Guide · 8 minute read
Artificial intelligence tools are increasingly appearing inside the software that health workers already use every day — from clinical documentation assistants to decision-support alerts embedded in electronic medical records. For a nurse, clinician, or hospital administrator encountering these tools for the first time, it helps to have a clear, practical mental model of what they actually do.
What these tools are actually doing
Most AI tools you will encounter in a clinical setting fall into a few broad categories: documentation assistance (turning spoken or typed notes into structured records), decision support (flagging patterns that may warrant a closer look), and administrative automation (scheduling, coding, and triage support). None of these tools are making diagnoses on their own — they are surfacing information and suggestions for a trained professional to evaluate.
What they can do well
AI tools are generally strong at pattern recognition across large amounts of data, reducing repetitive documentation work, and surfacing information that might otherwise be buried in a long chart. Used well, this can free up time for direct patient care.
Where they fall short
AI tools can reflect biases present in their training data, may perform differently across populations underrepresented in that data, and can be confidently wrong. They also generally lack the full context of a patient relationship that a clinician builds over time. This is why LDHI training emphasizes treating AI output as a second opinion to evaluate, not an instruction to follow.
A simple practice
Before acting on an AI-generated suggestion, ask: does this match what I am seeing in the patient in front of me? If there is a mismatch, your clinical judgment should take precedence. This habit, more than any specific tool, is what LDHI’s Responsible AI curriculum is built to reinforce.
This overview is adapted from concepts covered in more depth in LDHI’s Foundations of Artificial Intelligence in Healthcare course and our Responsible AI, Ethics, Privacy and Patient Safety course.