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Clinical data dictionary

By Dr Rida Akodad · Publication director · Updated 21 August 2026

A clinical data dictionary is the document that declares, for every variable in a study, what it means and what it accepts — before the first value is entered. It is the piece that makes a column interpretable by someone other than whoever created it.

Definition

The variable dictionary — often called a *codebook* — attaches to each column of the dataset a set of declared properties: a stable technical identifier, a readable label, a type, a measurement scale, a unit, bounds of the possible and the plausible, a closed list of categories for categorical variables, permitted reasons for absence, and mappings to standards.

Its decisive property is temporal: it is written before capture, not inferred afterwards. A dictionary reconstructed after the fact documents what the data appears to contain; a dictionary written in advance constrains what it may contain.

Why it matters

  • It makes the column interpretable. bmi = 31.2 means nothing without knowing whether the value was measured or computed, on what date, and by which formula.
  • It makes absence legible. An empty cell can mean "not sought", "sought and not found", or "not applicable". Those three cases are handled differently in analysis, and only the dictionary tells them apart.
  • It makes units comparable. A glucose value in mg/dL and another in mmol/L do not aggregate; declaring the unit makes conversion possible and checkable.
  • It makes automatic checking possible. Without declared bounds, no rule can refuse an aberrant value at entry.

Example

A dictionary entry for a score variable, as it appears in a urology study:

PropertyValueWhat it is for
Identifieripss_totalStable, never renamed — this is what the analysis script calls
LabelTotal IPSS scoreWhat a human reads
TypeIntegerForbids "moderate" in a numeric column
ScaleOrdinalDetermines which statistical tests are admissible
Unitpoint (dimensionless)Avoids confusion with a percentage
Possible bound0 – 35Beyond this the value is refused: the score does not exist
Plausible bound0 – 30Beyond this the value passes with a warning
Permitted absencenot sought · patient unable to answerTwo distinct situations, traced separately

Related standards

CDASH supplies reusable variable names and definitions for capture; UCUM normalises how units are written; LOINC identifies laboratory observations; the FAIR principles make metadata the condition of reuse.

Sources and standards