相关实验视频
Updated: Jun 18, 2025

05:37
An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
2.0K
评估欧洲金融保护指标的股权和覆盖政策敏感性
Jonathan Cylus1, Sarah Thomson2, Lynn Al Tayara2
1WHO Barcelona Office for Health Systems Financing, Barcelona, Spain; European Observatory on Health Systems and Policies, London, United Kingdom.
Health policy (Amsterdam, Netherlands)
|August 1, 2024
概括
世卫组织/欧洲指标比可持续发展目标指标更好地追踪欧洲卫生系统公平性和全民健康覆盖 (UHC) 的进展. 它对药品共同支付政策更加敏感,减少了灾难性的医疗支出风险.
科学领域:
- 卫生经济学 卫生经济学
- 公共卫生政策 公共卫生政策
- 健康的社会决定因素
背景情况:
- 实现全民健康覆盖 (UHC) 的进展往往以灾难性的医疗支出来衡量.
- 欧洲使用两个关键指标,即可持续发展目标 (SDG) 指标3.8.2和世卫组织欧洲区域办事处 (WHO/欧洲) 指标.
- 这些指标之间的差异可能会导致混乱并影响政策决策.
研究的目的:
- 为了比较可持续发展目标和世卫组织/欧洲指标对药品共同支付政策的敏感性.
- 评估欧盟国家的不同政策情景中灾难性支出风险.
- 确定哪个指标更有效地监测卫生系统公平性和UHC.
主要方法:
- 利用来自欧盟27个国家的统一家庭预算调查数据 (n=505,217个家庭).
- 估计了灾难性支出的风险,考虑了家庭特点和药品共同支付政策.
- 根据每个指标的各种共同支付政策组合,计算了灾难性支出 (LISA) 的预测概率.
主要成果:
- 世卫组织/欧洲指标显示,如果有两个或两个以上的保护性政策 (例如,低固定共同付款,与收入相关的豁免/上限),灾难性支出风险在统计学上显著降低.
- 在SDG指标下,所有保护性政策组合的信心区间与没有保护性政策重叠.
- 对这两个指标来说,自用药品支出强烈预测了灾难性支出.
结论:
- 世卫组织/欧洲指标比可持续发展目标指标更容易响应药品共同支付政策的变化.
- 世卫组织/欧洲指标是监测欧洲卫生系统公平性和全方位医疗保健进展的更合适工具.
- 当使用世卫组织/欧洲指标进行评估时,有关药品共同支付的政策干预措施的影响更为明显.
相关概念视频
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
124
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,...
124
Sensitivity, Specificity, and Predicted Value
241
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...
241
Margin of Error
4.0K
The margin of error is also called the maximum error of an estimate. The margin of error is the maximum possible or expected difference between the observed sample parameter value and the actual population parameter value. For proportion, it is the maximum difference between the value of sample proportion obtained from the data and the true value of population proportion. As the true value of the population parameter is not known, the margin of error is calculated using the sample statistic.
4.0K
Hazard Rate
97
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
97
Coefficient of Variation
3.8K
The coefficient of variation measures the dispersion of the data points or distribution around the mean. Using the coefficient of variation, we can compare two data series with drastically different means or different units of measurement. The coefficient of variation for a sample and a population is expressed as a percentage of the ratio of standard deviation to the mean.
The coefficient of variation is a practical statistical tool in finance. It allows investors to assess the volatility or...
The coefficient of variation is a practical statistical tool in finance. It allows investors to assess the volatility or...
3.8K
Actuarial Approach
70
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
70

