To determine the effect of hospital characteristics on failure to rescue after high-risk surgery in Medicare beneficiaries.
Reducing failure to rescue events is a common quality target for US hospitals. Little is known about which hospital characteristics influence this phenomenon and more importantly by how much.
We identified 1,945,802 Medicare beneficiaries undergoing 1 of six high-risk general or vascular operations between 2007 and 2010. Using multilevel mixed-effects logistic regression modeling, we evaluated how failure to rescue rates were influenced by specific hospital characteristics previously associated with postsurgical outcomes. We used variance partitioning to determine the relative influence of patient and hospital characteristics on the between-hospital variability in failure to rescue rates.
Failure to rescue rates varied up to 11-fold between very high and very low mortality hospitals. Comparing the highest and lowest mortality hospitals, we observed that teaching status (range: odds ratio [OR] 1.08–1.54), high hospital technology (range: OR 1.08–1.58), increasing nurse-to-patient ratio (range: OR 1.02–1.14), and presence of >20 intensive care unit (ICU) beds (range: OR 1.09–1.62) significantly influenced failure to rescue rates for all procedures. When taken together, hospital and patient characteristics accounted for 12% (lower extremity revascularization) to 57% (esophagectomy) of the observed variation in failure to rescue rates across hospitals.
Although several hospital characteristics are associated with lower failure to rescue rates, these macrosystem factors explain a small proportion of the variability between hospitals. This suggests that microsystem characteristics, such as hospital culture and safety climate, may play a larger role in improving a hospital's ability to manage postoperative complications.
Department of Surgery, Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI.
Reprints: Kyle H. Sheetz, MD, MS, Department of Surgery, Center for Healthcare Outcomes and Policy, University of Michigan, 2800 Plymouth Rd, Bldg 16, Flr 1, Ann Arbor, MI 48109. E-mail: email@example.com.
Disclosure: JBD reports having equity in Arbor Metrix. The company had no role in this study. KHS and AAG have no conflicts of interest. This work was funded by NIH/NIA R01 AG042340-01 and K08HS023621 issued to Amir A. Ghaferi.