Mwanga Daniel M, Waruingi Stella, Manolova Gergana, Wekesah Frederick M, Kadengye Damazo T, Otieno Peter O, Bitta Mary, Omwom Ibrahim, Iddi Samuel, Odero Paul, Kinuthia Joan W, Dua Tarun, Chowdhary Neerja, Ouma Frank O, Kipchirchir Isaac C, Muhua George O, Sander Josemir W, Newton Charles R, Asiki Gershim
African Population and Health Research Center (APHRC), Nairobi, Kenya.
Department of Mathematics, University of Nairobi, Nairobi, Kenya.
PLOS Digit Health. 2024 Nov 1;3(11):e0000646. doi: 10.1371/journal.pdig.0000646. eCollection 2024 Nov.
The availability of quality and timely data for routine monitoring of mental, neurological and substance use (MNS) disorders is a challenge, particularly in Africa. We assessed the feasibility of using an open-source data science technology (R Shiny) to improve health data reporting in Nairobi City County, Kenya. Based on a previously used manual tool, in June 2022, we developed a digital online data capture and reporting tool using the open-source Kobo toolbox. Primary mental health care providers (nurses and physicians) working in primary healthcare facilities in Nairobi were trained to use the tool to report cases of MNS disorders diagnosed in their facilities in real-time. The digital tool covered MNS disorders listed in the World Health Organization's (WHO) Mental Health Gap Action Program Intervention Guide (mhGAP-IG). In the digital system, data were disaggregated as new or repeat visits. We linked the data to a live dynamic reproducible dashboard created using R Shiny, summarising the data in tables and figures. Between January and August 2023, 9064 cases of MNS disorders (4454 newly diagnosed, 4591 revisits and 19 referrals) were reported using the digital system compared to 5321 using the manual system in a similar period in 2022. Reporting in the digital system was real-time compared to the manual system, where reports were aggregated and submitted monthly. The system improved data quality by providing timely and complete reports. Open-source applications to report health data is feasible and acceptable to primary health care providers. The technology improved real-time data capture, reporting, and monitoring, providing invaluable information on the burden of MNS disorders and which services can be planned and used for advocacy. The fast and efficient system can be scaled up and integrated with national and sub-national health information systems to reduce manual data reporting and decrease the likelihood of errors and inconsistencies.
获取用于精神、神经和物质使用（MNS）障碍常规监测的高质量及时数据是一项挑战，在非洲尤其如此。我们评估了使用开源数据科学技术（R Shiny）改善肯尼亚内罗毕市县健康数据报告的可行性。基于之前使用的手动工具，2022年6月，我们使用开源的Kobo工具箱开发了一个数字在线数据采集和报告工具。在内罗毕初级医疗保健机构工作的初级精神卫生保健提供者（护士和医生）接受培训，使用该工具实时报告其机构诊断出的MNS障碍病例。该数字工具涵盖了世界卫生组织（WHO）《精神卫生差距行动规划干预指南》（mhGAP-IG）中列出的MNS障碍。在数字系统中，数据按新就诊或复诊进行分类。我们将数据链接到使用R Shiny创建的实时动态可重现仪表板，以表格和图表形式汇总数据。2023年1月至8月，使用数字系统报告了9064例MNS障碍病例（4454例新诊断病例、4591例复诊病例和19例转诊病例），而2022年同期使用手动系统报告了5321例。与手动系统相比，数字系统的报告是实时的，手动系统的报告是每月汇总并提交。该系统通过提供及时完整的报告提高了数据质量。用于报告健康数据的开源应用程序对初级卫生保健提供者来说是可行且可接受的。该技术改善了实时数据采集、报告和监测，提供了关于MNS障碍负担以及可规划和用于宣传的服务的宝贵信息。这个快速高效的系统可以扩大规模并与国家和次国家卫生信息系统整合，以减少手动数据报告并降低错误和不一致的可能性。
