Health professionals especially in low-resource settings often lack the support and tools to follow evidence-based clinical recommendations for diagnosing patients and recommend the accurate diagnostic test to the patients. Diagnostic algorithms, developed by integrating patient health information and other external factors with evidence-based clinical protocols, can help improve the quality of care and the rational use of resources in a cost-effective manner. In regards to that a diagnostic decision support tool was developed to assist patients and at-risk population to make an optimal diagnostic test choice at the right time. The tool act as a value-based care that focuses on improving outcomes, increasing efficiency and reducing costs assisting in early detection, management of COVID-19 in a cost-effective manner. Advanced web-based COVID-19 dashboard assimilate multifaceted indicators for in-depth user analysis. By leveraging strengths across government stakeholders, health systems, data science, and community wisdom into an integrative dashboard, more targeted evidence-based decisions are possible to navigate the volatile pandemic climate. Implementing the continuous collaborative avenues and cyclic improvement philosophy will further bolster its responsiveness to arising needs. Both the depth and scale of data integrated through the dashboard will lead to more informed decision-making by health officials and policymakers. With flexible data visualizations and built-in algorithms, it will enable rapid analysis of the pandemic’s trajectory.
Ultimately the tool will help strengthen outbreak response strategies and resource allocation where they are needed most. While dashboard limitations exist in terms of data validation and quality at such a large scale, the recommendations and precedents within this design plan can serve as the base for the next generation of advanced, patient-centric public health dashboards.