Physician Analysis
Physician Analysis is a strategic application built to empower Physician Liaisons with actionable insights to identify, prioritize, and strengthen referral relationships.
Traditionally reliant on spreadsheets and fragmented workflows, liaisons often made decisions based on anecdotal evidence rather than data. Physician Analysis replaces that gap with a centralized, data-driven platform that visualizes alignment, referral behavior, episode volume, and financial impact, giving health systems a smarter way to grow partnerships and optimize market performance.
This project focused on delivering a user-centered solution to replace manual workflows with a modern, data-driven platform — ultimately empowering liaisons to make smarter, more impactful decisions.
category:
Design, Develop
services:
Figma, HTML, CSS
The Problem
Physician Liaisons were responsible for driving growth through strategic physician engagement—but were limited by outdated, fragmented tools. They lacked a reliable system to:
-
-
-
Identify high-value referral and rendering physicians.
-
Analyze alignment rates and lost episode trends.
-
Surface data-backed referral behavior patterns.
-
Build and optimize territory-based visit routes.
-
Create shareable, prioritized visit lists with measurable impact.
-
-
Without centralized insights, their efforts were reactive, time-consuming, and often based on incomplete or anecdotal data. As a result, health systems missed key opportunities to influence referral behavior, reduce leakage, and expand market share.
The Solution
Physician Analysis was purpose-built to modernize how Physician Liaisons identify, prioritize, and act on referral opportunities—replacing fragmented workflows with a unified, data-rich platform. The solution includes:
A centralized provider database enriched with alignment percentages, referral and rendering volume, financial charges, and specialty data.
Visualized trends showing aligned vs. lost episodes to uncover referral leakage and opportunities.
A dynamic route planning tool that builds efficient travel schedules based on prioritized physician lists.
Multi-level filtering across market, specialty, and engagement behaviors for targeting precision.
Exportable visit lists in PDF and CSV formats for offline access and reporting.
By combining referral insights, visit planning, and strategic analytics into one streamlined interface, Physician Analysis equips liaisons to make smarter, faster, and more measurable decisions.
UX Research
To build a product that truly supported the work of Physician Liaisons, the creation of two primary personas to represent our users: Sarah (a rising liaison still finding her strategic voice) and Michael (a senior liaison with a strong network and performance lens). These personas guided design priorities across usability, workflow planning, and data clarity.
-
-
-
How do liaisons currently decide which physicians to visit?
-
What sources of data (if any) inform those decisions?
-
How is physician performance tracked and organized?
-
What tools are used for planning and executing visit routes?
-
-
The findings revealed a clear need for centralized data, simpler planning workflows, and real-time insights into referral behavior—directly shaping the product’s feature set and interaction model.
User Personas: Understanding Our Liaisons
To humanize the research findings and keep user needs front and center, the development of two core personas was based on real interviews with Physician Liaisons. These personas guided the design decisions throughout the project, helping to prioritize usability, data clarity, and workflow efficiency.
Sarah Jennings
Physician Liaison, Mid-Career
Michael Park
Senior Physician Liaison, Veteran Strategist
Key Insights:
The research uncovered several consistent pain points that shaped the foundation of the platform:
There was no standardized or data-driven method for identifying which physicians to prioritize.
Referral patterns were difficult to track, with no visibility into alignment, lost episodes, or financial impact.
Travel planning was highly manual, often relying on local knowledge rather than optimized routes.
Liaisons wanted a clear, easy-to-use system that combined physician performance data with actionable visit planning tools.
These insights directly informed the platform’s core architecture—driving the design of visualized referral analytics, alignment scoring, and route-based workflow planning.
Design Process
Early Ideation & Wireframes
I started by sketching core workflows and screens based on research insights. These focused on:
- Making physician data sortable, filterable, and exportable.
- Visualizing alignment and referral opportunities.
- Building lists of targeted physicians.
- Simplifying route creation and travel planning.
Iterative Wireframes
Wireframes were rapidly tested with liaisons and stakeholders. Iteration cycles helped align user needs with business priorities, ensuring the solution balanced efficiency, clarity, and usability.
High-Fidelity Prototypes
Using Figma, I developed a polished, interactive prototype to validate workflows and refine UI components. Key features included:
- Physician List with performance indicators.
- Visual referral dashboards highlighting aligned vs. lost referrals.
- Route generation directly from saved physician lists.
- Simple export functionality
Prototypes were reviewed with leadership and users to secure alignment before handoff to development.
Final Design Highlights
The final design was shaped around the real-world workflows of Physician Liaisons—delivering clarity, mobility, and actionable insights in one streamlined platform. Key features include:
- Provider Insights — A sortable and filterable physician database enriched with alignment percentage, referral and rendering volume, charges, and specialty information.
Referral Analytics — Interactive visualizations highlighting aligned vs. lost episodes, referral behavior, and engagement trends.
Route Planning — Integrated mapping and optimization based on prioritized visit lists to streamline in-field travel.
Exportable Reports — Downloadable visit plans in PDF and CSV formats, enabling easy reporting and offline access.
This final solution gave liaisons the tools to move from reactive outreach to data-informed engagement strategies with measurable outcomes.
Outcome
The Physician Analysis platform was successfully designed, developed, and integrated into the daily workflow of Physician Liaisons. Early user feedback and stakeholder validation highlighted several key outcomes:
-
-
-
A significant reduction in manual tasks and spreadsheet dependency.
-
Faster, more strategic visit planning with optimized route generation.
-
Increased confidence in prioritizing outreach based on referral alignment and lost episode trends.
-
Stronger collaboration between liaison teams and leadership through shared, data-driven insights.
-
-
The application transformed a fragmented, manual process into a scalable, insight-led strategy for strengthening physician relationships and growing referral volume.
Reflection
This project highlights the transformative potential of connecting user insight with purposeful, user-centered design. By deeply engaging with Physician Liaisons through interviews and testing, we uncovered the real barriers they faced, fragmented data, inefficient planning, and a lack of visibility into referral behavior. The Physician Analysis platform was built to solve these challenges, helping liaisons move from guesswork to informed, strategic outreach.
The result was a powerful shift in how healthcare systems approach relationship-building: enabling faster planning, deeper visibility, and stronger alignment between physician engagement efforts and referral outcomes. What was once a manual, spreadsheet-driven process is now a scalable, insight-driven platform.
Looking forward, the potential for this tool extends beyond visit planning. By layering in physician influence insights, understanding which providers impact referral patterns across their networks, the platform can become a critical engine for identifying not just who to visit, but who influences who. This unlocks new dimensions of growth strategy, allowing health systems to focus not only on volume, but on network dynamics and long-term alignment.
This project stands as a testament to what’s possible when healthcare design puts both data and people at the center, and when we design not just for tasks, but for impact.
