LAUSR

BACKGROUND Real world data (RWD) is playing an increasing role in health care decisions. Employing RWD collected by electronic health records and other healthcare applications allows researchers the ability to evaluate treatment effects efficiently and upon broad populations. Applying a RWD approach to analyzing the impact of infection prevention programs can provide useful insights in cases where prospective studies are not initiated. METHODS As a use case, we examined the impact of hospital-wide Foley catheterization tray (FCT) conversions. 32 hospitals converted from one of three types of Foley catheterization trays (FCTs) – types B, C and D – to an FCT designed to foster aseptic technique (type A). Those conversions were implemented in conjunction with a refocus on catheter insertion and maintenance practices. The impact upon catheter-associated urinary tract infections (CAUTIs) and an algorithmically-derived measure of healthcare-associated infections (HAIs) were analyzed using an electronic infection surveillance system as the RWD source. RESULTS A total of 1,835,370 admissions, 530,485 urinary catheter-days and 3,400,873 patient-days were analyzed. A combination of subjective and objective HAI metrics was used to assess the conversions. Statistically significant CAUTI reductions were observed in a single type of Foley tray conversion (D-to-A). Statistically significant reductions in the algorithmically-derived HAI measure were observed across all three conversion types. CONCLUSIONS RWD analysis can provide useful insights as to the impact of infection prevention programs, particularly when analyzing endpoints that are electronically derived from existing data. The strengths of RWD analysis include relative ease of analysis and minimization of the Hawthorne effect. Those strengths must be balanced against the inability to control for all potential variables that may contribute to the observed results including the inability to quantify the individual impacts of product conversion and human factors effects.