Capstone · Board Pack
Healthcare AI Transformation Strategy
One document you return to after every module. Sections unlock as you gain the knowledge to answer them honestly. Everything you type is saved in this browser; the Board Pack preview assembles what you have written into a document you can print or save as PDF.
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Which concrete clinical or operational problem are you addressing? Who is harmed today, and how do you know?
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Describe the organisation: type of care, scale, digital maturity, decision-makers, constraints.
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Where across the care pathway could AI plausibly add value? For each candidate, name the decision it would change and the action that follows.
Unlocks once you complete Module 1 — From AI Idea to Healthcare Impact.
Which two or three use cases come first, and on what criteria?
Unlocks once you complete Module 3 — From Prediction to Clinical Utility.
What data, at what quality, with which labels and which access route?
Unlocks once you complete Module 2 — Can We Trust the Data?.
For your prioritised use case: which knowledge sources are in scope and who owns them, which actions the system is allowed to take, which autonomy level you are choosing and why, where the human approval gates sit, and how an answer or action can be traced afterwards. Design-level answers are expected; implementation detail is not.
Unlocks once you complete Module 5 — RAG, Tools & AI Agents for Practitioners.
What evidence would convince a sceptical clinical council?
Unlocks once you complete Module 6 — Evaluating Healthcare AI.
Your working regulatory classification, legal basis, governance bodies and sign-off path. This is a course exercise, not a legal or regulatory determination — confirm with your regulatory and legal advisers before acting on it.
Unlocks once you complete Module 9 — Regulation & Governance.
Failure modes, mitigations, monitoring and stopping criteria. This is a training draft, not a completed clinical safety case — it needs review under your organisation's clinical safety process.
Unlocks once you complete Module 7 — Safety, Human Factors & Responsible AI.
What changes in the actual work of clinicians and staff?
Unlocks once you complete Module 10 — Implementing & Scaling AI in Healthcare.
Sequenced plan from pilot to routine care, with decision gates.
Unlocks once you complete Module 10 — Implementing & Scaling AI in Healthcare.
Set out the shape of the portfolio and the reasoning behind it: which candidates are near-term value, which are strategic bets, which are enabling capabilities, which are high value but not ready (with the specific readiness gap and its owner), and which you are declining. Then state the sequence the dependencies force, and what you would stop.
Unlocks once you complete Module 8 — Strategy, Portfolio & Economics.
Argue one investment properly: the value hypothesis, the current-practice baseline, the expected value and the KPI that would show it, total cost of ownership across implementation and run, which benefits are cashable and which are not, who pays and who benefits, scenarios rather than a single return figure, what happens to any released capacity and who owns that decision, and the investment recommendation with the decision gate you are asking for.
Unlocks once you complete Module 8 — Strategy, Portfolio & Economics.
Clinical, operational, experience and safety indicators you will report.
Unlocks once you complete Module 10 — Implementing & Scaling AI in Healthcare.
From one department to the organisation — and to partners.
Unlocks once you complete Module 10 — Implementing & Scaling AI in Healthcare.
One page: the ask, the rationale, the risks, the decision required.
Unlocks once you complete Module 10 — Implementing & Scaling AI in Healthcare.