personal-health-records

name	personal-health-records
description	Connect your health records from any US health system via HealthEx, pull your complete clinical history, analyze it with Claude, and optionally export to a personal de-identified FHIR store with automated data quality curation via HealthClaw Guardrails. Supports Epic, Cerner, CommonWell, Carequality, and most major US EHR networks. Triggers when a user asks to connect health records, pull medical history, review lab results, check immunizations, identify care gaps, or export data to a personal FHIR store.
version	1.0.0
author	HealthClaw contributors
license	MIT
tools	{"required":["HealthEx:get_health_summary","HealthEx:get_conditions","HealthEx:get_labs","HealthEx:get_immunizations","HealthEx:get_medications","HealthEx:get_allergies","HealthEx:get_vitals","HealthEx:get_procedures","HealthEx:search","HealthEx:update_and_check_recent_records"],"optional":["healthclaw-local:fhir_seed","healthclaw-local:fhir_read","healthclaw-local:fhir_search","healthclaw-local:fhir_get_token","healthclaw-local:curatr_evaluate","healthclaw-local:curatr_apply_fix","healthclaw-local:fhir_commit_write"]}
references	{"healthex":"https://healthex.io","healthclaw":"https://github.com/aks129/HealthClawGuardrails","smart_health_connect":"https://github.com/aks129/SmartHealthConnect","fhir_spec":"https://hl7.org/fhir/R4","us_core":"https://hl7.org/fhir/us/core"}

Personal health records — HealthEx + HealthClaw

Connect your health records from any US health system, pull your complete clinical history, analyze it with Claude, and optionally store it in a personal FHIR data store with data quality curation.

Standards: All resources use FHIR R4 with US Core v6.1 profiles — the production standard used by US health systems. The /r6/fhir URL path in HealthClaw is a legacy route prefix from the project's experimental R6 ballot resource support; the actual clinical data (Conditions, Observations, Immunizations, etc.) is R4 and validated against US Core required fields.

---

Setup (do this once)

1. Connect HealthEx in Claude.ai

1. Go to claude.ai → Settings → Integrations
2. Find HealthEx and click Connect
3. Authorize with your HealthEx account (create one free at healthex.io if needed)
4. In HealthEx, connect your health systems: Epic, Cerner, CommonWell, Carequality, and most major US health networks are supported
5. Return to Claude — the HealthEx tools are now active in this session

To verify: ask Claude "Check when my health records were last updated" — it will call HealthEx:update_and_check_recent_records and confirm your connection.

2. Optional: Connect HealthClaw for local FHIR store

If you want to store, curate, and own a local de-identified copy of your records:

# Clone the HealthClaw Guardrails repo
git clone https://github.com/aks129/HealthClawGuardrails
cd HealthClawGuardrails

# Start the local stack (Flask guardrail proxy + MCP server + Redis)
cp .env.example .env        # edit with your STEP_UP_SECRET and ANTHROPIC_API_KEY
docker-compose up -d --build

# Confirm healthy
curl http://localhost:5000/r6/fhir/health

Add to .mcp.json in the repo root so Claude Code picks it up:

{
  "mcpServers": {
    "healthclaw-local": {
      "type": "http",
      "url": "http://localhost:3001/mcp",
      "headers": { "X-Tenant-ID": "my-health" }
    }
  }
}

---

Zero-setup demo (no install required)

A public Railway instance is pre-seeded with sample clinical data so you can try the full guardrail stack — MCP tools, curatr data quality, PHI redaction, step-up auth — without cloning anything.

Claude Desktop

Add this to your Claude Desktop MCP config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "healthclaw-demo": {
      "type": "streamable-http",
      "url": "https://healthclaw.up.railway.app/mcp",
      "headers": { "X-Tenant-ID": "desktop-demo" }
    }
  }
}

Restart Claude Desktop, then try:

Use the healthclaw-demo tools. Get a step-up token, then search for all
Patients in the store. Read the Condition and Observations for the patient.
Run curatr_evaluate on the Condition — it has an ICD-9 code that should be flagged.

Claude Code

Add to .mcp.json in any project directory:

{
  "mcpServers": {
    "healthclaw-demo": {
      "type": "http",
      "url": "https://healthclaw.up.railway.app/mcp",
      "headers": { "X-Tenant-ID": "desktop-demo" }
    }
  }
}

What's in the demo tenant

The desktop-demo tenant is auto-seeded on first deploy with:

Resource	Details
Patient	Maria Elena Rivera, DOB 1985-03-15, Boston MA
Condition	Diabetes mellitus — ICD-9 code 250.00 (intentionally deprecated, triggers curatr flag)
Observation	Glucose 180 mg/dL, HbA1c 8.1%, BP 138/88 mmHg
MedicationRequest	Metformin 500 MG Oral Tablet (RxNorm 860975)

The ICD-9 code is intentional — it demonstrates the curatr icd9-deprecated detection pattern. Ask Claude to evaluate it and propose a fix to ICD-10-CM E11.9.

Re-seed anytime

The seed endpoint is idempotent and additive:

# HTTP — call the running server
curl -X POST https://healthclaw.up.railway.app/r6/fhir/internal/seed \
  -H "Content-Type: application/json" \
  -d '{"tenant_id": "desktop-demo"}'

# Or via MCP tool
fhir_seed(tenant_id="desktop-demo")

Direct API access (no MCP)

The REST API works without MCP too:

BASE=https://healthclaw.up.railway.app/r6/fhir

# Health check
curl $BASE/health

# Search patients
curl "$BASE/Patient?_count=10" -H "X-Tenant-Id: desktop-demo"

# Read a specific resource
curl "$BASE/Condition/<id>" -H "X-Tenant-Id: desktop-demo"

---

How to pull your health data

Quick summary (start here)

Ask Claude:

Get my health summary

Claude calls HealthEx:get_health_summary — returns your active conditions, recent labs, current medications, allergies, immunizations, and clinical visits in one shot. Use this as a fast overview before pulling specific categories.

---

Pulling specific categories

Each category tool paginates backwards through time. Claude handles pagination automatically — you just specify how many years of history you want.

Standard pulls (ask Claude these directly):

Get all my conditions from the last 10 years
Get all my lab results since 2014
Get my complete immunization history
Get my medications from the last 5 years
Get all my allergies on record
Get my vital signs from the last 3 years
Get my procedures and surgeries

For Claude Code — explicit pagination pattern:

When pulling a full history, Claude must paginate until no more data is available. The response includes a beforeDate hint when more pages exist. Claude must keep calling until pagination stops:

Pull my complete condition history going back 15 years. Use get_conditions with
years=12, then check the pagination info in the response — if it says more data
is available, call again with the beforeDate from the response and years set to
cover the remaining range. Keep paginating until all data is retrieved.

---

Full export (all categories, all history)

This pulls everything in one session — conditions, labs, immunizations, allergies, vitals, medications, procedures — with full pagination across all categories.

Pull my complete health history across all categories going back 15 years.
For each category, paginate fully until all data is retrieved.
Summarize what was found: count of records per category, date range covered,
any data gaps or missing values you notice.

Expected output: a structured summary of everything in your record across all connected health systems, with counts by category and date range.

---

Analysis workflows

Care gaps and preventive screening

Based on my health records, identify any preventive care I may be overdue for.
Consider my age, gender, conditions, and immunization history.
Reference USPSTF guidelines for screening recommendations.

Claude checks your records against standard preventive care schedules:

• Colorectal cancer screening (colonoscopy, Cologuard) — USPSTF: age 45+
• Annual flu vaccine — last shot date vs current season
• COVID boosters — series completion and recency
• Lipid panel, HbA1c, blood pressure — based on age/risk factors
• Cancer screenings — mammogram, PSA, skin exam based on demographics

---

Lab trend analysis

Pull my lab results for the last 5 years and identify any values that
have been trending in a concerning direction, even if still within
normal range. Flag anything that has been consistently at the edge
of the reference range.

Compare my most recent labs to my results from 2 years ago.
What has changed? What looks better, what looks worse?

---

Medication review

Review my medication history for the last 5 years.
Identify: any medications that were started then stopped (and why if documented),
any dosage changes over time, and any gaps in chronic medication coverage.

---

Condition timeline

Build a chronological timeline of my medical conditions from first
documented to present. For each active condition, note how long I've
had it and whether there is documented treatment.

---

Cross-system reconciliation

When you have records from multiple health systems (e.g., AHN + UPMC), discrepancies are common. Claude can find them:

I have records from multiple health systems. Look for any contradictions
or inconsistencies across my records — same test with different results,
conflicting diagnoses, or the same information recorded differently.
Flag anything that needs reconciliation.

---

Pre-appointment preparation

I have an appointment with [specialist type] on [date] for [reason].
Pull my relevant health history and prepare a summary I can bring.
Include: relevant conditions, current medications, recent labs, and
any questions I should ask based on gaps in my record.

---

Second opinion research

I was diagnosed with [condition]. Pull everything in my record related
to this diagnosis — symptoms, test results, treatments tried — and
summarize the clinical picture. What does my record show about
how this was worked up?

---

Export to personal FHIR store (HealthClaw pipeline)

If you want to store your data locally with de-identification and quality curation:

Option A — Automated export (one command)

Requires the HealthClaw repo cloned and running (see Setup above):

# Get your HealthEx auth token from:
# Claude.ai → Settings → Integrations → HealthEx → copy OAuth Bearer token

HEALTHEX_AUTH_TOKEN=<your_token> python scripts/export_healthex_mcp.py \
  --patient-id my-health-id \
  --tenant-id my-health \
  --years 15 \
  --import \
  --step-up-secret $STEP_UP_SECRET

This runs the full pipeline:

1. Pulls all HealthEx categories with pagination
2. Maps to US Core R4 FHIR resources
3. Removes PHI (name, address, phone) while preserving clinical data and dates
4. Pre-tags data quality issues for curatr review
5. POSTs the bundle to your local HAPI store through the guardrail proxy
6. Creates a context envelope with SHA-256 provenance hashes

Option B — Claude-assisted export (no auth token needed)

Ask Claude to build the bundle from the live session pull:

Pull all my health data across all categories, fully paginated.
Then build a FHIR R4 transaction bundle with de-identified US Core resources.
Remove my name, address, and phone but keep my date of birth, gender,
and all clinical codes (SNOMED, ICD-10, LOINC, CVX).
Pre-tag any data quality issues you find with curatr meta annotations.
Write the bundle to healthclaw-bundle-[today's date].json.

Then import it:

python scripts/import_healthex.py \
  --bundle-file healthclaw-bundle-<date>.json \
  --tenant-id my-health \
  --step-up-secret $STEP_UP_SECRET

After import — curatr data quality review

In Claude Code with the local stack running:

Search my FHIR store for resources tagged with curatr flags.
For each flagged resource, explain the issue in plain language
and propose a fix. Wait for my confirmation before applying any fix.

Claude will:

1. Call curatr_evaluate on flagged resources
2. Present each issue with plain-language explanation
3. Propose the exact field change needed
4. Apply approved fixes with curatr_apply_fix
5. Create a Provenance record for each fix recording your stated intent
6. Generate an immutable AuditEvent trail of all changes

---

Common data quality issues Claude will find

When pulling from US health systems, these patterns appear frequently:

Issue	Severity	Example
Smoking history contradiction	High	AHN says Never, UPMC says Former — same LOINC code, different encounters
Antibody titer flagged H	Medium	Hep B S Ab 59.38 mIU/mL flagged High — this is immune protection, not pathology
Missing lab result	Low	Test ordered, no result value in imported record — incomplete C-CDA parse
ICD-9 code still present	Critical	Condition coded 250.00 (ICD-9) instead of E11.9 (ICD-10) — retired Oct 2015
Active condition, no treatment	Medium	Psoriasis active since 2017, no MedicationRequest or Procedure linked
Duplicate immunizations	Low	Same CVX code, same date, from two different health system imports

Claude detects all of these automatically during export and presents them for your review.

---

Telehealth and Telegram access (openclaw bot)

If you want to access your health data on mobile via Telegram:

# Add bot token to .env
TELEGRAM_BOT_TOKEN=<get from @BotFather>

# Start the openclaw service
docker-compose --profile openclaw up -d openclaw

Bot commands:

• /health — health summary
• /conditions — active conditions list
• /labs — most recent lab per test
• /curatr — list pending data quality issues
• /curatr fix <issue> — start a fix with patient attestation
• /approve — confirm pending write (step-up authorization)

The Telegram bot reads from and writes to the same local FHIR store as Claude Code. Every /approve creates the same Provenance record as a Claude Code curatr fix.

---

What HealthEx covers

HealthEx connects to the US health data exchange networks (CommonWell, Carequality, eHealth Exchange) and pulls from any participating EHR system including:

• Epic (most major academic medical centers and health systems)
• Cerner/Oracle Health
• MEDITECH
• athenahealth
• AllScripts
• Most major US payers (via USCDI claims data)

Not yet covered: dental records, mental health records from standalone behavioral health systems, records from health systems that have not joined national exchange networks.

---

Privacy and data ownership

• HealthEx reads your records read-only via SMART on FHIR — it cannot modify records in your EHR
• The HealthClaw local store runs on your machine — your data never leaves your network unless you configure an external upstream
• PHI fields (name, address, phone, facility MRN) are removed before storage
• All reads and writes are logged in an immutable AuditEvent trail
• You control every curatr fix — nothing is applied without explicit confirmation
• Delete your tenant data at any time: DELETE /r6/fhir/tenant/my-health

---

Troubleshooting

HealthEx tools not available

• Go to Claude.ai Settings → Integrations → confirm HealthEx shows Connected
• If it shows an error, click Reconnect and re-authorize

Records seem incomplete

• Call HealthEx:update_and_check_recent_records — it returns a URL to trigger a fresh sync
• Health systems batch-sync on different schedules; allow 24 hours after connecting

HealthClaw read tools return 400

• Confirm local stack is running: curl http://localhost:5000/r6/fhir/health
• Confirm .mcp.json has X-Tenant-ID header set
• Confirm Claude Code is opened from the repo root so .mcp.json is loaded

Import fails with step-up error

• Token TTL is 5 minutes — run fhir_get_token immediately before import_healthex.py
• Confirm STEP_UP_SECRET in .env matches what the Flask server is using

---

Reference — HealthEx tool quick reference

Tool	Use when	Key params
get_health_summary	First call, overview	none
get_conditions	Diagnoses, medical history	years, beforeDate
get_labs	Test results, bloodwork	years, beforeDate
get_immunizations	Vaccination history	years, beforeDate
get_medications	Prescriptions, dosages	years, beforeDate
get_allergies	Drug/food/env allergies	years, beforeDate
get_vitals	BP, weight, BMI, HR	years, beforeDate, vitals[]
get_procedures	Surgeries, imaging, scopes	years, beforeDate
search	Cross-category keyword lookup	query, limit
update_and_check_recent_records	Check sync status	none

All paginated tools return a beforeDate hint in their response when more data exists. Always paginate to completion before concluding a category is fully retrieved.