The Department of Health – Abu Dhabi (DoH) has announced today that it has cooperated with the Department of Government Support, DGS, represented by the Abu Dhabi Digital Authority, ADDA, to conduct two use cases on the methodology used in systems analysis to identify, clarify and organise system requirements, as part of an integrated project, the first phase of which includes five use cases in collaboration with four government entities.
The announcement took place at the Abu Dhabi Government Pavilion at GITEX Technology Week, 2020, in the presence of H.E. Sheikh Abdulla bin Mohamed Al Hamed, Chairman of the DoH.
The move comes as part of the Department of Government Support’s efforts to promote standards of data governance as one of the main pillars of Abu Dhabi’s digital transformation agenda.
The Data and Modern Technology team from ADDA worked closely with the DoH to implement the two use cases: the ‘Cardiovascular Disease Risk Calculator’ and the ‘Diabetes Risk Factor and Assessment Tool’. These are utilized to track and analyze big data and process it through artificial intelligence and machine learning techniques to detect certain patterns of data, and accordingly predict similar cases and provide better insight that helps in planning and supporting the decision-making process.
In both use cases, data for sick and healthy people is examined. The platform understands and links information such as age, family history, smoking habits and occurrence of chronic diseases, and through this information and more, can interpret and analyze the health of people, predict if they are at risk of contracting these diseases, and then activate a plan for early intervention, alerting potentially infected persons to change and modify their lifestyles and enhance the level of medical follow-up with them.
His Excellency Dr. Jamal Mohammed Obaid Al Kaabi, Undersecretary of the DoH, said: “This cooperation enhances integration between government departments in the Emirate of Abu Dhabi, as these joint government initiatives contribute to improving the quality of services, providing the highest standards of safety, and preserving public health. The two use cases will be used to increase the accuracy of detection of these two dangerous diseases, and thus reduce health costs and promote public health.”
H.E. Engineer Mohamed Abdel Hameed Al Askar, Director-General of the ADDA, said: “This achievement contributes to greater cooperation and integration between government entities in Abu Dhabi and supports the Emirate’s march of digital transformation and its position as a hub of digital innovation, regionally and globally. This cooperation with the DoH reflects the efforts of ADDA to create an innovative digital government that uses modern technologies to deliver government services that have a positive impact on society as a whole.”
The ‘Cardiovascular Disease Risk Calculator’ use case was developed by leveraging the American Heart Association CVD Risk Calculator and increasing accuracy through the usage of data. This case has two main components: Cardiologic Health Estimator, an AI-driven model that assesses heart health to help the relevant authorities predict and reduce the risk of cardiovascular disease in Abu Dhabi, and Patient Simulator, an AI-driven risk prediction score that simulates patients using data to assist in risk prediction and identify risk factors that cause cardiovascular diseases.
The ‘Diabetes Risk Factor and Assessment Tool’ use case helps identify the most frequent risk factors and develop a risk assessment tool to enhance the accuracy of the tests used to detect pre-diabetes, thus reducing Type 2 Diabetes cases. This case includes two main components: Population MonitorandSummary Dashboard, an AI-driven model that helps the Public Health Authorities predict and reduce the diabetes risk in Abu Dhabi, and Population Comparison and Patient Simulator, an AI-driven risk prediction score used to assist in identifying potential factors leading to incidents of diabetes and thereby helping to manage patient lifestyles and reduce the impact of contributing factors.
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