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Estimating the optimal perioperative chemotherapy utilization rate for muscle‐invasive bladder cancer
BACKGROUND: Identifying optimal chemotherapy (CT) utilization rates can drive improvements in quality of care. We report a benchmarking approach to estimate the optimal rate of perioperative CT for muscle‐invasive bladder cancer (MIBC). METHODS: The Ontario Cancer Registry and linked treated records...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797575/ https://www.ncbi.nlm.nih.gov/pubmed/31472011 http://dx.doi.org/10.1002/cam4.2449 |
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author | Karim, Safiya Mackillop, William J. Brennan, Kelly Peng, Yingwei Siemens, D. Robert Krzyzanowska, Monika K. Booth, Christopher M. |
author_facet | Karim, Safiya Mackillop, William J. Brennan, Kelly Peng, Yingwei Siemens, D. Robert Krzyzanowska, Monika K. Booth, Christopher M. |
author_sort | Karim, Safiya |
collection | PubMed |
description | BACKGROUND: Identifying optimal chemotherapy (CT) utilization rates can drive improvements in quality of care. We report a benchmarking approach to estimate the optimal rate of perioperative CT for muscle‐invasive bladder cancer (MIBC). METHODS: The Ontario Cancer Registry and linked treated records were used to identify neoadjuvant and adjuvant CT rates among patients with MIBC during 2004‐2013. Monte Carlo simulation was used to estimate the proportion of observed rate variation that could be due to chance alone. The criterion‐based benchmarking approach was used to explore whether social and health‐system factors were associated with CT rates. We also used the “pared‐mean” approach to identify a benchmark population of hospitals with the highest treatment rates. Hospital CT rates were adjusted for case mix and simulated using a multi‐level multivariable model and a parametric bootstrapping approach. RESULTS: The study population included 2581 patients; perioperative CT was delivered to 31% (798/2581). Multivariate analysis showed that treatment was strongly associated with patient socioeconomic status and hospital teaching status. The benchmark rate was 36%. Unadjusted CT rates were significantly different across hospitals (range 0%‐52%, P < .001). The unadjusted benchmark perioperative CT rate was 45% (95% CI 40%‐50%); utilization rate in nonbenchmark hospitals was 28% (95% CI 26%‐30%). When using simulated CT rates adjusted for case mix, the benchmark CT rate was 41% (95% CI 35%‐47%) and the nonbenchmark hospital CT rate was 30% (95% CI 28%‐32%). The simulation analysis suggested that the observed component of variation (38%) was outside the 95% CI (22%‐28%) of what could be expected due to chance alone. CONCLUSIONS: There is significant systematic variation in perioperative CT rates for MIBC across hospitals in routine practice. The benchmark perioperative CT rate for MIBC is 36%‐41%. |
format | Online Article Text |
id | pubmed-6797575 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-67975752019-10-21 Estimating the optimal perioperative chemotherapy utilization rate for muscle‐invasive bladder cancer Karim, Safiya Mackillop, William J. Brennan, Kelly Peng, Yingwei Siemens, D. Robert Krzyzanowska, Monika K. Booth, Christopher M. Cancer Med Clinical Cancer Research BACKGROUND: Identifying optimal chemotherapy (CT) utilization rates can drive improvements in quality of care. We report a benchmarking approach to estimate the optimal rate of perioperative CT for muscle‐invasive bladder cancer (MIBC). METHODS: The Ontario Cancer Registry and linked treated records were used to identify neoadjuvant and adjuvant CT rates among patients with MIBC during 2004‐2013. Monte Carlo simulation was used to estimate the proportion of observed rate variation that could be due to chance alone. The criterion‐based benchmarking approach was used to explore whether social and health‐system factors were associated with CT rates. We also used the “pared‐mean” approach to identify a benchmark population of hospitals with the highest treatment rates. Hospital CT rates were adjusted for case mix and simulated using a multi‐level multivariable model and a parametric bootstrapping approach. RESULTS: The study population included 2581 patients; perioperative CT was delivered to 31% (798/2581). Multivariate analysis showed that treatment was strongly associated with patient socioeconomic status and hospital teaching status. The benchmark rate was 36%. Unadjusted CT rates were significantly different across hospitals (range 0%‐52%, P < .001). The unadjusted benchmark perioperative CT rate was 45% (95% CI 40%‐50%); utilization rate in nonbenchmark hospitals was 28% (95% CI 26%‐30%). When using simulated CT rates adjusted for case mix, the benchmark CT rate was 41% (95% CI 35%‐47%) and the nonbenchmark hospital CT rate was 30% (95% CI 28%‐32%). The simulation analysis suggested that the observed component of variation (38%) was outside the 95% CI (22%‐28%) of what could be expected due to chance alone. CONCLUSIONS: There is significant systematic variation in perioperative CT rates for MIBC across hospitals in routine practice. The benchmark perioperative CT rate for MIBC is 36%‐41%. John Wiley and Sons Inc. 2019-08-31 /pmc/articles/PMC6797575/ /pubmed/31472011 http://dx.doi.org/10.1002/cam4.2449 Text en © 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Clinical Cancer Research Karim, Safiya Mackillop, William J. Brennan, Kelly Peng, Yingwei Siemens, D. Robert Krzyzanowska, Monika K. Booth, Christopher M. Estimating the optimal perioperative chemotherapy utilization rate for muscle‐invasive bladder cancer |
title | Estimating the optimal perioperative chemotherapy utilization rate for muscle‐invasive bladder cancer |
title_full | Estimating the optimal perioperative chemotherapy utilization rate for muscle‐invasive bladder cancer |
title_fullStr | Estimating the optimal perioperative chemotherapy utilization rate for muscle‐invasive bladder cancer |
title_full_unstemmed | Estimating the optimal perioperative chemotherapy utilization rate for muscle‐invasive bladder cancer |
title_short | Estimating the optimal perioperative chemotherapy utilization rate for muscle‐invasive bladder cancer |
title_sort | estimating the optimal perioperative chemotherapy utilization rate for muscle‐invasive bladder cancer |
topic | Clinical Cancer Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797575/ https://www.ncbi.nlm.nih.gov/pubmed/31472011 http://dx.doi.org/10.1002/cam4.2449 |
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