Suchergebnisse

Abstract. A model-based tsunami prediction system has been developed as part of the French Tsunami Warning Center (operational since 1 July 2012). It involves a precomputed unit source functions database (i.e., a number of tsunami model runs that are calculated ahead of time and stored). For the Mediterranean basin, the faults of the unit functions are placed adjacent to each other, following the discretization of the main seismogenic faults. An automated composite scenarios calculation tool is implemented to allow the simulation of any tsunami propagation scenario (i.e., of any seismic moment). Uncertainty on the magnitude of the detected event and inaccuracy of the epicenter location are taken into account in the composite scenarios calculation. Together with this forecasting system, another operational tool based on real time computing is implemented as part of the French Tsunami Warning Center. This second tsunami simulation tool takes advantage of multiprocessor approaches and more realistic seismological parameters, once the focal mechanism is established. Three examples of historical earthquakes are presented, providing warning refinement compared to the rough tsunami risk map given by the model-based decision matrix.

Background: Within infectious diseases in secondary care, understanding of the potential for behavioural changes arising from patient involvement in antimicrobial decision making is lacking. Shared decision making is becoming part of international policy. The United States have passed it into legislation and the United Kingdom has implemented a number of national interventions across healthcare pathways. This study aims to understand the level of patient involvement in decision making around antimicrobial use in secondary care and the potential consequences associated with it. Methods & Materials: Fourteen members of the public who had received antimicrobials from secondary care in the preceding 12 months were recruited to participate in group interviews. Group interactions were audio-recorded, transcribed verbatim, and thematically analysed. Results: Participants reported feelings of disempowerment during episodes of infection in secondary care. Information is currently communicated in a unilateral manner with individuals 'told' that they have an infection and will receive an antimicrobial (often unnamed), leading to loss of ownership, frustration, anxiety and ultimately distancing them from participation in decision making. This poor communication drives individuals to seek information from alternative sources, including on-line resources, which are associated with concerns over reliability and individualisation. This failure of communication and information provision from clinicians in secondary care influences individual's future ideas about infections and their management. This alters their future actions towards infections and antimicrobials and can drive non-adherence to prescribed antimicrobial regimes and loss-to-follow-up after discharge from secondary care. Conclusion: Current infection management and antimicrobial prescribing practices in secondary care may be failing to engage patients in the decision making process. It is vital that secondary care physicians do not view infection management episodes as discrete events, but as cumulative experiences which have the potential to drive future non-adherence to prescribed antimicrobial regimes and thus poor individual outcomes and antimicrobial resistance. This lesson is transferable to all settings of healthcare, where poor communication and information provision having the potential to influence future health seeking behaviours. We call for the development of clear, pragmatic mechanism to support healthcare professionals and patients engage in infection related decision making during consultations.

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. ; NICHD NIH HHS ; World Health Organization ; 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

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. ; NICHD NIH HHS ; World Health Organization ; 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