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通过口头尸检确定印度的死亡率(MINErVA):加强印度国家死亡率监测系统。

Mortality in India established through verbal autopsies (MINErVA): Strengthening national mortality surveillance system in India.

机构信息

Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi, India.

Dr Rajendra Prasad Centre of Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India.

出版信息

J Glob Health. 2020 Dec;10(2):020431. doi: 10.7189/jogh.10.020431.

DOI:10.7189/jogh.10.020431
PMID:33282224
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7688192/
Abstract

BACKGROUND

Following data access and storage concerns, Government of India transferred the management of its Sample Registration System (SRS) based mortality surveillance (formerly known as the Million Death Study) to an Indian agency. This paper introduces the new system, challenges it faced and its vision for future.

METHODS

The All India Institute of Medical Sciences (AIIMS), New Delhi, the new nodal agency, established the "Mortality in India Established through Verbal Autopsy" (MINErVA) platform with state level partners across India in November 2017. The network in its first three years has undertaken capacity building of supervisors conducting verbal autopsy under the SRS, established a panel of trained physician reviewers and developed three IT-based platforms for training, quality control and coding. Coding of VA forms started from January 2015 onwards, and the cause specific mortality fractions (CSMF) of the first 14 185 adult verbal autopsy (VA) records for 2015 were compared with earlier published data for 2010-2013 to check for continuity of system performance.

RESULTS

The network consists of 25 institutions and a panel of 676 trained physician reviewers. 916 supervisors have been trained in conducting verbal autopsies. More than 75 000 VA forms have been coded to date. The median time taken for finalizing cause of death on the coding platform is 37 days. The level of physician agreement (67%) and proportion of VA forms requiring adjudication (12%) are consistent with published literature. Preliminary CSMF estimates for 2015 were comparable with those for 2010-2013 and identified same top ten causes of death. In addition to the delay, two major challenges identified for coding were language proficiency of physician reviewers vis-à-vis language of narratives and quality of verbal autopsies. While an initial strategic decision was made to consolidate the system to ensure continuity, future vision of the network is to move towards technology-based solutions including electronic data capture of VAs and its analysis and improving the use of mortality data in decision making.

CONCLUSION

MINErVA network is now fully functional and is moving towards achieving global standards. It provides valuable lessons for other developing countries to establish their own mortality surveillance systems.

摘要

背景

由于数据访问和存储方面的问题,印度政府将其基于抽样登记系统(SRS)的死亡率监测(原称百万死亡研究)的管理工作转交给了一家印度机构。本文介绍了新系统、面临的挑战以及未来愿景。

方法

新德里的全印医学科学研究所(AIIMS)于 2017 年 11 月与印度各地的邦级合作伙伴建立了“印度死因推断验证”(MINErVA)平台。该网络在最初的三年中,对 SRS 下进行死因推断的监督人员进行了能力建设,建立了一个经过培训的医师审核员小组,并开发了三个基于 IT 的培训、质量控制和编码平台。自 2015 年 1 月起开始对 VA 表进行编码,2015 年,首批 14185 例成人死因推断(VA)记录的特定原因死亡率(CSMF)与之前发表的 2010-2013 年数据进行了比较,以检查系统性能的连续性。

结果

该网络由 25 个机构和一个由 676 名经过培训的医师审核员组成的小组组成。已经培训了 916 名监督人员进行死因推断。迄今为止,已经对超过 75000 份 VA 表进行了编码。在编码平台上确定死因的中位数时间为 37 天。医师一致性(67%)和需要裁决的 VA 表比例(12%)与已发表的文献一致。2015 年的初步 CSMF 估计值与 2010-2013 年的数据相当,确定了相同的十大死因。除了延迟之外,编码方面还面临两个主要挑战,即审核员的语言熟练程度与叙述语言和死因推断质量。尽管最初做出了整合系统以确保连续性的战略决策,但该网络的未来愿景是转向基于技术的解决方案,包括电子数据捕获 VA 及其分析,并改进在决策中使用死亡率数据。

结论

MINErVA 网络现在已经全面运作,并正在努力达到全球标准。它为其他发展中国家建立自己的死亡率监测系统提供了宝贵的经验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6f9/7688192/a2c8c5aaa078/jogh-10-020431-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6f9/7688192/73ac60fb0545/jogh-10-020431-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6f9/7688192/dba76ed4ea39/jogh-10-020431-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6f9/7688192/a2c8c5aaa078/jogh-10-020431-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6f9/7688192/73ac60fb0545/jogh-10-020431-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6f9/7688192/dba76ed4ea39/jogh-10-020431-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6f9/7688192/a2c8c5aaa078/jogh-10-020431-F3.jpg

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