Final exam: AI Training for Healthcare Professionals: Clinical Judgement Alongside Automated Advice

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Question 1 of 10

1. Question

Where in your healthcare setting would you most likely find AI already deployed?

Only in research laboratories
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In imaging interpretation, triage systems and ambient documentation tools
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Only in administrative functions like billing
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Primarily in nursing stations for staff scheduling
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Question 2 of 10

2. Question

If an AI diagnostic system has 90 percent sensitivity for a condition, what does this mean?

90 percent of people without the condition are correctly identified as disease-free
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Among people who actually have the condition, 90 percent are correctly identified
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The system is 90 percent accurate overall
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90 percent of positive predictions are correct
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Question 3 of 10

3. Question

Why might an AI diagnostic system perform well on validation data but poorly in your hospital?

The system was intentionally designed to fail in new settings
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Training data often comes from specific equipment, documentation practices and patient demographics that may not match your setting
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AI systems can only work in the exact hospital where they were developed
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Poor performance in new settings is actually the normal expectation
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Question 4 of 10

4. Question

What is automation bias in clinical decision making?

The bias in AI algorithms against certain patient groups
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The human tendency to accept algorithmic advice more readily than equivalent advice from another human
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A type of measurement error in diagnostic systems
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The tendency for algorithms to become increasingly accurate over time
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Question 5 of 10

5. Question

When should you consider overriding an AI diagnostic system’s recommendation?

Never, because algorithms are always more accurate than humans
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When your clinical judgment based on direct patient assessment and expertise leads to a different conclusion
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Only when you have published research contradicting the system
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When the system's processing time is too long
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Question 6 of 10

6. Question

What types of errors are most common in ambient documentation tools?

Only minor spelling mistakes that do not affect care
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Transcription errors with clinical terminology and natural language processing errors that infer incorrect structured data, potentially clinically meaningful
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Only errors that the system automatically corrects
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Errors that only appear in administrative sections, not clinical sections
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Question 7 of 10

7. Question

Under the EU AI Act Article 50 (in force since 2 August 2026), what must happen when high-risk AI is used in clinical care?

Patients must receive a detailed technical explanation of the algorithm
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Patients must be provided with patient information on a USB drive
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Patients must be informed when AI makes decisions significantly affecting them, transparency requirement
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Patients must sign an additional consent form every time an AI touches their care
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Question 8 of 10

8. Question

What is the first question your organisation should ask before deploying an AI system that processes patient data?

What is the cost of the software?
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Where does the data go when processed, and can the vendor retain, reuse or store it outside the UK?
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When was the system first released?
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Which department requested it first?
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Question 9 of 10

9. Question

What does DCB0129 govern in an NHS setting?

Only paper-based clinical records
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Mobile applications and web applications used by healthcare professionals, including their safety, data integrity and security
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Only administrative software, not clinical software
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Only systems used by patients, not by clinicians
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Question 10 of 10

10. Question

What should documentation of AI-assisted diagnosis include?

Only the AI system's name and output
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What the AI did, what you clinically assessed, and whether you agreed with or overrode the AI's output
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Only your clinical conclusion, without mentioning the AI at all
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A detailed explanation of how the algorithm works
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Final exam: AI Training for Healthcare Professionals: Clinical Judgement Alongside Automated Advice

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