RESUMO
A decision support system for district-level disease surveillance was piloted with the Port Loko District Health Management Team in Sierra Leone. Through a qualitative evaluation, the study explores the impact of the system on disease surveillance workflows. Results indicate that the system aided decision making for operational tasks, and reduced the time taken to analyze and report surveillance data. In addition, the study discusses the challenges of deploying a pilot system during the Ebola recovery in Sierra Leone, and proposes a high-level architecture for a modular, interoperable decision support system for disease surveillance for public health decision makers in low-resource health systems.
Assuntos
Técnicas de Apoio para a Decisão , Doença pelo Vírus Ebola/diagnóstico , Saúde Pública , Recursos em Saúde , Doença pelo Vírus Ebola/epidemiologia , Humanos , Serra Leoa , Fluxo de TrabalhoRESUMO
During the 2014 West African Ebola Virus outbreak it became apparent that the initial response to the outbreak was hampered by limitations in the collection, aggregation, analysis and use of data for intervention planning. As part of the post-Ebola recovery phase, IBM Research Africa partnered with the Port Loko District Health Management Team (DHMT) in Sierra Leone and GOAL Global, to design, implement and deploy a web-based decision support tool for district-level disease surveillance. This paper discusses the design process and the functionality of the first version of the system. The paper presents evaluation results prior to a pilot deployment and identifies features for future iterations. A qualitative assessment of the tool prior to pilot deployment indicates that it improves the timeliness and ease of using data for making decisions at the DHMT level.