Roger Branon Rodriguez
Back to home

CASE STUDY

Provider Portal (symplr)

Reducing cognitive load in a high-stakes credentialing workflow by designing clearer task flows, better status visibility, and calmer “what happens next” moments.

Enterprise SaaSCross-functional deliveryUX Research + DesignSystems + workflowsCompliance contextAccessibility-minded

ROLE

Senior UX Designer / Researcher

USERS

Providers · Credentialers · Schedulers

CONSTRAINTS

Complex data · strict rules · low patience

Note: screens are simplified/redacted to protect customer and patient data.
The Provider Portal surfaces credentialing tasks
The Provider Portal surfaces credentialing tasks, status, and next steps in a single, scannable view—designed to reduce uncertainty in high-stakes workflows.

OVERVIEW

What this was

The Provider Portal supports credentialing and related workflows that determine whether a provider can practice, where, and under what conditions.

The work centered on clarity: making the system legible when stakes are high and information is dense.

THE PROBLEM

Where people got stuck

  • Status uncertainty: “Did it submit?” “Is it pending?” “Who owns the next step?”
  • Data density: tables and documents without strong hierarchy.
  • Workflow ambiguity: multiple paths, inconsistent language, and surprise requirements.

These weren’t “UI issues.” They were trust issues. Confusion creates delays, rework, and support load.

Mapping the full journey from intake through verification
Mapping the full journey from intake through verification, review, and decision helped identify where ambiguity, delays, and handoff confusion most often occurred.
Complex tables and forms required careful hierarchy
Complex tables and forms required careful hierarchy, labeling, and grouping to help users quickly understand what mattered and what action was required next.

APPROACH

How I worked

I combined qualitative signals (where people hesitated, asked for reassurance, or escalated) with product constraints (policy, engineering realities, and legacy patterns).

  • Mapped “anxiety spikes” to specific steps and screens.
  • Defined crisp job stories for each role: provider, credentialer, scheduler.
  • Focused on a small set of repeatable improvements: information hierarchy, next-step clarity, and error recovery.

THE SOLUTION

What changed

The solution was a set of upgrades that made the system behave more predictably in messy reality.

  • Clearer status language and “what happens next” guidance.
  • Better scanning: stronger type hierarchy, grouping, and labels.
  • Reduced cognitive load by moving from “everything everywhere” to “what matters now.”
  • Guardrails for edge cases: incomplete info, rejected items, resubmission flows.
Clear status language and “what happens next” messaging reduced anxiety and support escalation by making system behavior predictable and explicit.
Clear status language and “what happens next” messaging reduced anxiety and support escalation by making system behavior predictable and explicit.
Improvements to contrast, focus states, table structure, and typography ensured the interface remained usable under pressure and across accessibility needs.
Improvements to contrast, focus states, table structure, and typography ensured the interface remained usable under pressure and across accessibility needs.

IMPACT

What improved

  • Fewer “where am I?” moments. Clearer ownership of next steps.
  • Better scanability in dense views (faster orientation).
  • Less rework from missed requirements and unclear states.

If you want, we can add 2–3 concrete metrics here (support ticket volume, time-to-complete, drop-off, error rate), or keep it qualitative if you can’t share numbers.

LEARNINGS

What I learned

In regulated systems, good UX is often less about delight and more about reducing ambiguity.

When the UI makes responsibility and next steps explicit, people don’t just move faster. They feel safer.

NEXT

What I’d do with more time

  • Instrument the “trust moments” (confusion, consent, repair) as measurable signals.
  • Expand pattern coverage across adjacent flows (documents, verification, escalations).
  • Formalize reusable guidance into a lightweight system or token-like library.