The data work nobody budgets for before an AI project
Patient identity, doctor masters, speciality taxonomies, system fragmentation and consent — the unglamorous work that decides whether a hospital AI pilot survives week three.
Patient identity, doctor masters, speciality taxonomies, system fragmentation and consent — the unglamorous work that decides whether a hospital AI pilot survives week three.
How to tell whether a stalled hospital has a demand, clinical, experience or reputation problem, and why running a fresh campaign first makes it worse.
How to build catchment awareness and referral groundwork before clinical hiring completes, what you can honestly promise, and why early media spend is usually wasted.
Eight structural traps that reward the platform and the agency while transferring money out of the hospital, and the metrics to refuse in order to avoid them.
The supply side of a hospital launch playbook travels well. Catchment behaviour, language, referrals, payer mix and pricing perception do not, and that is where launches fail.
Scoping, the statement of work clauses that prevent arguments, escalation ladders, knowledge transfer, and how to tell a struggling partner from a bad one.
Improving enquiry-to-appointment raises the yield of every channel at once, at no extra media cost. It is also the least glamorous number in the deck.
Why doctors resist digital change, how to tell an objection from a veto, and the credibility mistakes that take years to recover from.
The hiring order that works in a multi-unit hospital group, what to keep in-house, and why consumer-tech reflexes fail in a clinical environment.
You will not solve attribution in a hospital. You can decide how much wrongness to tolerate and still allocate a budget sensibly, which is a different problem.