A.I. Population Health Management Platform
Interoperability in healthcare
Medlytics leverages AI to standardize data for all healthcare systems, enabling interoperability in healthcare, value-based population health management, & precision health.
Our solution produces the ability to query patient information far faster, and much more accurate, than any front-end FHIR API. This helps physicians reduce the time spent looking at a computer screen, while providing patient data in near-real-time. We do the hard work on the back-end, so physicians can do the critical work on the front-end.
We’ve created the first true value-based, interoperability driven, population health management platform Medlytics' AI population health management platform is built to ingest petabytes of data leverages natural language processing to extract and transform unstructured data.
Our solution creates FHIRv4 profiles of your patient population. Get a 360 view of each patient, showcasing their individual longitudinal health record.
The ability to transform existing health care data into the new standard (FHIR), will spark innovation and yield better patient outcomes. Our technology is strategically built to implement and comply with the standards set forth by Health level 7, FHIR v4.0.1, and the US Core Implementation Guide v3.1.0.
360 VIEW OF EACH PATIENT IN YOUR PATIENT POPULATION | LONGITUDINAL HEALTH RECORD
Integrated care dELIvery powered by medlytics
360 VIEW OF EACH PATIENT IN FHIRv4 FORMAT
We enable data flow for your disparate data silos, giving you a complete picture of each patient's information in one location. Our solution provides updates in near-real-time and ensures both accuracy and efficiency. Harmonize your data for interoperability with MedltyicsAi. Our solution is built around FHIRv4.
REAL-WORLD PICTURE OF PATIENT JOURNEY, TREATMENT PATHWAYS, AND HEALTH OUTCOMES
INTEROPERABILITY IN HEALTHCARE
- The creation of patient journeys for specific diseases stages and finding probability at each stage.
- Determining high utilizers across multiple years (a classification problem).
- Forecasting census for operations reporting.
- Members at risk of churn.
- Member who are delaying care because of financial consideration.
- Operational throughout optimization.
- Members benefit from earlier intervention to prevent decline in health or identification of members at risk of readmissions.