Total 350 words used.
Advanced Analytics-driven Diabetes Management Program (AADM), a unique innovative technique operationalized by Emirates Health Services (EHS) won national recognition for its contribution to the healthcare sector of UAE. EHS consisting of 17 hospitals and 100+ primary healthcare/public health centers with a care coverage encompassing a huge population. By AADM, EHS through this artificial intelligence (AI) enhanced program, aimed to improve operational efficiency, care by showcasing trends/forecasts and a 5-year projection of the financial burden of diabetes in the UAE.
AADM was developed based on 10 million data records as a comprehensive platform with descriptive, predictive, and prescriptive analytics capabilities to facilitate executive decision-making for governmental officials and policymakers, where the Data->Information->Knowledge->Wisdom (DIKW) methodology was applied through the Cross Industry Standard Process for Data Mining (CRISP-DM) framework. As a governmental institution, EHS constantly supports meeting one of the key national priorities ‘world-class healthcare’ by developing comprehensive technical platforms like AADM that would provide an innovative evidence-based data-driven solution to analyze the diabetic population, and predict the demand for diabetes-related services for early interventions.
AADM through the analytical insights present diabetes distribution across the northern emirate’s population of UAE, contributed to the targeted care delivery for its population. The program supported quantifying the demand for resources and services for its associated comorbidities, and through the risk stratification algorithms to identify uncontrolled diabetes patients at higher risks. The model developed by EHS has patient traceability features to help in both developing care plans, and treatment regimens and to bring these patients back into the health system for improving the quality of life of the citizens. AADM enables the prediction of people at risk of deterioration of the disease and to find trends and service needs that shall be utilized in the future by the diabetic population. The analytics techniques used in the program help to 'predict' future visits which would support leaders in resource planning and foreseeing the expected service utilization much ahead and efficiently. The program highlighted that the cost of delayed medical intervention for diabetic high-risk groups will increase the financial burden by 8 million dirhams in the next five years.
Nomination Title: Advanced Analytics-driven Diabetes Management Program: A Technical innovation to predict Socioeconomic burden of diabetes
