The AI-Native Device Platform

Healthcare Lab Results Inbox Parser

Abnormal Results. Alert in Seconds. Not Hours.

Critical lab results should trigger an alert in seconds — not sit in an inbox. A persistent service parses every HL7/FHIR file the moment it arrives and routes out-of-range values to the alert queue instantly.

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The Problem
Critical Values Waiting to Be Noticed

Healthcare labs deliver results in a mix of formats — HL7 v2 messages, FHIR R4 JSON bundles, plain CSVs — and somebody has to triage them for abnormal values. In a high-volume practice, a clinician manually reviews dozens of result files before flagging a critical HbA1c or out-of-range eGFR. The process is slow, inconsistent under workload pressure, and a genuine patient safety risk when a critical result sits unread in an inbox.

High Volume, High Risk

Under workload pressure, critical values get missed. A result sitting unread in an inbox for hours is a patient safety issue — not an inconvenience.

Inconsistent Format Handling

Results arrive as HL7 v2, FHIR R4, and plain CSVs — each requiring different parsing logic. Manual handling is error-prone and slow across format variations.

How awaBerry Smart Automation Helps
Real-Time FHIR-Compliant Triage. Zero Manual Steps.
Persistent systemd service — monitors your HL7/FHIR inbox, evaluates LOINC codes, alerts in real time.

The Smart Automation Framework watches your HL7/FHIR inbox directory and, the moment a new result file arrives, parses it, checks every LOINC-coded observation against your reference ranges, and routes out-of-range values directly to your alert queue and FHIR server — in real time, with zero manual triage. Generated once from a plain-English description; runs as a persistent service with zero AI tokens per evaluation.

Step 1 — Describe the Parser

Write a prompt specifying your HL7/FHIR inbox directory, LOINC reference ranges file, FHIR endpoint URL, and alert queue path. Include log file location for parsing errors.

Step 2 — AI Generates the Clinical Service

Gemini CLI generates a Python service using hl7apy and fhirclient with LOINC code mapping, threshold evaluation, and structured alert POSTs to your FHIR endpoint. A systemd service unit is produced and installed.

Step 3 — Results Triaged in Real Time

The service runs continuously, processing every file that arrives — routing abnormal results to the alert queue and FHIR server within seconds. No queue builds up, no result goes unseen. Zero AI tokens per evaluation.

Setup & Configuration
One Prompt. Continuous Clinical Coverage.
Example Setup Prompt
"Watch $HL7_INBOX for new .hl7 and .json files. Parse LOINC-coded observations. For each result, check value against $REFERENCE_RANGES_JSON. If out-of-range, write an alert object to $ALERT_QUEUE and POST to $FHIR_ENDPOINT. Log all parsing errors to lab_parser.log."
Environment Variables
VariableExample Value
HL7_INBOX/var/hl7/inbox
REFERENCE_RANGES_JSON/etc/lab_parser/ranges.json
FHIR_ENDPOINThttps://fhir.clinic.local/Observation
ALERT_QUEUE/var/alerts/queue.json
Token Economics

Setup (one-time)

~15,000 tokens for complex clinical parsing logic. The most you'll ever pay for this pipeline.

Per Execution

Zero tokens — deterministic rule-based LOINC evaluation against reference ranges.

Service Runtime

Zero tokens — pure local Python execution as a systemd/launchd service.

Summary
Always On. Always Consistent. Zero Triage Overhead.

Abnormal lab results should trigger an alert in seconds, not sit in an inbox waiting for a human to notice them. The awaBerry Smart Automation Framework makes real-time, FHIR-compliant result triage a background service — always on, always consistent, written from a plain-English description of your clinical workflow.

Use Cases
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Version 2 Released
New in Version 2

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Describe what you want in plain English — awaBerry generates the script once using AI, then runs it on your devices forever at zero token cost.

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From Plain English to Fully Autonomous Execution.
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AI-native automation platform

awaBerry Automation is the combination of two tightly integrated products that together form a complete, AI-native automation platform.

#Local Execution #Gemini CLI #Gemini CLI GUI #Zero Token Cost #Agentic API #AI-Powered Automation #Encrypted Tunnels #Device Fleet #Plain English #Scheduled Tasks #Device-access-as-a-Service

Smart Automation Framework

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Real-time triage for every lab result

Start from a plain-English description of your clinical workflow. The framework handles everything else.

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