Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Utilize Amazon Comprehend Medical to derive insights from unstructured data, facilitating efficient search and query processes. Forecast health-related trends through Amazon Athena queries, alongside Amazon SageMaker machine learning models and Amazon QuickSight analytics. Ensure compliance with interoperable standards, including the Fast Healthcare Interoperability Resources (FHIR). Leverage cloud-based medical imaging applications to enhance scalability and minimize expenses. AWS HealthLake, a service eligible for HIPAA compliance, provides healthcare and life sciences organizations with a sequential overview of individual and population health data, enabling large-scale querying and analysis. Employ advanced analytical tools and machine learning models to examine population health patterns, anticipate outcomes, and manage expenses effectively. Recognize areas to improve care and implement targeted interventions by tracking patient journeys over time. Furthermore, enhance appointment scheduling and reduce unnecessary medical procedures through the application of sophisticated analytics and machine learning on newly structured data. This comprehensive approach to healthcare data management fosters improved patient outcomes and operational efficiencies.
Description
ZSegment is an innovative cloud-native interface engine developed by 314e Corporation, tailored to effortlessly link and unify clinical, financial, and administrative systems within healthcare organizations. With an impressive array of over 300 components, it facilitates real-time metrics grounded in open telemetry standards and is built on a Kubernetes-native framework utilizing Apache Camel to provide scalability, adaptability, and user-friendly customization options including version control (Git) and native custom schema support for HL7 v2, FHIR, X12, and CCD. Additionally, it boasts visual tools for message routing, Groovy scripting for data transformations, and secure message delivery through various protocols such as File, FTP, HTTP(S), and TCP. The platform also includes features like message indexing, tracing, editing/resubmission capabilities, and the ability to define custom jobs for data hygiene and operational oversight. As a modern alternative to traditional on-premise interface engines like Mirth Connect, ZSegment helps organizations reduce hardware procurement expenses and high licensing fees, making it a cost-effective solution for enhancing interoperability in healthcare systems. Furthermore, its cloud-native design means that organizations can quickly adapt to evolving demands without the constraints of legacy infrastructure.
API Access
Has API
No
API Access
Has API
No
Integrations
AWS AI Services
Yes
Amazon Athena
Yes
Amazon QuickSight
Yes
Amazon SageMaker
Yes
Amazon Web Services (AWS)
Yes
Apache Camel
No
Apache Groovy
No
Git
No
Kubernetes
No
Mirth Connect
No
Integrations
AWS AI Services
No
Amazon Athena
No
Amazon QuickSight
No
Amazon SageMaker
No
Amazon Web Services (AWS)
No
Apache Camel
Yes
Apache Groovy
Yes
Git
Yes
Kubernetes
Yes
Mirth Connect
Yes
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
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
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)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/healthlake/
Vendor Details
Company Name
314e Corporation
Founded
2004
Country
United States
Website
www.314e.com/zsegment/