Reliability of readmission rates as a hospital quality measure in cardiac surgery

Abstract

Background: Recent policy interventions have reduced payments to hospitals with higher-than-predicted risk-adjusted readmission rates. However, whether readmission rates reliably discriminate deficiencies in hospital quality is uncertain. We sought to determine the reliability of 30-day readmission rates after cardiac operations as a measure of hospital performance and evaluate the effect of hospital caseload on reliability.

Methods: We examined national Medicare beneficiaries undergoing coronary artery bypass graft operations for 2006 to 2008 (n=244,874 patients, n=1,210 hospitals). First, we performed multivariable logistic regression examining patient factors to calculate a risk-adjusted readmission rate for each hospital. We then used hierarchical modeling to estimate the reliability of this quality measure for each hospital. Finally, we determined the proportion of total variation attributable to three factors: true signal, statistical noise, and patient factors.

Results: A median of 151 (25% to 75% interquartile range, 79 to 265) coronary artery bypasses were performed per hospital during the 3-year period. The median risk-adjusted 30-day readmission rate was 17.6% (25% to 75% interquartile range, 14.4% to 20.8%). Of the variation in readmission rates, 55% was explained by measurement noise, 4% could be attributed to patient characteristics, and the remaining 41% represented true signal in readmission rates. Only 53 hospitals (4.4%) achieved a proficient level of reliability exceeding 0.70. To achieve this reliability, 599 cases were required during the 3-year period. In 33.7% of hospitals, a moderate degree of reliability exceeding 0.5 was achieved, which required 218 cases.

Conclusions: The vast majority of hospitals do not achieve a minimum acceptable level of reliability for 30-day readmission rates. Despite recent enthusiasm, readmission rates are not a reliable measure of hospital quality in cardiac surgery.

Conflict of interest statement

Disclosures

TS, has no conflicts of interest related to the content of this abstract. JBD is a consultant and has an equity interest in ArborMetrix, Inc, which provides software and analytics for measuring hospital quality and efficiency. The company had no role in conduction of this research or creation of this manuscript.

Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1

Calibration plot of observed vs. expected readmissions within deciles of predicted risk for patient level logistic regression model of 30-day readmissions.

Figure 2

The proportions of hospital variation in risk-adjusted post-CABG 30-day readmission rates attributable to “noise” or measurement error, patient factors, and hospital performance.

Figure 3

Relationship between reliability of post-CABG readmission rates and hospital volume of CABG based on national Medicare beneficiaries for 2006–2008.