Meeting Clinicians' Information Needs with Highly Tailored Knowledge Summaries

描述（由申请人提供）：该项目的重点是设计和评估方法，以改善临床医生的决策，通过生成临床医生量身定制和患者特定的知识摘要。知识摘要将由语义片段组成（即，提供有意义信息的小文本单元），这些信息与临床医生的患者特定信息需求相关。这种决策支持是很重要的，因为临床医生经常提出的信息需求在病人护理的过程中，这些需求在很大程度上未得到满足。未满足的信息需求是错过了自我导向学习和改善患者护理的机会。 虽然临床医生问题的答案通常可以在在线健康知识资源中找到，但重大障碍限制了这些资源用于患者护理。降低这些障碍的一种越来越流行的方法是在电子健康记录（EHR）系统中提供上下文敏感的“信息按钮”链接。基于临床背景，信息按钮预测临床医生的信息需求，并提供相关的知识资源链接。Infobutton很好地帮助临床医生满足简单的信息需求，但当（i）如果没有大量的认知努力扫描检索到的信息，就无法轻松找到答案;以及（ii）信息需求与EHR屏幕上未显示的数据相关时，它就不那么理想了。 在拟议的研究中，我们将利用重要的初步研究，最先进的信息提取和文本摘要工具，以及越来越多地采用EHR标准，解决以前方法的局限性。本研究将以资讯寻求行为理论为基础。本研究的目的和假设如下： * 利用患者的EHR数据生成知识摘要。H1：在查找患者特定问题的答案时，知识总结比手动搜索更有效。 * 识别有助于临床医生的信息需求和信息寻求行为的背景和认知因素。H1：（i）情境和认知因素与信息需求的类型相关;（ii）与追求信息需求的决定相关。 * 根据临床医生的背景和认知因素将知识摘要转换为定制的知识摘要。H1：临床医生定制的知识摘要比知识摘要更有效和高效，以满足临床医生的信息需求和改善决策。

DESCRIPTION (provided by applicant): This project focuses on designing and evaluating methods to improve clinician decision-making by generating clinician-tailored and patient-specific knowledge summaries. Knowledge summaries will consist of semantic fragments (i.e., small units of text that provide meaningful information) that are relevant to a clinician's patient specific information needs. This kind of decision support is important because clinicians often raise information needs in the course of patient care and these needs are largely unmet. Unmet information needs are missed opportunities for self-directed learning and improved patient care. Although answers to clinicians' questions can often be found in online health knowledge resources, significant barriers limit the use of these resources for patient care. An increasingly popular approach to lowering these barriers is to provide context-sensitive "infobutton" links within electronic health record (EHR) systems. Based on the clinical context, infobuttons anticipate clinicians' information needs and provide relevant links to knowledge resources. Infobuttons do a good job helping clinicians' meet simple information needs, but are less optimal when (i) answers cannot be easily found without substantial cognitive effort scanning the information retrieved; and (ii) the information need is associated with data not displayed on the EHR screen. In the proposed study, we will address limitations of previous approaches leveraging significant preliminary research, state-of-the-art information extraction and text summarization tools, and increasingly adopted EHR standards. The research will be guided by a foundation of information-seeking behavior theories. The study has the following aims and hypotheses: * Generate knowledge summaries leveraging patients' EHR data. H1: Knowledge summaries are more efficacious and efficient than manual search for finding answers to patient-specific questions. * Identify contextual and cognitive factors that contribute to clinicians' information needs and information-seeking behavior. H1: (i) Contextual and cognitive factors are associated with the type of information need; and (ii) with the decision to pursue an information need. * Transform knowledge summaries into tailored knowledge summaries based on clinician's contextual and cognitive factors. H1: Clinician tailored knowledge summaries are more efficacious and efficient than knowledge summaries for meeting clinicians' information needs and improving decision-making.