Streamlining Healthcare Workflows with Centralized Patient Data

🚨 The Problem: Care Flows Were Stuck in the Past

Awell’s Care Flows were designed to help healthcare teams coordinate patient care, but they had a major flaw: they weren’t learning from past data.

• Patients had to repeat the same info every time a new care flow started.
• Care teams were manually triggering workflows, even when the data was already available.
• Important patient updates (like a hospital discharge) weren’t automatically starting the right care flows, leading to delays in care.

This slowed everything down, frustrated patients, and made Awell’s workflows feel outdated. It was clear that the system needed to be more dynamic, data-driven, and automated to truly make an impact.

🎯 The Goal: Smarter, More Automated Care Flows

To make Awell’s Care Flows smarter and more efficient, the focus was on two key improvements:

✅ Centralized Patient Data – Make sure patient information (like conditions, past treatments, and preferences) carries over across workflows. No more redundant questions.

✅ Automated Care Flow Triggers – Use real-time patient data to start care flows when they’re actually needed, instead of relying on manual intervention.

The mission was simple: reduce friction, speed up workflows, and make the experience better for both patients and care teams.

🛠 The Process: From Problem to Solution

As the Lead Product Designer, I took a user-centered approach to redesign how patient data was handled:

1️⃣ Research & Understanding the Pain Points

• Conducted user interviews with care teams to map out where they struggled the most.
• Audited how patient data moved (or didn’t move) through Care Flows and where the breakdowns happened.
• Gathered insights on what data teams actually needed to improve their workflows.

Key Finding: Patient data was being collected, but not reused—leading to unnecessary manual work and inefficiencies.

2️⃣ Designing the Fix

With the core problems defined, I focused on creating a system that made patient data actually work for Care Flows:

• Centralized Data Access → Designed a patient data layer where past information is stored and automatically available for future workflows.
• Smart Workflow Triggers → Created rule-based automation to start care flows when patient data meets specific conditions (e.g., if a patient is discharged with high blood sugar, start a follow-up care flow).
• Seamless UX Integration → Made sure these new systems blended into existing workflows without adding complexity for care teams.

Tools & Methods Used:
✅ Wireframing & Prototyping – Created low-fidelity sketches and high-fidelity mockups to visualize how the new system would work.
✅ User Testing – Gathered feedback on how care teams would interact with automated workflows and data reuse.
✅ Iteration & Refinement – Improved based on testing results, ensuring a smooth experience before development.

3️⃣ Building & Iterating

• Worked closely with engineering to bring the new data system and automation features to life.
• Tested real-world workflows to ensure care teams could easily access and trust the data.
• Refined the UX to make automation feel intuitive, not overwhelming.

🚀 The Outcome: Faster, Smarter, More Efficient Care Flows

With the new system in place, Awell Care Flows became far more intelligent and user-friendly:

✨ Care teams save time – No more re-entering the same patient details over and over.
✨ Care flows start when they’re actually needed – Automated triggers ensure patients get the right care at the right time.
✨ Better patient experience – Less frustration from answering the same questions repeatedly.

By redesigning how patient data is handled, this project transformed Awell’s Care Flows from a manual, static system into a dynamic, data-driven experience that truly supports care teams and patients.