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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Autores principales:	Jinglin Song, Chen Chen, Shaoyang Zhao, Leming Zhou, Hong Chen
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/98358fb756754fb595cdf3f91f2ba848
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spelling	oai:doaj.org-article:98358fb756754fb595cdf3f91f2ba8482021-12-02T20:08:13ZTrading quality for quantity? Evidence from patient level data in China.1932-620310.1371/journal.pone.0257127https://doaj.org/article/98358fb756754fb595cdf3f91f2ba8482021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0257127https://doaj.org/toc/1932-6203In 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.Jinglin SongChen ChenShaoyang ZhaoLeming ZhouHong ChenPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0257127 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jinglin Song Chen Chen Shaoyang Zhao Leming Zhou Hong Chen Trading quality for quantity? Evidence from patient level data in China.
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.
format	article
author	Jinglin Song Chen Chen Shaoyang Zhao Leming Zhou Hong Chen
author_facet	Jinglin Song Chen Chen Shaoyang Zhao Leming Zhou Hong Chen
author_sort	Jinglin Song
title	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_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_sort	trading quality for quantity? evidence from patient level data in china.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/98358fb756754fb595cdf3f91f2ba848
work_keys_str_mv	AT jinglinsong tradingqualityforquantityevidencefrompatientleveldatainchina AT chenchen tradingqualityforquantityevidencefrompatientleveldatainchina AT shaoyangzhao tradingqualityforquantityevidencefrompatientleveldatainchina AT lemingzhou tradingqualityforquantityevidencefrompatientleveldatainchina AT hongchen tradingqualityforquantityevidencefrompatientleveldatainchina
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Trading quality for quantity? Evidence from patient level data in China.

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