Causes of deaths data, linkages and big data perspectives

Area of Science:

• Public Health
• Medical Informatics
• Data Science

Background:

• Cause-specific mortality data are crucial for public health monitoring globally.
• Physician-completed death certificates, standardized by the World Health Organization (WHO), form the basis for this data.
• The International Classification of Diseases (ICD-10) is used for coding causes of death, ensuring international comparability.

Purpose of the Study:

• To explore novel applications of data analysis methods, including big data, for mortality data.
• To examine the potential of linking mortality data with other health information sources.
• To highlight the importance of data quality and specific challenges in forensic medicine.

Main Methods:

• Utilizing standardized death certification and coding processes (e.g., Iris software).
• Applying advanced statistical and big data methodologies to mortality datasets.
• Focusing on data linkage with other health information systems, exemplified by France's centralized system.

Main Results:

• Standardized production processes enhance international comparability of cause-specific mortality data.
• Big data approaches offer new avenues for analyzing mortality trends and disease burdens.
• Data linkage significantly expands the analytical potential beyond traditional uses.

Conclusions:

• Cause-specific mortality data hold immense potential for public health research when analyzed with modern methods.
• The integration of big data techniques and data linkage can revolutionize disease burden assessment and policy evaluation.
• Ensuring high data quality, particularly in forensic contexts, remains paramount for reliable analysis.