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The evidence-preparation architecture

From decision need to decision-ready evidence

IMPRESIVE begins with the decision question, not with a database or a common data model. Whether a source can answer that question is assessed before any implementation route is chosen.

Flowchart for the IMPRESIVE evidence-preparation pathway

Technical detail for every step lives in Methods.

The IMPRESIVE evidence-preparation pathway, steps 1 to 9 A decision need is framed into questions covering disease burden, treatment use, effectiveness and safety. Data are characterized, then a fit-for-purpose assessment is made for each question and database. Pairs that pass go to the coordinating centre, which distributes one artefact per architecture: a common question, a common protocol, or a common data model with a shared analytical program. Site results return as aggregate output. The deliverables are pooling and assessing consistency, assessing transportability, evidence integration and visualization, and a fit-for-decision judgement. Pairs that fail bypass execution and go to second-best analysis, where the questions are redefined, data partners extended, or a prospective or external control used, feeding back into the decision need. Deliverables Identifying the decision need Framing the question(s) 1 Disease burden Treatment use Effectiveness Safety Feasibility & Fit-for-purpose assessment For each question and database 2 PASS FAIL Protocol & variable definition 3 Common question DataAnalysisResults Common protocol DataSame protocolResults Common Data Model (CDM) DataCDMSame analytical programResults Standardization 4 Quality validation 5 Distributed execution 6 Evidence integration 7 Visualization and interpretation 8 Second-best analysis Characterization is the deliverable 3bis Question refined and re-scoped Mapping extended, sites added Prospective or external control Next iteration Rebuild the common layers Fit-for-decision β€œTo what extent findings inform decision?”
  • Programme step
  • Evidence facet
  • Second-best route
  • Feedback to step 1
  • Each shape and colour is one data partner

How is each step implemented?

Get a look at definitions, ETL specifications, CDM mappings, quality checks, and analytical modules.

Open Methods