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The value of cause of death data

Medical certification of cause of death

Coding causes of death to statistical categories
The International Classification of Diseases

Cause of death: where there is no physician
Verbal autopsy diagnostic algorithms

Automated verbal autopsy
What is automated verbal autopsy and how does it differ from medical certification of cause of death?

Incorporating verbal autopsy into the civil registration and vital statistics system

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Incorporating verbal autopsy into the civil registration and vital statistics system

Conclusion

This topic has focused on the importance of cause of death (COD) data as part of civil registration and vital statistics (CRVS) systems for informing the development and implementation of health and development policies. Patterns of mortality are changing rapidly around the world as fertility declines, people age, and new diseases emerge, often as a result of changing environmental and climatic conditions. For health systems to respond, they urgently need usable data on patterns and causes of mortality. 

This topic has presented the two important methods for generating COD information. Medical certification of cause of death (MCCOD) is a well-developed method that has been successfully used in many countries for decades. But the approach relies on the presence of a physician or medically trained person who can complete a COD certificate in line with international standards. It is essential to continue providing the training needed to continue and extend MCCOD around the world.

At the same time, in many low and middle-income countries, many if not most deaths occur at home or in facilities where the skills needed to reliably medically certify COD are not available. Until recently, the only information on causes of death in populations has been generated for small areas in the course of health and demographic surveillance or research studies. Today, the situation is being transformed with the development of well-tested automated verbal autopsy methods that can applied at scale and in the context of CRVS strengthening efforts, to rapidly transform the availability and quality of COD data to better inform crucial health policy decisions.


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