NC CATCH: Advancing Public Health Analytics

Abstract

The North Carolina Comprehensive Assessment for Tracking Community Health (NC CATCH) is a Web-based analytical system deployed to local public health units and their community partners. The system has the following characteristics: flexible, powerful online analytic processing (OLAP) interface; multiple sources of multidimensional, event-level data fully conformed to common definitions in a data warehouse structure; enabled utilization of available decision support software tools; analytic capabilities distributed and optimized locally with centralized technical infrastructure; two levels of access differentiated by the user (anonymous versus registered) and by the analytical flexibility (Community Profile versus Design Phase); and, an emphasis on user training and feedback.The ability of local public health units to engage in outcomes-based performance measurement will be influenced by continuing access to event-level data, developments in evidence-based practice for improving population health, and the application of information technology-based analytic tools and methods.

Web-Based Geo-Visualisation of Spatial Information to Support Evidence-Based Health Policy: A Case Study of the Development Process of Health Tracks

“…The challenge of balancing privacy with the demand for more detailed spatial queries, in order to work towards facilitating access by external agencies, researchers and the general public, will be addressed by performing server-side analysis of individual-level data, with only aggregated information deployed to the client, provided the requested combination of dimensional cross-sections meets specified privacy and reliability criteria. Data will be stored in an Online Analytical Processing (OLAP) based data warehouse to minimise processing time and maximise data storage efficiency (Studnicki et al 2010;Tremblay et al 2007). Further details and technical specifications are described in Moncrieff et al (2013).…”

“…In order to get a comprehensive understanding of the health status and needs of a particular area, a broad range of health, environmental, demographic and other information is required, that can often be difficult and time consuming to obtain and collate (Nutley & Reynolds 2013). Online geovisualisation tools hold the promise of facilitating investigation of a broad range of large and complex datasets rapidly (Studnicki et al 2010); for example, an investigation into the varying contribution of community demographic composition within a defined region on multiple outcomes such as hospital separations, deaths, cancer incidence and communicable disease notifications.…”

“…The primary advantage of geospatial data is the ability to integrate, visualise and interrogate a wide range of data sources such as health outcomes, social demographic measures, risk factor prevalence and health service utilisation. Furthermore, the role of small area, multidisciplinary local community health networks is increasing in Australia, as is the requirement for outcomes-based performance measurement at local public health unit level, thus intensifying the need for access to cross sectoral health, environment and demographic data at the local level (Baum et al 2010;Gudes et al 2010; Australian Governement, Medicare Locals 2013; National Health Performance Authority 2013; Studnicki et al 2010).…”

Determining Community Health Status Priorities in an Online Analytic Processing (OLAP) Environment

“…In separate deployments in the states of North Carolina (CATCH) and, more recently, Florida (HealthTrac) investigators have established a web-based analytical environment with: a flexible and powerful online analytic processing (OLAP) interface; multiple sources of multidimensional, event-level data fully conformed to common definitions in a data warehouse structure; enabled utilization of publicly available decision support software tools; and distributed analytic capabilities with centralized technical infrastructure [11]. Utilizing the analytical capabilities of the OLAP analytical environment, the challenge was to create a community health status prioritizing system which would meet these functional requirements: 1) it must systematically apply a series of defined objective criteria; 2) it must be able to rank different types of health status outcomes (e.g., mortality rates, hospitalization rates); and 3) it must provide flexibility in the weighting of the evaluation criteria to enable iterative, “what-if” types of analyses.…”

Beyond information access: Support for complex cognitive activities in public health informatics tools

“…Technology, although essential, is only a means by which users “make best use of information” [5]. Much of the existing PHI literature focuses on the technological structures that facilitate information access [6, 7, 8, 9]. In such contributions, as well as in review papers that consider multiple PHI tools (e.g., [10, 3]), criteria for evaluation generally consist of meeting basic information access needs [11].…”