# AlvaHealth

Canonical: https://collabwire.io/works/alvahealth

## Summary

AlvaHealth is a Collabwire personal health analytics system for lab results, reference ranges, measurement history, supplementation, symptoms and longitudinal interpretation context - not a wellness or diagnosis product.

## Built to solve

Health data scattered across lab PDFs, disconnected reference ranges, isolated measurements, supplements, symptoms and advice without longitudinal context.

## Domain

Personal health analytics + lab result interpretation

## Role

Product architecture, data modelling, analyzer logic, health record system design

## Output

Lab result model, reference-range engine, history tracking, analyzer mode, health context layer

## Status

LIVE

## Tags

HEALTH TECH, ANALYTICS, LAB RESULTS, PERSONAL OS

## Problem

Most health data arrives as fragments. A PDF from one lab. A different reference range from another. A single result marked as normal without context. A supplement protocol in a note. A symptom in memory. A blood pressure reading somewhere else. A recommendation from one visit, disconnected from the next result.

That is not a system. Without longitudinal context, lab results stay disconnected snapshots instead of a health record someone can actually operate from.

## System

AlvaHealth turns those fragments into a private analytical layer. The core object is not just a lab parameter. It is a result with value, unit, reference range, source, lab flag, history, context and interpretation state.

The manual lab mode preserves the laboratory view: value, unit, reference range, flag, source and raw context. The analyzer mode adds trend, biological meaning, parameter relationships, priority, supplementation context and possible follow-up areas. The goal is not to replace a doctor or pretend that software can diagnose a person. The goal is to give the user a coherent operating map of their own health data over time.

## Architecture

A result must carry its reference logic with it. The model stores not only the value, but also fields such as ref_low, ref_high, ref_raw, source and lab_flag. A range extracted from a lab PDF is not the same thing as a range from a parameter database. A missing range is not the same thing as a normal result. A fallback value should not pretend to be the laboratory's own reference interval.

Without this distinction, health software becomes false clarity: clean interface, weak epistemology. AlvaHealth is built to preserve source, range provenance and history so trends and relationships stay meaningful across labs and formats.

## Outcome

Live at alvahealth.pl - lab result model, reference-range engine, history tracking and analyzer mode running as a longitudinal health record with interpretation context.

## Related services

- [product-architecture](https://collabwire.io/services/product-architecture)
- [backend-platforms](https://collabwire.io/services/backend-platforms)
- [operational-infrastructure](https://collabwire.io/services/operational-infrastructure)
- [ai-automation](https://collabwire.io/services/ai-automation)
- [product-prototyping](https://collabwire.io/services/product-prototyping)