Abstract
Background
The Hospital Readmissions Reduction Program reduces payments to hospitals with excess
readmissions for three common medical conditions and recently extended its readmission
program to surgical patients. We sought to investigate readmission intensity as measured
by readmission cost for high-risk surgeries and examine predictors of higher readmission
costs.
Materials and methods
We used the Healthcare Cost and Utilization Project's State Inpatient Database to
perform a retrospective cohort study of patients undergoing major chest (aortic valve
replacement, coronary artery bypass grafting, lung resection) and major abdominal
(abdominal aortic aneurysm repair [open approach], cystectomy, esophagectomy, pancreatectomy)
surgery in 2009 and 2010. We fit a multivariable logistic regression model with generalized
estimation equations to examine patient and index admission factors associated with
readmission costs.
Results
The 30-d readmission rate was 16% for major chest and 22% for major abdominal surgery
(P < 0.001). Discharge to a skilled nursing facility was associated with higher readmission
costs for both chest (odds ratio [OR]: 1.99; 95% confidence interval [CI]: 1.60-2.48)
and abdominal surgeries (OR: 1.86; 95% CI: 1.24-2.78). Comorbidities, length of stay,
and receipt of blood or imaging was associated with higher readmission costs for chest
surgery patients. Readmission >3 wk after discharge was associated with lower costs
among abdominal surgery patients.
Conclusions
Readmissions after high-risk surgery are common, affecting about one in six patients.
Predictors of higher readmission costs differ among major chest and abdominal surgeries.
Better identifying patients susceptible to higher readmission costs may inform future
interventions to either reduce the intensity of these readmissions or eliminate them
altogether.
Keywords
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Medicare Payment Advisory Commission. Report to Congress: promoting greater efficiency in Medicare. http://www.medpac.gov/documents/jun07_entirereport.pdf. Accessed June 5, 2014.
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Article info
Publication history
Published online: February 23, 2017
Accepted:
February 16,
2017
Received in revised form:
January 14,
2017
Received:
August 24,
2016
Identification
Copyright
© 2017 Elsevier Inc. All rights reserved.
