完美的）对话记录 所说内容，并应用各种文本分析和提取方法来创建草稿记录 遇到。此外，它将提供一个界面，允许患者和提供者检查 记录的事实并纠正和完善它们，也使用语音作为主要界面。 该项目的目标是开发和集成实现这一目标所需的组件，以 与儿童医院环境健康诊所的研究人员合作创建一个测试平台 实验可以指导系统开发和评估进展，并进行一系列 评估一系列目标的评估。首先，研究将表征 语音识别、信息提取和信息组织组件来处理目标 对话。其次，它将评估该系统可以收集更完整和更完整的假设。 比常规收集的记录更准确。随后，它将评估临床医生所花费的时间 使用该系统时，该系统被认为在多大程度上扰乱了患者与提供者的接触， 患者使用系统对其记录进行添加和更正的能力，以及主观 患者和提供者对系统使用的反应。 这项努力的成功应该会带来基于更完整和准确的更好的临床护理 数据。此外，临床数据也正在成为进行转化的重要资源。 医学研究，改进的数据显然非常有价值。项目叙述 组织良好、完整且准确的临床病例记录可以构成以下数据的基础： 临床护理以及临床和生物医学研究都可以休息。该项目采用了最先进的技术 以及“倾听”和解释患者与医疗保健提供者之间的接触的新技术 创建此类记录。它的成功应该会带来更好的医疗保健和更大的使用可能性 医学研究中的临床数据。