Cargando…

Confounders of mortality and hospitalization rate calculations for profit and nonprofit dialysis facilities: analytic augmentation

BACKGROUND: Patient outcomes have been compared on the basis of the profit status of the dialysis provider (for-profit [FP] and not-for-profit [NFP]). In its annual report, United States Renal Data System (USRDS) provides dialysis provider level death and hospitalization rates adjusted by age, race,...

Descripción completa

Detalles Bibliográficos
Autores principales: Brunelli, Steven M, Wilson, Steven, Krishnan, Mahesh, Nissenson, Allen R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4113666/
https://www.ncbi.nlm.nih.gov/pubmed/25047925
http://dx.doi.org/10.1186/1471-2369-15-121
_version_ 1782328317675831296
author Brunelli, Steven M
Wilson, Steven
Krishnan, Mahesh
Nissenson, Allen R
author_facet Brunelli, Steven M
Wilson, Steven
Krishnan, Mahesh
Nissenson, Allen R
author_sort Brunelli, Steven M
collection PubMed
description BACKGROUND: Patient outcomes have been compared on the basis of the profit status of the dialysis provider (for-profit [FP] and not-for-profit [NFP]). In its annual report, United States Renal Data System (USRDS) provides dialysis provider level death and hospitalization rates adjusted by age, race, sex, and dialysis vintage; however, recent analyses have suggested that other variables impact these outcomes. Our current analysis of hospitalization and mortality rates of hemodialysis patients included adjustments for those used by the USRDS plus other potential confounders: facility geography (end-stage renal disease network), length of facility ownership, vascular access at first dialysis session, and pre-dialysis nephrology care. METHODS: We performed a provider level, retrospective analysis of 2010 hospitalization and mortality rates among US hemodialysis patients exclusively using USRDS sources. Crude and adjusted incidence rate ratios (IRRs) were calculated using the 4 standard USRDS patient factors plus the 4 potential confounders noted above. RESULTS: The analysis included 366,011 and 34,029 patients treated at FP and NFP facilities, respectively. There were statistical differences between the cohorts in geography, facility length of ownership, vascular access, and pre-dialysis nephrology care (p < 0.001), as well as age (p < 0.01), race (p < 0.001), and vintage (p < 0.001), but not sex (p = 0.12). When using standard USRDS adjustments, hospitalization and mortality rates for FP and NFP facilities were most disparate, favoring the NFP facilities. Rates were most similar between providers when adjustments were made for each of the 8 factors. With the FP IRR as the referent (1.0), the hospitalization IRR for NFP facilities was 1.00 (95% confidence interval [CI] 0.97-1.02; p = 0.69), while the NFP mortality IRR was 1.01 (95% CI 0.97-1.05; p = 0.64). CONCLUSIONS: These data suggest there is no difference in mortality and hospitalization rates between FP and NFP dialysis clinics when appropriate statistical adjustments are made.
format Online
Article
Text
id pubmed-4113666
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-41136662014-07-30 Confounders of mortality and hospitalization rate calculations for profit and nonprofit dialysis facilities: analytic augmentation Brunelli, Steven M Wilson, Steven Krishnan, Mahesh Nissenson, Allen R BMC Nephrol Research Article BACKGROUND: Patient outcomes have been compared on the basis of the profit status of the dialysis provider (for-profit [FP] and not-for-profit [NFP]). In its annual report, United States Renal Data System (USRDS) provides dialysis provider level death and hospitalization rates adjusted by age, race, sex, and dialysis vintage; however, recent analyses have suggested that other variables impact these outcomes. Our current analysis of hospitalization and mortality rates of hemodialysis patients included adjustments for those used by the USRDS plus other potential confounders: facility geography (end-stage renal disease network), length of facility ownership, vascular access at first dialysis session, and pre-dialysis nephrology care. METHODS: We performed a provider level, retrospective analysis of 2010 hospitalization and mortality rates among US hemodialysis patients exclusively using USRDS sources. Crude and adjusted incidence rate ratios (IRRs) were calculated using the 4 standard USRDS patient factors plus the 4 potential confounders noted above. RESULTS: The analysis included 366,011 and 34,029 patients treated at FP and NFP facilities, respectively. There were statistical differences between the cohorts in geography, facility length of ownership, vascular access, and pre-dialysis nephrology care (p < 0.001), as well as age (p < 0.01), race (p < 0.001), and vintage (p < 0.001), but not sex (p = 0.12). When using standard USRDS adjustments, hospitalization and mortality rates for FP and NFP facilities were most disparate, favoring the NFP facilities. Rates were most similar between providers when adjustments were made for each of the 8 factors. With the FP IRR as the referent (1.0), the hospitalization IRR for NFP facilities was 1.00 (95% confidence interval [CI] 0.97-1.02; p = 0.69), while the NFP mortality IRR was 1.01 (95% CI 0.97-1.05; p = 0.64). CONCLUSIONS: These data suggest there is no difference in mortality and hospitalization rates between FP and NFP dialysis clinics when appropriate statistical adjustments are made. BioMed Central 2014-07-21 /pmc/articles/PMC4113666/ /pubmed/25047925 http://dx.doi.org/10.1186/1471-2369-15-121 Text en Copyright © 2014 Brunelli et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Brunelli, Steven M
Wilson, Steven
Krishnan, Mahesh
Nissenson, Allen R
Confounders of mortality and hospitalization rate calculations for profit and nonprofit dialysis facilities: analytic augmentation
title Confounders of mortality and hospitalization rate calculations for profit and nonprofit dialysis facilities: analytic augmentation
title_full Confounders of mortality and hospitalization rate calculations for profit and nonprofit dialysis facilities: analytic augmentation
title_fullStr Confounders of mortality and hospitalization rate calculations for profit and nonprofit dialysis facilities: analytic augmentation
title_full_unstemmed Confounders of mortality and hospitalization rate calculations for profit and nonprofit dialysis facilities: analytic augmentation
title_short Confounders of mortality and hospitalization rate calculations for profit and nonprofit dialysis facilities: analytic augmentation
title_sort confounders of mortality and hospitalization rate calculations for profit and nonprofit dialysis facilities: analytic augmentation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4113666/
https://www.ncbi.nlm.nih.gov/pubmed/25047925
http://dx.doi.org/10.1186/1471-2369-15-121
work_keys_str_mv AT brunellistevenm confoundersofmortalityandhospitalizationratecalculationsforprofitandnonprofitdialysisfacilitiesanalyticaugmentation
AT wilsonsteven confoundersofmortalityandhospitalizationratecalculationsforprofitandnonprofitdialysisfacilitiesanalyticaugmentation
AT krishnanmahesh confoundersofmortalityandhospitalizationratecalculationsforprofitandnonprofitdialysisfacilitiesanalyticaugmentation
AT nissensonallenr confoundersofmortalityandhospitalizationratecalculationsforprofitandnonprofitdialysisfacilitiesanalyticaugmentation