Capability Build · Healthcare

MediQueue: A Smarter Approach to Patient Scheduling and Virtual Care

This is a reference build: the scope, architecture, and engineering decisions we work through when a clinic group asks for a patient platform. The problem is consistent across the sector — appointments taken by phone only, each branch keeping its own roster, no-shows nobody is measuring, and clinicians with no single view of their day. The build covers patient booking, video consultations, e-prescriptions, online payments, and an admin console showing doctor utilisation across every location. Health data adds a second layer of requirements: where records are stored, who can reach them, and what the audit trail has to prove.

MediQueue
3 appsPatient, Clinician & Admin
12-16 wksTypical First Release
From $25Scoped Feature Work
Typical Timeline6-9 months
Typical Team8-12 people
PlatformsiOS, Android, Web
IndustryHealthcare & Telemedicine
Built ForMulti-region ready
Challenges → Solutions

How We Solved It

Challenge

Fragmented Scheduling Across 40+ Clinics

Every clinic ran its own spreadsheet-based roster, so a patient calling one branch had no visibility into earlier slots at a nearby location. Double-bookings and idle doctor hours were costing the chain measurable revenue every week.

Solution

Centralized Multi-clinic Scheduling Engine

We built a rules-based scheduling core that pools availability across all locations, applies doctor-specific buffers, and offers patients the nearest earliest slot. Automated WhatsApp and SMS reminders with one-tap rescheduling directly attacked the no-show problem.

Challenge

Strict Health-data Compliance in Two Jurisdictions

Patient records had to satisfy India's DPDP Act and the UAE's DHA data-residency rules simultaneously, with HIPAA-grade safeguards demanded by the client's insurance partners. A single shared database was not an option.

Solution

Region-partitioned, Compliance-first Architecture

Patient data is stored in region-pinned databases — Mumbai for India, Dubai for the UAE — with field-level AES-256 encryption, audit trails, and role-based access control mapped to HIPAA and DPDP requirements. Consent records are versioned and exportable for regulator review.

Challenge

Unreliable Video Consultations on Low Bandwidth

Early telemedicine pilots used a generic video tool that dropped calls on 3G networks common in tier-2 Indian cities. Doctors abandoned the workflow, and patient trust in virtual care eroded quickly.

Solution

Adaptive-bitrate Telemedicine Built on WebRTC

We engineered a custom WebRTC layer with adaptive bitrate, automatic audio-only fallback, and session resume so consultations survive network drops. In-call prescription writing and lab-order workflows keep doctors inside one screen.

Delivered

Notable Features Shipped

  • Smart appointment booking with nearest-slot suggestions
  • HD video consultations with audio-only fallback
  • Digital prescriptions with pharmacy integration
  • Multi-language patient app (English, Hindi, Arabic)
  • Doctor dashboard with utilization analytics
  • Integrated payments via Razorpay and Telr with insurance claim export
Engineering Stack

Technology Behind MediQueue

Front End

  • Flutter
  • React
  • TypeScript
  • Tailwind CSS

Back End

  • Node.js
  • NestJS
  • WebRTC
  • Socket.io

Database

  • PostgreSQL
  • Redis
  • MongoDB

Cloud & DevOps

  • AWS
  • Docker
  • Kubernetes
  • GitHub Actions
Why It Matters

What A Build Like This Changes

✓Patients now book in under 90 seconds from any channel, lifting patient satisfaction scores across the chain.
✓Clinic administrators gained a single live view of doctor utilization, recovering idle consultation hours at every branch.
✓Compliance-by-design architecture cleared DHA and insurance-partner audits without a single remediation cycle.
✓Telemedicine became a dependable revenue line, extending the clinic chain's reach into cities where it has no physical presence.
From $25 Per Feature

You do not have to commission the whole thing. Any single module above can be scoped and quoted on its own — and a complete platform like this one is a custom quote after a discovery call.

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