Characterising emergency centre encounters in Mbour, Senegal as emergent-emergency care, emergent-primary care or non-emergent

Emergency medicine is a relatively new specialty in Africa, with the first emergency med- icine training programme only started in South Africa in 2004. Continued emergency centre development and preparedness relies on a better understanding of the quantity and category of emergency centre encounters within the various African regions. Methods: This study was conducted over four, consecutive months in 2014 using a retrospective chart review, aimed to examine the types of visits made to one emergency centre at the Grande Mbour Hospital in Mbour, Senegal. The New York University Emergency Department Algorithm was used to clas- sify emergency centre encounters. Each diagnosis included in this study was classified per the algorithm as non-emergent; emergent but primary care treatable; emergent with emergency centre care needed but avoidable/preventable; and emergent with emergency centre care needed and not avoidable/pre- ventable. The algorithm also categorised diagnoses of injury, mental health problems, alcohol, or sub- stance abuse. Results: This study included 1268 diagnoses from the emergency centre. The most common presenta- tions in Mbour, Senegal were injuries, with 302 cases (33%), and from the category: emergent but primary care treatable, with 303 cases (33%). In total, 174 cases (19%) were classified as: non-emergent. While only 93 cases (10%) were considered: emergency care needed/preventable or avoidable, a substantial number (n = 218, 24%) were categorised as: emergent with emergency centre care needed and not avoid- able/preventable. Conclusion: This study provides the first description of patients presenting for care in the emergency cen- tre of Mbour’s hospital and demonstrates the wide range of illnesses and types of trauma that the emer- gency centre must accommodate while contending with the limited resources available in the area. Understanding the burden of disease will help prioritise resources appropriately.