"Health care costs are growing at an alarming pace and health problems are not being addressed early enough,” explains Jukka Suovanen, CEO of Odum. ”Our aim is to decrease illness-related absences by 30 percent among application users and add 10 healthy years to their lives."
"Based on an algorithm developed by VTT, we can predict the risk of illness-related absence from work among members of the working population over the next 12 months, with an up to 80 percent sensitivity,” says VTT’s Mark van Gils, the scientific coordinator of the project.
During the project Odum and VTT examined health data collected from 18–64 year-olds over the course of several years. The project received health data from a total of 120,000 working individuals.
"The data has been collected by Odum over the past 10 years from Finnish occupational healthcare customers. It includes self-assessments regarding sleep/alertness, weight, exercise habits, mood, ability to work, the type of work the respondent does, alcohol consumption, use of tobacco products, pain (musculoskeletal disorders) and diabetes risk " clarified Odum's Chief Marketing Officer Johanna Varje in an email exchange.
"The application has two different sections to it: the prediction and the health exam. The prediction asks 10 questions and a machine learning algorithm calculates the risk of becoming ill (need to stay home from work and see a medical professional). Based on the result, the application guides the user to continue to a health exam completed within the app.
The user is asked about 10 different health factors (around 52 questions) and then receives personal results and feedback for each health factor " Varje continued.
The feedback is created by a multidisciplinary team of medical professionals, it may be positive and tell the user to keep up his/her good work, guide the user to make lifestyle changes or to see a medical professional (or if the user is already receiving treatment the feedback may tell