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Next Steps

You've built a working CDS service. Here's how to take it further.

What You've Accomplished

In this tutorial, you:

  • Set up a HealthChain development environment
  • Learned FHIR basics (Patient, Condition, MedicationStatement)
  • Built an NLP pipeline with Document containers
  • Created a CDS Hooks gateway service
  • Tested with the sandbox and synthetic data

What to Do Next

Improve the NLP

The NLP was hard coded in our example. Load a trained model with the library you already use — spaCy, HuggingFace Transformers, LangChain — and run it directly inside your pipeline node in place of keyword matching.

Add FHIR Output

Convert extracted entities to FHIR resources by calling update_problem_list from within a pipeline node:

@pipeline.add_node
def extract_problems(doc: Document) -> Document:
    entities = [{"text": "hypertension", "cui": "38341003"}]
    doc.update_problem_list(entities, patient_ref="Patient/patient-001")
    return doc

# Now doc.fhir.problem_list contains FHIR Condition resources

Learn More

Explore HealthChain's cookbook documentation, we have a variety of cookbooks that will let you build upon the basics from this tutorial.

Congratulations!

You've completed the ClinicalFlow tutorial. You now have the foundation to build production-ready healthcare AI applications with HealthChain.