QAPI 137 - Improving Denominator Data for Catheter Associated Urinary Tract Infection (CAUTI) Surveillance

Background: Denominator data calculation precision is imperative to mandated public reporting, hospital performance comparisons, and data-driven infection prevention. However, retrospective reviews of indwelling urinary catheter (IUC) days reveal data capture inconsistencies due to electronic medical record upgrades, dated denominator data extract program, and incomplete IUC documentation. This quality improvement project explores revising the IUC days data extract logic to enhance data capture by 30% in non-critical care units within six months.

Methods: The “Plan-Do-Study-Act” (PDSA) was the framework for enhancing IUC days data capture accuracy, involving a retrospective medical record review (January to July 2023) of IUCs in the Lines, Drains, & Airways (LDA) flowsheet and LDA Avatar. The process measures included capturing individual inpatient admission encounter; applying date/time of inpatient admission status for existing IUCs; applying patient discharge date/time for undocumented IUC removals and/or disposition at discharge; and capping data extract at 23:00 hours with exclusion of IUCs removed prior to data extract time. Three PDSA cycles for extract logic revisions were employed, using urinary catheter standardized utilization ratio (SUR) and CAUTI standardized infection ratio (SIR) as risk measures.

Results: IUC data from EMR and foley days data report were validated. The first PDSA cycle resulted in 100% data capture and accuracy, but exposed instances of urostomy, nephrostomy, and IUC documented as “not present on assessment.” The second PDSA addressed ineligible drain types for CAUTI surveillance by implementing an exclusion criterion, but increased IUC days were noted. The third PDSA addressed superfluous IUC days by selecting 23:00 hours for maximum data capture and excluding IUCs removed prior to data extract time.

Conclusions: Accurate, timely IUC documentation is critical to data quality and integrity. The improved CAUTI denominator data quality results in more accurate predicted IUC days and infections when calculating SUR and SIR. Consequently, these improve infection prevention efforts in non-critical care units.