Illustrative engagement. A representative scenario showing how we approach this kind of work in healthcare. It does not describe a specific client; outcomes are described qualitatively.
Industry overview
What is shaping healthcare
Hospitals, clinics, diagnostics and health-tech companies need evidence from patients and professionals, gathered with verified respondents and strict privacy.
- Patients compare providers online
- Diagnostics and telemedicine are growing
- HCP opinion shapes referrals
Client background
A hospital chain, working in South India. This is an illustrative engagement: a representative scenario showing how we approach this kind of work, not a named client project.
- Organisation
- A hospital chain
- Sector
- Healthcare
- Team engaged
- IT & Development
- Services
- Mobile app development, API development & integration, UI/UX design
Client challenge
Patients called repeatedly to book appointments and collect reports.
Research objectives
- Deliver on the brief: a patient app for appointments and reports.
- Define requirements and success criteria the solution would be tested against.
- Deliver a reliable, secure solution the team can run and extend.
Target audience
Scope: Patient app.
Audiences we typically reach in healthcare
Patients and caregiversDoctors and specialistsNurses and staffDiagnostics customersHealth-tech users
Geographic coverage
Coverage: South India. Market: India.
- India
Research methodology
An iterative delivery approach: discovery, design, build and test in short cycles, with the client reviewing each step.
- 1Brief
- 2Patient app
- 3HIS integration
- 4Insight
We built an app for appointments, reports and bill payments, integrated with the hospital information system.
Mobile app developmentAPI development & integrationUI/UX design
Sampling strategy
- Users and stakeholders from every affected team took part in discovery workshops and acceptance testing.
Data collection
- Requirements were gathered through workshops, process walk-throughs and a review of existing systems and data.
Data quality & validation
- Peer code review on every change
- Automated and manual testing
- User-acceptance testing with the client
- Release checklist and rollback plan
Data analysis
- Usage and performance monitoring after launch
- Defect and support-ticket trends
- Process time before and after
Key findings
- Give patients their information without the phone queue.
Recommendations
- Build on the core insight: give patients their information without the phone queue.
- Track adoption and support tickets, and plan the next release from real usage.
Business impact
- Call volumes fell and patients accessed reports faster.
Impact is described qualitatively.
Deliverables & next steps
- Deployed solution with documentation and handover
- Support and maintenance plan
- Repeat the measure after changes are in place to track progress.
- A natural follow-on question: where does the journey break?