Grover Ashoo, Nair Saritha, Sharma Saurabh, Gupta Shefali, Shrivastava Suyesh, Singh Pushpendra, Kanungo Srikanta, Ovung Senthanro, Singh Charan, Khan Abdul Mabood, Sharma Sandeep, Palo Subrata Kumar, Chakma Tapas, Bajaj Anjali
Indian Council of Medical Research, New Delhi, India.
Indian Council of Medical Research-National Institute for Research in Digital Health and Data Science, New Delhi, India.
JMIR Res Protoc. 2024 Dec 20;13:e51493. doi: 10.2196/51493.
Mortality statistics are vital for health policy development, epidemiological research, and health care service planning. A robust surveillance system is essential for obtaining vital information such as cause of death (CoD) information.
This study aims to develop a comprehensive model to strengthen the CoD information in the selected study sites. The specific objectives are (1) to identify the best practices and challenges in the functioning of the Civil Registration and Vital Statistics (CRVS) system with respect to mortality statistics and CoD information; (2) to develop and implement interventions to strengthen the CoD information; (3) to evaluate the quality improvement of the Medical Certification of Cause of Death (MCCD); and (4) to improve the CoD information at the population level through verbal autopsy for noninstitutional deaths in the selected study sites.
An uncontrolled, before-after, mixed method study will be conducted in 3 blocks located in the districts of 3 states (Madhya Pradesh, Uttar Pradesh, and Odisha) in India. A baseline assessment to identify the best practices and challenges in the functioning of the CRVS system, along with a quality assessment of the MCCD, will be conducted. An intervention informed by existing literature and the baseline assessment will be developed and implemented in the study sites. The major components of intervention will include a Training of Trainers workshop, orientation of stakeholders in the functioning of the CRVS system, training of physicians and medical officers in the MCCD, and training of community health workers in World Health Organization Verbal Autopsy 2022 instrument. Postintervention evaluation will be carried out to assess the impact made by the intervention on the availability and quality improvement of CoD information in the selected study sites. The outcome will be measured in terms of the quality improvement of the MCCD and the availability of CoD information at population level through verbal autopsy in the selected study sites.
The project has been funded, and regulatory approval has been obtained from the Institutional Ethics Committee. The data collection process began in May 2023. The duration of the study will be for 24 months.
Our study is expected to provide a valuable contribution toward strengthening CoD information, which could be helpful for policy making and further research. The intervention model will be developed in collaboration with the existing functionaries of the health and CRVS systems in the selected study sites that are engaged in reporting and recording CoD information; this will ensure sustainability and provide lessons for upscaling, with the aim to improve the reporting of CoD information in the country.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51493.
死亡率统计对于卫生政策制定、流行病学研究和医疗服务规划至关重要。一个强大的监测系统对于获取诸如死因（CoD）信息等重要信息至关重要。
本研究旨在开发一个综合模型，以加强选定研究地点的死因信息。具体目标是：（1）确定民事登记和生命统计（CRVS）系统在死亡率统计和死因信息方面运作的最佳实践和挑战；（2）制定和实施加强死因信息的干预措施；（3）评估死因医学证明书（MCCD）的质量改进情况；（4）通过对选定研究地点非机构死亡进行口头尸检，在人群层面改善死因信息。
将在印度3个邦（中央邦、北方邦和奥里萨邦）的3个街区开展一项非对照、前后对比的混合方法研究。将进行基线评估，以确定CRVS系统运作中的最佳实践和挑战，同时对MCCD进行质量评估。将根据现有文献和基线评估制定并在研究地点实施一项干预措施。干预措施的主要组成部分将包括一个培训师培训研讨会、对CRVS系统运作中利益相关者的培训、对医生和医务人员进行MCCD培训，以及对社区卫生工作者进行世界卫生组织2022年口头尸检工具培训。干预后将进行评估，以评估干预措施对选定研究地点死因信息的可得性和质量改进所产生的影响。结果将根据MCCD的质量改进情况以及通过选定研究地点的口头尸检在人群层面获得的死因信息可得性来衡量。
该项目已获得资助，并已获得机构伦理委员会的监管批准。数据收集过程于2023年5月开始。研究为期24个月。
我们的研究有望为加强死因信息做出宝贵贡献，这可能有助于政策制定和进一步研究。干预模型将与选定研究地点参与报告和记录死因信息的卫生和CRVS系统现有工作人员合作开发；这将确保可持续性，并为扩大规模提供经验教训，旨在改善该国的死因信息报告。
国际注册报告识别号（IRRID）：DERR1-10.2196/51493。
