— Door 02 · Show, don't tell
A survey instrument,
already designed.
The fastest way to show I can do this brief is to do a slice of it. Here's a Smart Hospital research engine — the five strategic themes mapped to measurable questions, a sample of the instrument with real question types, an executive survey flow for hospital C-suite respondents, and the maturity model that turns responses into a defensible benchmark.
CONCEPT ONLY — This is my own concept research design, built to demonstrate survey-design and analysis craft. It is not the client's instrument, the questions are illustrative starting points to be refined with subject-matter experts, and no real data is shown.
02Sample of the instrument~20 questions · 5 shown
Q1
How would you describe your organisation's current Smart Hospital maturity?
MaturitySingle selectAnchors the benchmark
Level 1 — Foundational (digitising paper, core systems)
Level 3 — Connected (integrated data, early analytics)
Level 5 — Intelligent (AI-enabled, predictive, autonomous workflows)
Q2
Which AI use cases are live in your hospital today? (Select all that apply)
AI adoptionMulti-selectAdoption breadth
Clinical decision support / diagnostics
Patient flow & capacity prediction
Administrative / documentation automation
None yet — in evaluation
Q3
How well do your core clinical systems exchange data with each other?
InteroperabilityLikert 1–5Quant signal
1Siloed
2Limited
3Partial
4Broad
5Seamless
Q4
Rank the operational outcomes where digital initiatives have delivered the most measurable value.
OutcomesRankingPriority signal
☰ Patient flow / length of stay
☰ Clinical safety / error reduction
☰ Cost / efficiency
☰ Staff experience / retention
Q5
What is the single biggest barrier stopping you from scaling successful initiatives?
BarriersOpen textQual depth
Free-text response — coded later into themes (funding · skills · integration · governance · change fatigue) for the qualitative analysis.
03Executive survey flow · built for C-suite timebranching keeps it short & relevant
Screen
Role & organisation type — qualify the respondent
Anchor
Q1 maturity self-rating sets the path
Branch · Low maturity
Focus on barriers & roadmap intent
Branch · High maturity
Focus on AI value & scaling outcomes
Close
Outcomes ranking + one open reflection
Design principle: a C-suite respondent should finish in under 8 minutes. Branching means no one answers irrelevant questions — which lifts completion and data quality.
04The analysis framework · a 5-level maturity modelturns responses into a benchmark
01
Foundational
Core systems digitised; data largely siloed; AI absent or experimental.
02
Developing
Key systems integrated in pockets; basic analytics; first AI pilots underway.
03
Connected
Broad interoperability; data informing decisions; AI delivering value in defined areas.
04
Optimised
Predictive analytics embedded; AI scaling across workflows; measurable operational gains.
05
Intelligent
Seamless data; AI-enabled, partly autonomous workflows; continuous outcome improvement.
Every respondent is placed on this scale from their answers — so the whitepaper can report "X% of APAC hospitals sit at Level 3 or below," the kind of benchmark a C-suite reader can act on. Final levels would be validated with the client's subject-matter experts.