Challenging Assumptions of Outcomes and Costs Comparing Peritoneal and Hemodialysis

Abstract

Objectives: Policy makers have suggested increasing peritoneal dialysis (PD) would improve end-stage kidney disease (ESKD) outcomes and reduce Medicare spending compared with hemodialysis (HD). We compared mortality, hospitalizations, and Medicare spending between PD and HD among uninsured adults with incident ESKD.

Methods: Using an instrumental variable design, we exploited a natural experiment encouraging PD among the uninsured. Uninsured patients usually receive Medicare at dialysis month 4. For those initiating PD, Medicare covers the first 3 dialysis months, including predialysis services in the calendar month when dialysis started. Starting dialysis later in a calendar month increases predialysis coverage that is essential for PD catheter placements. The policy encourages PD incrementally when ESKD develops later in the month. Dialysis start day appears to be unrelated to patient characteristics and effectively "randomizes patients" to dialysis modality, mitigating selection bias.

Results: Starting dialysis later in the month was associated with an increased PD uptake: every week later in the month was associated with an absolute increase of 0.8% (95% confidence interval [CI] 0.6%-0.9%) at dialysis day 1 and 0.5% (95% CI 0.3%-0.7%) at dialysis month 12. We observed no significant absolute difference between PD and HD for 12-month mortality (-0.9%, 95% CI -3.3% to 0.8%), hospitalizations during months 7 to 12 (-0.05, 95% CI -0.20 to 0.07), and Medicare spending during months 7 to 12 (-$702, 95% CI -$4004 to $2909).

Conclusions: In an instrumental variable analysis, PD did not result in improved outcomes or lower costs than HD.

Keywords: costs; hemodialysis; instrumental variable; mortality; peritoneal dialysis.

Figure 1:. Comparing observed days of the month of dialysis start and predicted.

We show the proportion of uninsured patients starting dialysis at each numbered day of the month (in black) against the predicted distribution or the proportion of times the numbered day appears between 1/1/2006 and 12/31/2015 (in gray). Distributions exclude weekends and federal holidays. We show the cumulative distribution in Appendix Figure 2. The one-sample Kolmogorov-Smirnov statistic is the maximum distance between the predicted and observed cumulative distributions (p > 0.2). Abbreviations: KS = Kolmogorov-Smirnov statistic.

Figure 2:. Unadjusted Probability of Peritoneal Dialysis Use at Month 12.

We show the unadjusted and adjusted probabilities of peritoneal dialysis at dialysis start and the adjusted probability of peritoneal dialysis at month 12 in Appendix Figure 4. Abbreviations: PD = peritoneal dialysis.

Figure 3:. Unadjusted changes in mortality and spending by day of dialysis start.

We show unadjusted 12-month probability of death (Panel A) and total Medicare spending per patient in months 7–12 of dialysis (Panel B) by the day of dialysis start. Costs (Panel B) are modeled using log costs (grey dots) and without log transforming (block dots). Trends and slopes were computed using ordinary least squares without adjusting for other covariates. We show differences in hospitalization rates by day of dialysis start in Appendix Figure 5. Abbreviations: HD = hemodialysis, PD = peritoneal dialysis.