Automated matching of relevant research studies to patient records for EBM

自动将相关研究与 EBM 患者记录进行匹配

• 批准号: 8124800
• 负责人: Christopher D Rosin
• 金额: $ 14.98万
• 依托单位: PARITY COMPUTING, INC.
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2012-09-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8124800
• 关键词: Address; Affect; Awareness; Cereals; Clinical; Clinical Data; Clinical Research; Clinical Trials; Code; Complex; Computer software; Consensus; Controlled Clinical Trials; Cost Control; Data; Development; Diagnosis; Ensure; Evaluation; Evidence Based Medicine; Goals; Guidelines; Healthcare; Hospitals; Illinois; Individual; Informatics; Institutes; Lead; Literature; Manuals; Marketing; Measures; Medical; Methods; Metric; Mining; Monitor; Outcome; Patient Care; Patients; Performance; Phase; Physicians; Policies; Process; Program Evaluation; Protocols documentation; Publishing; Quality of Care; Records; Reliance; Research; Scheme; Software Tools; Structure; System; Techniques; Technology; Text; Ursidae Family; Variant; Work; abstracting; base; clinically relevant; cost effectiveness; design; improved; meetings; novel; parity; point of care; prototype; research study; software development; software systems; tool

DESCRIPTION (provided by applicant): Automated matching of relevant research studies to patient records for EBM Project Summary There is an urgent need to align the delivery, administration, and evaluation of healthcare with the most up-to-date evidence available from published results of clinical trials. This could improve healthcare outcomes and cost-effectiveness on a large scale. But the processes for bringing evidence to bear are currently limited and are applied unevenly. The standard approach to evidence-based medicine depends upon sustained labor-intensive efforts by physicians to identify and study new evidence relevant to their patients. The alternative is to provide automated software tools, but currently available tools are incomplete and are limited to applying simplified pre-digested guidelines to the available pre-structured patient data, which misses many important aspects expressed in the original clinical record. The proposed project will create a software system that overcomes these limitations by automatically identifying published research studies that contain the evidence most relevant to specific patient clinical records. The proposed software will do this by creating and then matching automatically-constructed summaries of both research studies and clinical records (including processing their full original unstructured text). This project will develop a prototype software system and conduct a rigorous evaluation of its accuracy. If successful, this effort will lead to software products that can improve efficiency and precision of healthcare evaluations and significantly raise physician awareness of relevant evidence affecting patient care. PUBLIC HEALTH RELEVANCE: Automated matching of relevant research studies to patient records for EBM Project Narrative The wealth of evidence in published medical research studies is applied unevenly today. If successful, the proposed project will lead to software products that automatically and accurately identify the medical evidence most relevant for individual patients based on their complete medical records. Such software products would have the potential to improve healthcare outcomes and cost-effectiveness on a large scale.

描述（由申请人提供）：EBM项目摘要相关研究与患者记录的自动匹配迫切需要将医疗保健的交付，管理和评估与临床试验结果中已发表的最新证据保持一致。这可以大规模改善医疗保健结果和成本效益。但是，目前提出证据的程序有限，而且应用不均衡。循证医学的标准方法依赖于医生持续的劳动密集型努力，以识别和研究与患者相关的新证据。替代方案是提供自动化软件工具，但目前可用的工具是不完整的，并且仅限于将简化的预消化指南应用于可用的预结构化患者数据，这错过了原始临床记录中表达的许多重要方面。拟议项目将创建一个软件系统，通过自动识别包含与特定患者临床记录最相关的证据的已发表研究，克服这些限制。拟议的软件将通过创建并匹配自动构建的研究和临床记录摘要（包括处理其完整的原始非结构化文本）来实现这一点。该项目将开发一个原型软件系统，并对其准确性进行严格评估。如果成功，这一努力将导致软件产品，可以提高医疗保健评估的效率和精度，并显着提高医生对影响患者护理的相关证据的认识。 公共卫生相关性：自动匹配相关的研究报告，以病人的记录，循证医学项目叙述的丰富的证据，在已发表的医学研究的应用不均衡的今天。如果成功，拟议的项目将导致软件产品，自动和准确地识别医疗证据最相关的个人病人的基础上，他们的完整的医疗记录。这些软件产品将有可能大规模改善医疗保健结果和成本效益。