Ontology-enhanced Information Retrieval to Improve Clinical Practice

描述（由申请人提供）： 退伍军人健康信息系统和技术架构（VistA）是一个软件应用程序的集成系统，直接支持退伍军人健康管理局（VHA）医疗机构的患者护理。为了促进退伍军人护理，VistA维护了大量患者相关数据的存储库，包括超过13亿个文本文档（例如，病程记录、出院总结）。计算机化患者记录系统（CPRS）是一个与VistA数据存储库接口的前端应用程序，允许临床医生在其电子健康记录（EHR）中输入，审查和更新有关退伍军人护理的所有方面的信息。对于患有复杂疾病和慢性疾病的退伍军人来说，成千上万或数万个基于文本的病程记录可能与他们的电子病历相关联。由于CPRS中缺乏复杂的搜索功能，因此搜索大量文本数据以找到有用的信息可能是一项艰巨的任务。 VistA EHR系统代表了VA临床护理的基石。这项试点研究是研究计划的第一步，最终目标是让临床医生更容易在退伍军人的EHR中找到相关信息，从而改善护理过程，并可能改善患者的预后。拟议的研究的目的是，以确定是否信息检索（IR）技术，发现是有用的，在搜索大型基于文本的数据库，如互联网或PubMed可以应用到VistA的进度说明。此外，我们将探讨是否包括从医学本体的临床相关概念的信息，提高IR结果。 总共将检查四个IR系统：（1）向量空间模型（基线）;（2）本体权重增强的向量空间模型;（3）潜在语义索引模型;（4）本体权重增强的潜在语义索引模型。SNOMED-CT本体将与通过Google的PageRank算法在本体内的相对重要性加权的概念一起使用。将根据其查找与选定记录相关的进展记录的能力对四种IR系统进行评价;其中相关性将由临床合作研究者判断。 待检索的文件集将包括来自James A.黑利退伍军人医疗中心（JAHVMC）的耐甲氧西林金黄色葡萄球菌（MRSA）检测呈阳性，另有五人检测呈阴性。MRSA感染与住院时间延长和慢性病患者的相关性提供了一组理想的IR系统测试患者。MRSA阳性患者的EHR可能包含大量异质性的病程记录（例如，医生记录、护理记录、实验室结果）。与这种复杂条件相关的大量和不同类型的音符将提供对所提出的IR技术的有效性的极好测试。 IR系统将使用从精确度和召回率导出的措施进行评估。精确Wilcoxon符号秩检验（一种非参数检验）将用于检查每项性能指标的IR系统的所有配对组合。

DESCRIPTION (provided by applicant): The Veterans Health Information Systems and Technology Architecture (VistA) is an integrated system of software applications that directly supports patient care at Veterans Health Administration (VHA) healthcare facilities. To facilitate veteran care, VistA maintains a massive repository of patient-related data, including over 1.3 billion textual documents (e.g., progress notes, discharge summaries). The Computerized Patient Record System (CPRS), a front-end application that interfaces with the VistA data repository, allows clinicians to enter, review, and update information concerning all aspects of a veteran's care in their electronic health record (EHR). For veterans with complex and chronic diseases, thousands or tens of thousands of text- based progress notes may be associated with their EHR. Searching through this vast amount of textual data to find useful information can be an arduous task due to the lack of sophisticated search capabilities within CPRS. The VistA EHR system represents the cornerstone of clinical care in the VA. This pilot study is the first step in a program of research, where the ultimate goal is to make finding relevant information within a veteran's EHR easier for clinicians, thus improving processes of care and, potentially, patient outcomes. The purpose of the proposed study is to determine if information retrieval (IR) techniques found to be useful in searching large text-based data repositories such as the Internet or PubMed can be applied to progress notes from VistA. In addition, we will explore whether including information about clinically-relevant concepts from a medical ontology improves IR results. A total of four IR systems will be examined: (1) vector space model (baseline); (2) vector space model enhanced with ontology weights; (3) latent semantic indexing model; and (4) latent semantic indexing model enhanced with ontology weights. The SNOMED-CT ontology will be used with concepts weighted via their relative importance within the ontology by Google's PageRank algorithm. The four IR systems will be evaluated based on their ability to find progress notes relevant to a selected note; where relevance will be judged by the clinical co- investigators. The document collection to be searched will consist of all progress notes over a 17-month period from a random sample of 20 patients from the James A. Haley Veterans Medical Center (JAHVMC) who tested positive for methicillin-resistant Staphylococcus aureus (MRSA) and five who did not test positive. The association of MRSA infections with prolonged hospital stays and patients with chronic conditions presents a cohort of patients that are ideal for testing IR systems. The EHR of MRSA-positive patients are likely to contain large numbers of progress notes of a heterogeneous nature (e.g., physician notes, nursing notes, laboratory results). The large quantity and diverse types of notes associated with this complex condition will provide for an excellent test of the effectiveness of the proposed IR techniques. The IR systems will be evaluated using measures derived from precision and recall. The exact Wilcoxon Signed Rank test, a non-parameteric test, will be used to examine all-pair combinations of IR systems for each performance measure.