A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNIFESP |
Texto Completo: | https://doi.org/10.1111/1471-0528.13509 https://repositorio.unifesp.br/handle/11600/58619 |
Resumo: | ObjectiveTo generate a global reference for caesarean section (CS) rates at health facilities. DesignCross-sectional study. SettingHealth facilities from 43 countries. Population/SampleThirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10045875 women giving birth from 43 countries for model testing. MethodsWe hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. Main outcome measuresArea under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. ResultsAccording to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (). ConclusionsThis article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS. Tweetable abstractThe C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. Tweetable abstract The C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. |
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A global reference for caesarean section rates (C-Model): a multicountry cross-sectional studyBenchmarkingcaesarean delivery ratescaesarean section rateslogistic regressionObjectiveTo generate a global reference for caesarean section (CS) rates at health facilities. DesignCross-sectional study. SettingHealth facilities from 43 countries. Population/SampleThirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10045875 women giving birth from 43 countries for model testing. MethodsWe hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. Main outcome measuresArea under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. ResultsAccording to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (). ConclusionsThis article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS. Tweetable abstractThe C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. Tweetable abstract The C-Model provides a customized benchmark for caesarean section rates in health facilities and systems.Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Social Med, Av Bandeirantes, BR-3900 Ribeirao Preto, BrazilWHO, World Bank Special Programme Res Dev & Res Traini, UNDP UNFPA UNICEF WHO, Dept Reprod Hlth & Res, CH-1211 Geneva, SwitzerlandUniv Paris 05, Sorbonne Paris Cite, UMR 216, Inst Dev Res, Paris, FranceWHO Reg Off Amer, Women & Reprod Hlth CLAP WR, Latin Amer Ctr Perinatol, Montevideo, UruguayEmory Univ, Rollins Sch Publ Hlth, Dept Epidemiol, Atlanta, GA 30322 USAParis Descartes Univ, Ctr Epidemiol & Biostat, Obstetr Perinatal & Pediat Epidemiol Res Team, Inserm U1153, Paris, FranceNatl Inst Publ Hlth, Ctr Populat Hlth Res, Cuernavaca, Morelos, MexicoUniv Technol, Fac Hlth, Sydney, NSW, AustraliaNatl Ctr Child Hlth & Dev, Dept Hlth Policy, Tokyo, JapanCtr Rosarino Estudios Perinat, Rosario, ArgentinaLindsay Stewart R&D Ctr, Off Res & Clin Audit, Royal Coll Obstetricians & Gynaecologists, London, EnglandLondon Sch Hyg & Trop Med, Dept Hlth Serv Res & Policy, London WC1, EnglandShanghai Jiao Tong Univ, Sch Med, Xinhua Hosp, Shanghai Key Lab Childrens Environ Hlth,Minist Ed, Shanghai 200030, Peoples R ChinaUniv Estadual Campinas, Sch Med Sci, Dept Obstet & Gynaecol, Campinas, SP, BrazilFamily Hlth Bur, Minist Hlth, Colombo, Sri LankaFiocruz MS, ENSP, BR-21045900 Rio De Janeiro, BrazilNatl Inst Hlth & Welf, Helsinki, FinlandUniv Tokyo, Grad Sch Med, Dept Paediat, Tokyo, JapanBayer Krankenhausgesellschaft, Bayer Arbeitsgemeinschaft Qualitatssicherun Stati, Munich, GermanyKhon Kaen Univ, Fac Med, Dept Obstet & Gynecol, Khon, Kaen, ThailandUniv Sao Paulo, Ribeirao Preto Med Sch, Dept Obstet & Gynaecol, BR-14049 Ribeirao Preto, BrazilMinist Sante, Direct Sante Famille, Ouagadougou, Burkina FasoUniv Washington, Inst Hlth Metr & Evaluat, Seattle, WA 98195 USAUniv Mongolia, Hlth Sci, Sch Publ Hlth, Ulaanbaatar, Mongol Peo RepGLIDE Tech Cooperat & Res, Ribeirao Preto, SP, BrazilUniv Sao Paulo, Ribeirao Preto Med Sch, Dept Paediat, BR-14049 Ribeirao Preto, SP, BrazilUniv Calif San Francisco, Dept Obstet & Gynaecol & Global Hlth Sci, San Francisco, CA 94143 USAKhon Kaen Univ, Fac Publ Hlth, Dept Biostat & Demog, Khon Kaen, ThailandUniv Fed Sao Paulo, Sch Med Sao Paulo, Dept Obstet, Sao Paulo, BrazilInter Amer Dev Bank, Social Protect & Hlth Div, Mexico City, DF, MexicoFortis Mem Res Inst, Gurgaon, Haryana, IndiaHosp Nacl Itaugua, Itaugua, ParaguayUniv Fed Sao Paulo, Sch Med Sao Paulo, Dept Obstet, Sao Paulo, BrazilWeb of ScienceNICHD NIH HHSWorld Health OrganizationNICHD NIH HHS: T32 HD052460World Health Organization: 001Wiley2020-11-03T14:40:33Z2020-11-03T14:40:33Z2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion427-436https://doi.org/10.1111/1471-0528.13509Bjog-An International Journal Of Obstetrics And Gynaecology. Hoboken, v. 123, n. 3, p. 427-436, 2016.10.1111/1471-0528.13509WOS000368998000022.pdf1470-0328https://repositorio.unifesp.br/handle/11600/58619WOS:000368998000022engBjog-An International Journal Of Obstetrics And GynaecologyHobokeninfo:eu-repo/semantics/openAccessSouza, J. P.Betran, A. P.Dumont, A.de Mucio, B.Pickens, C. M. GibbsDeneux-Tharaux, C.Ortiz-Panozo, E.Sullivan, E.Ota, E.Togoobaatar, G.Carroli, G.Knight, H.Zhang, J.Cecatti, J. G.Vogel, J. P.Jayaratne, K.Leal, M. C.Gissler, M.Morisaki, N.Lack, N.Oladapo, O. T.Tuncalp, O.Lumbiganon, P.Mori, R.Quintana, S.Passos, A. D. CostaMarcolin, A. C.Zongo, A.Blondel, B.Hernandez, B.Hogue, C. J.Prunet, C.Landman, C.Ochir, C.Cuesta, C.Pileggi-Castro, C.Walker, D.Alves, D.Abalos, E.Moises, E. C. D.Vieira, E. M.Duarte, G.Perdona, G.Gurol-Urganci, I.Takahiko, K.Moscovici, L.Campodonico, L.Oliveira-Ciabati, L.Laopaiboon, M.Danansuriya, M.Nakamura-Pereira, M.Costa, M. L.Torloni, M. R. [UNIFESP]Kramer, M. R.Borges, P.Olkhanud, P. B.Perez-Cuevas, R.Agampodi, S. B.Mittal, S.Serruya, S.Bataglia, V.Li, Z.Temmerman, M.Guelmezoglu, A. M.reponame:Repositório Institucional da UNIFESPinstname:Universidade Federal de São Paulo (UNIFESP)instacron:UNIFESP2022-02-08T12:47:28Zoai:repositorio.unifesp.br/:11600/58619Repositório InstitucionalPUBhttp://www.repositorio.unifesp.br/oai/requestbiblioteca.csp@unifesp.bropendoar:34652022-02-08T12:47:28Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)false |
dc.title.none.fl_str_mv |
A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study |
title |
A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study |
spellingShingle |
A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study Souza, J. P. Benchmarking caesarean delivery rates caesarean section rates logistic regression |
title_short |
A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study |
title_full |
A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study |
title_fullStr |
A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study |
title_full_unstemmed |
A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study |
title_sort |
A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study |
author |
Souza, J. P. |
author_facet |
Souza, J. P. Betran, A. P. Dumont, A. de Mucio, B. Pickens, C. M. Gibbs Deneux-Tharaux, C. Ortiz-Panozo, E. Sullivan, E. Ota, E. Togoobaatar, G. Carroli, G. Knight, H. Zhang, J. Cecatti, J. G. Vogel, J. P. Jayaratne, K. Leal, M. C. Gissler, M. Morisaki, N. Lack, N. Oladapo, O. T. Tuncalp, O. Lumbiganon, P. Mori, R. Quintana, S. Passos, A. D. Costa Marcolin, A. C. Zongo, A. Blondel, B. Hernandez, B. Hogue, C. J. Prunet, C. Landman, C. Ochir, C. Cuesta, C. Pileggi-Castro, C. Walker, D. Alves, D. Abalos, E. Moises, E. C. D. Vieira, E. M. Duarte, G. Perdona, G. Gurol-Urganci, I. Takahiko, K. Moscovici, L. Campodonico, L. Oliveira-Ciabati, L. Laopaiboon, M. Danansuriya, M. Nakamura-Pereira, M. Costa, M. L. Torloni, M. R. [UNIFESP] Kramer, M. R. Borges, P. Olkhanud, P. B. Perez-Cuevas, R. Agampodi, S. B. Mittal, S. Serruya, S. Bataglia, V. Li, Z. Temmerman, M. Guelmezoglu, A. M. |
author_role |
author |
author2 |
Betran, A. P. Dumont, A. de Mucio, B. Pickens, C. M. Gibbs Deneux-Tharaux, C. Ortiz-Panozo, E. Sullivan, E. Ota, E. Togoobaatar, G. Carroli, G. Knight, H. Zhang, J. Cecatti, J. G. Vogel, J. P. Jayaratne, K. Leal, M. C. Gissler, M. Morisaki, N. Lack, N. Oladapo, O. T. Tuncalp, O. Lumbiganon, P. Mori, R. Quintana, S. Passos, A. D. Costa Marcolin, A. C. Zongo, A. Blondel, B. Hernandez, B. Hogue, C. J. Prunet, C. Landman, C. Ochir, C. Cuesta, C. Pileggi-Castro, C. Walker, D. Alves, D. Abalos, E. Moises, E. C. D. Vieira, E. M. Duarte, G. Perdona, G. Gurol-Urganci, I. Takahiko, K. Moscovici, L. Campodonico, L. Oliveira-Ciabati, L. Laopaiboon, M. Danansuriya, M. Nakamura-Pereira, M. Costa, M. L. Torloni, M. R. [UNIFESP] Kramer, M. R. Borges, P. Olkhanud, P. B. Perez-Cuevas, R. Agampodi, S. B. Mittal, S. Serruya, S. Bataglia, V. Li, Z. Temmerman, M. Guelmezoglu, A. M. |
author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Souza, J. P. Betran, A. P. Dumont, A. de Mucio, B. Pickens, C. M. Gibbs Deneux-Tharaux, C. Ortiz-Panozo, E. Sullivan, E. Ota, E. Togoobaatar, G. Carroli, G. Knight, H. Zhang, J. Cecatti, J. G. Vogel, J. P. Jayaratne, K. Leal, M. C. Gissler, M. Morisaki, N. Lack, N. Oladapo, O. T. Tuncalp, O. Lumbiganon, P. Mori, R. Quintana, S. Passos, A. D. Costa Marcolin, A. C. Zongo, A. Blondel, B. Hernandez, B. Hogue, C. J. Prunet, C. Landman, C. Ochir, C. Cuesta, C. Pileggi-Castro, C. Walker, D. Alves, D. Abalos, E. Moises, E. C. D. Vieira, E. M. Duarte, G. Perdona, G. Gurol-Urganci, I. Takahiko, K. Moscovici, L. Campodonico, L. Oliveira-Ciabati, L. Laopaiboon, M. Danansuriya, M. Nakamura-Pereira, M. Costa, M. L. Torloni, M. R. [UNIFESP] Kramer, M. R. Borges, P. Olkhanud, P. B. Perez-Cuevas, R. Agampodi, S. B. Mittal, S. Serruya, S. Bataglia, V. Li, Z. Temmerman, M. Guelmezoglu, A. M. |
dc.subject.por.fl_str_mv |
Benchmarking caesarean delivery rates caesarean section rates logistic regression |
topic |
Benchmarking caesarean delivery rates caesarean section rates logistic regression |
description |
ObjectiveTo generate a global reference for caesarean section (CS) rates at health facilities. DesignCross-sectional study. SettingHealth facilities from 43 countries. Population/SampleThirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10045875 women giving birth from 43 countries for model testing. MethodsWe hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. Main outcome measuresArea under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. ResultsAccording to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (). ConclusionsThis article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS. Tweetable abstractThe C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. Tweetable abstract The C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016 2020-11-03T14:40:33Z 2020-11-03T14:40:33Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://doi.org/10.1111/1471-0528.13509 Bjog-An International Journal Of Obstetrics And Gynaecology. Hoboken, v. 123, n. 3, p. 427-436, 2016. 10.1111/1471-0528.13509 WOS000368998000022.pdf 1470-0328 https://repositorio.unifesp.br/handle/11600/58619 WOS:000368998000022 |
url |
https://doi.org/10.1111/1471-0528.13509 https://repositorio.unifesp.br/handle/11600/58619 |
identifier_str_mv |
Bjog-An International Journal Of Obstetrics And Gynaecology. Hoboken, v. 123, n. 3, p. 427-436, 2016. 10.1111/1471-0528.13509 WOS000368998000022.pdf 1470-0328 WOS:000368998000022 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Bjog-An International Journal Of Obstetrics And Gynaecology |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
427-436 |
dc.coverage.none.fl_str_mv |
Hoboken |
dc.publisher.none.fl_str_mv |
Wiley |
publisher.none.fl_str_mv |
Wiley |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UNIFESP instname:Universidade Federal de São Paulo (UNIFESP) instacron:UNIFESP |
instname_str |
Universidade Federal de São Paulo (UNIFESP) |
instacron_str |
UNIFESP |
institution |
UNIFESP |
reponame_str |
Repositório Institucional da UNIFESP |
collection |
Repositório Institucional da UNIFESP |
repository.name.fl_str_mv |
Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP) |
repository.mail.fl_str_mv |
biblioteca.csp@unifesp.br |
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1814268410731692032 |