相关实验视频

Updated: Jun 16, 2025

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy

E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy

Published on: August 1, 2019

使用电子健康记录在选择偏见下招募患者:一个两相采样框架

Guanghao Zhang¹, Lauren J Beesley², Bhramar Mukherjee¹

¹Department of Biostatistics, University of Michigan.

The annals of applied statistics

|August 16, 2024

概括

电子健康记录 (EHR) 为临床研究提供了有效的患者招募. 本研究介绍了一种最佳的两相采样方法,使用EHR共变量来提高队列选择效率并解决潜在的偏差.

科学领域:

生物统计学生物统计学
临床研究方法论临床研究方法论
医疗信息学医疗信息学

背景情况:

电子健康记录 (EHR) 对于在临床研究中高性价比的患者招募非常有价值.
从大型EHR数据库中对特定科学问题进行最佳的队列选择仍然是一个挑战.
电子健康记录中的辅助共变量可以提高昂贵结果下游分析的效率.

研究的目的:

提出一个最佳的两阶段采样设计,利用EHR辅助共变量进行有效的队列选择.
为了解决EHR数据中固有的潜在选择偏差,用于多相采样.
与传统的随机抽样相比,提高临床研究分析的效率.

主要方法:

开发了一种新的两相采样设计,利用来自EHR数据的预测辅助共变量.
扩展现有的两阶段采样文献,以考虑EHR选择偏差.
通过模拟研究和现实世界的应用来验证拟议的方法.

主要成果:

建议的最佳双相采样方法显示,比随机采样显著提高了效率.
该方法有效地考虑了EHR数据中的潜在选择偏差.
评估高血压患病率的应用程序显示了设计的实际实用性.

结论:

建议的最佳两相采样设计提高了从EHR中对临床研究队列选择的效率.
这种方法提供了一个强大的策略,以减轻基于EHR的研究中的选择偏见.
利用EHR共变量提供了一个强大的工具,可以提高临床研究的成本效益和统计能力.

关键词:

辅助信息辅助信息辅助信息电子健康记录是电子健康记录.选择偏差是一种选择偏差.研究设计研究设计采样是两个阶段的采样.

更多相关视频

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

相关概念视频

Bias in Epidemiological Studies

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:

Randomized Experiments

Randomized Experiments

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...

Group Design

Group Design

The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...

Blind Procedures

Blind Procedures

Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...

Study Designs in Epidemiology

Study Designs in Epidemiology

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...

Introduction to Epidemiology

Introduction to Epidemiology

Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...