Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Kymolog serves as a comprehensive platform for integrating medical device data and facilitating research, catering to hospitals, medical device manufacturers, and research teams alike. Its innovative edge agent aggregates data from various devices such as continuous glucose monitors, ECG monitors, pulse oximeters, blood-pressure monitors, and thermometers, transforming these readings into FHIR R4 Observations that include essential details like LOINC codes, UCUM units, device identifiers, and timestamps. The system aligns these readings with specific patients and encounters by utilizing bed or device assignments, seamlessly transferring the information to a hospital's existing electronic health record (EHR) system via either FHIR R4 or an HL7 v2 interface engine. Additionally, the gathered data can be preserved in a dedicated research repository, maintaining its device and time provenance for use in clinical studies and post-market evidence gathering. Kymolog's flexible architecture allows it to operate on-site, within a hospital-managed private cloud, or through the cloud infrastructure of device manufacturers; it also offers an optional hosted research store for de-identified data. Furthermore, users have the ability to configure device classes that extend beyond the pre-established mappings provided by the platform, enhancing its adaptability for various research needs. This versatility ensures that Kymolog can meet the evolving demands of healthcare data integration and research methodologies as they advance.
Description
Data schemas define the structure and content of various types of information, such as blood glucose levels, influencing how software applications manage that information. Often, systems must accommodate data from multiple devices or platforms, each presenting information in its own unique way. When all data related to a specific metric, like blood glucose, adheres to a unified schema, it becomes significantly easier to analyze and interpret that information, regardless of its original source. A standardized schema acts as a consistent point of reference for documentation, facilitating the use of data points across different contexts. In the realm of healthcare, the importance of common data schemas is magnified due to the intricate nature and significance of health-related information. For instance, recognizing the difference between fasting and non-fasting blood glucose levels is crucial for accurate clinical interpretation and decision-making. This shared understanding ensures that healthcare professionals can communicate effectively and make informed decisions based on reliable data.
API Access
Has API
Yes
API Access
Has API
No
Screenshots View All
No images available
Integrations
MEDITECH Expanse
Yes
Oracle Health
Yes
Veradigm EHR
Yes
eClinicalWorks
Yes
Integrations
MEDITECH Expanse
No
Oracle Health
No
Veradigm EHR
No
eClinicalWorks
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Saga IT
Founded
2016
Country
United States
Website
kymolog.com
Vendor Details
Company Name
Open mHealth
Country
United States
Website
www.openmhealth.org