Intelligent Data Translation

Hospitals Speak HL7. Your Database Speaks Rows and Columns.

Process2PointIA_Mapper is the universal translator between messy incoming data — HL7, CSV, JSON — and the clean, organized format your system actually needs.

No manual mapping code for every new hospital, clinic, or lab connection.


Incoming HL7 Message
MSH|^~__________CONTENT_PLACEHOLDER_____________amp;|HOSPITAL|...
PID|1||12345||DOE^JOHN||19851231|M
⇄ Process2PointIA_Mapper
First NameJOHN
Last NameDOE
Patient ID12345
Date of Birth12/31/1985
GenderMale
Parsing & mapping incoming fields…
The Challenge

Why Data Transformation Can't Be Optional

Hospitals, clinics, and labs constantly share patient data — almost never in the exact format your database requires.

🔀

Inconsistent Formats

Every source sends data differently — HL7, CSV, JSON, and more, with no two systems quite the same.

🧬

Unreadable Strings

HL7 messages look like dense, unbroken coded segments — not the neat rows and columns your database expects.

Failed Loads

Feed raw HL7 straight into your database and it simply fails — the structures don't match.

🛠️

Custom Code, Every Time

Without a translator, every new hospital or clinic connection means writing manual mapping code from scratch.

📥

Reads Any Format

HL7, CSV, JSON — the Mapper ingests whatever format your sources actually send.

🔄

Translates Automatically

Fields, formats, and terminology are converted to match your internal system — automatically.

🚫

No Manual Coding Per Source

Connect a new hospital, clinic, or lab without writing custom mapping code from scratch.

What It Is

A Universal Translator for Healthcare Data

Process2PointIA_Mapper is our intelligent data translation engine. It acts as a universal translator between a hospital's complex data — like HL7 — and your clean internal system.

Instead of writing manual code for every hospital or clinic you connect with, the Mapper automatically reads the incoming file, breaks it apart, cleans it up, and translates it into the perfect format for your database.

One engine. Any source format. Zero manual mapping code.

How the Process Works

From Raw Message to Clean Record in Five Steps

Every file — HL7, CSV, or JSON — takes the same disciplined journey through the Mapper.

1

Ingestion & Parsing

The Mapper reads the complex string of text and breaks it down into individual, readable pieces — finding exactly where the patient's name, ID, and medical codes are hidden inside the message.

2

Data Mapping

Incoming fields are connected directly to your internal database fields — for example, HL7 segment PID.5.1 maps straight to your LastName column.

3

Data Transformation

Mapping isn't enough — the data itself gets fixed on the fly so it matches your system exactly.

Date Fixes: 19851231 → 12/31/1985 Value Translation: "M" → "Male" Type Conversion: Text → Numbers
4

Logic & Rules

Business rules apply as the data flows through — for example, automatically calculating "Total Length of Stay" from admission and discharge dates and creating a brand-new column for it.

5

Validation & Delivery

Before anything reaches your main database, it's checked against your strict rules. Missing a critical ID? The system catches it, flags the row, and protects your database — then delivers the clean, fully transformed data.

In Short
Process2PointIA_Mapper takes messy, complicated files — like hospital HL7 messages — breaks them apart, cleans up the formatting, translates the terminology, and delivers perfectly organized data to your system.
See It In Action →
Let's Work Together

Stop Writing Mapping Code.
Start Translating Automatically.

Let's look at the formats your sources are sending today and show you how Process2PointIA_Mapper can take it from there.

OptiVera Solutions

Empowering healthcare and technology-driven organizations to achieve operational excellence through intelligent automation, advanced technology platforms, and strategic communications.

PO Box 1052
Riverview, FL 33568
United States
Copyright © 2026 OptiVera Solutions, LLC. All rights reserved.