Multivariate analyses to assess the effects of surgeon and hospital volume on cancer survival rates: a nationwide population-based study in Taiwan
Positive results between caseloads and outcomes have been validated in several procedures and cancer treatments. However, there is limited information available on the combined effects of surgeon and hospital caseloads. We used nationwide population-based data to explore the association between surg...
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| creator | Chang, Chun-Ming Huang, Kuang-Yung Hsu, Ta-Wen Su, Yu-Chieh Yang, Wei-Zhen Chen, Ting-Chang Chou, Pesus Lee, Ching-Chih |
| description | Positive results between caseloads and outcomes have been validated in several procedures and cancer treatments. However, there is limited information available on the combined effects of surgeon and hospital caseloads. We used nationwide population-based data to explore the association between surgeon and hospital caseloads and survival rates for major cancers.
A total of 11,677 patients with incident cancer diagnosed in 2002 were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity scores were used to assess the relationship between 5-year survival rates and different caseload combinations.
Based on the Cox proportional hazard model, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer survival rates, and hazard ratios ranged from 1.3 in head and neck cancer to 1.8 in lung cancer after adjusting for patients' demographic variables, co-morbidities, and treatment modality. When analyzed using the propensity scores, the adjusted 5-year survival rates were poorer for patients treated by low-volume surgeons in low-volume hospitals, compared to those treated by high-volume surgeons in high-volume hospitals (P |
| doi_str_mv | 10.1371/journal.pone.0040590 |
| format | Article |
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A total of 11,677 patients with incident cancer diagnosed in 2002 were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity scores were used to assess the relationship between 5-year survival rates and different caseload combinations.
Based on the Cox proportional hazard model, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer survival rates, and hazard ratios ranged from 1.3 in head and neck cancer to 1.8 in lung cancer after adjusting for patients' demographic variables, co-morbidities, and treatment modality. When analyzed using the propensity scores, the adjusted 5-year survival rates were poorer for patients treated by low-volume surgeons in low-volume hospitals, compared to those treated by high-volume surgeons in high-volume hospitals (P<0.005).
After adjusting for differences in the case mix, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer 5-year survival rates. Payers may implement quality care improvement in low-volume surgeons.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0040590</identifier><identifier>PMID: 22815771</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Aged ; Analysis ; Biology ; Breast cancer ; Buddhism ; Cancer ; Cancer patients ; Cancer research ; Cancer surgery ; Cancer therapies ; Cancer treatment ; Colorectal cancer ; Demographic variables ; Demographics ; Diagnosis ; Female ; General Surgery - manpower ; Hazard assessment ; Head & neck cancer ; Head and neck cancer ; Health care policy ; Health hazards ; Health surveillance ; Heart surgery ; Hospitals ; Hospitals, High-Volume - statistics & numerical data ; Hospitals, Low-Volume - statistics & numerical data ; Humans ; Internal medicine ; Lung cancer ; Lung diseases ; Male ; Medical care quality ; Medical personnel ; Medical societies ; Medicine ; Middle Aged ; Mortality ; Multivariate Analysis ; National health insurance ; Neighborhoods ; Neoplasms - mortality ; Neoplasms - surgery ; Oncology ; Online databases ; Oral cancer ; Patient outcomes ; Patients ; Physicians ; Population studies ; Population-based studies ; Preventive medicine ; Proportional Hazards Models ; Prostate cancer ; Public health ; Quality ; Review boards ; Socioeconomic factors ; Statistical models ; Surgeons ; Survival ; Survival Rate ; Taiwan - epidemiology ; Workloads</subject><ispartof>PloS one, 2012-07, Vol.7 (7), p.e40590-e40590</ispartof><rights>COPYRIGHT 2012 Public Library of Science</rights><rights>2012 Chang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Chang et al. 2012</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-71a08b1f40c0b5e01bb412489bbd9fe70d040fa4f50f8216e6123cbe2370f47b3</citedby><cites>FETCH-LOGICAL-c692t-71a08b1f40c0b5e01bb412489bbd9fe70d040fa4f50f8216e6123cbe2370f47b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398946/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398946/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22815771$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chang, Chun-Ming</creatorcontrib><creatorcontrib>Huang, Kuang-Yung</creatorcontrib><creatorcontrib>Hsu, Ta-Wen</creatorcontrib><creatorcontrib>Su, Yu-Chieh</creatorcontrib><creatorcontrib>Yang, Wei-Zhen</creatorcontrib><creatorcontrib>Chen, Ting-Chang</creatorcontrib><creatorcontrib>Chou, Pesus</creatorcontrib><creatorcontrib>Lee, Ching-Chih</creatorcontrib><title>Multivariate analyses to assess the effects of surgeon and hospital volume on cancer survival rates: a nationwide population-based study in Taiwan</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Positive results between caseloads and outcomes have been validated in several procedures and cancer treatments. However, there is limited information available on the combined effects of surgeon and hospital caseloads. We used nationwide population-based data to explore the association between surgeon and hospital caseloads and survival rates for major cancers.
A total of 11,677 patients with incident cancer diagnosed in 2002 were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity scores were used to assess the relationship between 5-year survival rates and different caseload combinations.
Based on the Cox proportional hazard model, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer survival rates, and hazard ratios ranged from 1.3 in head and neck cancer to 1.8 in lung cancer after adjusting for patients' demographic variables, co-morbidities, and treatment modality. When analyzed using the propensity scores, the adjusted 5-year survival rates were poorer for patients treated by low-volume surgeons in low-volume hospitals, compared to those treated by high-volume surgeons in high-volume hospitals (P<0.005).
After adjusting for differences in the case mix, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer 5-year survival rates. Payers may implement quality care improvement in low-volume surgeons.</description><subject>Aged</subject><subject>Analysis</subject><subject>Biology</subject><subject>Breast cancer</subject><subject>Buddhism</subject><subject>Cancer</subject><subject>Cancer patients</subject><subject>Cancer research</subject><subject>Cancer surgery</subject><subject>Cancer therapies</subject><subject>Cancer treatment</subject><subject>Colorectal cancer</subject><subject>Demographic variables</subject><subject>Demographics</subject><subject>Diagnosis</subject><subject>Female</subject><subject>General Surgery - manpower</subject><subject>Hazard assessment</subject><subject>Head & neck cancer</subject><subject>Head and neck cancer</subject><subject>Health care policy</subject><subject>Health hazards</subject><subject>Health surveillance</subject><subject>Heart surgery</subject><subject>Hospitals</subject><subject>Hospitals, High-Volume - statistics & numerical data</subject><subject>Hospitals, Low-Volume - statistics & numerical data</subject><subject>Humans</subject><subject>Internal medicine</subject><subject>Lung cancer</subject><subject>Lung diseases</subject><subject>Male</subject><subject>Medical care quality</subject><subject>Medical personnel</subject><subject>Medical societies</subject><subject>Medicine</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>Multivariate Analysis</subject><subject>National health insurance</subject><subject>Neighborhoods</subject><subject>Neoplasms - mortality</subject><subject>Neoplasms - surgery</subject><subject>Oncology</subject><subject>Online databases</subject><subject>Oral cancer</subject><subject>Patient outcomes</subject><subject>Patients</subject><subject>Physicians</subject><subject>Population studies</subject><subject>Population-based studies</subject><subject>Preventive medicine</subject><subject>Proportional Hazards Models</subject><subject>Prostate cancer</subject><subject>Public health</subject><subject>Quality</subject><subject>Review boards</subject><subject>Socioeconomic factors</subject><subject>Statistical models</subject><subject>Surgeons</subject><subject>Survival</subject><subject>Survival Rate</subject><subject>Taiwan - 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manpower</topic><topic>Hazard assessment</topic><topic>Head & neck cancer</topic><topic>Head and neck cancer</topic><topic>Health care policy</topic><topic>Health hazards</topic><topic>Health surveillance</topic><topic>Heart surgery</topic><topic>Hospitals</topic><topic>Hospitals, High-Volume - statistics & numerical data</topic><topic>Hospitals, Low-Volume - statistics & numerical data</topic><topic>Humans</topic><topic>Internal medicine</topic><topic>Lung cancer</topic><topic>Lung diseases</topic><topic>Male</topic><topic>Medical care quality</topic><topic>Medical personnel</topic><topic>Medical societies</topic><topic>Medicine</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>Multivariate Analysis</topic><topic>National health insurance</topic><topic>Neighborhoods</topic><topic>Neoplasms - mortality</topic><topic>Neoplasms - surgery</topic><topic>Oncology</topic><topic>Online databases</topic><topic>Oral cancer</topic><topic>Patient outcomes</topic><topic>Patients</topic><topic>Physicians</topic><topic>Population studies</topic><topic>Population-based studies</topic><topic>Preventive medicine</topic><topic>Proportional Hazards Models</topic><topic>Prostate cancer</topic><topic>Public health</topic><topic>Quality</topic><topic>Review boards</topic><topic>Socioeconomic factors</topic><topic>Statistical models</topic><topic>Surgeons</topic><topic>Survival</topic><topic>Survival Rate</topic><topic>Taiwan - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chang, Chun-Ming</au><au>Huang, Kuang-Yung</au><au>Hsu, Ta-Wen</au><au>Su, Yu-Chieh</au><au>Yang, Wei-Zhen</au><au>Chen, Ting-Chang</au><au>Chou, Pesus</au><au>Lee, Ching-Chih</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multivariate analyses to assess the effects of surgeon and hospital volume on cancer survival rates: a nationwide population-based study in Taiwan</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2012-07-17</date><risdate>2012</risdate><volume>7</volume><issue>7</issue><spage>e40590</spage><epage>e40590</epage><pages>e40590-e40590</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Positive results between caseloads and outcomes have been validated in several procedures and cancer treatments. However, there is limited information available on the combined effects of surgeon and hospital caseloads. We used nationwide population-based data to explore the association between surgeon and hospital caseloads and survival rates for major cancers.
A total of 11,677 patients with incident cancer diagnosed in 2002 were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity scores were used to assess the relationship between 5-year survival rates and different caseload combinations.
Based on the Cox proportional hazard model, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer survival rates, and hazard ratios ranged from 1.3 in head and neck cancer to 1.8 in lung cancer after adjusting for patients' demographic variables, co-morbidities, and treatment modality. When analyzed using the propensity scores, the adjusted 5-year survival rates were poorer for patients treated by low-volume surgeons in low-volume hospitals, compared to those treated by high-volume surgeons in high-volume hospitals (P<0.005).
After adjusting for differences in the case mix, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer 5-year survival rates. Payers may implement quality care improvement in low-volume surgeons.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>22815771</pmid><doi>10.1371/journal.pone.0040590</doi><tpages>e40590</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2012-07, Vol.7 (7), p.e40590-e40590 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1326218162 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Aged Analysis Biology Breast cancer Buddhism Cancer Cancer patients Cancer research Cancer surgery Cancer therapies Cancer treatment Colorectal cancer Demographic variables Demographics Diagnosis Female General Surgery - manpower Hazard assessment Head & neck cancer Head and neck cancer Health care policy Health hazards Health surveillance Heart surgery Hospitals Hospitals, High-Volume - statistics & numerical data Hospitals, Low-Volume - statistics & numerical data Humans Internal medicine Lung cancer Lung diseases Male Medical care quality Medical personnel Medical societies Medicine Middle Aged Mortality Multivariate Analysis National health insurance Neighborhoods Neoplasms - mortality Neoplasms - surgery Oncology Online databases Oral cancer Patient outcomes Patients Physicians Population studies Population-based studies Preventive medicine Proportional Hazards Models Prostate cancer Public health Quality Review boards Socioeconomic factors Statistical models Surgeons Survival Survival Rate Taiwan - epidemiology Workloads |
| title | Multivariate analyses to assess the effects of surgeon and hospital volume on cancer survival rates: a nationwide population-based study in Taiwan |
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