在印度尼西亚部署opensrp驱动的客户管理应用程序后,助产士服务覆盖率、工作质量和客户健康得到改善

K. Kurniawan, Inraini FitriaSyah, Ahmad Rafi Jayakusuma, Resty Asmauryanah Armis, Y. Lubis, M. A. Haryono, B. Harefa, A. Shankar
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引用次数: 1

摘要

在大多数低收入和中等收入国家,孕产妇和儿童保健服务的质量仍然不够理想。通常使用基于纸张的系统收集数据,但数据不完整,利用率不足,并且报告为可用性差的汇总指标。因此,我们为印度尼西亚的助产士开发了开放智能注册平台(OpenSRP)应用程序,其中将常规纸质注册转换为智能实时数据驱动的客户管理系统。2015年至2018年,在龙目岛中部地区对10个村庄的30名一线工作人员(助产士、营养学家和疫苗接种员)进行了配对研究,并将其与使用常规纸质系统的10个匹配村庄的工作人员进行了比较。初步结果显示,孕妇的完整产前护理(ANC)从对照组的55%增加到OpenSRP区的73% (p<0.05)。此外,产妇和新生儿的产后护理(PNC)访问率从对照组的1%增加到OpenSRP区的45%以上(p<0.05)。产妇和新生儿发病率和死亡率往往较低,为27%,而控制区为8%。使用OpenSRP系统,卫生工作者可以迅速采取行动,根据数据提供更优质的服务,从而对孕产妇和新生儿健康产生更大的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Midwife service coverage, quality of work, and client health improved after deployment of an OpenSRP-driven client management application in Indonesia
The quality of maternal and child health services remains suboptimal in most low and middleincome countries (LMIC). Data are routinely collected with paper-based systems but are incomplete, underutilized, and reported as poorly-usable aggregated indicators. Therefore, we developed the Open Smart Register Platform (OpenSRP) application for midwives in Indonesia wherein routine paper registers were transformed into a smart real-time data-driven client management system. The app running on Android tablets was deployed as a matched-pair study in Central Lombok District in 2015-2018 to 30 frontline workers (midwives, nutritionists, and vaccinators) in 10 villages, and compared to workers in 10 matched villages using the routine paper-based system. Preliminary results indicate complete antenatal care (ANC) for pregnant women increased from 55% in the control area to 73% in the OpenSRP area (p<0.05). Moreover, postnatal care (PNC) visits for mothers and neonates increased from 1% in the control area to over 45% (p<0.05) in the OpenSRP area. Maternal and neonatal morbidity and mortality tended to be lower at 27% compared to 8% in the control area. Using the OpenSRP system, health workers can take rapid action to provide better quality service based on data, which resulted in a higher impact on maternal and neonatal health.
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