In our recent fireside chat with Stephen Mallinak, President and General Manager of Provider at Datavant, and Christine Cunningham, Director of Health Information Management at UW Health, Madison WI, we explored how AI is reshaping medical coding and HIM. Rather than replacing professionals, AI augments their work automating routine tasks, improving accuracy, and even providing real-time insights for staffing and patient care. The future of healthcare lies in this partnership between human expertise and AI-driven efficiency.
You said AI isn’t going to take over healthcare — what about the administrative side of healthcare, such as coding and support?
While AI has significant potential to transform administrative functions in healthcare, including coding and operational support, it will not "take over" healthcare in its entirety. Healthcare is inherently complex, involving clinical judgment, empathy, and nuanced decision-making that require ongoing human engagement. Healthcare remains a deeply human-centered field that relies on clinical judgment, ethical considerations, and interpersonal communication, even on the administrative side. Rather than replacing people, AI will serve as a powerful support tool, especially for well-defined, repetitive tasks that currently strain the system.
That said, AI will play an increasingly critical role in making healthcare more cost-effective and efficient, especially in areas where administrative workload is growing faster than the available workforce. For example, in medical coding:
- Today, there are more than 2,500 open coding positions posted on LinkedIn.
- According to AHIMA and other credentialing bodies, nearly 40% of current coders will be eligible for retirement within the next seven years.
- At the same time, healthcare service demand continues to grow, increasing the volume of medical documentation that must be processed accurately and efficiently.
In this environment, AI is not just a helpful tool, it is becoming essential. AI-powered coding solutions can help providers keep pace with documentation demands while maintaining or improving accuracy and quality. These tools can assist coders by automating routine tasks, flagging potential errors, and accelerating the overall process, enabling human experts to focus on higher-complexity cases and oversight.
Ultimately, the future is not about AI replacing humans, but about AI augmenting the human workforce. By combining human expertise with AI-driven efficiency, healthcare organizations can improve quality, reduce costs, and meet the growing needs of patients and providers alike. Without these advancements, the industry risks falling behind in its ability to deliver timely, accurate, and compliant care documentation.
Could concurrent coding data be used in real time to assist patient unit staffing, especially in acute obstetrics where acuity can change dramatically even though the patient remains in the same bed?
Yes — there is significant potential for concurrent coding data to be leveraged in real time to support critical staffing decisions. In environments such as acute obstetrics, where patient acuity can shift rapidly without a change in bed assignment, having timely and accurate information is essential for optimal resource allocation. As automation and clinical documentation tools become more sophisticated, concurrent coding can move closer to the point of care, enabling actionable insights for care teams. Real-time coding data could help:
- Identify changes in patient complexity or risk level that warrant additional staffing or specialized expertise.
- Support dynamic adjustments in nurse-to-patient ratios to maintain safety and quality of care.
- Provide leadership with an early warning system for shifts in overall unit acuity, allowing proactive planning rather than reactive staffing changes.
While this capability is still emerging, the trajectory of AI and automation in healthcare suggests that the integration of concurrent coding with operational decision-making will continue to accelerate. Over time, we can expect this data to become a critical input in real-time staffing optimization, helping healthcare organizations deliver safe, efficient, and patient-centered care.
How can AI assist HIM professionals in those topics?
AI can assist Health Information Management (HIM) professionals by enhancing efficiency, accuracy, and decision-making across a range of functions. In areas such as medical coding, documentation review, and operational support, AI acts as a powerful augmentation tool rather than a replacement for human expertise.
Key ways AI can support HIM professionals include:
- Automating routine tasks: AI can handle repetitive coding assignments, documentation abstraction, and data entry, freeing HIM professionals to focus on higher-complexity cases that require critical thinking and clinical judgment.
- Improving accuracy and compliance: Natural language processing (NLP) and machine learning algorithms can detect documentation gaps, flag inconsistencies, and ensure codes meet payer and regulatory requirements.
- Real-time insights for operational decisions: Concurrent coding data, processed by AI, can provide immediate feedback on patient acuity and resource needs — which is especially valuable in highvariability environments like acute care and obstetrics.
- Workforce sustainability: With a significant portion of the HIM workforce nearing retirement, AI can help bridge the staffing gap by maintaining productivity and quality despite a shrinking pool of experienced professionals.
- Data-driven improvement: AI analytics can identify trends in errors, documentation issues, or claim denials, enabling targeted education and process improvement initiatives.
Ultimately, AI empowers HIM professionals to work more strategically — allowing them to spend less time on repetitive tasks and more time ensuring data quality, compliance, and support for better patient outcomes.
What are the latest innovations for Data governance and Health Information Exchange (HIE)?
Datavant understands that coding teams are under pressure to do more with less, but manual workflows make that nearly impossible.
Datavant’s AI-powered coding assistant was built for exactly this. It surfaces suggested codes, flags documentation issues and catches potential errors — giving coders what They need to move faster with fewer mistakes. Are you ready to explore how we could support your coding goals?
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