在临床决策工作流程中嵌入预测模型的策略
Tope Amusa1, Deborah Okunola1, Osayimwense Izinyon2
1Mathematics and Statistics (Biostatistics), Georgia State University, Atlanta, USA.
Cureus
|February 10, 2026
概括
在医疗保健中实施机器学习预测模型需要仔细整合到临床工作流程中. 成功的部署取决于利益相关者的合作,严格的监测,以及解决诸如警报疲劳等障碍,以获得持续的影响.
科学领域:
- 临床信息学 临床信息学
- 医疗保健服务研究 医疗服务研究
- 人工智能在医学中的应用
背景情况:
- 机器学习 (ML) 和统计预测工具越来越多地被开发用于医疗保健应用.
- 尽管取得了进展,但将这些工具转化为常规的临床实践并实现持续的影响仍然是一个重大挑战.
- 现有的关于这些模型在现实世界中实施的证据是分散的.
研究的目的:
- 综合关于将预测模型嵌入常规医疗保健决策中的经验证据.
- 确定实施团队关于成功部署这些工具的经验教训.
- 分析影响预测模型临床影响的障碍和促进因素.
主要方法:
- 采用了叙事审查方法,搜索主要数据库 (PubMed,Embase,Web of Science,IEEE Xplore) 和2010-2025年信息学期刊.
- 包括专注于现实世界部署多变量预测模型和报告实施结果的研究.
- 证据综合集中在败血症检测,患者病情恶化,医院再入院和紧急分组的模型上.
主要成果:
- 成功的嵌入策略涉及利益相关者的共同设计,仔细的门选择,全面的培训和持续的绩效监测.
- 一种深度学习性败血症模型 (COMPOSER) 显示,医院内死亡率降低,指南遵守率提高.
- 主要障碍包括工作流集成问题,警报疲劳,模型缺乏透明度,数据质量问题和治理不足.
结论:
- 预测模型通过经过精心设计的临床决策支持系统集成提供价值,坚持"五项权利"框架.
- 多学科治理,严格的监测和临床医师培训对于建立信任和确保有效使用模型至关重要.
- 实施团队应优先考虑校准和决策实用性指标,以及模型生命周期治理,以获得成功的临床整合.
相关概念视频
Decision Making
1.0K
Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Automatic decision-making is fast, intuitive, and relies on gut feelings...
1.0K
Predicting Molecular Geometry
46.1K
VSEPR Theory for Determination of Electron Pair Geometries
46.1K
Prediction Intervals
3.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
3.4K
Decision Making: P-value Method
7.0K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
7.0K
Sensitivity, Specificity, and Predicted Value
1.4K
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
Sensitivity is the...
1.4K
End Point Prediction: Gran Plot
1.2K
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
For potentiometric titration, the Gran plot is created by plotting...
1.2K


