Abstract: TH-OR106

Potential Impact of CMS Payment Policy on Misclassification of Dialysis-Requiring AKI (AKI-D) as ESRD: A National Temporal Trend Analysis

Session Information

  • Predicting AKI
    November 02, 2017 | Location: Room 282, Morial Convention Center
    Abstract Time: 06:06 PM - 06:18 PM

Category: Acute Kidney Injury

  • 003 AKI: Clinical and Translational

Authors

  • Lee, Benjamin J., University of California, San Francisco, San Francisco, California, United States
  • Johansen, Kirsten L., University of California, San Francisco, San Francisco, California, United States
  • McCulloch, Charles E., University of California, San Francisco, San Francisco, California, United States
  • Hsu, Chi-yuan, University of California, San Francisco, San Francisco, California, United States
Background

Difficulty in predicting which patients with AKI-D will recover to discontinue dialysis may result in misclassification of such patients as having ESRD, which may be detrimental to patient well-being and may falsely inflate estimates of national ESRD incidence. External factors such as reimbursement policies may influence misclassification.

Methods

Using US Renal Data System (USRDS) Standard Analytic Files, we studied all patients registered as having incident ESRD from 1995 to 2014 (n=2,049,212). Patients subsequently reported to be alive ≥90 days without continued dialysis treatments or kidney transplant were considered misclassified AKI-D and not true ESRD cases. We used linear regression and interrupted time-series (ITS) regression to estimate temporal trends in AKI-D misclassification, with particular attention to mid-2012 when the Centers for Medicare & Medicaid Services (CMS) changed reimbursement policy to forbid ESRD facilities from providing dialysis to AKI-D outpatients.

Results

The overall AKI-D misclassification rate was 6.2%, but with a distinct temporal trend (Figure). AKI-D misclassification increased on average 0.36% (95% CI 0.33-0.38%) per year from 2000 to 2010. It then abruptly changed in July 2012, when our univariate ITS model estimated that misclassification incidence decreased 2.14% (1.11-3.18%).

Conclusion

Approximately 1 in every 16 patients in the ESRD registry is actually misclassified AKI-D, a much higher proportion than reported previously. The incidence of misclassification increased throughout the first decade of the 21st century but subsequently decreased around the time of a key Medicare reimbursement policy change.

6-month absolute count (bar graph) and 6-month cumulative incidence (%, line graph) of AKI-D misclassification in the USRDS.

Funding

  • NIDDK Support