Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
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
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
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