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Current Artificial Intelligence Uses in LUGPA Urology Practices

Gary Lloyd | Nov 10,26 | 01:31 EST

Technology

Artificial intelligence is changing the healthcare landscape across medicine disciplines. A LUGPA panel discussed how AI is currently being used across urology practices.

Ambient Scribe Technologies Ambient scribes are AI-powered tools designed to listen to clinician-patient conversations and create structured clinical notes, significantly reducing the manual documentation burden on physicians. This technology helps mitigate burnout and dissatisfaction among healthcare professionals. Beyond basic transcription, some ambient scribe platforms can offer clinical suggestions, such as recommending diagnosis codes, and can even post orders directly into the electronic medical record system. Dr. Alexander Epelbaum, a market president at Integrated Medical Professionals and a practicing urologist, has been a key figure in implementing ambient documentation into daily clinic operations. He emphasizes that the ideal use of AI in this context is as a 'silent partner' that supports clinicians without disrupting their existing workflows. Dr. Epelbaum's initiative led to the launch of ambient scribe technology across the entire New York market after a successful pilot phase. Within just three months of its launch, the system generated 44,000 notes, representing over 4000 hours of transcription time saved. Despite the automation, Dr. Epelbaum stresses that clinicians retain full responsibility for the content and accuracy of the notes. He advises that AI cannot make assumptions, meaning all pertinent information must be explicitly stated by the clinician for it to be accurately captured in the generated notes. Agentic AI Agentic AI represents a significant advancement in artificial intelligence, moving beyond single-task solutions to systems capable of autonomously executing complex instructions. Jared Olafsson, the business operations manager at Urology San Antonio in Texas, highlighted this evolution, noting that users can now dictate tasks to AI and have it build solutions independently. As an example, he mentioned using Claude Code to develop a physician call schedule manager. This system intelligently analyzes historical holiday and weekend data to ensure fairness in scheduling, demonstrating AI's ability to handle intricate, data-rich, and rule-based problems effectively. Olafsson underscored that AI excels in environments characterized by abundant data and well-defined rules. His practice currently employs agentic AI in their call center through speech-to-speech models. This implementation allows an AI agent to immediately answer every incoming call, efficiently routing it to the appropriate department or individual. This application not only streamlines call management but also aims to reduce caller wait times and mitigate frustration often associated with navigating traditional multi-level phone trees. Given the rapid pace of AI development, with capabilities expanding two to three times every six months, Olafsson cautioned against entering into long-term technology agreements. He also stressed the importance of thoroughly understanding a problem before prematurely seeking an AI solution, advocating for a cautious and well-informed approach to AI adoption. AI App Creation Dr. Daoud Dajani, Chief Medical Officer at Chesapeake Urology in Maryland, shared his experience in leveraging AI for internal practice improvements. He utilizes AI to create constructive feedback and practical suggestions for his clinic staff. Specifically, Dr. Dajani employed Replit to build a custom platform that processes and analyzes patient survey data. This platform is designed to identify recurring themes and insights from patient feedback, subsequently generating personalized advice for staff members on areas where they can enhance their performance and patient care. Future AI Tools? During the panel discussion, a significant area of interest emerged regarding the prospective applications of AI in revenue cycle management for urology practices. It was envisioned that within the next few years, AI tools could autonomously handle complex tasks such as medical coding, effectively identify patterns leading to claim denials, and manage the generation of automatic denial letters. Furthermore, a highly anticipated development is the potential for AI agents to autonomously process prior authorization requests. This would involve AI systems thoroughly analyzing patient records and communicating directly with insurance companies. If such capabilities become fully realized, the typically lengthy prior authorization process, which can currently take weeks, could be dramatically reduced to a mere few minutes, representing a transformative efficiency gain for healthcare administration.

Ambient Scribe Technologies

Ambient scribes are AI-powered tools designed to listen to clinician-patient conversations and create structured clinical notes, significantly reducing the manual documentation burden on physicians. This technology helps mitigate burnout and dissatisfaction among healthcare professionals. Beyond basic transcription, some ambient scribe platforms can offer clinical suggestions, such as recommending diagnosis codes, and can even post orders directly into the electronic medical record system. Dr. Alexander Epelbaum, a market president at Integrated Medical Professionals and a practicing urologist, has been a key figure in implementing ambient documentation into daily clinic operations. He emphasizes that the ideal use of AI in this context is as a 'silent partner' that supports clinicians without disrupting their existing workflows. Dr. Epelbaum's initiative led to the launch of ambient scribe technology across the entire New York market after a successful pilot phase. Within just three months of its launch, the system generated 44,000 notes, representing over 4000 hours of transcription time saved. Despite the automation, Dr. Epelbaum stresses that clinicians retain full responsibility for the content and accuracy of the notes. He advises that AI cannot make assumptions, meaning all pertinent information must be explicitly stated by the clinician for it to be accurately captured in the generated notes.

Agentic AI

Agentic AI represents a significant advancement in artificial intelligence, moving beyond single-task solutions to systems capable of autonomously executing complex instructions. Jared Olafsson, the business operations manager at Urology San Antonio in Texas, highlighted this evolution, noting that users can now dictate tasks to AI and have it build solutions independently. As an example, he mentioned using Claude Code to develop a physician call schedule manager. This system intelligently analyzes historical holiday and weekend data to ensure fairness in scheduling, demonstrating AI's ability to handle intricate, data-rich, and rule-based problems effectively. Olafsson underscored that AI excels in environments characterized by abundant data and well-defined rules. His practice currently employs agentic AI in their call center through speech-to-speech models. This implementation allows an AI agent to immediately answer every incoming call, efficiently routing it to the appropriate department or individual. This application not only streamlines call management but also aims to reduce caller wait times and mitigate frustration often associated with navigating traditional multi-level phone trees. Given the rapid pace of AI development, with capabilities expanding two to three times every six months, Olafsson cautioned against entering into long-term technology agreements. He also stressed the importance of thoroughly understanding a problem before prematurely seeking an AI solution, advocating for a cautious and well-informed approach to AI adoption.

AI App Creation

Dr. Daoud Dajani, Chief Medical Officer at Chesapeake Urology in Maryland, shared his experience in leveraging AI for internal practice improvements. He utilizes AI to create constructive feedback and practical suggestions for his clinic staff. Specifically, Dr. Dajani employed Replit to build a custom platform that processes and analyzes patient survey data. This platform is designed to identify recurring themes and insights from patient feedback, subsequently generating personalized advice for staff members on areas where they can enhance their performance and patient care.

Future AI Tools?

During the panel discussion, a significant area of interest emerged regarding the prospective applications of AI in revenue cycle management for urology practices. It was envisioned that within the next few years, AI tools could autonomously handle complex tasks such as medical coding, effectively identify patterns leading to claim denials, and manage the generation of automatic denial letters. Furthermore, a highly anticipated development is the potential for AI agents to autonomously process prior authorization requests. This would involve AI systems thoroughly analyzing patient records and communicating directly with insurance companies. If such capabilities become fully realized, the typically lengthy prior authorization process, which can currently take weeks, could be dramatically reduced to a mere few minutes, representing a transformative efficiency gain for healthcare administration.