儿童死亡证明的准确性:基于人口的回顾性分析
Masahito Yamamoto1,2, Masahito Hitosugi2, Eisuke Ito3
1Department of Pediatrics, Nagahama Red Cross Hospital, Nagahama 526-8585, Shiga, Japan.
Pediatric reports
|November 24, 2025
概括
儿科死亡证明经常包含错误,特别是来自产科医生的错误. 提高准确性需要更好的医生教育和审查流程,以确保可靠的儿童死亡率数据.
科学领域:
- 儿科死亡率 儿科死亡率
- 公共卫生监督 公共卫生监督
- 医疗文件准确性 医疗文件准确性
背景情况:
- 准确的儿科死亡证明对于可靠的死亡统计和公共卫生战略至关重要.
- 以前的研究表明,儿科死亡证明中经常存在不准确性,包括模糊的术语和遗漏.
- 本研究探讨了日本石家庄县儿童死亡证明的准确性,确定了常见的错误和与流行病相关的趋势.
研究的目的:
- 为了评估日本石家庄县儿科死亡证明的准确性.
- 识别儿科死亡证明中的常见错误,并分析医生专业的差异.
- 检查COVID-19大流行之前和之后儿童死亡的潜在原因的变化.
主要方法:
- 对391份儿科死亡证明 (2015-2023) 的基于人口的回顾性审查.
- 由两名儿科医生和两名法医病理学家进行独立审查,以评估准确性和分类错误.
- 医生专业错误率的比较和COVID-19前后潜在原因分布的分析.
主要成果:
- 30.9%的儿科死亡证明包含错误,其中产科医生错误率最高 (92.9%),法医错误率最低 (8.4%).
- 最常见的错误是列出非特定的机制 (例如,心脏骤停),而不是死亡的实际原因.
- 在COVID-19后,急性疾病死亡人数下降 (16.8%至4.0%),先天性疾病死亡人数增加 (12.6%至24.3%).
结论:
- 儿科死亡证明经常出现错误,特别是由产科医生填写的死亡证明.
- 关键的挑战包括错误地将机制归类为死亡原因,以及不充分报告先天性异常.
- 加强医生教育和系统审查过程对于提高公共卫生干预措施的准确性和信息化至关重要.
相关概念视频
01:20Actuarial Approach
280
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,...
280
01:22Life Tables
481
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,...
481
01:22Applications of Life Tables
316
Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
316
01:24Kaplan-Meier Approach
541
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,...
541
01:21Cancer Survival Analysis
633
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
633
02:20Longitudinal Research
13.0K
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...
13.0K