Navaneeth Nair, Chief Product Officer at Infinx Healthcare, has provided insights into how the company sees the role of technology and AI in modern healthcare finance. Infinx has been developing automated, cloud-based revenue cycle management (RCM) solutions for nearly a decade and has evolved a platform that aims to streamline tasks, provide smart automation, and integrate easily with existing customer systems.
Initially focussing on prior authorization in revenue cycles, Infinx integrated human input with technology to facilitate more effective RCM. This approach integrated mundane tasks with AI to reduce the necessity for human input, with manual intervention retained for important clinical and healthcare regulatory decisions.
Infinx also created a standalone Revenue Cycle Automation platform, providing customers with a range of pre-built automation options. The company recognized the value of a platform that can self-adapt and improve over time, harnessing extensive data for continuous improvement and development of more intelligent AI functionality.
To decode healthcare payer behavior, machine learning has been used to handle tasks previously conducted with manual rules. The technology adapts to changes in payer policies and decisions, increasing accuracy and responsiveness. AI has been used to manage unstructured data prevalent in revenue cycle processing, with document capture technologies developed for more effective and reliable data processing.
The Infinx Patient Access Plus platform demonstrates the ability for continuous learning, with the AI improving with each processed prior authorization request. The system helps determine the need for prior authorization, predicts turnaround times, and identifies potential information gaps to improve efficiency. Predictive analytics are used to adapt to payer behavior and policy changes and to optimize claim submissions to prevent denials.
Infinx’s own data analytics software converts data into actionable information. It provides better insights across all revenue cycle stages for more data-driven decisions. Intelligent workforce management has also been integrated into the platform, using algorithms to identify resource needs and efficiently assign and regulate work.
Looking ahead, Infinx looks to further integrate AI, automation, and human collaboration into healthcare systems. This approach aims to improve healthcare system efficiency and patient care by reducing human errors, data siloes, and discrepancies caused by legacy systems. As AI and machine learning-led solutions gain momentum in healthcare, Infinx remains committed to its central belief that the integration of technology and human collaboration can create a more effective, patient-centric healthcare system.
