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AI exposure report
Will AI replace Health Information Technologists and Medical Registrars?
Many of your tasks are within reach of AI. The role will change, so it pays to act now.
Task exposure to today's AI
High exposure
This is the occupation's typical task mix. Your own score can be up to 30 points higher or lower depending on how you work: routine share, people contact, judgment and how much you already use AI.
Get your personal scoreWill AI replace Health Information Technologists and Medical Registrars?
Not entirely. Today's AI tools can take on about 50% of the typical work in this occupation, mostly: compile medical care and census data for statistical reports on diseases treated, surgery performed, or use of hospital beds. The parts that stay human include: Identify, compile, abstract, and code patient data, using standard classification systems.; Manage the department or supervise clerical workers, directing or controlling activities of personnel in the medical records department.; Resolve or clarify codes or diagnoses with conflicting, missing, or unclear information by consulting with doctors or others or by participating in the coding team's regular meetings..
People who learn to use AI for the automatable parts keep the edge. The 3-phase plan below shows where to start.
Which tasks AI can take on
The largest tasks in this occupation, their share of the working week, and how much of each today's AI tools can do.
+ 10 more tasks (40% of the week) in the full test.
Your human edge
- Identify, compile, abstract, and code patient data, using standard classification systems.
- Manage the department or supervise clerical workers, directing or controlling activities of personnel in the medical records department.
- Resolve or clarify codes or diagnoses with conflicting, missing, or unclear information by consulting with doctors or others or by participating in the coding team's regular meetings.
AI tools to try
Clinical documentation and transcription assistantsChatGPT / Claude for patient information (no patient data)Clinical decision support in your systemsRelated roles
A 3-phase AI learning plan
Phase 1
Less documentation time
- AI transcription and note drafting where your organisation allows it.
- Patient information leaflets in plain language.
- Never put identifiable patient data into public tools.
Project
Use AI to rewrite 10 de-identified coding query templates and patient record-release letters into plain language, then measure reading-level drop and minutes saved per document.Phase 2
Evidence and decision support
- Guideline and literature summaries with AI, checked in the source.
- Understand how decision-support tools reach their output.
- Know the limits and liability.
Project
Have AI summarise the current ICD-10-CM/PCS and cancer registry (SEER/AJCC staging) coding guideline updates, verify every rule in the official source, and log the error rate.Phase 3
AI in care processes
- Coordination, scheduling and handover with AI help.
- Take part in your organisation's AI projects.
- Teach colleagues safe use.
Project
Build an AI-assisted workflow that drafts the monthly tumor registry or bed-utilisation statistical report, then run a 60-minute training for your records team on safe prompts and PHI rules.