Data-Driven Telehealth Billing Model for Secure Messaging

 

2025-006
   
Technology Overview

The rapid rise of secure messaging (SM) as a telehealth service has transformed patient-provider communication, offering convenience, continuity of care, and expanded access. However, the traditional billing model has become increasingly outdated, especially with the introduction of generative AI, which reduces the time required to review and respond to messages. This has created a critical need for a more data-driven reimbursement system.

Current time-based billing fails to reflect the complexity of clinical inquiries, or the effort required to navigate electronic health records (EHR) in crafting appropriate responses. Moreover, this system lacks transparency, leaving patients uncertain about potential charges and posing risks to engagement, access, and health equity. 

Background

Invented by Dr. Dong-Gil Ko and collaborators at the University of Cincinnati, this novel Fee-for-Complexity-and-Time (FFCT) model introduces a revolutionary approach to SM billing. Drawing on machine learning and a knowledge management framework, the technology captures and analyzes providers’ EHR interaction patterns, measuring both the breadth and depth of information research in response to patient messages. This model provides proven predictive accuracy significantly surpassing current methods, directly aligning clinical complexity with reimbursement.

Advantages and Benefits
  • AI-Compatible Billing
  • Objective and Scalable
  • Improves Fairness and Transparency
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Patents
Serial No. File Date Patent No. Issued Date
Other Media
Inventor(s)
  • Dong-Gil Ko
Contact
Madison Bourbon
Sr. Licensing Associate, Physical Sciences
Lead Inventor