Every Medicinrådet decision, already read.
Comparators, utility weights, survival models and assumptions, extracted from every appraisal and cited to the page they came from.
The 0.09 gap is an instrument artefact: VIALE-A used EQ-5D-5L, QUAZAR the older 3L, which scores remission systematically higher.
Built for the analysts at HTA consultancies and pharma market-access teams who build Danish submissions.
Why now
Record volume. Zero structured access.
Medicinrådet decides more than ever, and every decision adds precedent your next submission is judged against.
The submitted Excel model is never published. The vurderingsrapport is the only public trace of the inputs the council accepted, and it is a Danish PDF built for reading, not for reuse.
There is no structured database to fall back on. The only free cross-agency HTA database missed 75% of sampled appraisals in a 2025 peer-reviewed audit.
Sources: Medicinrådets årsberetninger 2024–2025 · Lif's Medicinrådstracker · INAHTA database completeness study (2025).
How it works
From dossier to model input. In three moves.
The workflow a health economist actually runs, with no re-reading required.
Browse by sygdomsområde.
Start where a health economist thinks: pick a disease area and see every appraisal, with its Medicinrådet status.
Pull the cited inputs.
Utilities, survival models and assumptions, each as applicant → council and cited to the passage.
Reconcile with the Why Engine.
When two dossiers disagree on a value, ask why. Retrieval over the full texts explains the gap.
AI agents
Ask the corpus. Agents do the reading.
Pose the question a submission raises. Agents retrieve the passages, reconcile the numbers, and answer with citations you can open.
The agents
Evidence you can defend. In a submission.
Three agents work the corpus, and everything they claim is anchored to a citation you can open, not a black box.
Extraction agent
Every number, traced applicant → council.
Every utility weight, survival model and assumption pulled from the PDF as an applicant → council value, traced to the exact passage. No more re-reading 90-page vurderinger.
Synthesis agent
The methodology, read for you.
Risk-of-bias on each source study, and EQ-5D-3L → 5L normalisation so values from different eras are comparable.
Why Engine agent
Ask why two dossiers disagree.
Retrieval over the full texts explains the gap: instrument, population, or council adjustment, with citations.
The 0.09 gap is an instrument artefact: VIALE-A elicited utilities with EQ-5D-5L, QUAZAR with the older 3L, which scores remission systematically higher. Normalised to 5L, the values converge.
Trust
Compliance-grade. By default.
The guarantees a pharma legal review asks about first, answered up front.
Never trained on your data.
Your questions, files and models stay yours. Nothing you do in Evidens is used to train a model, ours or anyone else's.
GDPR-first, EU-hosted.
EU data residency, SSO, and an audit trail on every extracted value, built to pass a pharma compliance review.
Redactions stay redacted.
Values printed XXXX in the source are never inferred, estimated or reconstructed. Public documents only.
Fresh every day.
Agents watch Medicinrådet and re-scrape daily, so new anbefalinger and vurderinger land the day they publish.
“Half my model-building time goes into finding and re-justifying inputs I've already seen in an old vurdering. This is that time back.”
Questions a health economist asks first.
Private beta
Built for Nordic HTA teams.
We're onboarding a first cohort of health economists working on Danish submissions, with Sweden, Norway and EU JCA reports on the roadmap. Tell us what you'd reuse most and we'll prioritise it.
- Denmark (Medicinrådet) live first
- Your inputs, cited back to the source PDF
- Export to your model, not another silo