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web www.hl7.dk
web www.hl7.dk IG © 2026+ HL7 Denmark . Package hl7.fhir.dk.hackathons#1.0.0 based on FHIR 4.0.1 . Generated 2026-06-23
Links: Table of Contents | QA Report
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web hl7.dk Welcome to the Danish Hackathon 2026 (Dk-hackathon) - a health data hackathon organized by HL7 Denmark , held at the Forskerparken 10 (at MedCom) in Odense, Denmark on October 6, 2026 .
web 2026.e-sundhedsobservatoriet.dk The Dk-hackathon is held the day before the Danish e-health conference eSundhedsobservatoriet .
web fhir.fi This hackathon is part of the Nordic Health Data Hackathons series.
web hl7.dk HL7 Denmark
web github.com PRs to this IG are welcome at hl7dk/dk-hackathons
web github.com This track explores whether AI agents can give patients programmatic, FHIR-based access to Danish health data portals that do not natively expose a FHIR API. The approach is inspired by the Dhroxy project, developed as part of the c3po initiative , which already uses AI agents to map the data models and REST APIs of sundhed.dk onto a FHIR REST interface.
web github.com This track explores whether AI agents can give patients programmatic, FHIR-based access to Danish health data portals that do not natively expose a FHIR API. The approach is inspired by the Dhroxy project, developed as part of the c3po initiative , which already uses AI agents to map the data models and REST APIs of sundhed.dk onto a FHIR REST interface.
web www.sundhed.dk This track explores whether AI agents can give patients programmatic, FHIR-based access to Danish health data portals that do not natively expose a FHIR API. The approach is inspired by the Dhroxy project, developed as part of the c3po initiative , which already uses AI agents to map the data models and REST APIs of sundhed.dk onto a FHIR REST interface.
web github.com Dhroxy
web github.com c3po add-ons
web hl7.dk Profile the output against the Danish national profiles — dk-core and the eHealth Infrastructure IG ( dk.ehealth.sundhed.fhir.ig.core ) — not just vanilla R4
web ehealth.sundhed.dk Profile the output against the Danish national profiles — dk-core and the eHealth Infrastructure IG ( dk.ehealth.sundhed.fhir.ig.core ) — not just vanilla R4
web www.mitid.dk MitID
web www.nspop.dk Two things are common to almost all of them: citizens authenticate with MitID (typically brokered through NemLog-in as OIDC/SAML), and the patient is identified by CPR-nummer — the Danish equivalents of the Swedish BankID and personnummer. National backend services on the NSP ( Den Nationale Serviceplatform ) add their own layer: professional access uses a SOSI ID-kort SAML assertion over DGWS (Den Gode Webservice, SOAP), while delegated citizen access uses OIO-IDWS , all carried over Sundhedsdatanettet (SDN) .
web www.sundhed.dk sundhed.dk / MinSundhed app
web github.com already partly covered by Dhroxy ; the natural starting point is to extend it
web minlaegeapp.dk Min Læge (minlaegeapp.dk)
web booking.rm.dk MineAftaler Region Midtjylland (booking.rm.dk)
web booking.rn.dk MineAftaler Region Nordjylland (booking.rn.dk)
web mit.rsyd.dk Mit Sygehus / MineAftaler Syddanmark (mitsygehus.dk)
web minsp.dk Min Sundhedsplatform (minsp.dk)
web fhir.epic.com MitID → MyChart session. Epic speaks FHIR internally (see fhir.epic.com ), but the regions publish no patient-facing FHIR endpoint — the MyChart web/JSON API has to be mapped
web www.fmk.dk Fælles Medicinkort (FMK)
web www.sundhedsdatastyrelsen.dk Det Danske Vaccinationsregister (DDV)
web www.webreq.dk WebReq / WebPatient
web sundhedsdatastyrelsen.dk Min Graviditet / Graviditetsmappen
web ehealth.sundhed.dk The eHealth Infrastructure / FUT platform ( ehealth.sundhed.dk/fhir , package dk.ehealth.sundhed.fhir.ig.core ) is a national FHIR R4 backbone for telemedicine and shared care — and the conformance target for the resources you produce in this track.
web github.com Most of these systems also have Android apps on Google Play (e.g. Min Læge , MinSundhed , MineAftaler , Mit Sygehus , Epic MyChart ). These apps are valid targets for decompilation and static analysis (e.g. using jadx or apktool ) and can reveal API endpoints, request formats, and authentication flows that are not documented anywhere publicly.
web apktool.org Most of these systems also have Android apps on Google Play (e.g. Min Læge , MinSundhed , MineAftaler , Mit Sygehus , Epic MyChart ). These apps are valid targets for decompilation and static analysis (e.g. using jadx or apktool ) and can reveal API endpoints, request formats, and authentication flows that are not documented anywhere publicly.
web github.com The c3po add-ons plugin
web www.scrapingbee.com Browser DevTools — Copy as cURL — The quickest way to capture a single request. Open the Network tab, right-click any request, and choose Copy → Copy as cURL (see full tutorial ). The result is a self-contained shell command you can paste directly into a terminal or hand to an AI tool: 
                
curl 'https://booking.rm.dk/MineAftaler/api/appointments' \
  -H 'Accept: application/json' \
  -H 'X-Requested-With: XMLHttpRequest' \
  -H 'Cookie: SESSION=abc123; XSRF-TOKEN=xyz'
web mitmproxy.org Proxy — Route traffic through mitmproxy or Charles Proxy for richer inspection and scripting.
web github.com Android app decompilation — If the portal has an Android app, download the APK and decompile it with jadx or apktool to extract hardcoded endpoints and request schemas without needing to intercept live traffic.
web apktool.org Android app decompilation — If the portal has an Android app, download the APK and decompile it with jadx or apktool to extract hardcoded endpoints and request schemas without needing to intercept live traffic.
web github.com Tip: Before feeding a HAR file to an AI tool, scrub or replace real patient values (names, CPR-numre, dates of birth) with synthetic equivalents — the structure and field names are what matter for mapping, not the actual data. har-sanitizer (Cloudflare) can help automate this step. Alternatively, chrome-devtools-mcp lets an AI agent connect directly to Chrome DevTools and observe network traffic in real time, skipping the manual export step entirely.
web github.com Tip: Before feeding a HAR file to an AI tool, scrub or replace real patient values (names, CPR-numre, dates of birth) with synthetic equivalents — the structure and field names are what matter for mapping, not the actual data. har-sanitizer (Cloudflare) can help automate this step. Alternatively, chrome-devtools-mcp lets an AI agent connect directly to Chrome DevTools and observe network traffic in real time, skipping the manual export step entirely.
web hl7.dk Map — For each data type returned (appointments, lab results, medications, …) identify the closest FHIR R4 resource and draft a simple mapping table. Where a Danish profile exists, map to it: prefer dk-core profiles and the eHealth Infrastructure IG ( dk.ehealth.sundhed.fhir.ig.core ) over plain R4, and use Danish/Nordic code systems (CPR, SOR, the Nordic terminology server ) where they apply.
web ehealth.sundhed.dk Map — For each data type returned (appointments, lab results, medications, …) identify the closest FHIR R4 resource and draft a simple mapping table. Where a Danish profile exists, map to it: prefer dk-core profiles and the eHealth Infrastructure IG ( dk.ehealth.sundhed.fhir.ig.core ) over plain R4, and use Danish/Nordic code systems (CPR, SOR, the Nordic terminology server ) where they apply.
web github.com Build — Use an AI coding agent to scaffold a lightweight proxy server (any language/framework) that authenticates against the target portal and re-exposes the data as FHIR R4. If you are working in Claude Code, drive the planning with the fhir-facade-plan skill from the c3po add-ons plugin (see below). If your target is sundhed.dk, start from Dhroxy instead of an empty repo.
web github.com API Documentation — Consider using api-mapper to turn your captured traffic into an OpenAPI spec.
web github.com The c3po add-ons repository is a Claude Code plugin that packages the fhir-facade-plan skill. The skill is the planning workflow this track is built around: you hand it your captured HAR (and optionally an OpenAPI spec), and it walks Phases 1–5 below — HAR/OpenAPI analysis → FHIR resource mapping → tech-stack recommendation → architecture → implementation roadmap — entirely in plan mode, surfacing decisions for your approval before any code is written.
web github.com A short demo or write-up suitable for contributing back to the c3po initiative
web github.com c3po initiative repositories — reference implementations including Dhroxy (Denmark) and inroxy (Sweden)
web github.com Dhroxy — a working FHIR proxy that maps sundhed.dk to a FHIR REST interface; the natural starting point for a sundhed.dk target
web github.com c3po add-ons — Claude Code plugin providing the fhir-facade-plan skill used in this track
web ehealth.sundhed.dk eHealth Infrastructure FHIR IG — Danish national FHIR R4 profiles ( dk.ehealth.sundhed.fhir.ig.core ); the conformance target for your output
web hl7.dk dk-core — HL7 Denmark's base FHIR profiles (Patient, Organization, etc.)
web www.nspop.dk NSP / nspop — documentation for Den Nationale Serviceplatform and its security services (DGWS, OIO-IDWS, SOSI)
web www.medcom.dk MedCom — Danish standards body for healthcare data exchange
web github.com chrome-devtools-mcp — MCP server that gives an AI agent direct access to Chrome DevTools (network tab, console, DOM) — useful for live traffic inspection without a manual HAR export
web github.com api-mapper — turn captured traffic into an OpenAPI spec
web docs.fire.ly Dokumentation af Firely .NET SDK kan findes her: https://docs.fire.ly/projects/Firely-NET-SDK/
web www.researchprotocols.org Casen er sammensat på baggrund af: https://www.researchprotocols.org/2020/6/e16964 https://link.springer.com/article/10.1007/s40688-020-00341-6 https://en.wikipedia.org/wiki/Children%27s_Depression_Inventory#cite_note-CDI-1
web link.springer.com Casen er sammensat på baggrund af: https://www.researchprotocols.org/2020/6/e16964 https://link.springer.com/article/10.1007/s40688-020-00341-6 https://en.wikipedia.org/wiki/Children%27s_Depression_Inventory#cite_note-CDI-1
web en.wikipedia.org Casen er sammensat på baggrund af: https://www.researchprotocols.org/2020/6/e16964 https://link.springer.com/article/10.1007/s40688-020-00341-6 https://en.wikipedia.org/wiki/Children%27s_Depression_Inventory#cite_note-CDI-1
web docs.ehealth.sundhed.dk Denne IG overholder i det store hele FUT implementation guiden, men der er ikke lavet en egentlig afhængighed, fordi der var brug for nye koder, da det er en ny klinisk case. Tag et kig derover i løbet af dagen: https://docs.ehealth.sundhed.dk/latest-released/ig/index.html Til gengæld har vi lavet en formel afhængighed mellem denne implementation guide og dk-core https://hl7.dk/fhir/core/1.1.0/index.html
web hl7.dk Denne IG overholder i det store hele FUT implementation guiden, men der er ikke lavet en egentlig afhængighed, fordi der var brug for nye koder, da det er en ny klinisk case. Tag et kig derover i løbet af dagen: https://docs.ehealth.sundhed.dk/latest-released/ig/index.html Til gengæld har vi lavet en formel afhængighed mellem denne implementation guide og dk-core https://hl7.dk/fhir/core/1.1.0/index.html

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