Utilizing Electronic Health Records to Measure and Improve Prostate Cancer Care

 描述(申请人提供)：前列腺癌是男性最常见的恶性肿瘤。新诊断的男性面临复杂的治疗选择，每个治疗选择都有不同的以患者为中心的后天结果的风险(例如，尿液和勃起功能障碍)。目前，患者和临床医生不能很容易地比较不同治疗方法中以患者为中心的结果之间的权衡，因为关于这些权衡的经验证据不存在，因为以患者为中心的结果通常不会以可评估的格式记录下来。然而，电子医疗记录(EHR)免费文本是以患者为中心的结果的丰富、未开发的来源。我们建议组装一个健壮的数据挖掘工作流，以高效和准确地从EHR中的结构化数据和自由文本中捕获治疗和结果质量指标。我们将通过基于网络的风险评估工具将这些证据交到临床医生和患者手中。我们的建议有三个创新方面。首先，我们将开发一个EHR前列腺癌数据库，该数据库将允许分析临床护理数据和诊断细节。其次，我们将创建新的质量度量的本体论表示，这些表示将是公开的，并且可以跨EHR系统可靠地计算。第三，我们将组装一个健壮的数据挖掘工作流，它通过专注于基于本体的词典来注释自由文本来扩展现有方法。结合这组创新组件将独特地允许我们使用现有的EHR来有效地研究不同治疗方法中以患者为中心的结果之间的权衡。在目标1中，我们将创建识别EHR中的高质量指标数据所需的构建块。我们将开发一个电子病历数据库，将质量指标映射到医学词汇和本体，并创建电子质量指标表型。在目标2中，我们将使用质量度量词汇表扩展我们的数据挖掘工作流，并使用它来收集与质量度量相关的数据。在目标3中，我们将开发一个基于网络的工具，将我们前两个目标中评估的经验证据与患者和临床特征相结合，以评估患者在不同治疗方案中以患者为中心的结果的个性化风险。我们的网络工具将显示这种个性化的风险预测，以帮助临床医生和患者选择提供最佳预测生活质量的治疗方案，因为他们对 每一个以病人为中心的结果。这项提案将通过为临床医生和患者提供所需的经验证据，来比较不同治疗方法以患者为中心的结果之间的权衡，从而解决前列腺癌治疗和研究的证据方面的一个关键差距。我们的工作与我国对电子健康记录“有意义的使用”和对医疗保健服务的全面评估的关注是一致的，也与NCI对提高癌症护理服务质量的关注是一致的。

 DESCRIPTION (provided by applicant): Prostate cancer is the most common malignancy in men. Newly diagnosed men face complex treatment choices, each with different risks of acquired patient-centered outcomes (e.g. urinary and erectile dysfunction). Currently, patients and clinicians cannot easily compare the trade-offs among patient-centered outcomes across different treatments because the empirical evidence regarding these trade-offs does not exist, because patient centered outcomes are not routinely recorded in assessable formats. However, electronic healthcare records (EHR) free text is a rich, untapped source of patient centered outcomes. We propose to assemble a robust data-mining workflow to efficiently and accurately capture treatment and outcome quality metrics from structured data and free-text in EHRs. We will put this evidence in the hands of both clinicians and patients through a web-based risk assessment tool. Our proposal has three innovative aspects. First, we will develop an EHR prostate cancer database that will allow for clinical care data to be analyzed alongside diagnostic details. Second, we will create novel ontological representations of quality metrics that will be public and reliably calculable across EHR-systems. Third, we will assemble a robust data- mining workflow that expands on existing methods by focusing on ontology-based dictionaries to annotate free text. Combining this set of innovative components will uniquely allow us to use existing EHRs to efficiently study the trade-offs among patient-centered outcomes across different treatments. In Aim 1 we will create the building blocks needed to identify quality metric data in EHRs. We will develop an EHR-database, map quality metrics to medical vocabularies and ontologies, and create electronic quality metric phenotypes. In Aim 2, we will expand our data-mining workflow with quality metric vocabulary and use it to gather data relevant to quality metrics. In Aim 3 we will develop a web-based tool that integrates the empirical evidence assessed in our first two aims with patient and clinical characteristics to estimate patients' personalized risks of patient centered outcomes across treatments. Our web tool will display such personalized risk predictions, to help clinicians and patients choose a treatment option that offers the best predicted quality of life given the importance they assign to each patient-centered outcome. This proposal will address a critical gap in evidence for prostate cancer treatment and research by providing clinicians and patients with empirical evidence needed to compare the trade-offs among patient centered outcomes across different treatments. Our work is consistent with our nation's focus on EHR `meaningful use' and the comprehensive assessment of healthcare delivery, and with NCI's focus on improving the quality of cancer care delivery.