Cargando…

Performance Comparison among the Major Healthcare Financing Systems in Six Cities of the Pearl River Delta Region, Mainland China

BACKGROUND: The healthcare system of mainland China is undergoing drastic reform and the optimal models for healthcare financing for provision of primary care will need to be identified. This study compared the performance indicators of the community health centres (CHCs) under different healthcare...

Descripción completa

Detalles Bibliográficos
Autores principales: Wong, Martin C. S., Wang, Harry H. X., Wong, Samuel Y. S., Wei, Xiaolin, Yang, Nan, Zhang, Zhenzhen, Li, Haitao, Gao, Yang, Li, Donald K. T., Tang, JinLing, Wang, Jiaji, Griffiths, Sian M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3460811/
https://www.ncbi.nlm.nih.gov/pubmed/23029474
http://dx.doi.org/10.1371/journal.pone.0046309
_version_ 1782244987928313856
author Wong, Martin C. S.
Wang, Harry H. X.
Wong, Samuel Y. S.
Wei, Xiaolin
Yang, Nan
Zhang, Zhenzhen
Li, Haitao
Gao, Yang
Li, Donald K. T.
Tang, JinLing
Wang, Jiaji
Griffiths, Sian M.
author_facet Wong, Martin C. S.
Wang, Harry H. X.
Wong, Samuel Y. S.
Wei, Xiaolin
Yang, Nan
Zhang, Zhenzhen
Li, Haitao
Gao, Yang
Li, Donald K. T.
Tang, JinLing
Wang, Jiaji
Griffiths, Sian M.
author_sort Wong, Martin C. S.
collection PubMed
description BACKGROUND: The healthcare system of mainland China is undergoing drastic reform and the optimal models for healthcare financing for provision of primary care will need to be identified. This study compared the performance indicators of the community health centres (CHCs) under different healthcare financing systems in the six cities of the Pearl River Delta region. METHODS: Approximately 300 hypertensive patients were randomly recruited from the computerized chronic disease management records provided by one CHC in each of the six cities in 2011 using a multi-stage cluster random sampling method. The major outcome measures included the treatment rate of hypertension, defined as prescription of ≥ one antihypertensive agent; and the control rate of hypertension, defined as systolic blood pressure levels <140 mmHg and diastolic blood pressure levels <90 mmHg in patients without diabetes mellitus, or <130/80 mmHg among patients with concomitant diabetes. Binary logistic regression analyses were conducted with these two measures as outcome variables, respectively, controlling for patients’ socio-demographic variables. The financing system (Hospital- vs. Government- vs. private-funded) was the independent variable tested for association with the outcomes. RESULTS: From 1,830 patients with an average age of 65.9 years (SD 12.8), the overall treatment and control rates were 75.4% and 20.2%, respectively. When compared with hospital-funded CHCs, patients seen in the Government-funded (adjusted odds ratio [AOR] 0.462, 95% C.I. 0.325–0.656) and private-funded CHCs (AOR 0.031, 95% C.I. 0.019–0.052) were significantly less likely to be prescribed antihypertensive medication. However, the Government-funded CHC was more likely to have optimal BP control (AOR 1.628, 95% C.I. 1.157–2.291) whilst the privately-funded CHC was less likely to achieve BP control (AOR 0.146, 95% C.I. 0.069–0.310), irrespective of whether antihypertensive drugs were prescribed. CONCLUSIONS: Privately-funded CHCs had the lowest rates of BP treatment and control due to a variety of potential factors as discussed.
format Online
Article
Text
id pubmed-3460811
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-34608112012-10-01 Performance Comparison among the Major Healthcare Financing Systems in Six Cities of the Pearl River Delta Region, Mainland China Wong, Martin C. S. Wang, Harry H. X. Wong, Samuel Y. S. Wei, Xiaolin Yang, Nan Zhang, Zhenzhen Li, Haitao Gao, Yang Li, Donald K. T. Tang, JinLing Wang, Jiaji Griffiths, Sian M. PLoS One Research Article BACKGROUND: The healthcare system of mainland China is undergoing drastic reform and the optimal models for healthcare financing for provision of primary care will need to be identified. This study compared the performance indicators of the community health centres (CHCs) under different healthcare financing systems in the six cities of the Pearl River Delta region. METHODS: Approximately 300 hypertensive patients were randomly recruited from the computerized chronic disease management records provided by one CHC in each of the six cities in 2011 using a multi-stage cluster random sampling method. The major outcome measures included the treatment rate of hypertension, defined as prescription of ≥ one antihypertensive agent; and the control rate of hypertension, defined as systolic blood pressure levels <140 mmHg and diastolic blood pressure levels <90 mmHg in patients without diabetes mellitus, or <130/80 mmHg among patients with concomitant diabetes. Binary logistic regression analyses were conducted with these two measures as outcome variables, respectively, controlling for patients’ socio-demographic variables. The financing system (Hospital- vs. Government- vs. private-funded) was the independent variable tested for association with the outcomes. RESULTS: From 1,830 patients with an average age of 65.9 years (SD 12.8), the overall treatment and control rates were 75.4% and 20.2%, respectively. When compared with hospital-funded CHCs, patients seen in the Government-funded (adjusted odds ratio [AOR] 0.462, 95% C.I. 0.325–0.656) and private-funded CHCs (AOR 0.031, 95% C.I. 0.019–0.052) were significantly less likely to be prescribed antihypertensive medication. However, the Government-funded CHC was more likely to have optimal BP control (AOR 1.628, 95% C.I. 1.157–2.291) whilst the privately-funded CHC was less likely to achieve BP control (AOR 0.146, 95% C.I. 0.069–0.310), irrespective of whether antihypertensive drugs were prescribed. CONCLUSIONS: Privately-funded CHCs had the lowest rates of BP treatment and control due to a variety of potential factors as discussed. Public Library of Science 2012-09-28 /pmc/articles/PMC3460811/ /pubmed/23029474 http://dx.doi.org/10.1371/journal.pone.0046309 Text en © 2012 Wong et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Wong, Martin C. S.
Wang, Harry H. X.
Wong, Samuel Y. S.
Wei, Xiaolin
Yang, Nan
Zhang, Zhenzhen
Li, Haitao
Gao, Yang
Li, Donald K. T.
Tang, JinLing
Wang, Jiaji
Griffiths, Sian M.
Performance Comparison among the Major Healthcare Financing Systems in Six Cities of the Pearl River Delta Region, Mainland China
title Performance Comparison among the Major Healthcare Financing Systems in Six Cities of the Pearl River Delta Region, Mainland China
title_full Performance Comparison among the Major Healthcare Financing Systems in Six Cities of the Pearl River Delta Region, Mainland China
title_fullStr Performance Comparison among the Major Healthcare Financing Systems in Six Cities of the Pearl River Delta Region, Mainland China
title_full_unstemmed Performance Comparison among the Major Healthcare Financing Systems in Six Cities of the Pearl River Delta Region, Mainland China
title_short Performance Comparison among the Major Healthcare Financing Systems in Six Cities of the Pearl River Delta Region, Mainland China
title_sort performance comparison among the major healthcare financing systems in six cities of the pearl river delta region, mainland china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3460811/
https://www.ncbi.nlm.nih.gov/pubmed/23029474
http://dx.doi.org/10.1371/journal.pone.0046309
work_keys_str_mv AT wongmartincs performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT wangharryhx performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT wongsamuelys performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT weixiaolin performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT yangnan performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT zhangzhenzhen performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT lihaitao performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT gaoyang performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT lidonaldkt performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT tangjinling performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT wangjiaji performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina
AT griffithssianm performancecomparisonamongthemajorhealthcarefinancingsystemsinsixcitiesofthepearlriverdeltaregionmainlandchina