solutions and methodology
The information system of dHealth uses wearable devices, offered by carefully selected manufacturers, and provides a detailed analysis of health statuses using the data received from the devices.
We have carefully chosen smart devices from manufacturers whose specific products are best suited to collect all-day (24/7) health telemetry data. This selection process was based on the accuracy of biosensors, taking into account the standard measurement frequency, wearable comfort, battery capacity, data transfer convenience, price, distribution among the users, and more.
We deal with broad and detailed, all-day health telemetry data received from thousands of users. That takes up a lot of space, thus requiring Big Data-levels of database storage. By understanding the sensitivity and privacy of health data, we focus great attention on ensuring operational security and functionality.
The heart of our system is unique algorithms, which process data and use the latest achievements in artificial intelligence and machine learning, neural networks, deep learning algorithms and ensemble learning methods. dHealth operates in large data surroundings and uses specialized Big Data systems, which require non-standard solutions.
When algorithms detect connections between telemetry data and diseases in a large population of users, they assign each user to specialized risk groups, periodically updating an estimate of their suitability to the group, tracking the user’s “movement” in the particular group (up or down), and monitoring the status between individual groups (better or worse). When the “movement” of “going down” is recorded, an automatic recommendation on how to correct the appropriate health risk is immediately created and offered.
Output of the Results
The user interface not only displays stored telemetry data, but also provides early reports, health warnings, and, if necessary, recommendations from supervising doctors. The system interactively communicates with the user via e-mail or phone notifications, asking questions, reporting risks, and offering recommendations.
dHealth uses and maintains sensitive personal data from each patient, including bio-signals, health status, and direct notes from the patient. Our data and security governance protocols are based on state-of-the art techniques, as well as the highest health industry standards and best practices.
Medical Specialist’s Feedback
With dHealth, medical specialists are given a unique opportunity to monitor a greater number of patients. When our diligent algorithms detect anomalies in users’ health telemetry data, a notification is immediately issued to the appropriate health care professional. This enables them to evaluate the information, making adjustments or recommendations accordingly. The health care professional’s feedback is not only useful to the patient, but further helps our algorithms enhance and hone their future decisions.
We allow the user to enter telemetric data that is not registered by any wearable devices, such as pain, general complaints, and replies to the special periodic questionnaires. We allow the user to communicate with their supervising doctor directly through dHealth, speeding along care and better tailoring their care plan.
The dHealth system integrates easily with health care providers’ existing digital tools
dHealth is compatible with various wearable devices, smart scales, and blood pressure devices