Redesigning the EHR around the provider's day
A decade-old clinical EHR, rebuilt around the provider's day — and a model for how AI earns a clinician's trust: it drafts and recommends, the clinician reviews and approves, and the record stays accountable.
Product Design
Reframed a decade-old EHR around the provider's day-loop — prep, encounter, note, follow-up — instead of the software's module structure.
Defined the reviewable pattern that lets AI draft a clinical note while the clinician stays accountable: provenance, edit, approval, and commit as first-class states.
Turned that boundary into platform interaction patterns other product teams could adopt — not a one-off screen.
Independent providers needed an EHR that cut administrative load without compromising clinical accountability.
Tebra — formed from the merger of Kareo and PatientPop — supports more than 100,000 healthcare providers. I led product design for the clinical product: redesigning a decade-old EHR experience and defining how AI could support notes, chart review, and billing decisions in ways a clinician could inspect and trust.
The bet wasn't to make the interface feel futuristic. It was to make complex clinical work calmer, faster, and more defensible — without ever letting the software become the author of the medical record.
Provider research and workflow analysis showed a system that asked clinicians to adapt to software structure instead of the other way around. And the moment AI entered the workflow, a harder question surfaced: a clinical note isn't just text — it's a legal, billable, accountable artifact. AI could draft one in seconds. Nothing established said how a clinician stays accountable for something a model wrote.
- Documentation work spilled into nights and weekends.
- Patient context was scattered across notes, schedules, and billing workflows.
- Legacy EHR patterns didn't mirror how providers actually think through a day.
- AI was promising but unsafe until source, review, correction, and approval were explicit, inspectable states.
I translated provider research, competitive EHR analysis, and regulatory constraints into a product design roadmap — moving from concept prototypes to documentation patterns, patient-review flows, annual-visit support, and billing-adjacent decision surfaces. One judgment held the work together: AI assists, the clinician authors, and the system makes the difference visible.
Design around the visit
Reorganized prep, encounter, note, and follow-up work into a provider day-loop instead of isolated screens.
Make AI reviewable
AI could draft and recommend, but provenance, edit states, and approval controls kept the clinician accountable for the record.
Separate facts from assistance
Deterministic systems owned record state and workflow rules; AI handled synthesis and drafting, never the source of truth.
I led a design team of 5 across Tebra's Care Delivery and Patient Experience, partnering with Product, Engineering, and go-to-market — and, in the later AI-native work, with data/ML and compliance. The clearest VP-level signal in the work is the boundary model: AI speeds clinical work only when the product makes authorship, evidence, and responsibility visible — turning AI from a novelty into a workflow participant a clinician can trust.
Judgment under ambiguity
Set the rule that AI assists and the clinician authors, then made authorship, evidence, and approval visible as design states rather than disclaimers.
Led across functions
Drove the clinical design direction with Product, Engineering, and go-to-market, aligning a regulated workflow around the provider's day.
Reusable trust patterns
Provenance, edit states, approval, and commit became platform interaction patterns, not one-off UI details.
Clinical workflow concepts
AI drafts and recommends. Clinicians review and approve. The record stays accountable.
Documentation that defends itself
AI-generated SOAP notes with a draft → source → edit → approve → commit model — reducing the burden that spills into nights and weekends while keeping the clinician accountable for the record.
An EHR around the provider's day
Reframed a decade-old clinical experience around the provider's day-loop — documentation, context, review, billing — on a platform serving 100,000+ providers.
Reusable trust patterns
Turned provenance, edit states, and approval into platform interaction patterns the whole product could adopt, led across Care Delivery and Patient Experience.