A Proposed Role for Integrating Clinical AI: The 'Algorithmic Consultant'

As artificial intelligence systems become more common in healthcare, it’s important to consider how they can be integrated into clinical workflows effectively. For those of us working to build intelligent care pathways, a recent article in npj Digital Medicine offers a practical perspective. It points out that direct physician-AI interaction can produce inconsistent results. For example, some studies show that when clinicians are given an algorithm’s output, their predictive performance does not reliably improve. The authors suggest it may be impractical to expect all physicians to develop the specialized expertise needed to select, use, and interpret the output of every complex AI tool. The article compares this expectation to asking a general practitioner to interpret the unprocessed output of an MRI machine without assistance from a radiologist.

To address this gap between AI tools and clinical practice, the article proposes a new type of specialist: the “algorithmic consultant”. This role is modeled after the clinical pharmacist, who guides medication use within a hospital. The algorithmic consultant would have two primary functions. At the point of care, they would provide guidance on selecting the appropriate AI model for a specific clinical question and help interpret the model’s output. Beyond individual consultations, they would also perform a system-level governance role, managing the institution’s portfolio of AI models. This would include vetting new models, implementing safeguards for their use, monitoring for performance changes, and ensuring algorithmic fairness, similar to how a pharmacist helps manage a hospital’s drug formulary.

This proposed model aligns with our approach at CarePathIQ, where we aim to augment clinical practice with tools that are both effective and safe. The concept of an algorithmic consultant offers a structured way to manage the complexities of AI in a clinical setting. Instead of placing the full burden of AI evaluation on individual clinicians, this specialist role would provide expert support, helping to ensure that new technologies are applied appropriately. By creating a dedicated resource for AI oversight, healthcare systems can better translate the potential of these tools into daily practice and support providers in delivering patient-centered care.