Eka Care.

A patient record is only useful if every read and write can be explained months later.

Client: Eka Care
Sector: Healthcare
Scope: App + web
Stack: Flutter, React, Python

Overview

Patient records and telemedicine at national scale, with the consent and audit model the category demands.

01 — The challenge

What made it hard.

Clinical data carries consequences ordinary products do not. Records sit across practice software, labs and insurers, and every access has to be attributable, reversible and defensible under audit.

Fragmented systems

Records sit across practice software, labs and insurers, each with its own format.

Clinician time

If a workflow adds thirty seconds per patient, adoption dies quietly however good the product is.

Regulatory surface

Health regulation changes what you can store, where, and for how long.

02 — The product

What we shipped.

Patient-facing records, history and results alongside telemedicine consultation with scheduling, notes and prescriptions attached to the encounter.

03 — The build

How it holds up.

The data model and consent rules were settled before any endpoint was written, because both constrain everything downstream. Prototypes went in front of clinicians early.

The system
Consent is modelled as data rather than logic, so a rule change does not require a release. The audit trail is written on the same transaction as the record itself, which means it cannot drift from what actually happened.