Both Patient and Facility Contribute to Achieving the Centers for Medicare and Medicaid Services' Pay-for-Performance Target for Dialysis Adequacy

Abstract

The Centers for Medicare and Medicaid Services (CMS) designated the achieved urea reduction ratio (URR) as a pay-for-performance measure, but to what extent this measure reflects patient characteristics and adherence instead of its intent to reflect facility performance is unknown. Here, we quantified the contributions of patient case-mix and adherence to the variability in achieving URR targets across dialysis facilities. We found that 92% of 10,069 hemodialysis patients treated at 173 facilities during the last quarter of 2004 achieved the target URR Ն65%. Mixed-effect models with random intercept for dialysis facility revealed a significant facility effect: 11.5% of the variation in achievement of target URR was attributable to the facility level. Adjusting for patient case-mix reduced the proportion of variation attributable to the facility level to 6.7%. Patient gender, body surface area, dialysis access, and adherence with treatment strongly associated with achievement of the URR target. We could not identify specific facility characteristics that explained the remaining variation between facilities. These data suggest that if adherence is not a modifiable patient characteristic, providers could be unfairly penalized for caring for these patients under current CMS policy. These penalties may have unintended consequences.

Variation in the Level of eGFR at Dialysis Initiation across Dialysis Facilities and Geographic Regions

“…Other studies have examined variability across facilities and geographic regions regarding dialysis practices (27)(28)(29)(30)(31)(32)(33)(34)(35)(36). Two recent studies of 173 United States dialysis facilities reported significant facility variations for arteriovenous fistula use and dialysis adequacy (urea reduction ratio .65%) of 7.6% and 11.5%, respectively (28,29). These findings and similar findings have led to the implementation of quality improvement programs targeting these metrics and serve as a baseline measure for improvement.…”

Rethinking Thirty-Day Hospital Readmissions: Shorter Intervals Might Be Better Indicators Of Quality Of Care

“…7 For each postdischarge interval, from one day to ninety days, we fitted a separate model and estimated the ICC, which represents the proportion of variation in readmission risk associated with the hospital, compared to variation associated with all other factors. 27–29 Additional statistical details are reported in Appendix 1b. 24 …”

“…21 Although this measure has been used in similar research, 22,27,29 hospital quality is a complicated construct that might not be fully captured by any single metric. For example, low ICCs could indicate that all hospitals have similarly excellent (or poor) quality, or that all patients have similar risk of readmission (at any hospital), although the latter interpretation is less plausible.…”

Comparative effectiveness studies to improve clinical outcomes in end stage renal disease: the DEcIDE patient outcomes in end stage renal disease study

“…The population of patients within DCI is diverse and is demographically representative of the US dialysis population, with an overrepresentation of African Americans [23]. Information about comorbid conditions, hospitalization dates, oral and intravenous medications, quality of life, the delivered dialysis prescription, as well as physician, nurse, dietician and social worker progress notes are entered into an electronic medical record.…”