随着Shipman:在初级保健中监测死亡率的试点系统
Paul Aylin1, Nicky Best, Alex Bottle
1Department of Epidemiology and Public Health, Imperial College London, St Mary's Campus, Norfolk Place, W2 1PF, London, UK. p.aylin@imperial.ac.uk <p.aylin@imperial.ac.uk>
Lancet (London, England)
|August 21, 2003
概括
统计过程控制图表可以在一般实践中监控死亡. 这些累积和图表,当正确应用时,提供了一个可行的系统来检测潜在的问题,尽管数据质量对于准确性至关重要.
科学领域:
- 医学统计 医学统计
- 公共卫生监督 公共卫生监督
- 初级医疗保健医学 一级医疗保健医学
背景情况:
- 对哈罗德·希普曼罪行的调查显示,在一般实践中对死亡的监测不足.
- 现有的系统缺乏强大的方法来检测初级保健机构中不寻常的死亡率模式.
研究的目的:
- 评估累积和图 (CUSUM) 在一般实践中监测死亡的有用性.
- 评估统计过程控制系统的可行性,以早期检测初级保健死亡率数据中的潜在问题.
主要方法:
- 利用了来自五个英格兰卫生当局 (1993-1999) 的家庭医生和实践水平的年度死亡数据.
- 采用累积和图,用经验计算的虚假检测和成功检测值,调整为多次测试和Poisson外变化.
- 对未测量的case-mix变化进行统计调整的图表.
主要成果:
- 在1009名家庭医生中,33人 (包括Shipman) 超过了标准化死亡率增加2SD的警报值.
- 该系统实现了97%的成功检测,错误报警率为5%.
- 数据质量差和患者因素 (养老院/临终关怀) 被确定为大多数额外警报的可能原因.
结论:
- 累积总和图表提供了一个实用的工具,用于监测在初级保健中的死亡,当适当地使用时.
- 改善死亡数据的质量对于有效实施此类监测系统至关重要.
- 这种方法可以通过识别一般实践死亡率的潜在问题来提高患者的安全性.
相关概念视频
Introduction to Vital Signs
Vital signs are physiological measurements that help key into the status of the body's essential functions. These include body temperature, pulse rate, respiratory rate, and blood pressure, commonly abbreviated as T, P, R, and BP. Some healthcare settings also consider oxygen saturation (SpO2) and, in specific contexts, pain and level of consciousness as additional vital signs.
Vital signs help healthcare professionals assess an individual's well-being and detect any functional changes or...
Vital signs help healthcare professionals assess an individual's well-being and detect any functional changes or...
Introduction To Survival Analysis
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time until a...
The primary goal of survival analysis is to estimate survival time—the time until a...
Life Tables
A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
Actuarial Approach
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,...
Kaplan-Meier Approach
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
Hazard Rate
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...

