Literature DB >> 12191978

Measuring the efficacy of a quality improvement program in dialysis adequacy with changes in center effects.

Jeffrey C Fink1, Min Zhan, Steven A Blahut, Michael Soucie, William M McClellan.   

Abstract

End-stage renal disease (ESRD) patients treated with hemodialysis have a high mortality rate, which is largely due to inadequate dialysis. Dialysis adequacy, measured by the urea reduction ratio (URR), tends to be correlated within dialysis facilities with wide variations in average center adequacy. These are characteristics of a center effect, which can have an important impact on dialysis adequacy. This study measured the center effect observed in an ESRD Network before and after a successful quality improvement project (QIP). URR values were recorded on patients sampled from 196 facilities in ESRD Network 6 before (pre-QIP, n = 5309) and after (post-QIP, n = 5753). These data was used to determine the within center correlation (rho) of individual URR values and between center variation in aggregate URR values in both samples. The overall mean URR improved from the pre- to post-QIP sample (mean URR 64.7 +/- 0.1 versus 69.8 +/- 0.1, respectively; P = 0.001). There was a high degree of within center correlation in dialysis adequacy across the facilities, which significantly diminished post-QIP (rho, 0.15 [95% CI, 0.12 to 0.18] versus rho, 0.06 [95% CI, 0.04 to 0.08]). The between center variation in mean URR also declined from the pre-QIP to the post-QIP sample (SD, 3.6 versus 2.8). In conclusion, there is a center effect on dialysis adequacy measurable in an ESRD Network, which diminishes after a successful QIP; therefore, when implementing a QIP to improve dialysis adequacy, changes in the center effect should be considered a potential indicator of the efficacy of the intervention.

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Year:  2002        PMID: 12191978     DOI: 10.1097/01.asn.0000027978.98194.1f

Source DB:  PubMed          Journal:  J Am Soc Nephrol        ISSN: 1046-6673            Impact factor:   10.121


  10 in total

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Authors:  Manish M Sood; Braden Manns; Allison Dart; Brett Hiebert; Joanne Kappel; Paul Komenda; Anita Molzahn; David Naimark; Sharon Nessim; Claudio Rigatto; Steven Soroka; Michael Zappitelli; Navdeep Tangri
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6.  Predictors of haemoglobin levels and resistance to erythropoiesis-stimulating agents in patients treated with low-flux haemodialysis, haemofiltration and haemodiafiltration: results of a multicentre randomized and controlled trial.

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7.  Differences in quality of life of hemodialysis patients between dialysis centers.

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Journal:  BMC Nephrol       Date:  2016-02-27       Impact factor: 2.388

9.  Monitoring of hemodialysis quality-of-care indicators: why is it important?

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10.  Assessing value-based health care delivery for haemodialysis.

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  10 in total

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