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Industry track, The AI Decision Course

AI in healthcare

For leaders in hospitals, health systems and health companies: easing the documentation burden on clinicians, deciding what AI may see in the patient record, prior authorization, and who carries the risk when AI touches care.

10 short lessons. Each one is a short read with a card your team fills in and three AI prompts to test it. Part of The AI Decision Course: membership is $299 a year and includes all 12 courses, with a full refund within 14 days.

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About this course

This course covers bringing AI into hospitals, health systems and health companies: taking the documentation burden off clinicians first, naming the use before AI touches the patient record, and fitting clinical AI into the clinician's day. It also covers prior authorization a rung at a time, how far AI may go with patients, paying for health AI, and who carries the risk when AI touches care.

You leave able to pick the first clinical users by documentation load and to name the use before AI touches the patient record, from care to operations. You can also put AI on prior authorization a rung at a time, keep a person on anything that reaches a payer, and allocate every risk control in the contract before deployment.

Lessons in this course

  1. Take the documentation burden off your clinicians first3-minute read, Free to read
  2. Before AI touches the patient record, name the use4-minute read
  3. Clinical AI that helps the clinician decide, and fits the day3-minute read
  4. Watch the patient all the time, or test now and then?3-minute read
  5. Put AI on prior authorization, one rung at a time3-minute read
  6. Will anyone pay for the health AI you build?3-minute read
  7. How far to let AI go with your patients4-minute read
  8. Your first regulated medical AI claim: one question, one study3-minute read
  9. Who carries the risk when AI touches care4-minute read
  10. Access to the specialist, not a better specialist2-minute read

Back to the course list

Questions

How do we reduce the documentation burden on clinicians?

Start with the clinicians who write the most notes, and gate the rollout on a note bar a clinician panel signs while every note still gets read. Ask consent aloud and log it, and measure time in the record and after-hours work from day one. The lesson 'Take the documentation burden off your clinicians first' covers the start.

How far should AI go with patient messages?

Tier patient channels by consequence: rescheduling for an established patient can run fully automated, while symptom triage needs a tested bar and a human checkpoint. Keep clinical judgment with a person, and tell patients when a machine is involved, since patients who dislike AI mostly accept it once the disclosure is routine. The lesson 'How far to let AI go with your patients' covers the tiers.

Who carries the risk when AI touches patient care?

Name who answers before rollout, because with no one answerable the clinician holds the risk. Allocate every risk control in the contract, stamp which system and which version touched the record, and own only the decisions you helped make. The lesson 'Who carries the risk when AI touches care' covers the allocation.

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