Healthcare-Associated Infections Data Presentation and Reporting Standardization Toolkit

Monday, June 23, 2014: 1:00 PM
Belmont II, Renaissance Hotel
Andrea Alvarez , Virginia Department of Health, Richmond, VA
Lindsey Weiner , Centers for Disease Control and Prevention, Atlanta, GA

Brief Summary:
Numerous organizations including state health departments, federal agencies, and consumer groups analyze and disseminate healthcare-associated infection (HAI) surveillance data from the National Healthcare Safety Network (NHSN).  Stakeholders use NHSN data to summarize infection trends, inform consumers, and develop infection prevention policies, among other purposes. Although multiple groups are using the same data source (NHSN), their analysis methods and presentation styles can vary greatly, thus potentially leading to conflicting results, consumer confusion, and misinterpretation of the data. The Council of State and Territorial Epidemiologists (CSTE) passed a position statement (13-ID-02) in June 2013 highlighting the immediate need for a standardized approach to HAI data presentation and analysis. In response to this, a multidisciplinary workgroup was convened to develop a consensus of best practices in the reporting and communication of HAI data analyses, with special considerations on how to improve accessibility of an HAI public report to a non-professional audience. The workgroup has created a toolkit that details several options and considerations for the presentation of HAI outcomes such as device-associated infections, surgical site infections, and laboratory-identified events and their infection metrics (e.g., the standardized infection ratio). Given the variable nature of HAI surveillance infrastructure in state health departments and the legislative or regulatory mandates that prescribe how data are to be presented, a range of communication strategies are shared and a model HAI report is provided. States and other organizations are encouraged to incorporate the principles from this toolkit into their HAI reports, dashboards, and data analyses where possible.