开发个人参与者数据完整性工具,以评估使用个人参与者数据的随机试验的完整性
Kylie E Hunter1, Mason Aberoumand1, Sol Libesman1
1NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia.
Research synthesis methods
|August 19, 2024
概括
研究人员开发了一种新工具,使用个人参与者数据 (IPD) 评估医学研究的完整性. 该工具可以更好地检测不值得信赖的研究,提高医疗保健证据的质量.
科学领域:
- 医学研究诚信 医学研究诚信
- 临床试验方法论 临床试验方法论
- 在医疗保健中的数据科学.
背景情况:
- 对医学研究的完整性日益关注,需要先进的检测方法.
- 目前的工具通常依赖于汇总数据 (AD),这可能不足以进行彻底的可信度评估.
- 个人参与者数据 (IPD) 审查对于识别临床试验中微妙的完整性问题至关重要.
研究的目的:
- 描述个人参与者数据 (IPD) 完整性工具的开发.
- 创建一个标准化和自动化工具来检测可用IPD随机试验中的完整性问题.
- 提高医学研究数据的可靠性和可信度.
主要方法:
- 进行文献审查以确定现有的完整性评估项目.
- 召集了一个专家咨询小组来改进和标准化该工具的项目.
- 在两次IPD元分析 (116项试验) 中试验了该工具,并对13个数据集进行了验证.
- 根据试点和验证结果,代地改进了该工具.
主要成果:
- 确定了120个完整性项目,按数据要求 (AD,IPD或两者) 分类.
- 开发了一个初始基于共识的工具,包含11个AD项目和12个IPD项目.
- 最终的IPD完整性工具包括7个AD领域 (13个项目) 和8个IPD领域 (18个项目).
- 验证成功识别了所有已知完整性问题研究.
结论:
- 开发的IPD完整性工具有效地检测使用个人参与者数据的随机试验中的完整性问题.
- 这个工具使研究人员,编辑和利益相关者能够提高医学证据的可信度.
- 通过这样的工具确保数据质量对于基于证据的医疗保健至关重要.
更多相关视频
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
14.4K
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
7.0K
相关概念视频
Statistical Software for Data Analysis and Clinical Trials
525
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
525
Ethics in Research
22.9K
Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound.
22.9K
Data Validation
5.0K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Nursing assessment guides are generally based on holistic models rather than medical...
5.0K
Randomized Experiments
6.8K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Simple randomization
Simple...
6.8K
Methods of Documentation III: PIE
1.4K
Problem-intervention-evaluation (PIE) is a systematic approach to documentation used in healthcare settings for clinical decision-making and patient care planning. It is a structured approach to organizing patient data based on problems, interventions, and evaluations. Here's a breakdown of its key features and considerations:
1.4K
Reliability and Validity
12.7K
Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
12.7K
