Clinical Expert App — Built from Scratch
Scale: Enterprise-scale, global operations with multiple interconnected SaaS platforms.
Product/System impacted: A new standalone application for HCP (Healthcare Professional) profiling and analysis.
Challenge
Main problem: the Client lacked a dedicated application to give commercial and medical teams a structured, feature-rich view of Healthcare Professionals (HCPs) — including individual profiles, list management, and advanced data filters.
Why it existed: Existing apps did not provide a unified HCP-centric experience. Teams needed a specialized tool to profile, analyze, and manage HCPs in one place to support targeting and engagement strategies.
Impact before project: HCP data was fragmented across tools, limiting the ability to build targeted outreach lists, compare providers, and analyze clinical patterns at scale.
Goals / Success Criteria
Top goals:
- Build the Clinical Expert app from scratch with a general HCP table view, filters, and individual HCP profile pages
- Enable personal HCP list management for users
- Deliver new Instant Insights metrics and rich data visualization charts
Key metrics: Feature completeness vs. spec; on-time sprint delivery; user ability to create and manage custom HCP lists; chart rendering accuracy.
Constraints: Delivery within defined sprint timeline; must align with the Client’s existing design language and data infrastructure.
Our Role
FLS responsibility: Embedded within the Client’s team as full delivery partners — contributing product design, UI/UX, frontend and backend development, and QA from the ground up.
Scope & timeline: Full build from scratch; delivered on time across all sprint milestones.
Teams involved: Project Manager, Business Analyst, 2 Frontend Developers, 2 Backend Developers, QA Analyst.
Approach
Key delivery phases: Requirements & UX design → Core table & profile build → Advanced features (filters, lists, charts) → QA & release.
Risk-reducing decisions: Investing upfront in UX design before development began ensured alignment with user needs and reduced rework. Territory bucket switching was introduced early to validate data-layer assumptions.
Quality assurance: Sprint-embedded QA; ongoing performance investigation for features requiring 20x speed optimization.
Solution
As part of the Client’s extended team, we co-delivered the Clinical Expert app — a fully new HCP profiling platform with advanced data visualization, list management, and analytical capabilities, built from the ground up.
Core components:
- General HCP table view with multi-criteria filters and territory bucket switching
- Individual HCP profile pages with detailed clinical data
- ‘My Lists’ — personal HCP list creation and management
- New charts: Latest Treatment, Patient Gender & Age Distribution, Treatment Pattern, SDoH, Payer Mix
- 3 new Instant Insights metrics for deeper analysis
Differentiator: Delivered a large number of features within compressed sprint timelines — while simultaneously investigating performance optimizations targeting 20x speed improvement for key interactions.
Technology
Stack: Frontend and backend aligned with the Client’s platform ecosystem; advanced chart libraries for multi-dimensional data visualization.
Tooling: QA-integrated delivery pipeline; performance benchmarking for speed optimization.
Accelerators: Reusable chart components from SOW 1; shared data layer integrations.
Results
Measurable improvements:
- Full app delivered from scratch on time, meeting all sprint objectives
- 5 new chart types added, enabling multi-dimensional HCP and patient analysis
- Personal HCP list management introduced — a net-new capability for end users
- Performance optimization roadmap initiated targeting 20x speed improvements
Strongest impact statements:
- Commercial and medical teams gained a dedicated, high-quality HCP profiling tool — a capability we built together as an integrated part of the Client’s ecosystem
- The speed and breadth of feature delivery demonstrated what a deeply integrated team can accomplish when working as one unit within the Client’s product organisation
Before / After Snapshot
| Metric | Before | After |
| HCP profiling tool | No dedicated app existed | Full Clinical Expert app launched |
| HCP list management | Not available | ‘My Lists’ feature — personal list creation |
| Data visualization | No charts in HCP context | 5 new chart types (Treatment, SDoH, Payer Mix, etc.) |
| Instant Insights metrics | Baseline set | +3 new metrics added |
| Delivery | Greenfield risk | All sprint goals met on time |
AI Enablement
AI was not a primary component of SOW 2. However, the app architecture and data models built during this phase laid the foundation for AI/LLM exploration in subsequent SOWs.