Improved Estimates of the Comparative Treatment Effects of CABG and PCI

描述（申请人提供）：本申请解决了挑战领域10和特定挑战主题10-HL- 101*，“用于处理研究的医疗保健数据的信息技术”，特别是挑战主题10-HL-101*，“开发数据共享和分析方法，以从大规模观察数据，特别是从电子健康记录中获得的数据，对心血管、肺和血液疾病的比较治疗效果和结局的可靠估计。“电子健康数据的可用性现在允许研究人员比较接受相同临床条件不同治疗的患者的结果，这将有利于评估在代表性实践环境中观察到的典型患者的治疗，而不是仅仅依赖于正式的随机对照试验。观察性比较的主要局限性是许多因素可能影响治疗的选择或临床结局，因此从观察性数据得出的治疗比较可能不可靠。本研究的目的是评价几种统计方法，以冠状动脉旁路移植术和冠状动脉血管成形术作为测试病例，从观察数据中获得可靠的治疗比较。将在来自北方加州Kaiser Permanente的电子记录的大型观察数据库中比较各种分析方法，随后将使用10项随机临床试验之一的7，812例随机接受手术或血管成形术的个体患者的独立数据库评估这些方法的有效性。将采用各种观察方法，包括倾向评分法、工具变量法和新兴技术，根据基线临床特征确定总体比较有效性和有效性变化。然后将采用最可靠的方法比较试验中代表性较差的患者组（例如，75岁以上的患者），以及其他大型数据集，如医疗保险文件。在这项冠状动脉疾病测试案例研究中验证的方法将成为更通用的工具，可广泛应用于评估其他疗法和其他患者人群。目前的提案将通过在斯坦福大学医学和其他地方创造或保留两个新的就业机会来积极影响经济。（根据加州生物医学行业的数据，生物医学组织每雇用一名员工，就会有三到五名员工受雇于为该行业服务的公司。） 公共卫生相关性：该项目将开发使用电子医疗记录信息的方法，以可靠地比较心脏病的治疗方法。更好地使用常规实践中收集的电子数据的方法将有助于比较常规医疗保健环境中治疗的获益和风险。

DESCRIPTION (provided by applicant): This application addresses Challenge Area 10 and specific Challenge Topic 10-HL- 101*,"Information Technology for Processing Healthcare Data for Research," specifically to the challenge topic 10-HL-101*, "Develop data sharing and analytic approaches to obtain from large- scale observational data, especially those derived from electronic health records, reliable estimates of the comparative treatment effects and outcomes of cardiovascular, lung, and blood diseases." The availability of electronic health data now permits researchers to compare the outcomes of patients who received different treatments for the same clinical condition, which would be advantageous by assessing treatment among typical patients seen in representative practice settings rather than relying solely upon formal randomized controlled trials with highly selected patients. The major limitation of observational comparisons is that many factors may affect either the choice of treatment, or clinical outcomes, so comparisons of treatment derived from observational data may not be reliable. The goal of this study is to evaluate several statistical approaches to derive reliable treatment comparisons from observational data using coronary artery bypass graft surgery and coronary angioplasty as the test case. Various analytic methods will be compared in a large observational database from the electronic records of Kaiser Permanente of Northern California, and the validity of these methods will subsequently be assessed using an independent database of 7,812 individual patients randomized to surgery or angioplasty in one of ten randomized clinical trials. A variety of observational methods, including propensity score approaches, instrumental variables approaches and emerging techniques, will be applied to determine both overall comparative effectiveness and variations in effectiveness according to baseline clinical characteristics. The most reliable method(s) will then be applied to compare surgery and angioplasty in patient groups that were poorly represented in the trials (e.g., patients more than 75 years old), as well as in other large datasets, such as Medicare files. The methods validated in this test case study of coronary disease will then be more general tools that may be applied broadly to evaluate other therapies and other patient populations. The current proposal would positively impact the economy by creating or retaining two new jobs at Stanford Medicine and elsewhere. (According to the California Biomedical Industry, for every one employee of a biomedical organization, another three to five will be employed in firms that service that industry.) Public Health Relevance: This project will develop methods to use information from electronic medical records to reliably compare treatments for heart disease. Better methods to use electronic data collected in routine practice will help compare the benefits and risks of treatments in routine medical care settings.