iDFax: AI-Powered Software for Healthcare Fax Management

UTHealth creators have utilized artificial intelligence (AI) to create a software tool that is integrated with existing electronic health records (EHR) systems to automate medical fax management, resulting in a 3.6x reduction in fax processing time or 60k hours compared to legacy systems. Efficiency in time and money on this task helped conserve resources so billing providers could see more patients. iDFax has been launched at UTHealth clinics, integrated with EHR, and has processed over 1.5 million faxes to date.

Current Challenges with Fax Processing

Despite advances in interoperability and EHR usage, healthcare organizations still rely on fax to share critical medical information such as referrals, prescriptions, and authorizations. The existing fax processing workflow is highly manual, with data entry, indexing, and search all requiring direct action from clinical staff. There is no commercially available, automated and secure solution on the market that can alleviate workforce strain and maximize efficiency and outcomes.

Introducing: iDFax

UTHealth creators have developed iDFax, a cloud-based, HIPAA-compliant AI solution that helps healthcare enterprises save time, reduce workforce strain, and improve patient care, through instant and automatic fax document processing. iDFax reduces human processing time by 3.6x leveraging AI-powered automation of manual tasks, supporting expedited referrals and improving patient care. iDFax is built to support healthcare enterprises, with HIPAA-compliant technology, a user-friendly software, and secure integration with existing IT infrastructure. iDFax automatically extracts physician name, patient name, and patient date of birth while identifying document type. iDFax also automatically retrieves and links patient records from EHR if they exist, only requiring verification of important details.

Technology Differentiators

• Secure Integration: iDFax is HIPAA-compliant and fully integrated with EHR/legacy system for log and records management.

• Increased Accuracy: iDFax trains on local data, supporting accurate transcription and reducing potential manual errors associated with this process.

• AI-Powered Backend: iDFax has the AI capability to improve image quality in terms of distortion, contrast, and rotation as well as to detect tables, tabular data, handwriting, and named entities with over 95% accuracy. It also includes built-in GPT Chat for fax documents.

• Resulting in 60k hours of time saving on 1.5 million faxes, a 3.6x reduction in fax processing time at currently deployed sites

• Complete Automation Features: iDFax capabilities include auto-splitting, de-duplication, custom filters and keyword search, real-time analysis and reporting, and E-Signature.

Key Outcomes

iDFax reduces fax processing time by at least 3.6x or 60k hours of time saving on 1.5 million faxes at currently deployed sites.

Intellectual Property Status

Available for licensing

About the Creators

Martin J. Citardi, MD

Vice Dean for Clinical Technology

Chair of Otorhinolaryngology-Head & Neck Surgery

Xiaoqian Jiang, Ph.D.

Associate VP for Medical AI, Chair of Department of Health Data Science and Artificial Intelligence

Professor in Biomedical Informatics and Bioengineering

Jiajie Zhang, Ph.D.