Evaluating Readmission Rates in Dialysis Facilities with or Without Adjustment for Hospital Effects

• Activity Number: 160
• Type: Topic Contributed
• Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Section on Risk Analysis
• Author(s): Kevin (Zhi) He*+ and John David Kalbfleisch and Yijiang Li and Yi Li
• Companies: University of Michigan and University of Michigan and Google and University of Michigan
• Keywords: mixed effects ; flagging ; readmission ; standardization

Abstract

Motivated by the evaluation of readmission rates among kidney dialysis facilities in the United States, this study is to evaluate the impact of including discharging hospitals on the estimation of Facility-level Standardized Readmission Ratios (SRRs). The estimation of SRRs consists of two steps. First, we model the dependence of readmission events on facilities and patient-level characteristics, with or without the adjustment for discharging hospitals. Second, based on the model, the standardization is achieved by computing the ratio of the number of observed events to the number of expected events given the case-mix in that facility. A challenging aspect of our motivating example is that the number of parameters is very large. To solve this problem, we propose a structured Newton-Raphson algorithm for logistic fixed effects model and an approximate EM algorithms for the logistic mixed effects model. We considered a re-sampling and simulation technique to draw inference. Finally, our method of `flagging' outlier facilities also involved converting the observed p-values to Z-statistics and using the empirical null distribution, which accounts for overdispersion in the data.