Our 2024 AI Wrap-Up reflects on our key insights and best practices this year while driving AI transformation in healthcare. In this edition, we hear from CodaMetrix CEO and President Hamid Tabatabaie, Chief Customer Officer Tara Bradley, and Chief Technology Officer Chris Gervais as they share their expertise on selecting, implementing, and optimizing healthcare AI solutions.
AI has incredible long-term potential to revolutionize clinical decision-making and workflows, but most clinical use cases require rigorous validation and thoughtful implementation before they can truly impact patient care. The debate now is about balancing investment in long-term transformation with more immediate, tangible benefits.
In contrast, AI's role in reducing administrative waste and burdens is already here. At a time when providers are overwhelmed by administrative complexity, labor shortages, and cost pressures, AI-driven automation offers real, immediate solutions. Whether it’s in medical coding, revenue cycle management, or operational efficiency, AI can streamline processes, reduce errors, and free up time for clinical staff to focus on patient care.
The most realistic and impactful role for AI in the near term is in transforming administrative functions. Moving forward, we should temper clinical expectations and focus on AI's practical applications today.
In my work leading AI implementation in health systems, I’ve seen firsthand how it transforms the organization—optimizing resources, improving financial outcomes, and giving time back to physicians. I’ve learned that the key to achieving long-term success with your autonomous coding strategy lies in thinking holistically, rather than focusing on isolated problems.
Many health systems are cautious and judicious with their data sharing – an understandable impulse – but AI thrives on ample data. Good machine learning models require data about what happened at a particular visit as well as the contextual data that supports the visit. It’s important to help partners understand the value of sharing as much data as possible in a meaningful and secure way.
Health systems often underestimate how quickly our solutions can be implemented into their systems, but also the layers of technical integrations needed to do so. By answering the most foundational questions from the get-go, establishing technical resources and getting data permissions in place immediately upon contract signing, the implementation can be sped up, with cases automating in less than three months.
Change management can be an obstacle when adopting an AI-based platform and shouldn’t be an afterthought. Rather than leave it to partners, we have processes in place guided by previous experience to help prioritize transparency and address any feelings of uncertainty that may arise.
This time of year offers an opportunity to reflect on the accomplishments shared with the health systems CodaMetrix is proud to call partners. It’s also a time for leaders and professionals across health information management, technology, and business to collaborate on ways to optimize and advance AI, recognizing the progress made and the work still ahead.
By producing clinically comprehensive code sets, improving revenue cycle management outcomes is just the tip of the iceberg. This rich data can inform clinical research and improve patient care plans, ultimately transforming the health system’s coding workflows.
Automation enables coders to focus on more complex cases, while routine tasks are streamlined, reducing costs and improving speed across health systems. As an added benefit, the AI models undergo rounds of optimization by learning from human coding activity. This continuously improves coverage and accuracy, while ultimately increasing the speed of claim submission.
As understanding and confidence builds in the advantages AI offers, providers and their staff will be able to utilize their time differently. That’s a future that should appeal to revenue cycle managers, providers and patients alike.
As we close out 2024, we reflect on the progress made and the lessons learned in advancing AI in healthcare. Each step forward brings us closer to a more efficient, innovative future. Together with our partners, we remain committed to learning, growing, and making a lasting impact. That’s a wrap!
