Chandana S. Jayasundara, Indu A. Jayawaradane, Dulani L. Samaranayake, Ananda Perera
{"title":"Validation of RobsApp - Audit tool for Caesarean Section Trends","authors":"Chandana S. Jayasundara, Indu A. Jayawaradane, Dulani L. Samaranayake, Ananda Perera","doi":"10.4038/sljog.v45i2.8097","DOIUrl":null,"url":null,"abstract":"Robson classification is a globally recognised method in systematically classifying all pregnant women admitted for delivery. The World Health Organization (WHO) and the International Federation of Gynecology and Obstetrics (FIGO) recommend the Robson classification as a global standard for assessing, monitoring and comparing CS rates within and between heath care facilities, over time. Continuous audit of admission and delivery data is an essential component in service quality improvements including caesarean section rates. Previously we have reported data acquisition and quality as the main problems in carrying out a continuous audit in absence of a centralised electronic database. We developed and validated an app based on the hybrid JQuery Mobile (JQM) technology with an option for scalability to the regional and national level in the future for real time acquisition and analysis of admissions data in a maternity care setting using Robson classification.","PeriodicalId":186118,"journal":{"name":"Sri Lanka Journal of Obstetrics and Gynaecology","volume":"122 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sri Lanka Journal of Obstetrics and Gynaecology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4038/sljog.v45i2.8097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Robson classification is a globally recognised method in systematically classifying all pregnant women admitted for delivery. The World Health Organization (WHO) and the International Federation of Gynecology and Obstetrics (FIGO) recommend the Robson classification as a global standard for assessing, monitoring and comparing CS rates within and between heath care facilities, over time. Continuous audit of admission and delivery data is an essential component in service quality improvements including caesarean section rates. Previously we have reported data acquisition and quality as the main problems in carrying out a continuous audit in absence of a centralised electronic database. We developed and validated an app based on the hybrid JQuery Mobile (JQM) technology with an option for scalability to the regional and national level in the future for real time acquisition and analysis of admissions data in a maternity care setting using Robson classification.
罗布森分类是全球公认的系统分类所有孕妇入院分娩的方法。世界卫生组织(世卫组织)和国际妇产科学联合会(FIGO)建议将罗布森分类作为一项全球标准,用于评估、监测和比较卫生保健机构内部和机构之间的长期CS率。对入院和分娩数据的持续审计是改善服务质量(包括剖宫产率)的重要组成部分。以前,我们报告了数据采集和质量是在没有集中电子数据库的情况下进行持续审计的主要问题。我们开发并验证了一款基于混合JQuery Mobile (JQM)技术的应用程序,该应用程序可以在未来扩展到区域和国家层面,使用Robson分类在产科护理环境中实时获取和分析入院数据。