Reliability-Adjusted Composite Measures for the Prevention of Healthcare-Associated Infections (HAIs)

• Activity Number: 534 - Contributed Poster Presentations: Section on Statistics in Epidemiology
• Type: Contributed
• Date/Time: Wednesday, August 1, 2018 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Mathew Sapiano* and Jonathan R Edwards
• Companies: CDC and Center for Disease Control & Prevention
• Keywords: Health; surveillance; composite; Reliability adjustment; Generalized linear mixed models; MCMC

Abstract

The National Healthcare Safety Network (NHSN), developed and used by the Centers for Disease Control and Prevention (CDC) for surveillance of healthcare-associated infections (HAIs), provides benchmark measures, such as standardized infection ratio (SIRs), that CDC and its partners use for prevention purposes. Benchmarks exist for each HAI measure separately, but a composite HAI measure could provide a more rounded assessment of HAI prevention opportunities. Reliability adjustment was applied to six HAI SIRs from each facility to account for low HAI exposure using the Adjusted Ranking Metric (ARM). The ARM is based on the SIR with a reliability adjustment calculated using a Bayesian mixed effects model fitted using MCMC. ARMs were adjusted to account for differences in exposure to HAI type and to allow for comparison between HAIs with differing frequency and severity. The resulting composite was calculated for six HAIs in 4068 facilities based on 2015 data and provides a meaningful summarization of infection experience. The flexibility of the technique provides an opportunity for stakeholders to customize the composite measure to their own prevention needs and targets.