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Abstract:
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To inform stakeholders of prevention progress in hospital-associated infections (HAI), indirect standardization method using standardized infection ratio (SIR) is widely used by U.S. hospitals to compare with the standard baseline population. But, state health departments have recently underscored a need to rank hospitals in their jurisdiction to prioritize prevention. To address this, we introduced a direct standardization method using catheter-associated urinary tract infection (CAUTI) data reported to CDC in 2014 under the CMS's inpatient quality reporting program requirement. We estimated standardized CAUTI rate for each hospital in a selected state as a function of predicted marginal by Poisson regression after controlling for differences in hospital characteristics such as bed size, unit type. Marginal prediction method could also compute standardized rate even for small hospitals with low risk of CAUTI, which would otherwise have zero SIR value. Hospitals(n=319) were then ranked by standardized CAUTI rates. It is concluded that standardized rates were directly comparable among hospitals, and hospital ranks such obtained could help prioritize targeted prevention for any HAI.
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