Effectiveness studies with securely pooled healthcare data and adjusted analyses

通过安全汇总的医疗数据和调整后的分析进行有效性研究

基本信息

批准号：
7938849
负责人：
Sebastian G. Schneeweiss
金额：
$ 45.06万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-09-24 至 2012-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7938849
关键词：
Address Aging Algorithms Amendment Analgesics Cardiovascular system Cessation of life Code Computerized Medical Record Data Data Aggregation Data Element Data Set Data Sources Databases Death Rate Development Diagnostic radiologic examination Effectiveness Electronic Health Record Electronics Ensure Epidemiology Event Goals Grant Health Health Personnel Healthcare Heterogeneity Individual Infarction Information Systems Insurance Journals Laboratories Life Medicare Meta-Analysis Methodology Methods Morbidity - disease rate Myocardial Infarction Outcome Outcome Assessment Patients Peer Review Performance Pharmaceutical Preparations Physicians Population Privacy Proton Pump Inhibitors Publishing Randomized Research Research Methodology Research Personnel Rheumatoid Arthritis Safety Sentinel Source Structure Subgroup TNF gene Techniques Testing Training United States Food and Drug Administration Work Writing acute coronary syndrome clopidogrel comparative comparative effectiveness database structure effectiveness research improved inhibitor/antagonist meetings patient privacy percutaneous coronary intervention post-market routine care web page

项目摘要

Description (provided by applicant): The Food and Drug Administration Amendments Act (FDAAA) requires FDA to obtain access to multiple distributed large claims and electronic medical records databases covering 100 million lives by 2012. The pooled database will provide sufficient size to study extremely rare events and a platform for extensive comparative safety and effectiveness research with routine care data. This will include patients underrepresented in many trials, including aging populations with multiple morbidities. Data privacy requirements will limit sharing of detailed patient information, although such information is critical for multivariate adjustment of confounders and valid causal inference. Another major unsolved issue is how to combine heterogeneous information content from various health care databases in order to maximize confounding control. This proposal seeks to advance methods for pooling heterogeneous individuallevel electronic healthcare data in order to allow for pooled analyses with full multivariate adjustment with no sharing of private patient data. --- We will develop and test methods and algorithms for pooling both like and heterogeneous data elements, combining claims information from multiple health care providers and then augmenting these claims with electronic medical record and laboratory values. The methods will be neutral with respect to coding standards and will be robust to heterogeneous database structures. --- We will use the methods to perform three example studies, each of which requires pooled data due to infrequent exposure, small patient subgroups, rare outcomes, or a combination of these: (1) effectiveness of high- versus low-potency statin use after acute coronary syndrome with respect to myocardial infarction and cardiovascular death; (2) effectiveness of TNF inhibitors in patients with rheumatoid arthritis with respect to reducing pain medication use and improvement in lab values and X-ray diagnostics; (3) reduced effectiveness of clopidogrel in the presence of proton pump inhibitors in patients with acute coronary syndrome and/or percutaneous coronary intervention, potentially leading to increased re-infarction rates and death versus clopidogrel alone. --- We will explore, both statistically and operationally, when pooling of individual-level data will out-perform aggregate-level meta-analysis, and test the hypothesis that aggregate-level meta-analysis will yield substantially similar point estimates in most scenarios. --- We will publish and provide SAS code for all methods developed, and provide training sessions to relevant groups of researchers in order to broaden the scope and ensure lasting impact of the work performed. This 2-year project will significantly advance methodology for pooling individual-level information from diverse health care databases. The work will allow for comparative effectiveness and safety analyses that is of highpriority for payers (Medicare) and regulators (FDA) and will provide multivariate-adjusted results with no threat to patient privacy. The focus is on broad and expedited practical applicability.

描述（由申请人提供）：《食品药品监督管理修订法》（FDAAA）要求FDA访问到2012年到2012年涵盖1亿寿命的多个分布式大型索赔和电子医疗记录数据库。汇总数据库将提供足够的规模，以研究极为罕见的事件，并提供了与常规护理数据进行扩展的比较安全和有效性研究的平台。这将包括在许多试验中代表性不足的患者，包括多种病因的老龄化人群。数据隐私要求将限制详细的患者信息的共享，尽管此类信息对于混杂因素的多元调整和有效的因果推断至关重要。另一个主要未解决的问题是如何结合来自各种医疗保健数据库的异质信息内容，以最大化混杂的控制。该建议旨在推进汇总异质个人水平电子医疗数据的方法，以便允许进行完整的多元调整的汇总分析，而无需共享私人患者数据。 ---我们将开发和测试用于汇总喜欢和异构数据元素的算法，结合来自多个医疗保健提供者的索赔信息，然后将这些索赔与电子病历和实验室价值相结合。这些方法在编码标准方面将是中性的，并且对于异质数据库结构将是鲁棒的。 ---我们将使用这些方法进行三个示例研究，每项研究都需要汇总数据，这是由于不经常暴露，较小的患者亚组，罕见结果或这些组合的组合：（1）高功能与急性冠状动脉综合征与心肌梗死和心脏血管血管血管造成的急性冠状动脉综合征的有效性；（2）TNF抑制剂在降低止痛药物使用以及实验室值和X射线诊断方面的改善方面的类风湿关节炎患者的有效性；（3）在存在急性冠状动脉综合征和/或经皮冠状动脉干预患者的质子泵抑制剂的情况下，氯吡格雷的有效性降低，可能导致重新施加率和死亡与单独的氯吡格雷相对于氯吡格雷。 ---我们将在统计和操作上进行探索，当单个级别数据的汇总将超过骨料级荟萃分析时，并检验了在大多数情况下骨料级荟萃分析将产生基本相似点估计值的假设。 ---我们将为开发的所有方法发布并提供SAS代码，并向相关研究人员提供培训课程，以扩大范围并确保执行工作的持久影响。这个为期两年的项目将大大推动从不同的医疗保健数据库中汇总个人级信息的方法。这项工作将允许对付款人（Medicare）和监管机构（FDA）的比较有效性和安全性分析，并将提供多元调整后的结果，而对患者隐私没有威胁。重点是广泛而加快的实用适用性。