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Trading quality for quantity? Evidence from patient level data in China

In China, overcrowding at hospitals increases the workload of medical staff, which may negatively impact the quality of medical services. This study empirically examined the impact of hospital admissions on the quality of healthcare services in Chinese hospitals. Specifically, we estimated the impac...

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Detalles Bibliográficos
Autores principales: Song, Jinglin, Chen, Chen, Zhao, Shaoyang, Zhou, Leming, Chen, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445449/
https://www.ncbi.nlm.nih.gov/pubmed/34529680
http://dx.doi.org/10.1371/journal.pone.0257127
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author Song, Jinglin
Chen, Chen
Zhao, Shaoyang
Zhou, Leming
Chen, Hong
author_facet Song, Jinglin
Chen, Chen
Zhao, Shaoyang
Zhou, Leming
Chen, Hong
author_sort Song, Jinglin
collection PubMed
description In China, overcrowding at hospitals increases the workload of medical staff, which may negatively impact the quality of medical services. This study empirically examined the impact of hospital admissions on the quality of healthcare services in Chinese hospitals. Specifically, we estimated the impact of the number of hospital admissions per day on a patient’s length of stay (LOS) and hospital mortality rate using both ordinary least squares (OLS) and instrumental variable (IV) methods. To deal with potential endogeneity problems and accurately identify the impact of medical staff configuration on medical quality, the daily air quality index was selected as the IV. Furthermore, we examined the differential effects of hospital admissions on the quality of care across different hospital tiers. We used the data from a random sample of 10% of inpatients from a city in China, covering the period from January 2014 to June 2019. Our final regression analysis included a sample of 167 disease types (as per the ICD-10 classification list) and 862,722 patient cases from 517 hospitals. According to our results, the LOS decreased and hospital mortality rate increased with an increasing number of admissions. Using the IV method, for every additional hospital admission, there was a 6.22% (p < 0.01) decrease in LOS and a 1.86% (p < 0.01) increase in hospital mortality. The impact of healthcare staffing levels on the quality of care varied between different hospital tiers. The quality of care in secondary hospitals was most affected by the number of admissions, with the average decrease of 18.60% (p < 0.05) in LOS and the increase of 6.05% (p < 0.01) in hospital mortality for every additional hospital admission in our sample. The findings suggested that the supply of medical services in China should be increased and a hierarchical diagnosis and treatment system should be actively promoted.
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spelling pubmed-84454492021-09-17 Trading quality for quantity? Evidence from patient level data in China Song, Jinglin Chen, Chen Zhao, Shaoyang Zhou, Leming Chen, Hong PLoS One Research Article In China, overcrowding at hospitals increases the workload of medical staff, which may negatively impact the quality of medical services. This study empirically examined the impact of hospital admissions on the quality of healthcare services in Chinese hospitals. Specifically, we estimated the impact of the number of hospital admissions per day on a patient’s length of stay (LOS) and hospital mortality rate using both ordinary least squares (OLS) and instrumental variable (IV) methods. To deal with potential endogeneity problems and accurately identify the impact of medical staff configuration on medical quality, the daily air quality index was selected as the IV. Furthermore, we examined the differential effects of hospital admissions on the quality of care across different hospital tiers. We used the data from a random sample of 10% of inpatients from a city in China, covering the period from January 2014 to June 2019. Our final regression analysis included a sample of 167 disease types (as per the ICD-10 classification list) and 862,722 patient cases from 517 hospitals. According to our results, the LOS decreased and hospital mortality rate increased with an increasing number of admissions. Using the IV method, for every additional hospital admission, there was a 6.22% (p < 0.01) decrease in LOS and a 1.86% (p < 0.01) increase in hospital mortality. The impact of healthcare staffing levels on the quality of care varied between different hospital tiers. The quality of care in secondary hospitals was most affected by the number of admissions, with the average decrease of 18.60% (p < 0.05) in LOS and the increase of 6.05% (p < 0.01) in hospital mortality for every additional hospital admission in our sample. The findings suggested that the supply of medical services in China should be increased and a hierarchical diagnosis and treatment system should be actively promoted. Public Library of Science 2021-09-16 /pmc/articles/PMC8445449/ /pubmed/34529680 http://dx.doi.org/10.1371/journal.pone.0257127 Text en © 2021 Song et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Song, Jinglin
Chen, Chen
Zhao, Shaoyang
Zhou, Leming
Chen, Hong
Trading quality for quantity? Evidence from patient level data in China
title Trading quality for quantity? Evidence from patient level data in China
title_full Trading quality for quantity? Evidence from patient level data in China
title_fullStr Trading quality for quantity? Evidence from patient level data in China
title_full_unstemmed Trading quality for quantity? Evidence from patient level data in China
title_short Trading quality for quantity? Evidence from patient level data in China
title_sort trading quality for quantity? evidence from patient level data in china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8445449/
https://www.ncbi.nlm.nih.gov/pubmed/34529680
http://dx.doi.org/10.1371/journal.pone.0257127
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