Healthcare Apps Enhancement — Physician Profile & Clinical File

Scale: Enterprise-scale, operating globally with multiple SaaS-based analytical applications used by medical and commercial teams.

Product/System impacted: Five of the Client applications — Smart Targeting, Provider Insights, Patient Disease Insights, Patient Population Journey, and Clinical File.

Challenge

Main problem: Multiple Client healthcare applications had limitations in user experience, data visualization, and analytical depth. The Physician Profile View lacked comprehensive data representation, and the Clinical File app had functional gaps impacting workflow efficiency for medical teams.

Why it existed: The apps had accumulated technical debt over time, and rapid growth in healthcare data complexity outpaced the existing feature set. Users needed richer data insights and more intuitive interactions to support clinical and commercial decision-making.

Impact before project: Limited data visibility, inefficient user workflows, and an inability to conduct deep analysis within the platform led to reduced adoption and slower decision-making for healthcare professionals.

Goals / Success Criteria

Top goals:

• Enhance Physician Profile View with richer data visualization and improved filtering
• Significantly improve the Clinical File app’s functionality and user experience
• Deliver new analytical metrics in Instant Insights across multiple apps

Key metrics: Feature delivery within sprint timelines; improvement in UI/UX quality; reduction of technical debt lines; user satisfaction with new data views.

Constraints: All deliverables must be completed within defined sprint cycles without disrupting existing app stability.

Our Role

FLS responsibility: Embedded within the Client’s product and engineering team, contributing UI/UX enhancement, feature development, technical debt reduction, and performance optimization across five applications.

Scope & timeline: Phased delivery across multiple sprints; all goals delivered on time.

Teams involved: Project Manager, Business Analyst, 1 Frontend Developer, 2 Backend Developers, QA Analyst.

Approach

Key delivery phases: Discovery & scoping → UI/UX redesign → Feature implementation → Performance optimization → QA & release.

Risk-reducing decisions: Phased feature rollout across sprints minimized risk; refactoring was paired with feature delivery to reduce technical debt without separate dedicated sprints.

Quality assurance: QA analyst embedded in every sprint; code review process with refactoring validation before merge; hundreds of lines of redundant code removed.

Solution

Delivered a comprehensive enhancement of five of the Client’s healthcare analytics apps, adding richer data visualization, improved physician profiling, and deeper clinical insights.

Core components:

• Enhanced Physician Profile View with name search, pagination, and KOL score visualization
• Clinical File app: major UI/UX overhaul and functional improvements
• New charts: Persistence, Time-to-Treatment, Treatment Pattern, Select HCPs (KOL buckets)
• 3 new metrics added to Instant Insights for PPJ and PDI
• Optimized filtering logic for Provider Insights and Patient Disease Insights apps

Differentiator: Simultaneous delivery of new features and architectural cleanup — the joint team reduced technical debt while meeting all feature goals, improving long-term maintainability alongside short-term delivery.

Technology

Stack: Frontend and backend technologies aligned with the Client’s existing platform; chart libraries for advanced data visualization.

Tooling: QA-integrated sprint workflow; code review pipeline; performance monitoring.

Accelerators: Reusable chart components; optimized filtering modules.

Results

Measurable improvements:

• All sprint goals delivered on time across every phase
• Hundreds of lines of redundant code removed, improving architecture quality
• 5 apps improved with enhanced UX — faster, more intuitive workflows
• 3 new Instant Insights metrics added, enabling deeper data analysis for PDI and PPJ users

Strongest impact statements:

• Clinical and commercial teams gained richer data views without changing their existing workflow — delivered collaboratively as part of the Client’s extended product team
• Architectural cleanup reduced future maintenance burden while delivering new capabilities simultaneously

Before / After Snapshot

AI Enablement

AI was not a primary component of SOW 1. The focus was on platform enhancement, UX improvement, and feature delivery. AI integration was explored in later SOWs as a natural progression of the platform’s capabilities.