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What is Reveleer?
Leverage the Reveleer platform to oversee every aspect of the medical record retrieval and review workflow alongside your dedicated team. You have the freedom to implement your initiatives with your personnel, while Reveleer stands ready to provide additional guidance and expertise whenever necessary. Our platform ensures you have complete visibility across the entire process. You can either manage your HEDIS® and risk adjustment efforts independently or enlist the support of Reveleer’s experienced specialists if desired. The platform allows you the flexibility to conduct a thorough medical record review or concentrate on particular stages of the workflow. With its robust reporting features, you can track your programs in real-time, keeping yourself informed about all changes, whether they relate to closed or outstanding gaps, match results, or non-match scenarios. In addition, the comprehensive reporting and chart history accessible through the platform streamline your outreach, collection, and review efforts, significantly boosting overall operational efficiency. This capability ensures that your team can swiftly adjust to evolving requirements while consistently upholding a high standard of accuracy and effectiveness during the review process. Additionally, the platform's user-friendly interface makes it easy for your team to navigate and utilize all features effortlessly.
What is Amazon Comprehend Medical?
Amazon Comprehend Medical is an NLP service designed to adhere to HIPAA standards, employing machine learning to extract health information from medical documents without necessitating any prior expertise in machine learning from its users. A vast amount of healthcare data is found in unstructured formats, such as physicians' notes, clinical trial reports, and patient histories. Relying on traditional, manual methods for data extraction is not only time-consuming but also prone to errors, as rule-based automation often fails to capture essential contextual details, resulting in incomplete data retrieval. This lack of reliability can significantly undermine the effectiveness of large-scale analytics, which are critical for advancements in the healthcare and life sciences industries, ultimately impeding potential enhancements in patient care and operational effectiveness. By utilizing this sophisticated service, healthcare organizations can gain invaluable insights and improve their decision-making capabilities, ultimately leading to better outcomes for patients. This transformative approach represents a significant leap forward in how health data can be leveraged for greater efficiency and efficacy in medical practices.
Integrations Supported
AWS AI Services
AWS App Mesh
Amazon Comprehend
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Reveleer
Date Founded
2009
Company Location
United States
Company Website
www.reveleer.com
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/comprehend/medical/
Categories and Features
Categories and Features
Data Extraction
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Natural Language Processing
Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization