Reliable Performance of Cancer Screening using a Computer-based Monitoring System

描述（由申请人提供）：尽管通过早期检测有可能减少癌症负担，但筛查计划的有效性往往受到基于系统的因素和人为因素的破坏。这项申请的主要目的是开发和评估一种名为TRACS的基于计算机的技术，以监测个体患者的癌症筛查过程，并在必要时进行干预，以确保筛查可靠有效地进行。TRACS的干预措施包括向临床医生和/或患者提供可靠的通知。然而，与许多其他提醒系统不同，TRACS在通知之后继续监视患者的护理。 在本申请阶段，TRACS将用于解决乳腺癌筛查性乳房X线摄影的异常或可疑结果随访的可靠性。将在TRACS知识库中创建一个知识模块，用于监测异常筛查乳房X线照片的随访。知识模块包括过程定义，该过程定义为临床场景指定适当的行动过程，以及在过程中做出决策的逻辑规则。在下一阶段，将增加更多的知识模块，以全面支持乳腺癌、宫颈癌和结肠癌的筛查。 TRACS的一个重要功能是能够使用名为HITex的自然语言处理引擎从临床文本文档中提取信息。几种癌症筛查测试的报告，如乳房X光检查、宫颈涂片和结肠镜检查，都是以文本文档的形式提供的。因此，必须能够从这些文件中提取有关信息供TRACS使用。将定制HITex，以便从筛查乳房X线照片报告中提取放射科医生的建议。具体而言，它将提取放射科医生是否建议进行非常规随访。如果是这种情况，HITex将提取建议的后续行动（例如，诊断性乳房X线照片、超声或针吸活组织检查）。 TRACS将在新英格兰医疗中心（NEMC）进行部署和评估，NEMC是波士顿的一个大型城市医疗中心。评价的第一步是确认HITex可以准确提取来自NEMC的筛查乳腺X线照片报告的信息。在此阶段，TRACS软件和异常乳腺X线摄影随访知识模块将在NEMC的模拟环境中进行测试。这些测试将使用以前在NEMC接受过筛查性乳房X光检查的患者的记录进行。TRACS在这些情况下的行为将由NEMC的专家小组进行评级。在下一阶段，TRACS将在NEMC部署。计划简介本计划拟发展的软件，旨在改善对多项常见癌症的早期识别。它将通过对癌症筛查结果异常的患者的管理进行可靠的后续工作来做到这一点。

DESCRIPTION (provided by applicant): Despite their potential to reduce cancer burden through early detection, the effectiveness of screening programs is often undermined by systems-based factors and human factors. The broad aims of this application are to develop and evaluate a computer-based technology called TRACS to monitor the process of cancer screening in individual patients and intervene as necessary to ensure that the screening is conducted reliably and effectively. Interventions in TRACS consist of reliable notifications to clinicians and/or patients. However, unlike many other reminder systems, TRACS continues to monitor the care of the patient subsequent to the notification. In this phase of the application, TRACS will be used to address the reliability of follow up of abnormal or equivocal results from screening mammography for breast cancer. A knowledge module will be created in TRACS knowledge base for the monitoring of the follow up of abnormal screening mammograms. A knowledge module comprises the process definition that specifies the appropriate course of actions for a clinical scenario and logical rules for making decisions within the process. In the next phase, additional knowledge modules will be included for comprehensive support for screening of breast cancer, cervical cancer, and colon cancer. An important feature of TRACS will be the ability to extract information from clinical text documents using a natural language processing engine called HITex. Reports of several cancer screening tests, such as mammography, cervical smear, and colonoscopy, are in the form of text documents. Thus it is important to be able to extract relevant information from these documents for use by TRACS. HITex will be customized to extract the recommendations of the radiologist from screening mammogram reports. Specifically, it will extract whether the radiologist recommends a non-routine follow up. If that is the case, HITex will extract the recommended follow up (e.g., diagnostic mammogram, ultrasound, or needle biopsy). TRACS will be deployed and evaluated at the New England Medical Center (NEMC), a large urban medical center in Boston. The first step in the evaluation will be to confirm that information from screening mammogram reports from NEMC can be extracted accurately by HITex. During this phase, the TRACS software and the abnormal mammography follow up knowledge module will be tested in a simulated setting at NEMC. The tests will be conducted using records of patients who had previously undergone screening mammography at NEMC. The behavior of TRACS for these cases will be rated by a panel of experts from NEMC. In the next phase, TRACS will be deployed operationally at NEMC. Project Narrative The software proposed to being developed under this project aims to improve the early identification of a number of commonly occurring cancers. It will do so by following up reliably on the management of those patients that have abnormal results in cancer screening tests.