Using artificial intelligence, AI, for predictive and prescriptive diabetes care can lead to significant positive socio-economic impacts. According to our socio-economic impact study focusing on quantifying expected benefits of using Intelligent Wellbeing for diabetes care. The anticipated positive impact comes from direct cost savings in healthcare, increased productivity due to reduced sick leaves and better healdh and increased wellbeing.
Analysing the available data enables organisations to answer three key questions - what is the situation now, what will things look like in the future, and what can we do to improve this predicted outcome.
Predictive and prescriptive use of data can reduce the risk of diabetes and for those already diagnosed, the risk of severe complications. In the case of prevention, the service could alert a doctor about a risk of future diagnosis, and thus by taking action now a person could continue his/her life without diabetes. In the case of early diagnosis a person could get better care and help with maintaining health control and thus avoiding costly complications.
According to our study, on national level in Finland, the service could help save 280 MEUR from direct healthcare cost and yield 930 MEUR increase in productivity on annual basis. At the same time, patients’ wellbeing and quality of life would increase.
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