Impact of Clinical Decision Support Systems on Diagnostic Accuracy in Rwanda

Purpose: The purpose of this article was to analyze impact of clinical decision support systems on diagnostic accuracy in Rwanda. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: In Rwanda, integrating Clinical Decision Support Systems (CDSS) has improved diagnostic accuracy by about 10–12%, particularly in rural settings where real-time, evidence-based guidance aids clinicians. This enhancement has led to earlier detection of diseases such as malaria and pneumonia, streamlining workflows and reducing patient waiting times. However, challenges with infrastructure and training persist, underscoring the need for sustained investment and evaluation. Unique Contribution to Theory, Practice and Policy: Technology acceptance model (TAM), diffusion of innovations theory & dual process theory may be used to anchor future studies on the impact of clinical decision support systems on diagnostic accuracy in Rwanda. In practice, healthcare organizations should invest in regular training programs and continuous professional development to ensure that clinicians are well-versed in utilizing CDSS effectively. Policymakers should facilitate the widespread adoption of CDSS by creating standardized protocols and guidelines that ensure quality and interoperability across healthcare systems.