Small update: New lab test tracking guides are being released!

Andrius J. — Sun, 15 Mar 2026 09:24:12 +0000

Why medical lab results should not live in PDFs

Andrius J. ・ Mar 13

#biomarkers #quantifiedself #healthtracker #webdev

Medical Record Guides

Upload medical records and health documents, extract structured data, and keep your health history organized in one private place.

medicalhistory.app

Why medical lab results should not live in PDFs

Andrius J. — Fri, 13 Mar 2026 20:59:03 +0000

Why medical lab results should not live in PDFs

Every year millions of people receive blood test results.

Most of those results arrive as PDF documents.

A typical workflow looks like this:

Visit a clinic
Receive a PDF report by email or through a patient portal
Look at the numbers once
Archive the document somewhere

Six months later another PDF arrives, and the process repeats.

At first glance this seems reasonable. But there is a structural problem.

Health data is stored as snapshots, not timelines

Medical lab systems usually present results as individual reports, not as a historical dataset.

So people see something like this:

Ferritin: 75

Reference range: 30–300

A year later:

Ferritin: 60

Reference range: 30–300

Still “within range”.

Another year later:

Ferritin: 45

Reference range: 30–300

Still technically normal.

But if you look at the trend, something very different appears:

75 → 60 → 45

Iron stores are clearly declining.

The problem is that most people never see the trend.

Because the results are scattered across separate PDFs, emails, and hospital portals.

PDFs are great for documents, terrible for data

PDFs are excellent for preserving formatting.

They are not great for:

structured data
time series
long-term tracking

A blood test report is essentially a dataset, but it is delivered as a document.

Which means people cannot easily:

compare results across years
detect slow biomarker changes
understand long-term health patterns

The missing layer: a personal health timeline

What people actually need is something much simpler.

A way to convert medical reports into structured data over time.

Conceptually the workflow should look like this:

Upload medical reports

↓

Extract biomarker values

↓

Build a timeline of lab results

Instead of isolated numbers, you would see something like:

Ferritin

2019 — 75

2020 — 60

2021 — 45

Suddenly the signal becomes obvious.

The same idea applies to many commonly tested biomarkers:

ferritin
creatinine
vitamin D
ApoB
triglycerides
CRP
glucose

These markers are often tested repeatedly over years, but the information remains locked in separate documents.

Building a tool for this

After running into this problem myself, I started building a tool to make this easier.

The idea is straightforward:

upload lab reports
extract biomarker values
automatically build a timeline of results

Early version:

https://medicalhistory.app

The goal is not to interpret medical results or replace clinicians.

The goal is simply to organize personal health data in a way that makes trends visible.

Because many health signals only become clear when you look at changes over time, not at a single test result.

They key infrastructure problem in healthcare

Healthcare has incredibly advanced diagnostic capabilities.

But personal health data is still often stored in formats that are difficult to analyze outside clinical systems.

In many cases the missing piece is not new diagnostics — it is better organization of existing data.

Lab results already exist.

They just need to move from PDF archives to structured timelines.

If you're interested in this space or working on health data infrastructure, I'd be curious to hear your thoughts.

DEV Community: Andrius J.

Small update: New lab test tracking guides are being released!

Why medical lab results should not live in PDFs

Andrius J. ・ Mar 13

Medical Record Guides

Why medical lab results should not live in PDFs

Why medical lab results should not live in PDFs

Health data is stored as snapshots, not timelines

PDFs are great for documents, terrible for data

The missing layer: a personal health timeline

Building a tool for this

They key infrastructure problem in healthcare