WIKAYA technology is a result of the significant advancement we have witnessed in the past several decades in understanding the causes of diseases, human behavior, and the machine learning capabilities. WIKAYA is a product of integrating state-of-the-art knowledge and implementation of two fields:
Prevention of chronic diseases has been focused by the healthcare service providers for a long time because of the potential huge impact it can have on the status of the population health and, consequently, on the cost of healthcare services.
While the causes of chronic diseases are mostly well known and can be identified even in advance, the main challenge remains the compliance of the population to the prevention guidelines, and in most cases, there is also a lack of awareness and knowledge to what needs to be done.
The preventions guidelines are usually very generic (healthy weight, healthy nutrition, a stop to smoking, physical activity, etc.) and mostly without any prioritization.
WIKAYA prevention is comprehensive and includes 3 areas:
- Lifestyle changes
- Screening tests
- Awareness content
In Phase I, WIKAYA focuses on Primary and Secondary prevention of the following diseases:
- Ischemic Heart Disease
- Lung Cancer
- Colon Cancer
- Breast Cancer
And later will include Stroke and Chronic Obstructive Pulmonary Disease- COPD.
WIKAYA platform helps in preventing these diseases, so it only applies to individuals without these chronic diseases.
In Phase II, WIKAYA will provide Tertiary prevention as well, e.g.- helping patients with chronic disease to better manage their disease and prevent complications.
The traditional approach of prevention begins with risk calculation, using evidence-based disease risk calculators that has been in use by physician for many years. The main weakness in this approach is that risk is composed of two groups of factors:
- Modifiable- those that the individual can change (nutrition, physical activity, smoking, etc.)
- Non-modifiable (age, sex, race, family history, etc.)
- Lifestyle Changes:
WIKAYA approach is summarized by the slogan “Think Prevention”, rather than risk. So we focus on the modifiable risk factors and measure the effort, not the result, since at the end of the day, this is what really matters when it comes to creating impact.
For example, if we have two individuals with different family history, age, and genetics, that they both exercise 3 hours a week, eat healthy, and do not drink alcohol. They can have different cholesterol levels since this can also be affected by genetics. So in terms of risk, they are different, but in terms of preventions, they perform the same operation. To make this easier, we created the Prevention score, which is a unique scoring system developed by WIKAYA to give a clear indication to the level of prevention effort each individual/user is making. The scoring is derived from risk calculation based on the Population Attribution Fraction while isolating the modifiable risk factors that will be the only factors to be included in calculating the Prevention Score. The recommendations for lifestyle changes are delivered based on the need to manage risk factors, and prioritized based on their impact (hence the scoring)
- Screening Tests:
Early detection of diseases can help, and in some cases, improve the outcome in terms of mortality and morbidity.
WIKAYA default recommendations for screening tests are based on the U.S. Preventive Services Task Force (USPSTF) recommendations (but can also be amended to comply with any other jurisdictional health organization.
- Awareness Content:
Health literacy has proven to be an important factor in the prevention of diseases in general and chronic diseases specifically. WIKAYA algorithms provide personally-customized health education content to improve awareness and help our users make appropriate health decisions. WIKAYA tests the knowledge of the individual periodically and updates the scoring accordingly.
II- Artificial Intelligence:
WIKAYA uses data algorithms to predict compliance to prevention recommendations and prioritize them accordingly.
There are several ways to achieve the target level of physical activity, users can go to the gym, work out at home, do morning walk, evening walk, do it daily or 3 times a week. And many other variations.
Our algorithms collect data through mobile devices (smartphone, wearable) analyze it, and calculate compliance probability for several forms of prevention recommendations to provide the recommendation with the highest probability (and the highest impact per the scoring system).