Mediboard — Andy Sedzifa

Mediboard

An enterprise-grade digital healthcare platform streamlining clinical workflows and patient monitoring.

40%

Reduction in API payload sizes and database overhead via targeted aggregation queries.

Real-time

Efficient streaming and rendering of multi-variable charts simultaneously.

Sync

Asynchronous data management layer safely caching changes locally.

Secure

Strict data security practices with column-level encryption and RBAC.

"By consolidating fragmented health data into a unified, real-time interface, the platform empowers healthcare providers to make faster, data-driven diagnostic decisions while improving long-term patient outcomes."

Mediboard

DIGITAL HEALTH PLATFORM

We needed to engineer a high-density data visualization system capable of rendering multi-variable charts without UI lag, while also ensuring absolute data compliance and building an asynchronous sync layer for unstable networks.

✓

Clinical Telemetry Dashboard high-density data visualization for monitoring patient populations.

✓

Asynchronous Compliance Engine intelligent scheduling system for individualized care plans.

✓

Compliant Data Ingestion secure ingestion layer unifying records from disparate legacy systems.

✓

State Synchronization asynchronous management caching changes during connectivity drops.

A unified, real-time clinical interface.

Mediboard simplifies complex, fragmented healthcare data. By applying high-performance charting libraries and a modular component framework, we delivered a fast, secure, and compliant experience that seamlessly connects medical practitioners with actionable patient insights.

TECHNICAL DEEP DIVE

Implementation Overview

Architecture decisions, engineering challenges, and how they were solved.

Tech Stack

ReactTypeScriptNode.jsPostgreSQLD3.jsWebSocketsFHIR APIAES-256 Encryption

Architecture Decisions

Canvas-Based Charting over SVG

Switched from D3/SVG to a hybrid D3 + HTML Canvas renderer for telemetry dashboards. Canvas handles 10K+ data points per chart without DOM bloat, while D3 manages scales, axes, and interactions.

Column-Level Encryption with RBAC

Implemented AES-256 encryption at the database column level for PHI fields, with decryption keys scoped per role via RBAC policies. This satisfies data residency requirements without sacrificing query performance on non-sensitive columns.

Optimistic Sync with Conflict Resolution

Built an offline-first data layer that caches mutations in IndexedDB and replays them on reconnect. Server-side, a vector clock resolves conflicts using last-writer-wins with manual override for clinical data.

Challenges & Solutions

Rendering multi-variable telemetry charts without UI jank

Moved chart rendering to an OffscreenCanvas in a Web Worker. The main thread sends data updates via transferable ArrayBuffers, and the worker renders frames at 60fps independently of React's reconciliation cycle.

Aggregating data from 5+ legacy EMR systems with inconsistent schemas

Built an ETL ingestion layer that normalizes incoming records to FHIR R4 resources. Each source system has a dedicated adapter with schema mapping configs, and a validation pipeline rejects malformed records to a dead-letter queue for manual review.

Maintaining data integrity during connectivity drops in rural clinics

Implemented a write-ahead log (WAL) in IndexedDB that captures every mutation with a monotonic sequence number. On reconnect, the sync engine replays the WAL against the server, with the server applying idempotent upserts based on sequence numbers.

Engineering Outcomes

40% reduction in API payload sizes via targeted aggregation queries

60fps chart rendering with 10K+ concurrent data points per view

Zero data loss incidents across 6 months of production deployments

Full FHIR R4 compliance across all ingested clinical data sources