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基于 IT 的患者招募有效性:在德国十所大学附属医院进行的中断时间序列研究的研究方案。

Effectiveness of IT-supported patient recruitment: study protocol for an interrupted time series study at ten German university hospitals.

机构信息

Institute of Medical Biometry and Statistics, Medical Faculty and Medical Center, University of Freiburg, Freiburg im Breisgau, Germany.

Chair of Medical Informatics, Institute of Artificial Intelligence and Informatics in Medicine, Klinikum rechts der Isar, School of Medicine and Health, Technical University of Munich, Munich, Germany.

出版信息

Trials. 2024 Feb 16;25(1):125. doi: 10.1186/s13063-024-07918-z.

Abstract

BACKGROUND

As part of the German Medical Informatics Initiative, the MIRACUM project establishes data integration centers across ten German university hospitals. The embedded MIRACUM Use Case "Alerting in Care - IT Support for Patient Recruitment", aims to support the recruitment into clinical trials by automatically querying the repositories for patients satisfying eligibility criteria and presenting them as screening candidates. The objective of this study is to investigate whether the developed recruitment tool has a positive effect on study recruitment within a multi-center environment by increasing the number of participants. Its secondary objective is the measurement of organizational burden and user satisfaction of the provided IT solution.

METHODS

The study uses an Interrupted Time Series Design with a duration of 15 months. All trials start in the control phase of randomized length with regular recruitment and change to the intervention phase with additional IT support. The intervention consists of the application of a recruitment-support system which uses patient data collected in general care for screening according to specific criteria. The inclusion and exclusion criteria of all selected trials are translated into a machine-readable format using the OHDSI ATLAS tool. All patient data from the data integration centers is regularly checked against these criteria. The primary outcome is the number of participants recruited per trial and week standardized by the targeted number of participants per week and the expected recruitment duration of the specific trial. Secondary outcomes are usability, usefulness, and efficacy of the recruitment support. Sample size calculation based on simple parallel group assumption can demonstrate an effect size of d=0.57 on a significance level of 5% and a power of 80% with a total number of 100 trials (10 per site). Data describing the included trials and the recruitment process is collected at each site. The primary analysis will be conducted using linear mixed models with the actual recruitment number per week and trial standardized by the expected recruitment number per week and trial as the dependent variable.

DISCUSSION

The application of an IT-supported recruitment solution developed in the MIRACUM consortium leads to an increased number of recruited participants in studies at German university hospitals. It supports employees engaged in the recruitment of trial participants and is easy to integrate in their daily work.

摘要

背景

作为德国医学信息学倡议的一部分,MIRACUM 项目在十所德国大学医院建立了数据集成中心。嵌入式 MIRACUM 用例“护理警报-患者招募的 IT 支持”旨在通过自动查询符合资格标准的患者存储库并将其作为筛选候选人,来支持临床试验的招募。本研究的目的是通过增加参与者的数量,来调查在多中心环境中开发的招募工具是否对研究招募有积极影响。其次要目标是衡量所提供 IT 解决方案的组织负担和用户满意度。

方法

本研究使用了 15 个月的中断时间序列设计。所有试验都在随机长度的对照阶段开始,进行常规招募,并在干预阶段进行改变,增加额外的 IT 支持。干预措施包括应用一个招募支持系统,该系统使用在普通护理中收集的患者数据,根据特定标准进行筛选。所有入选试验的纳入和排除标准都使用 OHDSI ATLAS 工具转换为机器可读格式。定期检查数据集成中心的所有患者数据是否符合这些标准。主要结果是每个试验和每周标准化的参与者人数,标准化因子为每周目标参与者人数和特定试验的预期招募持续时间。次要结果是招募支持的可用性、有用性和效果。基于简单平行组假设的样本量计算可以在 5%的显著性水平和 80%的功效下,用总共 100 个试验(每个地点 10 个)证明效应大小为 d=0.57。描述入选试验和招募过程的数据是在每个地点收集的。主要分析将使用线性混合模型进行,每周的实际招募人数和试验标准化为每周和试验的预期招募人数作为因变量。

讨论

在 MIRACUM 联盟中开发的基于 IT 的招募解决方案的应用导致德国大学医院研究中招募的参与者人数增加。它支持参与招募试验的员工,并且易于整合到他们的日常工作中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d9c/10870691/6c18d0dca614/13063_2024_7918_Fig1_HTML.jpg

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