研究协议 - 评估荷兰围产物注册局 (Perined) 的数据质量:使用来自IUGR风险选择 (IRIS) 研究的医院记录进行数据比较研究
Hilde Plomp1,2, Corine Verhoeven1,2,3,4,5,6, Lilian Peters1,2,5
1Midwifery Academy Amsterdam Groningen, Inholland University of Applied Sciences, Amsterdam, The Netherlands.
F1000Research
|February 14, 2025
概括
本研究通过与医院记录和病例报告表格 (CRFs) 进行比较,评估了荷兰围产科注册表 (Perined) 的数据质量. 结果将告知用户关于注册表数据在围产期研究的准确性.
科学领域:
- 围产期流行病学 围产期流行病学
- 医疗信息学 医疗信息学
- 数据质量评估数据质量评估
背景情况:
- 荷兰孕产妇登记 (Perined) 是荷兰孕产妇数据的关键资源,用于质量分析和研究.
- 基于注册表的研究的准确性在很大程度上取决于基础数据的质量.
- 关于Perined数据库的特定数据质量的知识有限.
研究的目的:
- 评估荷兰围产物注册局 (Perined) 的数据质量.
- 将Perined数据的准确性与IUGR风险选择 (IRIS) 研究中的详细医院记录和病例报告表 (CRF) 进行比较.
- 提供对基于注册表的数据可靠性的洞察力,用于孕产妇和新生儿护理研究.
主要方法:
- 使用来自IRIS研究子样本的数据,重点关注有风险的新生儿及其母亲.
- 将Perined数据与来自医院记录的深入临床数据以及CRF的基线人口统计数据进行比较.
- 评估所有变量的数据完整性和可靠性,使用百分比协议,类内相关系数和卡帕统计数据.
主要成果:
- 对于每个变量,Perined数据的完整性将被计算出来.
- 通过将Perined数据与医院记录和CRF进行比较来评估可靠性.
- 包括类内相关系数和卡帕统计数据在内的统计措施将用于量化协议.
结论:
- 这项研究将为Perined注册表的数据质量提供关键的见解.
- 结果将使研究人员和医疗保健提供者了解使用Perined数据的准确性和局限性.
- 这项研究作为评估围产健康中注册表数据质量的模型.
相关概念视频
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
112
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
112
01:20Comparing the Survival Analysis of Two or More Groups
122
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
122
01:00Detection of Gross Error: The Q Test
5.5K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
5.5K
01:03Data Validation
4.9K
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...
4.9K
01:52Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K