The archetype explorer
Sixteen ways to turn judgment into a number
Every CLIOH study is one of twelve archetypes — or a hybrid of two. The right one is set by what you want to produce, whether the panel’s consensus is the answer or is graded against patient outcomes, and what you compare. Pick by deliverable below, or let the decision tree choose for you.
Take the 5-question decision treeWhat do you want to produce?
12Research / Discovery CLIOH
rank candidate drivers of a phenomenon to aim the next study.
Educational / Training CLIOH
make the tacit priority order of senior faculty explicit and teachable — convert "you'll just know it when you've seen enough" into a measured, curriculum-ready hierarchy.
Classification / Nosology CLIOH
turn a severity continuum into outcome-validated categorical grades.
Triage / Priority CLIOH
map case features → an urgency score for live prioritization (OR booking, ED throughput, transport).
Calibration / Assessment CLIOH
measure how well an individual's clinical judgment agrees with an expert-consensus reference scale — i.e., score a person, not a variable.
Outcome-Importance CLIOH
rank which outcomes a trial (or a condition's management) should measure — producing an interval-scale, patient-aligned endpoint hierarchy.
Risk-Factor Weighting CLIOH
turn expert pairwise judgments of predictor variables into a weighted clinical prediction-rule score — an expert prior you can deploy before big-N outcome data exists, then validate empirically later.
Patient-Centered Preference CLIOH
measure population-level patient/family preference weights over treatment attributes and burdens, to inform shared decision-making and labeling.
AI / Algorithm Calibration CLIOH
label or benchmark a clinical AI's outputs against an expert-consensus interval scale, so the model is measured on the surgeons' own ruler — not an arbitrary one.
Resource / Implementation Priority CLIOH
rank a portfolio of competing interventions, projects, or sites for finite funding or QI-deployment effort — turning a contentious budget meeting into a measured, defensible priority order.
Phenotype / Classification Boundary CLIOH
locate the decision boundary between two or more discrete clinical phenotypes — not rank a single severity dimension.
Diagnostic Hierarchy CLIOH
given a patient's presenting features, produce a feature-conditional ordering of the differential diagnosis — which condition is most likely, second, third — as a decision-support aid.
Combinations
4· two deliverables from one elicitationCalibration × Educational CLIOH
from one faculty elicitation, produce both a teaching tool (Educational §2) and a trainee assessment (Calibration §5).
Discovery × Outcome-Importance CLIOH
combine variable discovery (Discovery §1) with endpoint ranking (Outcome-Importance §6) to produce a complete multicenter-trial-design package — which variables to measure and which outcomes to power on.
Classification × AI-Calibration CLIOH
turn an expert classification worth scale (Classification §3) into the continuous regression target that trains or benchmarks a clinical AI (AI-Calibration §9).
Triage × Risk-Factor CLIOH
from one covariate-structured elicitation, get both a live prioritization score (Triage §4) and the implicit risk-factor weights (Risk-Factor §7) as a second deliverable.