Previously physicians had to go through verbal autopsy reports to determine the causes of death, which was tedious, time consuming and prone to bias. The new AI model, developed by a beneficiary of the AI4D Africa Scholarship project, enables the government to determine the causes of out-of-hospital deaths in real time and, therefore, plan for timely interventions based on morbidity patterns.
A beneficiary of the AI4D Africa scholarship project has developed a unique AI model that can easily determine causes of deaths for patients who die out of hospital.
Consequently, the government of Tanzania is now changing how it collects, compiles and reports mortality statistics in the country.
Dr Mahadia Tunga, who was funded by the AI4D Africa Scholarship project, recently graduated with a Phd in Data Science from the University of Dar – es -Salaam. The Project is funded by the
International Development Research Centre (IDRC) and the Swedish International Development Cooperation Agency (SIDA)
Her model was prompted by the high number of people who die out of hospital and whose causes of death is not recorded or wrongly determined.
The model is based on a list of about 500 questions developed by WHO, which is administered by community health volunteers in Tanzania to collect data on the symptoms leading to death for those who die out of hospital. This process is known as verbal autopsy. This data could then be used by physicians to determine the causes of death.
Out of a list of 500 questions in the WHO questionnaire, she identified a minimal set of optimal questions that could be used to establish the causes of death and also to reduce the time someone interviews.
“These questions record signs and symptoms to determine the causes of death. Currently it takes at least 45 minutes and is very tedious and time consuming,” she said.
She then developed the model using existing data to determine cause of death for those who die out of hospital. To validate the accuracy of the model, the Ministry of health compared results of the verbal autopsy generated by the model with those verified by the physicians. The model registered 97% accuracy.
Previously, the Ministry of Health in Tanzania compiled verbal autopsy and medically certified reports separately.
“Previously, to compile mortality statistics, physicians had to go through the questions to determine the cause of death, which was tedious and could be also be biased. It also comes with the risk of double counting,’ she explained.
This methodology has now changed: this year’s report will integrate both sets of data – medically certificated reports and verbal autopsy generated by the model – into one national mortality statistics report.
She is now working with the Ministry to use the verbal autopsy based on the model to generate causes of death in real time rather than wait for the physician to go through the data and determine the causes of death.
“Previously, CHVs had to share the results with the physicians to determine the cause of death after every year but this tool will give the results instantly.
The government will be able to know the causes of death in real time and plan for interventions based on morbidity patterns instead of getting the results a year later,” she said.
Appointment to head Tanzania Data Lab (dLab)
On 8th May, 2023, Dr Tunga was appointed as Executive Director of Tanzania Data Lab (dLab). She was one among four founders of dLab and had been part of the Senior Management of dLab from the time it was a project; she was leading the Data Science Department of the lab. Tanzania Data Lab (dLab) is a world class data and innovation lab that harnesses the potential of the data revolution and the fourth industrial revolution in solving local, regional, and global sustainable development challenges through data and innovation.
The lab embraces a systems approach in suffusing data driven decision making and policy making by strengthening data policies, practice and use, and leverage data driven innovation and data partnerships to improve the lives of people. Apart from Tanzania, the lab also operates in Kenya, Uganda, Rwanda, Democratic Republic of Congo, Ethiopia, Egypt, Ghana, South Africa, Zimbabwe, and Kosovo.
The Role of AI4D Africa Scholarship project
According to Dr Tunga, this model would not have been developed as quickly as it was without support from the AI4D Africa Scholarship project.
“Conducting this kind of study is expensive. It required the researcher to go to the field and understand how the data is being collected, validation, getting permits, engaging Ministry officials. It helped me a lot with regard to financial and also credibility of the work. This support also made me complete my Phd studies in record 3 years or less,” she said.
She is now working closely with WHO verbal autopsy working group to incorporate narratives on the verbal autopsy reports to improve their quality.