Hospital acquired infections (HAIs) are major causes of morbidity, mortality, and healthcare costs in the
To utilize hierarchical/mixed models for health care acquired infections at various facilities in Pennsylvania (PA) and consequently obtain SIRs scores for each of the facilities. Compare this approach to determine SIR scores with the more standard Poisson non-hierarchical approach.
In PA, although all HAIs are required to be reported through the National Healthcare Safety Network (NHSN), a smaller number are being used to calculate infection rates (which require denominator data) for obtaining SIRs. This analysis focuses on calculating SIRs for catheter-associated urinary tract infections (CAUTIs) and central line-associated bloodstream infections (CLABSIs). Data from July 2008-March 2009 (the baseline period) were used here. Factors assessed in the modeling include: medical school affiliation, number of licensed beds, and the device utilization ratio (DUR) which is the number of device days divided by the number of patient days. The nine months of data were also collapsed to one point of time to increase the sample sizes of infection counts per facility. A Poisson distribution for these variables was assessed and compared to a hierarchical/mixed model approach in finding expected values for the SIRs.
We used Poisson models to assess relevant risk factors for both CAUTI and CLABSI. Here, the DUR was generally found to be significant but most of resulting SIRs were not significantly different than a chance result.
From this exploratory study, we hypothesize that the hierarchical/mixed model is more efficient than other models for evaluating risk factors for the HIAs.