Quantifying Regional and Health Care Variations to Identify Ways to Improve Hemodialysis Service Quality and Survival Outcomes

The authors examined variations in hemodialysis care and quantified the effect of these variations on all-cause mortality. Insurance claims data from April 1, 2017 to March 30, 2018 were reviewed. In total, 2895 hospital patients were identified, among whom 398 died from various causes. Controlling...

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Published in:American Journal of Medical Quality
Main Author: Jamal A.; Babazono A.; Li Y.; Yoshida S.; Fujita T.; Kim S.-A.
Format: Article
Language:English
Published: Wolters Kluwer Health 2021
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115448524&doi=10.1097%2f01.JMQ.0000735484.44163.ce&partnerID=40&md5=3a13654746b1a3e25c4a084a0e39a8c9
id 2-s2.0-85115448524
spelling 2-s2.0-85115448524
Jamal A.; Babazono A.; Li Y.; Yoshida S.; Fujita T.; Kim S.-A.
Quantifying Regional and Health Care Variations to Identify Ways to Improve Hemodialysis Service Quality and Survival Outcomes
2021
American Journal of Medical Quality
36
5
10.1097/01.JMQ.0000735484.44163.ce
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115448524&doi=10.1097%2f01.JMQ.0000735484.44163.ce&partnerID=40&md5=3a13654746b1a3e25c4a084a0e39a8c9
The authors examined variations in hemodialysis care and quantified the effect of these variations on all-cause mortality. Insurance claims data from April 1, 2017 to March 30, 2018 were reviewed. In total, 2895 hospital patients were identified, among whom 398 died from various causes. Controlling effects of the facility and secondary medical care areas, all-cause mortality was associated with older age, heart failure, malignancy, cerebral stroke, severe comorbidity, and the first and ninth centile of physician density. Multilevel analyses indicated a significant variation at facility level (σ22 0.27, 95% confidence interval: 0.09-0.49). Inclusion of all covariates in the final model significantly reduced facility-level variance. Physician density emerged as an important factor affecting survival outcome; thus, a review of workforce and resource allocation policies is needed. Better clinical management and standardized work processes are necessary to attenuate differences in hospital practice patterns. © The Authors 2021.
Wolters Kluwer Health
10628606
English
Article

author Jamal A.; Babazono A.; Li Y.; Yoshida S.; Fujita T.; Kim S.-A.
spellingShingle Jamal A.; Babazono A.; Li Y.; Yoshida S.; Fujita T.; Kim S.-A.
Quantifying Regional and Health Care Variations to Identify Ways to Improve Hemodialysis Service Quality and Survival Outcomes
author_facet Jamal A.; Babazono A.; Li Y.; Yoshida S.; Fujita T.; Kim S.-A.
author_sort Jamal A.; Babazono A.; Li Y.; Yoshida S.; Fujita T.; Kim S.-A.
title Quantifying Regional and Health Care Variations to Identify Ways to Improve Hemodialysis Service Quality and Survival Outcomes
title_short Quantifying Regional and Health Care Variations to Identify Ways to Improve Hemodialysis Service Quality and Survival Outcomes
title_full Quantifying Regional and Health Care Variations to Identify Ways to Improve Hemodialysis Service Quality and Survival Outcomes
title_fullStr Quantifying Regional and Health Care Variations to Identify Ways to Improve Hemodialysis Service Quality and Survival Outcomes
title_full_unstemmed Quantifying Regional and Health Care Variations to Identify Ways to Improve Hemodialysis Service Quality and Survival Outcomes
title_sort Quantifying Regional and Health Care Variations to Identify Ways to Improve Hemodialysis Service Quality and Survival Outcomes
publishDate 2021
container_title American Journal of Medical Quality
container_volume 36
container_issue 5
doi_str_mv 10.1097/01.JMQ.0000735484.44163.ce
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115448524&doi=10.1097%2f01.JMQ.0000735484.44163.ce&partnerID=40&md5=3a13654746b1a3e25c4a084a0e39a8c9
description The authors examined variations in hemodialysis care and quantified the effect of these variations on all-cause mortality. Insurance claims data from April 1, 2017 to March 30, 2018 were reviewed. In total, 2895 hospital patients were identified, among whom 398 died from various causes. Controlling effects of the facility and secondary medical care areas, all-cause mortality was associated with older age, heart failure, malignancy, cerebral stroke, severe comorbidity, and the first and ninth centile of physician density. Multilevel analyses indicated a significant variation at facility level (σ22 0.27, 95% confidence interval: 0.09-0.49). Inclusion of all covariates in the final model significantly reduced facility-level variance. Physician density emerged as an important factor affecting survival outcome; thus, a review of workforce and resource allocation policies is needed. Better clinical management and standardized work processes are necessary to attenuate differences in hospital practice patterns. © The Authors 2021.
publisher Wolters Kluwer Health
issn 10628606
language English
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