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Comment & Response
November 2019

More Considerations on Both Model Assumptions and Results Interpretations—Evaluating Readmission—Reply

Author Affiliations
  • 1Department of Health Policy and Management, Sol Price School of Public Policy, University of Southern California, Los Angeles
  • 2Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles
  • 3Division of General Internal Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California
JAMA Intern Med. 2019;179(11):1599-1600. doi:10.1001/jamainternmed.2019.4721

In Reply Du et al raise 3 issues with our study.1 First, in one analysis, we use methods described by Linden2 and Davis3 to estimate the extent to which regression to the mean (RTM) explains changes in excess readmissions after implementation of the Hospital Readmission Reduction Program (HRRP). As noted by Du et al, this analysis assumes that excess readmission ratios (ERRs) follow a gaussian distribution, but this assumption is violated for 2 of 3 conditions analyzed. Second, they question our choice to analyze RTM in ERRs rather than risk-adjusted readmissions. Finally, they question whether our estimates establish that RTM causally led to a decline in excess readmissions. Below, we respond to each of these concerns.

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