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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

Established in Chicago, Illinois, PatientIQ provides a platform for healthcare providers, medical device manufacturers, life sciences companies, and payers to enhance their practices through data-driven medicine. It is recognized as the largest collaborative platform for healthcare professionals aimed at improving patient outcomes. By equipping healthcare providers with cutting-edge technology, PatientIQ fosters a culture of data-driven medical practice. In the competitive landscape of the U.S. healthcare market, all parties involved face mounting pressure to demonstrate their value effectively. A key factor in determining "value" lies in the objective measurement of patient outcomes. However, quantifying these outcomes presents challenges that are costly, complex, and fraught with technological obstacles. Despite these difficulties, outcomes represent the most significant currency in the future of value-based healthcare. Thus, a clear and reliable solution to systematically measure, analyze, and benchmark outcomes among various stakeholders presents a significant opportunity for growth in the digital health sector. As the industry evolves, the need for such innovative solutions will only become more pronounced.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS AI Services Yes 
AWS App Mesh Yes 
Amazon Comprehend Yes 
Care Director No 
EPIC HRMS No 
Intergy EHR No 
MEDITECH BCA No 
NextGen Healthcare EHR No 
Oracle Health Population Health Management No 
athenaClinicals No 
eClinicalWorks No 

Integrations

AWS AI Services No 
AWS App Mesh No 
Amazon Comprehend No 
Care Director Yes 
EPIC HRMS Yes 
Intergy EHR Yes 
MEDITECH BCA Yes 
NextGen Healthcare EHR Yes 
Oracle Health Population Health Management Yes 
athenaClinicals Yes 
eClinicalWorks 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) Yes 
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) Yes 
In Person Yes 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/comprehend/medical/

Vendor Details

Company Name

PatientIQ

Country

United States

Website

www.patientiq.io/about

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 

Product Features

Electronic Data Capture

Audit Trail No 
CRF Tracking No 
Data Entry No 
Data Verification No 
Distributed Capture No 
Document Imaging No 
Document Indexing No 
Forms Management No 
Remote Capture No 
Study Management No 

Patient Engagement

Appointment Scheduling No 
Care Planning No 
Collaboration No 
Messaging No 
Mobile Access No 
Patient Education No 
Patient Portal No 
Personal Health Record No 
Progress Tracking No 
Self Management No 

Alternatives

Alternatives

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