Enhancing the Efficiency of Pragmatic Clinical Trials Using Administrative Data: Analysis of the STRIDE Study

使用管理数据提高实用临床试验的效率：STRIDE 研究分析

• 批准号: 10365009
• 负责人: Denise Esserman
• 金额: $ 46.06万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-15 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10365009
• 关键词: Acute; Adult; Aging; Agreement; Algorithms; Caring; Clinical Data; Clinical Trials; Cluster randomized trial; Code; Communities; Cost Analysis; Cost Savings; Cost efficiency; Coupled; Data; Data Analyses; Data Collection; Data Sources; Detection; Elderly; Electronic Health Record; Event; Fee-for-Service Plans; Gills; Goals; Healthcare Systems; Individual; Injury; International Classification of Diseases; Intervention; Interview; Machine Learning; Medical Records; Medicare; Methods; Modeling; Myocardial Infarction; Outcome; Participant; Patient Self-Report; Patients; Population; Positioning Attribute; Pragmatic clinical trial; Publishing; Reference Standards; Reproducibility; Research; Research Personnel; Research Proposals; Running; Savings; Sensitivity and Specificity; Site; Source; Stroke; System; Techniques; Testing; Text; Time; Variant; Work; adjudicate; algorithm development; automated algorithm; clinical care; comparative; cost; design; disease diagnosis; fall injury; follow-up; health care service utilization; health care settings; human old age (65+); insight; intervention effect; machine learning algorithm; multiple data sources; pragmatic trial; primary outcome; prospective; simulation; treatment as usual

Project Summary & Abstract Pragmatic clinical trials aim to test interventions within typical healthcare settings to produce generalizable results. Successfully implementing pragmatic trials requires overcoming a number of challenges, including acquiring data as efficiently and non-intrusively as possible, so as to encourage maximum study participation at lowest cost. Administrative data are a potential solution for some pragmatic trials. These data derive from routine activities in the healthcare system, including clinical care (e.g., billing systems; use of electronic health records). With administrative data, participants can be passively followed over long time periods, potentially with decreased participant burden, decreased loss to follow-up from inability to contact a participant and decreased cost compared to alternatives (e.g., participant interview or review of medical records). All of these features could enhance both internal and external validity and reduce the overall cost of a trial. Limited empirical work exists on the comparative value of various data sources for ascertaining outcomes in pragmatic trials. We are in a unique position to the leverage the Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) trial, a ten-site pragmatic, cluster-randomized trial focused on serious fall injury in community- dwelling older adults, to determine whether outcome ascertainment in pragmatic clinical trials could be simplified through automated data collection, without introducing significant imprecision or bias, thus reducing costs. STRIDE has multiple sources of data including multiple reference standards (adjudicated outcomes; self-reported outcomes) and two administrative data sources (fee-for-service Medicare data; administrative data from clinical trial sites). We will be able to couple currently available administrative data with newly available Medicare Advantage data to have a complete administrative picture of this almost universally Medicare eligible population. Complete data will give us the opportunity to achieve the overall goal of this research proposal, which is to develop a framework for determining whether administrative data can be used in pragmatic clinical trials in a Medicare eligible population to efficiently and accurately ascertain the primary outcome. To achieve this goal, our project has three aims: (1) develop and validate algorithms for detecting serious fall injuries from administrative data against the reference standards of STRIDE events; (2) determine the impact of the algorithms on trial findings; and (3) assess the cost efficiency (savings) of conducting the trial using administrative data.

项目总结及摘要 务实的临床试验旨在测试典型医疗环境中的干预措施，以产生可推广的结果 结果。成功实施务实试验需要克服许多挑战，包括 尽可能高效、非侵入性地获取数据，以鼓励最大程度的研究参与 以最低的成本。行政数据是一些实用试验的潜在解决方案。这些数据来源于 医疗保健系统中的日常活动，包括临床护理（例如计费系统；电子健康的使用 记录）。有了管理数据，参与者就可以被长期被动地跟踪，潜在的 参与者负担减轻，因无法联系参与者而导致的后续损失减少， 与替代方案（例如参与者访谈或病历审查）相比，成本降低。所有这些 这些功能可以增强内部和外部有效性并降低试验的总体成本。有限的 存在关于各种数据源的比较价值的实证工作，以确定务实的结果 试验。我们处于独特的地位，可以利用战略来减少伤害并增强信心 老年人 (STRIDE) 试验是一项十个地点的实用性整群随机试验，重点关注社区中的严重跌倒伤害 居住的老年人，以确定实用临床试验中的结果确定是否可以 通过自动数据收集进行简化，不会引入明显的不精确或偏差，从而减少 成本。 STRIDE 拥有多个数据源，包括多个参考标准（裁决结果； 自我报告的结果）和两个行政数据源（按服务收费的医疗保险数据；行政数据 数据来自临床试验地点）。我们将能够将当前可用的管理数据与新的管理数据结合起来 可用的 Medicare Advantage 数据几乎可以全面了解这方面的完整管理情况 符合医疗保险资格的人群。完整的数据将使我们有机会实现这个总体目标 研究提案，旨在制定一个框架来确定行政数据是否可以用于 在符合医疗保险资格的人群中进行务实的临床试验，以有效、准确地确定主要疾病 结果。为了实现这一目标，我们的项目有三个目标：（1）开发和验证检测算法 根据 STRIDE 赛事参考标准的管理数据造成严重跌倒伤害； (2)确定 算法对试验结果的影响； (3) 评估进行试验的成本效率（节省） 使用行政数据。