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评估在印度口头尸检中分配死亡原因的方法

Sudhir K Benara¹, Saurabh Sharma¹, Atul Juneja¹

¹Indian Council of Medical Research-National Institute of Medical Statistics, New Delhi, India.

Frontiers in big data

|September 11, 2023

概括

医生编码的口头尸检 (PCVA) 在确定印度死亡原因方面超过了计算机编码的口头尸检 (CCVA) 方法. 需要进一步的多中心研究来改善CCVA的性能.

科学领域:

公共卫生公共卫生
医疗信息学医疗信息学
流行病学流行病学

背景情况:

医生编码的口头尸检 (PCVA) 是确定死亡原因 (COD) 的标准,在医疗认证较低的地区.
计算机编码口语尸检 (CCVA) 提供了效率和成本效益,但需要在不同的环境中对PCVA进行验证.
在COD分配的印度环境中,CCVA方法的性能仍未得到充分探索.

研究的目的:

评估和比较PCVA与三种CCVA方法 (InterVA 5,InSilico,Tariff 2.0) 的性能,以确定印度的死亡原因.
通过使用参考标准数据集,评估不同口语尸检 (VA) 编码方法的准确性和可靠性.
提供关于CCVA适用于印度COD确定性的见解.

主要方法:

利用世界卫生组织 (WHO) 2016年VA工具对德里三级医院的2,120个参考标准病例进行了研究.
PCVA涉及双重独立的医生审查与裁决.
使用因果特定死亡率分数 (CSMF),灵敏度,正预测值 (PPV),CSMF准确度和卡帕统计数据来评估绩效.

主要成果:

PCVA获得了最高的CSMF准确度 (0.79),显著超过了Tariff 2.0 (0.67),InterVA (0.66) 和InSilicoVA (0.62) 的表现.
PCVA表现出最高的一致性 (57%) 和卡帕得分 (0.54),表明卓越的可靠性.
与CCVA方法相比,PCVA对20种死亡原因中的15种表现出更高的敏感性.

结论:

在研究样本中评估的方法中,PCVA方法在确定死亡原因方面表现优越.
目前的CCVA方法需要进一步开发和验证,以便在印度人口中准确地分配COD.
建议在未来使用世卫组织VA工具进行更大的样本大小的多中心研究,以提高CCVA的性能.

关键词:

印度印度印度死亡原因死亡原因计算机编码的口头尸检 (CCVA)医生编码的口头尸检 (PCVA)在口头解剖中,进行了口头尸检.

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