Dr. Elsa: Integrated, Intelligent Healthcare

About Solution

Dr. Elsa is a Health Assistant tool, powered by data and Artificial Intelligence, that supports healthcare workers (HCWs) in rural areas in East Africa through diagnostic decision support, next step recommendations, and predicting disease outbreaks. Our tool is delivered to HCWs through a mobile application, and acts like a general physician or specialist, guiding the HCW towards a more evidence-based, data-backed decisions. The Health Assistant is also able to analyze existing health data to predict infectious disease outbreaks 6 months in advance, allowing health providers and governments to better prepare for these outbreaks. We are currently building Dr. Elsa for use in three important areas: infectious disease, non-communicable disease (including cancer), and pediatric care. If successful, healthcare providers will be able to make more informed care decisions about their patients, therefore decreasing the number of misdiagnoses, decreasing the use of antibiotics, decreasing the amount of time and money a patient has to spend in the care system, and increasing the healthcare workers level of support and respect in the community. We hope to see improved health outcomes for infants and adolescents in East Africa (in support of SDG 3 and other national priorities) and an increase in the number of patients who access high-quality, data-driven healthcare services. Our outbreak prediction models, which will be able to give healthcare workers and the government more insight on the spread of disease, will ideally decrease the number of patients who need to access overcrowded facilities by providing accurate predictions months in advance and supporting resource allocation.


Our solution has been built entirely in Tanzania, uses contextually relevant data to train models, and is applicable across the African continent. We have built our tools to be accessible on a variety of devices, increasing the ease and availability of the tool for rural healthcare workers. We have completed early proof of concept testing in Tanzania, and we are in the beginning stages of a larger efficacy pilot in the country to determine the accuracy of our models/ algorithms against the Gold Standard of Care at identifying diseases based on patient history, patient demographics, and current symptoms. Our tools have also gained recognition among the Ministry of Health and other influential technology leaders in the country. Once reaching market, we will directly impact the lives of healthcare workers and patients by improving healthcare delivery and health outcomes. We expect to support 10,000 healthcare workers in the next 5 years with smart tools that assist with diagnostics, next steps, and disease outbreak predictions.



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