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Multicenter Study
. 2018 Feb;105(2):513-520.
doi: 10.1016/j.athoracsur.2017.08.012. Epub 2017 Nov 23.

Determinants of Variation in Pneumonia Rates After Coronary Artery Bypass Grafting

Alexander A Brescia  1 , J Scott Rankin  2 , Derek D Cyr  3 , Jeffrey P Jacobs  4 , Richard L Prager  5 , Min Zhang  6 , Roland A Matsouaka  3 , Steven D Harrington  7 , Rachel S Dokholyan  3 , Steven F Bolling  1 , Astrid Fishstrom  1 , Sara K Pasquali  8 , David M Shahian  9 , Donald S Likosky  10 ; Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative
Affiliations
Multicenter Study

Determinants of Variation in Pneumonia Rates After Coronary Artery Bypass Grafting

Alexander A Brescia et al. Ann Thorac Surg. 2018 Feb.

Abstract

Background: Although conventional wisdom suggests that differences in patient risk profiles drive variability in postoperative pneumonia rates after coronary artery bypass grafting (CABG), this teaching has yet to be empirically tested. We determined to what extent patient risk factors account for hospital variation in pneumonia rates.

Methods: We studied 324,085 patients undergoing CABG between July 1, 2011, and December 31, 2013, across 998 hospitals using The Society of Thoracic Surgeons Adult Cardiac Database. We developed 5 models to estimate our incremental ability to explain hospital variation in pneumonia rates. Model 1 contained patient demographic characteristics and admission status, while Model 2 added patient risk factors. Model 3 added measures of pulmonary function, Model 4 added measures of cardiac anatomy and function and medications, and Model 5 further added measures of intraoperative and postoperative care.

Results: Although 9,175 patients (2.83%) experienced pneumonia, the median estimated distribution of pneumonia rates across hospitals was 2.5% (25th to 75th percentile: 1.5% to 4.0%). Wide variability in pneumonia rates was evident, with some hospitals having rates more than 6 times higher than others (10th to 90th percentile: 1.0% to 6.1%). Among all five models, Model 2 accounted for the most variability at 4.24%. In total, 2.05% of hospital variation in pneumonia rates was explained collectively by traditional patient factors, leaving 97.95% of variation unexplained.

Conclusions: Our findings suggest that patient risk profiles only account for a fraction of hospital variation in pneumonia rates; enhanced understanding of other contributory factors (eg, processes of care) is required to lessen the likelihood of such nosocomial infections.

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Figures

Fig 1
Fig 1
Selection criteria schema for coronary artery bypass grafting (CABG) patients from The Society of Thoracic Surgeons Adult Cardiac Surgery Database (STS-ACSD). (VAD = ventricular assist device.)
Fig 2
Fig 2
Estimated distribution of hospital-specific postoperative pneumonia rates. The area between any two points on the x-axis represents the proportion of hospitals within that range.
Fig 3
Fig 3
Model estimates explaining factors of hospital variation in pneumonia rates.
See this image and copyright information in PMC

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