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NC CATCH: Advancing Public Health Analytics.

James Studnicki¹, John W Fisher, Christopher Eichelberger

¹University of North Carolina, Charlotte, College of Health and Human Services, Department of Public Health Sciences.

Online Journal of Public Health Informatics

|April 10, 2013

Summary

The North Carolina Comprehensive Assessment for Tracking Community Health (NC CATCH) system offers flexible data analysis for public health units. It supports evidence-based practices and information technology for improved population health outcomes.

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Area of Science:

Public Health Informatics
Health Services Research
Data Analytics

Background:

Local public health units require robust tools for performance measurement.
Effective health tracking necessitates integrated, multidimensional data.
Community health initiatives benefit from evidence-based practices and advanced analytics.

Purpose of the Study:

To describe the North Carolina Comprehensive Assessment for Tracking Community Health (NC CATCH) system.
To highlight the system's features for supporting public health decision-making.
To discuss factors influencing the use of data and technology in population health.

Main Methods:

Deployment of a Web-based analytical system (NC CATCH) to public health units.
Implementation of a data warehouse with conformed, multidimensional event-level data.
Development of a flexible Online Analytic Processing (OLAP) interface with tiered user access.
Emphasis on user training and feedback integration.

Main Results:

NC CATCH provides a flexible, powerful OLAP interface for health data analysis.
The system integrates multiple data sources into a structured data warehouse.
Distributed analytic capabilities with centralized infrastructure are established.
Differentiated user access levels (anonymous/registered) and analytical flexibility (Community Profile/Design Phase) are implemented.

Conclusions:

NC CATCH enhances the capacity of local public health units for outcomes-based performance measurement.
Continued access to event-level data is crucial for population health improvement.
The application of IT-based analytic tools and evidence-based practices is vital for advancing public health.