About HAPP

Preventive healthcare is transforming the healthcare approach and gaining importance day by day. The most important reason for that is preventive healthcare is easier, more painless and less costly than regular treatment process after the diagnosis. Regarding these reasons preventive healthcare leads to social & economical improvement to the society.

A today preventive healthcare application mostly requires regular visits to doctors. These visits are time consuming for both patients and doctors, and patients generally cannot find that time to go and do that visits. In these visits doctors only cover the physical states and biological values that are not enough.

Just as health encompasses a variety of physical and mental states, so do disease and disability, which are affected by environmental factors, genetic predisposition, disease agents, and lifestyle choices. Doctors are not capable of covering all environmental factors, genetic predisposition, disease agents and lifestyle choices. So there is a need for using all these multiple data sources and evaluating these data with high accuracy to achieve correct diagnosis. Especially predictive diagnosis, which can lead early phase treatments and a perfect appliance of preventive healthcare.

This is the point where HAPP (Health Analysis & Prediction Program) comes in. HAPP is a cloud application which gathers patient related information from multiple sources, analyze that information and make predictions to achieve preventive healthcare.

DESCRIPTION

Our application is a platform, which runs on a cloud server. This platform gathers patients' biological, environmental and social information and makes prudential diagnoses and risk analyses. Within this scope, our application unites the most important three factors:

1. Gathering information about the patients' life-styles and medical conditions from multiple sources.

Besides the gathered data from hospital records, patients' life-style will be determined by collecting data from multiple sources like social networks. For achieving a judgment with a fair degree of accuracy, this collected data will be synchronized with regular test findings, environmental and regional factors

2. Being a personalized & centralized host system.

Gathered data about a patient's life-style and medical history from multiple sources are personal. Because of that, medical history of the patients' family and general past experiences about the disease will be considered when making a diagnosis. By doing so, a specialized diagnose and treatment method can be offered to patient in addition to generic ones. Due to these data will be gathered on a central platform, which is our application, the communication between doctors, patients and even patient's relatives will become solid and easier.

3. Respecting patients' privacy and processing encrypted information.

Patient privacy is a sensitive and important ethical issue to consider. The violation rate is high in our country and we are lack of regulations to prevent this kind of behavior. For avoiding any kind of violation, our application will use personal data encrypted. Nobody except the right owners, even the admins of the platform will not be capable of display the data.