Skip to main content

An adapter for transfer DigitalTWIN Clinic Description to FHIR

Project description

Digitaltwins on FHIR

Python3.9+ PyPI - Version

Usage

  • Setup and connect to FHIR server
from digitaltwins_on_fhir.core import Adapter

adapter = Adapter("http://localhost:8080/fhir/")

Load data to FHIR server

Primary measurements

  • Load FHIR bundle
 await adapter.loader().load_fhir_bundle('./dataset/dataset-fhir-bundles')
  • Load DigitalTWIN Clinical Description (primary measurements)
measurements = adapter.loader().load_sparc_dataset_primary_measurements()
with open('./dataset/measurements.json', 'r') as file:
    data = json.load(file)

await measurements.add_measurements_description(data).generate_resources()
  • Add Practitioner (researcher) to FHIR server
from digitaltwins_on_fhir.core.resource import Identifier, Code, HumanName, Practitioner

await measurements.add_practitioner(researcher=Practitioner(
  active=True,
  identifier=[
    Identifier(use=Code("official"), system="sparc.org",
               value='sparc-d557ac68-f365-0718-c945-8722ec')],
  name=[HumanName(use="usual", text="Xiaoming Li", family="Li", given=["Xiaoming"])],
  gender="male"
))

Workflow

Search

References in Task (workflow tool process) resource

  • owner: Patient reference
  • for: ResearchStudy (Assay) reference
  • focus: ActivityDefinition (workflow tool) reference
  • basedOn: ResearchSubject (patient research subject) reference
  • requester (Optional): Practitioner (researcher) reference
  • references in input
    • ImagingStudy
    • Observation
    • DocumentReference
  • references in output
    • ImagingStudy
    • Observation
    • DocumentReference
Example
  • Find a specific workflow process
    • If known: patient, assay, and workflow tool uuids
client = adapter.async_client

# Step 1: find the patient
patient = await client.resources("Patient").search(
                                    identifier="patient-xxxx").first()
# Step 2: find the assay
assay = await client.resources("ResearchStudy").search(
                                    identifier="dataset-xxxx").first()
# Step 3: find the workflow tool
workflow_tool = await client.resources("ActivityDefinition").search(
                                    identifier="workflow-tool-xxxx").first()
# Step 4: find the research subject (cohort in assay)
research_subject = await client.resources("ResearchSubject").search(
                                    patient=patient.to_reference().reference,
                                    study=assay.to_reference().reference).first()
workflow_tool_process = await client.resources("Task").search(
                                    subject=assay.to_reference(),
                                    focus=workflow_tool.to_reference(),
                                    based_on=research_subject.to_reference(),
                                    owner=patient.to_reference()).first()
  • Find all input resources of the workflow tool process
inputs = workflow_tool_process.get("input")
for i in inputs:
    input_reference = i.get("valueReference")
    input_resource = await input_reference.to_resource()
  • Find the input data comes from with dataset
    • Assume we don't know the dataset and patient uuids at this stage
composition = await client.resources("Composition").search(
                                    title="primary measurements", 
                                    entry=input_reference).first()
dataset_uuid = composition.get_by_path([
        'identifier',
        {'system':'https://www.auckland.ac.nz/en/abi.html'},
        'value'
    ], '')
dataset = await client.resources("Composition").search(identifier=dataset_uuid).fetch_all()
  • Find all output resources of the workflow tool process
outputs = workflow_tool_process.get("output")
for output in outputs:
    output_reference = output.get("valueReference")
    output_resource = await output_reference.to_resource()

References in PlanDefinition (workflow) resource

  • action
    • definition_canonical: ActivityDefinition (workflow tool) reference
Example
  • If known workflow uuid
    • Find all related workflow tools
      workflow = await client.resources("PlanDefinition").search(
                                          identifier="sparc-workflow-uuid-001").first()
      actions = workflow.get("action")
      
      for a in actions:
          if a.get("definitionCanonical") is None:
              continue
          resource_type, _id = a.get("definitionCanonical").split("/")
          workflow_tool = await client.reference(resource_type, _id).to_resource()
      
    • Find all related workflow processes
      assay = await client.resources("ResearchStudy").search(
                                      identifier="dataset-xxxx").first()
      workflow_tool_processes = await client.resources("Task").search(
                                          subject=assay.to_reference()).fetch_all()
      

Search in DigitalTWINS on FHIR methods

search = adapter.search()
  • Finding all primary measurements for a patient
measurements = await self.search.get_patient_measurements("xxx-xxxx")
  • Find which workflow, tool, and primary data was used to generate a specific derived measurement observation
res = await self.search.get_workflow_details_by_derived_data("Observation", "xxxx-xxxx")
  • Find all inputs and their dataset uuid for generating the Observation
res = await self.search.get_all_inputs_by_derived_data("Observation","xxx-xxxx")
  • Find all tools and models used by a workflow and their workflow tool processes
res = await self.search.get_all_workflow_tools_by_workflow(
                    name="Automated torso model generation - script")
  • Find inputs and outputs of a given tool in a workflow
res = await self.search.get_all_inputs_outputs_of_workflow_tool(
                    name="Tumour Position Correction (Manual) Tool")

Reference in resource

  • ResearchStudy - Study
    • principalInvestigator: Practitioner reference
  • ResearchStudy - Assay
    • protocol: [ PlanDefinition(Workflow) reference ]
    • partOf: [ ResearchStudy(Study) reference ]
  • ResearchSubject - Assay cohort
    • individual(patient): Patient reference
    • study: ResearchStudy(Assay) reference
    • consent: Consent reference
  • ResearchSubject - dataset cohort
    • individual(patient): Patient reference
    • consent: Consent reference
  • Composition - primary measurements
    • author: [ Patient reference, Practitioner reference ]
    • subject: ResearchSubject reference
    • entry: [ Observation reference, ImagingStudy reference, DocumentReference reference ]
  • ImagingStudy
    • subject: Patient reference
    • endpoint: [ Endpoint Reference ]
    • referrer: Practitioner reference
  • Observation - primary measurements
    • subject: Patient reference
  • DocumentRefernce
    • subject: Patient reference
  • PlanDefinition:
    • action.definitionCanonical: ActivityDefinition reference string
  • ActivityDefinition:
    • participant: [ software uuid, model uuid ]
  • Task:
    • owner: patient reference
    • for(subject): ResearchSubject(Assay) reference
    • focus: ActivityDefinition(workflow) tool reference
    • basedOn: research subject reference
    • requester (Optional): practitioner reference
    • input: [ Observation reference, ImagingStudy reference ]
    • output: [ Observation reference, ImagingStudy reference ]

Work steps

  • Upload measurements dataset (primary measurements)
  • Upload workflow / workflow tools
  • Create Assay (get practitioner, study, and workflow process information)

DigitalTWIN on FHIR Diagram

DigitalTWIN on FHIR

Contributors

Linkun Gao

Chinchien Lin

Ayah Elsayed

Jiali Xu

Gregory Sands

David Nickerson

Thiranja Prasad Babarenda Gamage

Publications

  1. Paper Title One, Author1, Author2. Journal Name, Year.
  2. Paper Title Two, Author1, Author2. Conference Name, Year.

Please cite the corresponding paper if you use this project in your research.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

digitaltwins_on_fhir-1.4.0.tar.gz (72.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

digitaltwins_on_fhir-1.4.0-py3-none-any.whl (91.3 kB view details)

Uploaded Python 3

File details

Details for the file digitaltwins_on_fhir-1.4.0.tar.gz.

File metadata

  • Download URL: digitaltwins_on_fhir-1.4.0.tar.gz
  • Upload date:
  • Size: 72.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for digitaltwins_on_fhir-1.4.0.tar.gz
Algorithm Hash digest
SHA256 c3a7cd54d48819c79298366b903bccd2b6e9747837341dd98b86bd817dd9442d
MD5 ee979f59d92431a7a6389760e978415d
BLAKE2b-256 de9cc5d033bd2c9e16fc084e9b77a959fbf9f416278f03dd9af31e884de27e11

See more details on using hashes here.

File details

Details for the file digitaltwins_on_fhir-1.4.0-py3-none-any.whl.

File metadata

File hashes

Hashes for digitaltwins_on_fhir-1.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 1f0adfa5006eae1e3532035080da2a27bd5de0f3f67ddcf1a36be7d0978a31dc
MD5 724161d93225140c0f5847410944abee
BLAKE2b-256 93e8f2b066cd0053a9b96a8e89df72b73de4b49dea441515f8f95a8cca0b6c1e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page