估计药物参与致命的过量服用与不完整的信息的估计
Keith M Drake1, Christopher J Ruhm2
1Greylock McKinnon Associates, Hanover, New Hampshire.
American journal of preventive medicine
|July 7, 2023
概括
准确的药物过量统计至关重要. 对死亡证明数据的简单纠正显著提高了阿片类药物和可卡因参与计数的准确性,解决了未经纠正的数据中的低估.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 生物统计学 生物统计学
背景情况:
- 死亡证书通常缺乏致命过量服用的特定药物信息.
- 不准确的数据可能导致低估药物参与,特别是阿片类药物和可卡因.
- 以往的校正方法已经开发出来,以解决这些数据的限制.
研究的目的:
- 检查死亡证明上的药物过量数据现有纠正的准确性.
- 评估这些校正方法的修改.
- 为了比较纠正的死亡率与未经纠正的死亡率.
主要方法:
- 利用美国国家卫生统计中心的大量药物过量使用数据集 (1999-2020年).
- 采用多种方法来估计在未分类过量中阿片类药物和可卡因的参与.
- 评估了使用平均绝对偏差的预测准确性,并比较了经过纠正的与未经纠正的死亡率.
主要成果:
- 基于回归的校正随着添加固定状态效应而有所改善.
- 对县特征或有助于原因的补充控制没有显著提高准确性.
- 纯粹的模型,按比例分配未指定的死亡人数,提供了准确的预测,特别是在县级分析中.
- 未经纠正的数据大大低估了阿片类药物和可卡因的参与,并且可以随着时间的推移扭曲趋势.
结论:
- 不完整的死亡证明信息导致不准确的药物特定过量计数.
- 相对简单的校正方法可以大大提高过量剂量数据的准确性.
- 纠正的数据对于了解致命过量药物参与的真实范围至关重要.
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