ITS 91 - Automation of Standardized Infection Ratio (SIR) to Reduce Manual Work and Support Targeted and Flexible Analysis of Healthcare-associated Infections (HAIs)

Background: Improving patient safety by preventing healthcare-associated infections (HAIs) is a priority for our department. The SIR is the primary summary measure used by the National Healthcare Safety Network (NHSN) to risk adjust HAIs. Access to sensitive protected health information (PHI) data in NHSN is restricted to a limited group of people at our facility, however broad data accessibility is critical for our HAI reduction efforts. An automated and dynamic tool was developed to expand our use of the SIR measure, eliminating manual work to generate and export SIRs via the NHSN database.

Methods: Following the fixed parameters and parameter estimates published by NHSN, we used either a logistic regression or a negative binomial regression model to calculate the number of predicted infections via our department’s structured query language (SQL) database. This data is extracted and calculated daily using SQL and Statistical Analysis System (SAS) programming, all from which we built a Tableau dashboard available via an enterprise Tableau Server.

Results: In addition to eliminating manual work and allowing broader access to timely SIR analysis, our automated and improved workflow allowed us the flexibility to fill two analytic gaps that the NHSN database currently does not provide. We created an SSI Targeted Assessment for Prevention (TAP) report for our adult and pediatric surgical procedures allowing us to assess areas for prevention efforts. In addition, to provide separate monthly C. difficile SIR for our pediatric and adult patient populations, we automated the calculation of these SIRs via our SQL database.

Conclusions: By eliminating the reliance on NHSN and manual export, this automated approach, coupled with a data visualization dashboard, delivers real-time data for leadership and Infection Preventionists to identify those areas with the greatest need for improvement, intervene promptly, and reduce HAIs with operational efficiency.