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Tennr

Free App

AI-powered healthcare document automation platform

Document automation
Data extraction
Referral processing
Patient scheduling

About Tennr

Launched Sep 12, 2024

Categories

Industry :

Healthcare

Website

Description

AI-powered healthcare document automation platform

Tennr is an advanced AI platform designed to streamline healthcare paperwork processing. It uses a sophisticated document reasoning model, RaeLLM™ 7B, trained on over 3 million healthcare documents to automate tasks like referral processing, patient scheduling, and data extraction from faxes and other paperwork.
Tennr website

Tennr Key Features

  • AI-POWERED DOCUMENT PROCESSING, AUTOMATED REFERRAL MANAGEMENT, EHR INTEGRATION, PATIENT COMMUNICATION AUTOMATION, INSURANCE VERIFICATION, PRIOR AUTHORIZATION HANDLING, DATA EXTRACTION AND DIGITIZATION

Tennr Use Cases

  • STREAMLINING REFERRAL WORKFLOWS, REDUCING ADMINISTRATIVE BURDEN, IMPROVING PATIENT ONBOARDING, ENHANCING BILLING ACCURACY, ACCELERATING INSURANCE PROCESSES

Pros

  • Streamlines healthcare paperwork processing, saving time and reducing manual effort.
  • Utilizes RaeLLM™ 7B, a sophisticated document reasoning model which enhances accuracy in automation tasks.
  • Capable of automating various tasks such as referral processing, patient scheduling, and data extraction from faxes and other paperwork.
  • Trained on a large dataset of over 3 million healthcare documents, ensuring comprehensive understanding and reliability.
  • Improves efficiency in healthcare settings by reducing administrative burden.

Cons

  • Potential issues with data privacy and security, as sensitive healthcare information is involved.
  • May require integration with existing systems, which could be complex and time-consuming.
  • Initial setup and training for healthcare providers might be necessary to fully utilize the app's features.
  • Depending on the AI model, there could be occasional errors or inaccuracies that need manual verification.
  • Relies on the quality and diversity of the training dataset, which might affect performance in different healthcare contexts.

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