You know that feeling when you get your blood test results and it all looks like Greek? That's the problem FHIRInsight is here to solve. It started with the idea that medical data shouldn't be scary or confusing – it should be something we can all use. Blood tests are incredibly common for checking our health, but let's be honest, understanding them is tough for most folks, and sometimes even for medical staff who don't specialize in lab work. FHIRInsight wants to make that whole process easier and the information more actionable.
🤖 Why We Built FHIRInsight
It all started with a simple but powerful question:
“Why is reading a blood test still so hard — even for doctors sometimes?”
If you’ve ever looked at a lab result, you’ve probably seen a wall of numbers, cryptic abbreviations, and a “reference range” that may or may not apply to your age, gender, or condition. It’s a diagnostic tool, sure — but without context, it becomes a guessing game. Even experienced healthcare professionals sometimes need to cross-reference guidelines, research papers, or specialist opinions to make sense of it all.
That’s where FHIRInsight steps in.
We didn’t build it just for patients — we built it for the people on the frontlines of care. For the doctors pulling back-to-back shifts, for the nurses catching subtle patterns in vitals, for every health worker trying to make the right call with limited time and lots of responsibility. Our goal is to make their jobs just a little bit easier — by turning dense, clinical FHIR data into something clear, useful, and grounded in real medical science. Something that speaks human.
FHIRInsight does more than just explain lab values. It also:
- Provides contextual advice on whether a test result is mild, moderate, or severe
- Suggests potential causes and differential diagnoses based on clinical signs
- Recommends next steps — whether that’s follow-up tests, referrals, or urgent care
- Leverages RAG (Retrieval-Augmented Generation) to pull in relevant scientific articles that support the analysis
Imagine a young doctor reviewing a patient’s anemia panel. Instead of Googling every abnormal value or digging through medical journals, they receive a report that not only summarizes the issue but cites recent studies or WHO guidelines that support the reasoning. That’s the power of combining AI and vector search over curated research.
And what about the patient?
They’re no longer left staring at a wall of numbers, wondering what something like “bilirubin 2.3 mg/dL” is supposed to mean — or whether they should be worried. Instead, they get a simple, thoughtful explanation. One that feels more like a conversation than a clinical report. Something they can actually understand — and bring into the discussion with their doctor, feeling more prepared and less anxious.
Because that’s what FHIRInsight is really about: turning medical complexity into clarity, and helping both healthcare professionals and patients make better, more confident decisions — together.
🔍 Under the Hood
Of course, all that simplicity on the surface is made possible by some powerful tech working quietly in the background.
Here’s what FHIRInsight is built on:
- FHIR (Fast Healthcare Interoperability Resources) — This is the global standard for health data. It’s how we receive structured information like lab results, patient history, demographics, and encounters. FHIR is the language that medical systems speak — and we translate that language into something people can actually use.
- Vector Search for RAG (Retrieval-Augmented Generation): FHIRInsight enhances its diagnostic reasoning by indexing scientific PDF papers and trusted URLs into a vector database using InterSystems IRIS native vector search. When a lab result looks ambiguous or nuanced, the system retrieves relevant content to support its recommendations — not from memory, but from real, up-to-date research.
- Prompt Engineering for Medical Reasoning: We’ve fine-tuned our prompts to guide the LLM toward identifying a wide spectrum of blood-related conditions. Whether it’s iron deficiency anemia, coagulopathies, hormonal imbalances, or autoimmune triggers — the prompt guides the LLM through variations in symptoms, lab patterns, and possible causes.
- LiteLLM Integration: A custom adapter routes requests to multiple LLM providers (OpenAI, Anthropic, Ollama, etc.) through a unified interface, enabling fallback, streaming, and model switching with ease.
All of this happens in a matter of seconds — turning raw lab values into explainable, actionable medical insight, whether you’re a doctor reviewing 30 patient charts or a patient trying to understand what your numbers mean.
🧩 Creating the LiteLLM Adapter: One Interface to Rule All Models
Behind the scenes, FHIRInsight’s AI-powered reporting is driven by LiteLLM — a brilliant abstraction layer that allows us to call over 100+ LLMs (OpenAI, Claude, Gemini, Ollama, etc.) through a single OpenAI-style interface.
But integrating LiteLLM into InterSystems IRIS required something more permanent and reusable than Python scripts tucked away in a Business Operation. So, we created our own LiteLLM Adapter.
Meet LiteLLMAdapter
This adapter class handles everything you’d expect from a robust LLM integration:
- Accepts parameters like
prompt, model, and temperature - Loads your environment variables (e.g., API keys) dynamically
To plug this into our interoperability production, we wrapped it in a dedicated Business Operation:
- Handles production configuration via standard
LLMModel setting - Integrates with the FHIRAnalyzer component for real-time report generation
- Acts as a central “AI bridge” for any future components needing LLM access
Here’s the core flow simplified:
set response = ##class(dc.LLM.LiteLLMAdapter).CallLLM("Tell me about hemoglobin.", "openai/gpt-4o", 0.7)
write response
🧭 Conclusion
When we started building FHIRInsight, our mission was simple: make blood tests easier to understand — for everyone. Not just patients, but doctors, nurses, caregivers... anyone who’s ever stared at a lab result and thought, “Okay, but what does this actually mean?”
We’ve all been there.
By blending the structure of FHIR, the speed of InterSystems IRIS, the intelligence of LLMs, and the depth of real medical research through vector search, we created a tool that turns confusing numbers into meaningful stories. Stories that help people make smarter decisions about their health — and maybe even catch something early that would’ve gone unnoticed.
But FHIRInsight isn’t just about data. It’s about how we feel when we look at data. We want it to feel clear, supportive, and empowering. We want the experience to be... well, kind of like “vibecoding” healthcare — that sweet spot where smart code, good design, and human empathy come together.
We hope you’ll try it, break it, question it — and help us improve it.
Tell us what you’d like to see next. More conditions? More explainability? More personalization?
This is just the beginning — and we’d love for you to help shape what comes next.
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