Getting Started Guide

Getting Started Guide

Health Assistant is a self-hosted, open-source health records platform. This guide takes you from a fresh login to a working record in about an hour: add the first person, upload a lab report, read your biomarker trends, and — if you want AI features — connect an LLM. It assumes someone has already installed the app; if not, start with the Installation Guide.

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You don't have to do all of this. The app is fully usable for manual record-keeping without an LLM or any integration — you just skip the AI-assisted steps.

1. Sign in

Open the app URL your installer gave you (typically http://localhost for a local Docker install).

  • First time here? A fresh install detects that no admin exists and redirects you to a setup wizard instead of the login screen. Pick the admin email, password, and organization name there — you choose them, there are no defaults. (If you're accessing remotely, the wizard asks for a one-time setup token printed in the backend container logs, so a stranger can't claim your instance before you do.)
  • Returning? Sign in with the email and password you set up during first-run.

After login you land on the Dashboard, a drag-and-drop grid of cards you can rearrange per person (trends, reminders, imaging previews).

Roles in one line. SYSTEM_ADMIN runs the whole install; ADMIN runs a tenant; MANAGER and USER get progressively narrower views. Most of this guide assumes you're an admin on a personal install — the only things you can't do at lower roles are hidden from the UI automatically.

2. Pick — or create — the active person

Health Assistant organizes everything per person. The header has a person switcher; the entire UI refocuses on whoever is selected.

  • To switch: use the person picker in the top bar.
  • To create the first person: open the Create menu (bottom of the sidebar) → New patient, or go to Patients (/patients) and add one. Fill in at least the name and date of birth.
  • To track yourself: create a patient record for yourself, then have an admin link it to your user account (a Patient record's user_id is set by an admin). Once linked, the app auto-selects you on login. You can see which records are linked to you on Profile (/profile) under "Your Linked Records".

Many pages show an empty state until a person is selected — that's normal. Pick a person first.

3. Optional: connect an LLM (for OCR, chat, and Magic Fill)

The app works without any AI — you'd just type everything by hand. To turn on document extraction, the chat assistant, and Magic Fill, connect an OpenAI-compatible LLM provider (OpenAI itself, a local model via vLLM/Ollama, or a self-hosted gateway).

  1. Go to Settings → AI Configuration (/settings/ai-config).
  2. On the Providers tab, add a provider: name, base URL, and your API key. The key is Fernet-encrypted at rest and masked in every response.
  3. On the Models tab, register the model IDs that provider offers (e.g. gpt-4o-mini).
  4. On the Task Assignments tab, pick which model handles which task (OCR, structured extraction, chat). Defaults are sensible — you can leave them.

That's it. AI features are now live. If you skip this, the rest of this guide still works; you'll just enter lab data manually instead of having it extracted from a photo.

The AI never writes your record. Every AI-proposed action — adding a medication, defining a biomarker, starting a journey — opens a review card. You edit and approve; only then does the write happen, through the same endpoint a manual action would use.

4. Upload a lab report

This is the fastest way to populate a record. Go to Examinations → Upload (/examinations/upload) or use Create → New examination.

  1. Pick the person (already set if you selected one in the header).
  2. Add files — drag in a PDF, an image, or snap a photo. The page supports three modes:
    • Single — one examination, one or more attached files.
    • Bulk — several examinations at once, each with its own files.
    • Smart — many files auto-grouped into one examination.
  3. Set the basics — date, category (e.g. Clinical, Lab), optionally the doctor and organization.
  4. Save. Files upload and the backend queues an OCR + extraction task per file.

What happens next runs in the background:

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When processing finishes:

  • Documents (/documents) shows the uploaded files with previews.
  • Biomarkers (/analytics/trends) charts any extracted lab results.
  • The Examination detail page (/examinations/:id) groups the documents, your notes, and the linked biomarker results in one place.

You can watch live progress in Task Manager (/task-monitor) or the Flower dashboard (/flower/ on a Docker install).

5. Create an examination manually

An examination is the container for a clinical visit — its documents, your notes, and the biomarker results that came out of it. Even without a file upload you can create one:

  1. Create → New examination (or a patient's detail page).
  2. Set the date, category, and optionally the doctor/organization.
  3. Write notes in the rich-text editor (Markdown supported).
  4. Save. You can attach documents and link biomarkers to it later from the examination's detail page.

Examinations are the backbone of the timeline — health journeys and the calendar both reference them.

6. Read your biomarker trends

Go to Biomarkers (/analytics/trends). Each row is a biomarker (cholesterol, glucose, thyroid, vitamins — anything you've had tested) charted over time. For each result you get:

  • Value + unit, normalized across labs so switching providers doesn't break your trend line.
  • Normal/abnormal flagging against the biomarker's reference range.
  • Relative score (0.0–1.0) — where the result sits inside its reference range, lab-agnostic.

Click any biomarker to open its detail page (/biomarkers/details/:id) for the full history, reference ranges, and source documents. Correlative Analytics (/analytics/correlative) lets you overlay trends to spot patterns (e.g. sleep vs. resting heart rate).

If a biomarker you need isn't in the default catalog, you can define it manually from Catalogs (/catalogs?type=biomarker) — or ask the AI assistant to propose one (which you then approve).

7. Track medications, vaccinations, and allergies

These live under Patient Record → Treatments & Alerts in the sidebar, and are all per-person:

  • Medications (/medications) — your prescriptions, each linked to a drug in the shared reference catalog.
  • Vaccinations (/vaccinations) — doses, lot numbers, dates, linked to the vaccine catalog.
  • Allergies (/allergies) — allergies and intolerances. Patient-scoped list + allergen catalog detail page (/allergies/details/:id); active allergies also surface on the dashboard card.

There's a useful distinction: the catalog (/catalogs) is the shared reference library of drugs, vaccines, biomarkers, etc., while the items above are your instances of them. If a drug isn't in the catalog yet, you can define it inline while adding a prescription.

8. Start a health journey

A health journey (clinical event) spans multiple visits and carries its own custom fields — a pregnancy with trimester, a chronic condition with pain intensity, a surgical recovery with dose. Go to Create → New clinical event (or Patient Record → Health Journeys at /events).

  1. Pick a journey type (these come from a seeded catalog; you can add your own).
  2. Set the dates and any custom fields the type defines.
  3. Link the examinations that fed into it.

Journey detail pages (/events/:id) show the timeline of linked visits and let you update the custom fields as the journey progresses.

9. Connect a wearable or other integration

Integrations are per-person — each person connects their own. Go to Settings → Integrations (/settings/integrations) with a person selected in the header.

  • Available integrations are grouped by category (wearables, labs, webhooks, FHIR servers, bridges).
  • Pick one and step through its config flow (OAuth2 for some, an API key or webhook URL for others).
  • Once connected, it shows under Active and starts syncing on a schedule. High-frequency data (heart rate, steps, continuous glucose) goes into the time-series store so it doesn't bloat your clinical records.

You can also receive data from any custom script via the webhook integration (HMAC-verified), or build your own with the Integrations SDK.

10. Ask the AI assistant

Open AI Assistant (/ai-assistant). The assistant is grounded in your data — it answers using your biomarker history, medications, documents, and the catalog, and cites what it's drawing from.

Try things like:

  • "What does my latest cholesterol result mean?"
  • "How has my vitamin D changed over the last year?"
  • "Track this as a new journey" — it proposes; you approve in a review card.
  • "Add this medication" / "define this biomarker" — same propose-then-approve flow.

There's also Magic Fill: paste discharge notes or raw lab text into an examination and the assistant maps it into structured fields for you to confirm. It never writes directly — every proposal is a card you review, edit, and approve.

11. Make it yours

  • Install as an app — it's a PWA. Add it to your phone or desktop for a full-screen, offline-capable app with push notifications.
  • Rearrange the dashboard — drag the cards (/dashboard) and save the layout per person.
  • Appearance — /settings/appearance for theme and visualization options.
  • Notifications — /settings/notifications for medication reminders, follow-ups, and out-of-range biomarker alerts.
  • Languages — English and Greek, switchable in preferences.
  • Backups — admins can export a FHIR R4B Bundle + ZIP from /settings/export-import.

12. Where to go next

ΠροηγούμενοSelf-Hosted InstallationΕπόμενοArchitecture Overview