利用机器学习来预测护士的营业额意图,并发现关键预测因素:一项跨国调查
Veysel Karani Baris1, Yubo Fu2, Brad Gilbreath3
1Faculty of Nursing, Nursing Management Department, Dokuz Eylul University, Izmir, Turkey.
Journal of advanced nursing
|October 2, 2025
概括
机器学习准确地预测护士的流通意图,确定工作满意度是关键因素. 这种方法有助于为医疗保健组织制定有针对性的保留策略.
科学领域:
- 护理劳动力研究 护理劳动力研究
- 医疗信息学 医疗信息学
- 预测分析在医疗保健中的应用
背景情况:
- 护士轮流是影响全球医疗保健系统的一个重要问题.
- 确定营业额意向的预测因素对于开发有效的保留策略至关重要.
- 机器学习为分析复杂的医疗数据提供了先进的功能.
研究的目的:
- 使用机器学习 (ML) 预测护士的流动意图.
- 确定营业额意向的关键心理,组织和人口预测因素.
- 为了比较三个国家的ML模型性能:美国,土耳其和马耳他.
主要方法:
- 在1625名护士中进行了跨部门,跨国调查.
- 评估了20个变量,包括工作满意度,心理安全和工作参与度.
- 采用了六个ML算法 (逻辑回归,随机森林,XGBoost等) 用于预测和特征重要性分析.
主要成果:
- 后勤回归证明了最高的预测性能 (AUC=0.890).
- 在所有模型中,工作满意度是最有影响力的预测因素.
- 其他重要的预测因素包括国家 (美国),工作经验,抑郁症和心理安全.
结论:
- 机器学习有效地预测使用多维数据的护士轮流意图.
- 这种数据驱动的框架支持有针对性的保留策略,并增强了组织的稳定性.
- 这些发现为医疗保健领导者提供了可操作的见解,以改善护士保留率.
相关概念视频
Current Trends in Nursing II
3.3K
Trends in nursing are multifactorial and associated with changes in society, within the nursing profession, and in other professions. Notably, telehealth and remote nursing contribute to successful healthcare delivery for numerous patients and help reduce stress for nurses due to nursing shortages. Nurses can reach patients, monitor their conditions, and interact with them using computers, audio, visual accessories, and telephones—for example, remote patient monitoring systems. Likewise,...
3.3K
Current Trends in Nursing I
5.3K
Current trends in nursing include:
5.3K
Nursing Interventions II: Selecting and Classifying the Nursing Interventions
3.1K
Creating and executing a nursing diagnosis helps nurses plan care and guide patient, family, and community interventions. They are developed based on a patient's physical evaluation and support measuring the outcomes. It is not recommended to select random interventions throughout the planning process. Instead, consider the following six essential factors when choosing interventions:
3.1K
Steps in Outbreak Investigation
492
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
492
Longitudinal Research
13.1K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
13.1K
Regression Toward the Mean
6.8K
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...
6.8K

