Data quality assurance measures (DQAMs) for electronic death investigation data

Area of Science:

• Forensic Science
• Public Health Informatics
• Data Management

Background:

• Accurate death investigation data is vital for public health surveillance and research.
• Ensuring the integrity of collected data prevents errors in analysis and reporting.
• Existing data collection processes may have vulnerabilities that impact data quality.

Purpose of the Study:

• To outline the importance and methods of data quality assurance measures (DQAMs) in death investigations.
• To present a foundational approach for developing DQAMs.
• To identify specific death investigation variables suitable for quality assurance.

Main Methods:

• Discussion of manual and computerized procedures for data validation.
• Presentation of DQAMs focusing on data collection, entry, accuracy, consistency, and coding.
• Identification of key variables within death investigations amenable to quality checks.

Main Results:

• DQAMs encompass checks for completeness, accuracy, consistency, and correct coding of death investigation data.
• Quality assurance ensures the reliability of computer-generated documents and data for research.
• Specific death investigation variables are highlighted as critical points for implementing DQAMs.

Conclusions:

• Robust DQAMs are essential for maintaining the accuracy and reliability of death investigation data.
• Standardized DQAMs improve the utility of data for public health initiatives and scientific research.
• A systematic approach to DQAM development can enhance overall data quality in death investigations.