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Analysis of factors influencing the outpatient workload at Chinese health centres
BACKGROUND: Although the community health service system is now established in China, the utilisation of the community health service institutions is low due to the lack of a gate-keeping role of the primary health service providers and referrals among the three-tiered health service institutions. I...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2904333/ https://www.ncbi.nlm.nih.gov/pubmed/20525381 http://dx.doi.org/10.1186/1472-6963-10-151 |
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author | Xu, Jing Wang, Wenxin Li, Yongbin Zhang, Juan Pavlova, Milena Liu, Hua Yin, Ping Lu, Zuxun |
author_facet | Xu, Jing Wang, Wenxin Li, Yongbin Zhang, Juan Pavlova, Milena Liu, Hua Yin, Ping Lu, Zuxun |
author_sort | Xu, Jing |
collection | PubMed |
description | BACKGROUND: Although the community health service system is now established in China, the utilisation of the community health service institutions is low due to the lack of a gate-keeping role of the primary health service providers and referrals among the three-tiered health service institutions. In addition to this, patients who can afford to pay, often seek best services in big hospitals to guarantee the quality of care. Thus, the need of guiding the patients to the community health services and increasing the utilisation of the community health service institutions is becoming an urgent problem, which hinders the future development of community health services. This study focuses on the question of how to increase the utilisation of Chinese community health centres (HCs). METHODS: A cross-sectional Base-line Survey of Chinese City Community Health Service System Building using the multi-staged cluster sampling was conducted to collect data from all HCs in 28 key contact cities. Relevant indicators of totally 1790 HCs were analysed. The statistical methods included ANONVA and logistic regression. RESULTS AND CONCLUSIONS: The analysis suggested several key factors for increasing the outpatient workload (OW) at the HCs: establishing an adequate referral system among the different levels of the health system; enhancing the qualification of health personnel and increasing the compensation by the health insurance for services provided at HCs. Other key factors with a positive effect on the OW included: the government ownership of the HCs, the scale of the institutions, the medical equipment used, the mix of health services provided, and the women in childbearing age in the residence. |
format | Text |
id | pubmed-2904333 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-29043332010-07-15 Analysis of factors influencing the outpatient workload at Chinese health centres Xu, Jing Wang, Wenxin Li, Yongbin Zhang, Juan Pavlova, Milena Liu, Hua Yin, Ping Lu, Zuxun BMC Health Serv Res Research Article BACKGROUND: Although the community health service system is now established in China, the utilisation of the community health service institutions is low due to the lack of a gate-keeping role of the primary health service providers and referrals among the three-tiered health service institutions. In addition to this, patients who can afford to pay, often seek best services in big hospitals to guarantee the quality of care. Thus, the need of guiding the patients to the community health services and increasing the utilisation of the community health service institutions is becoming an urgent problem, which hinders the future development of community health services. This study focuses on the question of how to increase the utilisation of Chinese community health centres (HCs). METHODS: A cross-sectional Base-line Survey of Chinese City Community Health Service System Building using the multi-staged cluster sampling was conducted to collect data from all HCs in 28 key contact cities. Relevant indicators of totally 1790 HCs were analysed. The statistical methods included ANONVA and logistic regression. RESULTS AND CONCLUSIONS: The analysis suggested several key factors for increasing the outpatient workload (OW) at the HCs: establishing an adequate referral system among the different levels of the health system; enhancing the qualification of health personnel and increasing the compensation by the health insurance for services provided at HCs. Other key factors with a positive effect on the OW included: the government ownership of the HCs, the scale of the institutions, the medical equipment used, the mix of health services provided, and the women in childbearing age in the residence. BioMed Central 2010-06-05 /pmc/articles/PMC2904333/ /pubmed/20525381 http://dx.doi.org/10.1186/1472-6963-10-151 Text en Copyright ©2010 Xu 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 cited. |
spellingShingle | Research Article Xu, Jing Wang, Wenxin Li, Yongbin Zhang, Juan Pavlova, Milena Liu, Hua Yin, Ping Lu, Zuxun Analysis of factors influencing the outpatient workload at Chinese health centres |
title | Analysis of factors influencing the outpatient workload at Chinese health centres |
title_full | Analysis of factors influencing the outpatient workload at Chinese health centres |
title_fullStr | Analysis of factors influencing the outpatient workload at Chinese health centres |
title_full_unstemmed | Analysis of factors influencing the outpatient workload at Chinese health centres |
title_short | Analysis of factors influencing the outpatient workload at Chinese health centres |
title_sort | analysis of factors influencing the outpatient workload at chinese health centres |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2904333/ https://www.ncbi.nlm.nih.gov/pubmed/20525381 http://dx.doi.org/10.1186/1472-6963-10-151 |
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