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features
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support

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Description

Amazon Comprehend Medical is a natural language processing (NLP) service compliant with HIPAA that leverages machine learning to retrieve health information from medical texts without requiring any prior machine learning expertise. A significant portion of health data exists in unstructured formats such as physician notes, clinical trial documentation, and patient medical records. The traditional approach of manually extracting this data is labor-intensive and inefficient, while automated methods based on strict rules often overlook crucial contextual details, leading to incomplete data capture. Consequently, this limitation results in valuable information remaining untapped for large-scale analytical efforts that are essential for progressing the healthcare and life sciences sectors, ultimately impacting patient care and operational efficiencies. By addressing these challenges, Amazon Comprehend Medical enables healthcare professionals to harness their data more effectively for better decision-making and innovation.

Description

Our platform fosters consistency, continuity, and scalability throughout our interconnected portfolio, allowing customers to enhance their operational efficiency, make informed decisions, and achieve better patient outcomes while driving innovation in our evolving healthcare system. By leveraging advanced data and analytics alongside patient engagement and collaboration tools, the Change Healthcare platform empowers both providers and payers to streamline workflows, obtain the necessary information precisely when needed, and ensure the delivery of the safest and most appropriate clinical care possible. We facilitate seamless access to data and promote interoperability among various data sources, thereby supporting CMS patient access and interoperability regulations, which ultimately leads to real-time access to clinical documents. This approach is instrumental in managing risk adjustment effectively, boosting HEDIS scores, and ensuring timely and precise payments through quicker adjudication. Furthermore, our commitment to innovation positions us to adapt to the changing landscape of healthcare while continually improving the services we offer.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS AI Services Yes 
AWS App Mesh Yes 
Amazon Comprehend Yes 
InvisaClaim No 
Novari Health No 
Owl Practice No 
Vetriq No 

Integrations

AWS AI Services No 
AWS App Mesh No 
Amazon Comprehend No 
InvisaClaim Yes 
Novari Health Yes 
Owl Practice Yes 
Vetriq 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) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
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

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/comprehend/medical/

Vendor Details

Company Name

Change Healthcare

Founded

2007

Country

United States

Website

www.changehealthcare.com

Product Features

Data Extraction

Disparate Data Collection No 
Document Extraction No 
Email Address Extraction No 
IP Address Extraction No 
Image Extraction No 
Phone Number Extraction No 
Pricing Extraction No 
Web Data Extraction No 

Natural Language Processing

Co-Reference Resolution No 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing No 
Part-of-Speech Tagging No 
Sentence Segmentation No 
Stemming/Lemmatization No 
Tokenization No 

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