Silvana Maria Quintana, Geraldo Duarte, Cynthia Pileggi-Castro, C. Prunet, C Landman, Ahmet Metin Gülmezoglu, Ana Pilar Betrán, Maria do Carmo Leal, Kapila Jayaratne, P Borges, Gleici da Silva Castro Perdona, Olufemi T. Oladapo, Chimedsuren Ochir, Torloni, A. Zongo, K Takahiko, Guillermo Carroli, P.B. Olkhanud, Alessandra Cristina Marcolin, Liana Campodonico, João Paulo Souza, B de Mucio, Suzanne Serruya, N Lack, CM Gibbs Pickens, Catherine Deneux-Tharaux, AD Costa Passos, Ö Tunçalp, Malinee Laopaiboon, Ecd Moises, Domingos Alves, Eduardo Ortiz-Panozo, Marcos Nakamura-Pereira, José Guilherme Cecatti, Zhuoyang Li, Naho Morisaki, Béatrice Blondel, Dilys Walker, Ipek Gurol-Urganci, Edgardo Abalos, Alexandre Dumont, Jian Zhang, Joshua P. Vogel, HE Knight, Leonardo Moscovici, R Mori, Erika Ota, Ganchimeg Togoobaatar, Elisabeth Meloni Vieira, Maria Laura Costa, Pisake Lumbiganon, Cristina Beatriz Cuesta, Suneeta Mittal, Mika Gissler, Marleen Temmerman, Suneth Agampodi, M Danansuriya, Kramer, Carol J. R. Hogue, Bernardo Hernández, Vicente Bataglia, Lívia Oliveira-Ciabati, Ricardo Pérez-Cuevas, and Elizabeth A. Sullivan
NICHD NIH HHS World Health Organization 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. Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Social Med, Av Bandeirantes, BR-3900 Ribeirao Preto, Brazil WHO, World Bank Special Programme Res Dev & Res Traini, UNDP UNFPA UNICEF WHO, Dept Reprod Hlth & Res, CH-1211 Geneva, Switzerland Univ Paris 05, Sorbonne Paris Cite, UMR 216, Inst Dev Res, Paris, France WHO Reg Off Amer, Women & Reprod Hlth CLAP WR, Latin Amer Ctr Perinatol, Montevideo, Uruguay Emory Univ, Rollins Sch Publ Hlth, Dept Epidemiol, Atlanta, GA 30322 USA Paris Descartes Univ, Ctr Epidemiol & Biostat, Obstetr Perinatal & Pediat Epidemiol Res Team, Inserm U1153, Paris, France Natl Inst Publ Hlth, Ctr Populat Hlth Res, Cuernavaca, Morelos, Mexico Univ Technol, Fac Hlth, Sydney, NSW, Australia Natl Ctr Child Hlth & Dev, Dept Hlth Policy, Tokyo, Japan Ctr Rosarino Estudios Perinat, Rosario, Argentina Lindsay Stewart R&D Ctr, Off Res & Clin Audit, Royal Coll Obstetricians & Gynaecologists, London, England London Sch Hyg & Trop Med, Dept Hlth Serv Res & Policy, London WC1, England Shanghai Jiao Tong Univ, Sch Med, Xinhua Hosp, Shanghai Key Lab Childrens Environ Hlth,Minist Ed, Shanghai 200030, Peoples R China Univ Estadual Campinas, Sch Med Sci, Dept Obstet & Gynaecol, Campinas, SP, Brazil Family Hlth Bur, Minist Hlth, Colombo, Sri Lanka Fiocruz MS, ENSP, BR-21045900 Rio De Janeiro, Brazil Natl Inst Hlth & Welf, Helsinki, Finland Univ Tokyo, Grad Sch Med, Dept Paediat, Tokyo, Japan Bayer Krankenhausgesellschaft, Bayer Arbeitsgemeinschaft Qualitatssicherun Stati, Munich, Germany Khon Kaen Univ, Fac Med, Dept Obstet & Gynecol, Khon, Kaen, Thailand Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Obstet & Gynaecol, BR-14049 Ribeirao Preto, Brazil Minist Sante, Direct Sante Famille, Ouagadougou, Burkina Faso Univ Washington, Inst Hlth Metr & Evaluat, Seattle, WA 98195 USA Univ Mongolia, Hlth Sci, Sch Publ Hlth, Ulaanbaatar, Mongol Peo Rep GLIDE Tech Cooperat & Res, Ribeirao Preto, SP, Brazil Univ Sao Paulo, Ribeirao Preto Med Sch, Dept Paediat, BR-14049 Ribeirao Preto, SP, Brazil Univ Calif San Francisco, Dept Obstet & Gynaecol & Global Hlth Sci, San Francisco, CA 94143 USA Khon Kaen Univ, Fac Publ Hlth, Dept Biostat & Demog, Khon Kaen, Thailand Univ Fed Sao Paulo, Sch Med Sao Paulo, Dept Obstet, Sao Paulo, Brazil Inter Amer Dev Bank, Social Protect & Hlth Div, Mexico City, DF, Mexico Fortis Mem Res Inst, Gurgaon, Haryana, India Hosp Nacl Itaugua, Itaugua, Paraguay Univ Fed Sao Paulo, Sch Med Sao Paulo, Dept Obstet, Sao Paulo, Brazil NICHD NIH HHS: T32 HD052460 World Health Organization: 001 Web of Science