In recent years, the world has seen a tremendous amount of growth in aging population. To accommodate this population in time of very hectic and demanding lifestyles of the patients, healthcare providers are adopting various cloud and web-based solutions which are helping the providers and patients to bring the healthcare services at home. Such services are proving to be highly successful in various parts of the world.
The service providers can easily connect with patients suffering from diseases like depression, chronic diseases, diabetes, hypertension and other chronic diseases via eTelehealth solution from their facility. Physicians can ask basic questions and follow-ups.
eTelehealth is useful for growing number of elderly patients who can’t travel, patients from remote locations, house mothers and very busy professional who can’t visit the doctor due to busy schedules.
LANTIX offers eTelehealth solution which is an extended version of its eMED solution. This provides a complete end-to-end secure solution to the service providers.
Providers can track, monitor, alter and manage chronic disease patients from a single system. Patients can also manage to track their health through the system in real-time.
The system is configured to work with various connected devices like glucose monitors, Electronic scales, blood pressure cuffs, sleep monitoring devices and pedometers.
LANTIX makes all the collected data readily available to the caregiver to make an informed decision.
Physicians can review all the data along with patient history in a single system as part of their visit which can help the physicians to diagnose the medical condition and manage medicine accordingly.
LANTIX can also integrate video solution which can help the physicians to make an interactive communication with their patients.
LANTIX Can Provide Resources
PYTHON And R Developers
Lantix Can Provide Services
DM and ER modeling As a Service
Co-colated OLTP and OLAP data warehouse design and solution implementation
Dimentional Modeling for ETL engine
Hadoop based Data Lake Design