Abstract

Introduction: Effective healthcare infection prevention strategies rely upon the collection, analysis and reporting of valid and robust data. To appropriately engage stakeholders, data must also be interpretable and available in a timely manner. The objective of this presentation is to highlight the requirements for successful data management systems for infection prevention programs. Methods: Existing national and international surveillance programs will be used to demonstrate the range of data management systems that are employed, the required resources, and the range of objectives and deliverables for small- and large-scale datasets. Results: The scope of an infection prevention program must be defined to enable objectives of data handling to be specified. Hospital, regional and national contexts are contrasted to illustrate the range of objectives for data management systems: informing quality improvement processes, bench-marking, research, public reporting, and performance monitoring/funding. Key elements of a national data reporting system are defined: governance, standardised surveillance methodology, peer-grouping, risk-adjustment, and reporting functionality. Methods for improving the efficiency of data handling include adoption of accepted surveillance methods and automated data feeds. Human resources and IT maintenance are acknowledged as ongoing requirements for data handling, especially when surveillance methods are refined over time. Conclusions: For surveillance to be effectual, data handling/management must be appropriate. When planning a surveillance strategy the scope and specifications of data handling and warehousing need to be considered a priori for timely, robust and reliable data to adequately inform quality improvement process and research agenda.

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