Developing a machine-learning algorithm to identify those people with a higher risk of not improving their risk factors could save lives and reduce the cost of cardiovascular diseases.
Ibermutua is mutual insurance company, partner with the Social Security at national level in Spain. It provides an assistance network to about 120 own centers and more than 1,000 concerted distributed throughout the country. The services provided:
- Comprehensive protection in the coverage of professional risks: occupational accident and illness and prevention of occupational hazards and improvement of working and health conditions in companies.
- Temporary Disability Management (work leave) due to common illness and non-work accident.
- Protection for cessation of activity of self-employed or self-employed workers.
Ibermutua protects a working population of more than 1,000,000 people, half of them attend periodic medical check-ups every year. We have observed that some workers with cardiovascular risk factors and high global cardiovascular risk do not improve their profile over the years and even worsen it despite the recommendations of lifestyle changes and pharmacological treatment. In contrast, there are other patients who improve their cardiovascular risk factors and also maintain that improvement over time and their health doesn’t decline again. Developing a machine-learning algorithm to identify those people with a higher risk of not improving their risk factors could save lives and reduce the cost of cardiovascular diseases.
The challenge has the following sample datasets available for download
- Checkup: Personal cardiovascular history, cardiovascular risk factors, cardiovascular risk profile, lifestyles, health cost reduction, safe life
- Duration of sick leave, morbimortality, diagnoses, complementary tests
Ibermutua has more than 4 million medical examinations of more than 3 million workers, who undergo a medical check-up every year, from 2005 to 2018. Additionally, it has data of morbimortality during the period.
Ibermutua expects to have an accurate predictive model that will help them to identify those people with a higher risk of not improving their risk factors and therefore be able to incorporate greater specific actions aimed at increasing control of cardiovascular risk factors, reducing mortality and saving the costs associated with this type of disease, which is the first cause of global mortality. Healthcare professionals would account with an application that, in the context of their clinical visit, could identify the patient’s profile (poor compliance, medium compliance, high compliance) and generate specific recommendations which would be adapted to each profile, periodicity and factors that are contributing to the treatment follow-up, etc. Ibermutua expects to decrease mortality, increase the better control of cardiovascular risk factors and their associate costs. The improvement in cardiovascular risk profile due to better control of cardiovascular risk factor is also translated into a very important aspect, as it is the duration and cost of sick-leave absent that will reduce very significantly the direct and indirect cost.