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Geocoding coronial data: tools and techniques to improve data quality.

Darren Freestone¹, Dianne Williamson, Dennis Wollersheim

¹Department of Health Information Management, School of Public Health & Human Biosciences, Faculty of Health Sciences, La Trobe University Bundoora, Victoria, Australia. D.Freestone@latrobe.edu.au

Health Information Management : Journal of the Health Information Management Association of Australia

|October 23, 2012

Summary

Geocoding location data improves health research accuracy. Key factors like source documents, data cleaning, and software settings significantly impact geocoded data quality for better injury surveillance and prevention strategies.

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Area of Science:

Public Health
Geographic Information Systems (GIS)
Health Informatics

Background:

Demographic data, particularly location, is crucial for understanding population health and evaluating interventions.
Effective injury surveillance and prevention strategies rely on accurate and quality-assured location data.
Geocoding is increasingly utilized in health research for spatial data analysis.

Purpose of the Study:

To analyze trends in the use of location-based data from Australia's National Coroners Information System (NCIS).
To identify factors influencing the quality of geocoded data within the NCIS.
To assess the impact of these factors on data quality.

Main Methods:

Systematic analysis of the geocoding process applied to NCIS data.
Identification and evaluation of key factors affecting geocoding quality.
Examination of data quality assurance and classification methods.

Main Results:

Source documentation, data cleaning procedures, and software configurations were identified as critical factors impacting geocoded data quality.
Specific trends in the utilization of NCIS location data by researchers were observed.
The extent of impact of identified factors on data quality was quantified.

Conclusions:

Improving data quality in geocoding requires careful attention to source documentation, data cleaning, and software settings.
Enhanced geocoding processes can lead to more reliable spatial analysis of health data.
Better data quality ultimately informs more accurate health research, analysis, and interpretation, particularly in injury surveillance.