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 10 045 875 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 (www.who.int/reproductivehealth/publications/maternal_perinatal_health/c-model/en/).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.

BackgroundThe partograph is currently the main tool available to support decision-making of health professionals during labour. However, the rate of appropriate use of the partograph is disappointingly low. Apart from limitations that are associated with partograph use, evidence of positive impact on labour-related health outcomes is lacking. The main goal of this study is to develop a Simplified, Effective, Labour Monitoring-to-Action (SELMA) tool. The primary objectives are: to identify the essential elements of intrapartum monitoring that trigger the decision to use interventions aimed at preventing poor labour outcomes; to develop a simplified, monitoring-to-action algorithm for labour management; and to compare the diagnostic performance of SELMA and partograph algorithms as tools to identify women who are likely to develop poor labour-related outcomes.Methods/DesignA prospective cohort study will be conducted in eight health facilities in Nigeria and Uganda (four facilities from each country). All women admitted for vaginal birth will comprise the study population (estimated sample size: 7,812 women). Data will be collected on maternal characteristics on admission, labour events and pregnancy outcomes by trained research assistants at the participating health facilities. Prediction models will be developed to identify women at risk of intrapartum-related perinatal death or morbidity (primary outcomes) throughout the course of labour. These predictions models will be used to assemble a decision-support tool that will be able to suggest the best course of action to avert adverse outcomes during the course of labour. To develop this set of prediction models, we will use up-to-date techniques of prognostic research, including identification of important predictors, assigning of relative weights to each predictor, estimation of the predictive performance of the model through calibration and discrimination, and determination of its potential for application using internal validation techniques.DiscussionThis research offers an opportunity to revisit the theoretical basis of the partograph. It is envisioned that the final product would help providers overcome the challenging tasks of promptly interpreting complex labour information and deriving appropriate clinical actions, and thus increase efficiency of the care process, enhance providers’ competence and ultimately improve labour outcomes.Please see related articles ‘http://dx.doi.org/10.1186/s12978-015-0027-6’ and ‘http://dx.doi.org/10.1186/s12978-015-0028-5’.Electronic supplementary materialThe online version of this article (doi:10.1186/s12978-015-0029-4) contains supplementary material, which is available to authorized users.

RESUMO O Acesso Avançado (AA) é um formato de organização de agenda em unidades de saúde na Atenção Primária à Saúde que prega a máxima ‘Faça hoje o trabalho de hoje!’. Ele busca ativamente reduzir a demanda reprimida de atendimentos, reduzir o absenteísmo e ampliar o acesso aos usuários do Sistema Único de Saúde (SUS). O objetivo deste trabalho foi relatar aspectos da implementação do AA em uma Unidade de Saúde da Família (USF). Foram realizadas entrevistas com os profissionais da USF acerca do AA e, de forma preliminar, foram utilizados os dados do Sistema de Informação de Atenção Básica (Siab), do E-SUS e das agendas físicas, para comparação numérica de alguns parâmetros entre antes e depois da implantação e implementação do AA.