Genesis Healthcare

Scope of Work

Multiple Projects, One Mission

This case study covers one of several major initiatives I’ve led across two tenures at Genesis Healthcare — first as a Product Designer (2019–2022), and now as Senior Product Designer (2024–present). During my first tenure, I built the design system that would later serve as the foundation for the platform described here.

Due to the nature of this work, specific product screens are protected under NDA. What follows is an approved summary of my contributions, with representative imagery where actual interfaces cannot be shown.

The Problem

44,000 Employees, Dozens of Disconnected Systems

Genesis Healthcare operates 290+ facilities across the country. When I started, every department ran on different systems — different logins, different interfaces, different password reset flows. Clinical staff were mentally exhausted before they even reached a patient.

Training deadlines arrived via email and routinely landed in junk folders. Benefits went unused because employees didn’t know they existed. IT support was overwhelmed by password reset tickets alone. And I was the only designer on the project, shipping iteratively across 4–6 week cycles.

Key Insight

Clinical Staff Spent More Time Navigating Systems Than Using Them

I ran click-tracking across the existing tools, interviewed clinicians and directors, deployed facility-wide surveys, and benchmarked enterprise healthcare platforms. Being a licensed OT practitioner was a real research advantage: I already understood these workflows from the inside, so I could tell the difference between what staff said slowed them down and what actually did.

Every method converged on the same answer. Staff already had the tools they needed; those tools were just scattered across systems with no shared logic for where anything lived, so people lost their time to hunting. Navigation was the real problem to solve, not missing features.

The Other Problem

Training Compliance Was Falling Through the Cracks

When it came to required courses — both Continuing Education Credits (CEUs) for state licensure renewal and mandatory company trainings — there was simply no straightforward way to track any of it. You couldn’t tell how many CEUs you had, which company trainings you’d actually completed, or which courses were even required versus optional. Deadlines and requirements were communicated exclusively via email — and those emails routinely landed in spam.

This wasn’t a compliance failure or a motivation problem. It was a structure problem. The information existed; it just wasn’t findable.

The Pivot

The Version That Shipped Wasn’t the One I Was Asked to Build

My research pointed to one unified platform. Leadership wasn’t sold on going that far, so the first funded direction was a lighter “hub” — a landing page that linked out to all the existing systems without replacing any of them. I designed and piloted it.

It tested poorly. Staff called it “not an improvement”: it added a layer on top of the mess instead of clearing it. So I built a working prototype of the unified platform on my own time and demoed it to stakeholders directly, instead of trying to win the argument in a deck.

Seeing it worked better than describing it. The unified approach became the funded direction, and it’s what shipped.

The Solution

One Platform, One Login, One Source of Truth

Universal Single Sign-On — One authenticated entry point replaced dozens of separate logins. Staff access every tool, resource, and system from a single dashboard without re-entering credentials.

Unified Information Architecture — Built on click-tracking data and user research, the new IA (Information Architecture) organized tools by clinical workflow rather than department. The structure mirrors how staff actually think about their work, not how the organization is charted.

Design System at Scale — I used the component library I built during my first tenure to keep visual and interaction patterns consistent across every surface. This sped up development and cut QA cycles significantly.

Centralized Communications Hub — Company news, benefits enrollment, policy updates, and facility-specific announcements surfaced directly in the platform — no more relying on emails that never get read.

The AI Assistant

A Custom-Built AI That Guides, Not Replaces

The centerpiece of the platform is a custom AI assistant I designed and helped architect. Unlike generic chatbots, this one knows where you are and is able to assess what you’re likely trying to do (or need to do) — so it gives you the right answer before you have to ask the right question.

It answers policy questions, walks staff through benefits enrollment, explains CEU requirements by state, and routes complex issues to the right department. Every response cites its source, so staff can see exactly where an answer came from before they act on it.

Security had to be airtight. The system is HIPAA-compliant by design, with strict access permissions and a full activity log built into every interaction. Clinical staff trust it because it was designed by someone who understands what’s at stake when healthcare tools fail.

The EdTech Solution

CEU Tracking That Finally Works

I designed a dedicated education module built around one priority: making it effortless to find, watch, and track the right courses with as few clicks as possible. Research showed that staff wanted courses sorted by the highest CEU value first — so they could knock out their annual licensure requirements as efficiently as possible. That became the default sort.

For staff in states and disciplines that require an ethics CEU, the AI identifies those requirements automatically and pins the relevant course at the top — no searching, no guessing.

Progress tracking is front and center: completion percentages, upcoming deadlines, and recommended courses are all visible without leaving the page. The AI assistant also nudges staff about approaching deadlines and suggests courses based on their role and state requirements.

Results & Impact

Reflection

What I Learned

On useful AI vs. performative AI: Every AI feature I shipped had to pass one test: would a knowledgeable coworker do this better? If the answer was yes, the feature wasn’t ready. That test is the whole reason the assistant leans on context rather than clever prompting — a good coworker already knows your role, your state, and what’s due before you ask.

On being both designer and clinician: Knowing the clinical side meant I didn’t have to translate terminology or spend weeks earning rapport. It also introduced bias. I knew the workflows well enough to assume pain points the data didn’t actually support, so I leaned on click-tracking to keep myself honest.

What I’d do differently: I’d instrument measurement from day one. The results were strong, but cleaner per-feature attribution would have let me say precisely which change drove which gain instead of reading them as one combined lift. I’d also stand up an A/B framework earlier — the organization wasn’t built for it, but even small controlled tests would have sharpened every decision after.