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What is Crosby Health Apollo?

Many healthcare professionals depend on Apollo by Crosby Health to develop, submit, and track appeals, which significantly eases the pressure associated with clinical denials. Demonstrating an advanced grasp of clinical scenarios, Apollo surpasses all other medical language models across critical performance indicators. Its targeted training enables it to handle a variety of billing functions with remarkable precision, including auditing, charge capture, and denial management. Recognized as the swiftest clinical language model on the market, it features the most extensive context length, producing outputs at an astounding rate of 60 words per second while managing documents as lengthy as 300 pages. Our AI meticulously crafts persuasive appeal letters for each denial, optimizing the potential for recovery through carefully constructed arguments. By integrating various payor portals and fax numbers into one cohesive platform, Apollo streamlines both the submission and tracking processes for every appeal. Additionally, it alleviates the workload for providers by automating the appeal creation, and it is proficient in identifying medical necessity within documentation. With just a single click, providers can effortlessly submit appeals to any insurance company. This cutting-edge solution not only simplifies the workflow but also significantly boosts the overall effectiveness of healthcare administration, ensuring that providers can focus more on patient care rather than administrative hurdles. Overall, Apollo revolutionizes the appeals process, marking a significant advancement in healthcare technology.

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.

Media

Media

Integrations Supported

AWS AI Services
AWS App Mesh
Amazon Comprehend
EPIC HRMS
MEDITECH Expanse
Net Health Employee Health
Oracle Health Population Health Management

Integrations Supported

AWS AI Services
AWS App Mesh
Amazon Comprehend
EPIC HRMS
MEDITECH Expanse
Net Health Employee Health
Oracle Health Population Health Management

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

Crosby Health

Company Location

United States

Company Website

www.crosbyhealth.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

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