Abstract
Rwanda’s Ministry of Health (MOH) is currently working to eliminate malnutrition and stunting in children less than five years. The backbone of this project has been the development of the Rwandan Fortified Blended Foods programme, which oversees and manages the delivery of care and food for children in the poorest families in country. To support this effort, the MOH identified the need for a growth tracking application (app) to facilitate the detection of and intervention in cases of anomalous child development. This thesis explores the process of developing, implementing and user-testing a nutrition and growth tracking app in Rwanda, as well as the potential benefits of using a Clinical Decision Support System (CDSS). It looks at the different challenges and opportunities that might arise for developers and health workers in the implementation and use of the app. The app calculates Z-scores based on anthropometric measurements, which represents deviations from normal growth, and uses growth charts to present the results. The app gives health workers Clinical Decision Support (CDS) during patient consultation, presenting a health status of the child based on the calculated Z-scores. Additionally, based on user feedback, another app prototype was developed to help health managers aggregate and synthesize growth data. The overarching goal of the thesis is to improve our stock of knowledge about the use of CDSSs in low-resources settings. CDSSs are characterized by a lacuna of research, although it is suggested that they may significantly improve patient outcomes in developing countries. The study is based on an action research framework that both generated empirical data and enabled field testing of the app. The results of the research shows great potential for the use of CDSSs in Rwanda compared to the existing paper based system. Based on feedback from health workers, experts and managers, it was found that the growth tracking app shows potential for lessening workload and improving workflow, reducing calculation errors, and improving patient feedback. However, because of limited time to field test the app, collect user feedback and implement improvements, the results of this study should only be considered indicative. Further, iterative development and testing of the app throughout Rwanda will be required in the future.