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Work / Banfield Veterinary
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SECTIONS
00 · Cover
01 · Overview
02 · My Role
03 · The Problem
04 · Process
05 · The Solution
06 · Reflection
PROJECT
Banfield · Vet software
clientBanfield
viaPhoton
roleUX Designer
domainVeterinary care
platformPractice software
typeClinical tooling
TWO MODULES
Smart Reco
nutrition decision support
Inventory
medication & ordering
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◇ 00 · Cover
CASE STUDY · PHOTON × BANFIELD Veterinary · Clinical

Banfield: decision support, built into the exam room

Banfield Pet Hospital's veterinary teams run on practice software that has to keep up with a live exam. At Photon I designed two modules for it: Smart Reco, which recommends the right nutrition product from a patient's clinical picture, and an Inventory and medication flow for prescribing and dispensing. The goal: turn judgment calls a vet makes from memory into something the software supports, in the moment.

Banfield vet software: recommend, prescribe, dispense
◇ 01 · Overview

Project overview

The product

Banfield runs one of the largest networks of veterinary hospitals in the US, and its clinicians work inside a practice-management system that holds the patient, the visit, the medical record, and the orders. I worked on two modules within it: a nutrition recommendation engine and a medication/inventory flow, both used live, during an appointment, alongside everything else a vet is tracking.

The brief

Design clinical decision support that fits the existing software, not a separate tool. Smart Reco had to take a patient's clinical inputs and return the best-fit nutrition products with a rationale a vet could trust and share. The medication flow had to make prescribing, take-home or in-hospital, structured, validated, and fast.

DESIGN GOAL

Support the call, don't make it. Give the vet a fast, defensible recommendation and a structured way to prescribe, so the right decision is the easy one, without taking judgment out of their hands.

◇ 02 · My Role

My role

I was a UX designer at Photon, the product studio working with Banfield, responsible for the Smart Reco and Inventory modules. I took both from wireframes through high-fidelity screens: the filter-to-recommendation flow, its empty and edge states, the shareable report, and the medication and ordering screens.

As with my later enterprise work, the discipline was designing inside an existing clinical system: respecting its dense, information-heavy layout and patterns while introducing decision support and structured prescribing the product hadn't had before.

Flows & states Wireframe → hi-fi Decision-support UX Dense clinical layouts Design within an existing system
◇ 03 · The Problem

A vet has minutes and two decisions that ran on memory

A vet in an exam has minutes, a talking client, and a patient who can't describe symptoms. Two recurring decisions, what to feed and what to prescribe, leaned heavily on memory and disconnected tools. The work was to make both faster and more consistent without adding clicks to an already busy screen.

PAIN 01

Nutrition picked from memory

Recommending the right food meant recalling products across diagnoses, breeds, and conditions. Inconsistent, hard to justify, and easy to get wrong under time pressure.

PAIN 02

Nothing to hand the owner

Even a good recommendation lived only in the vet's head or a quick note. Owners left without a clear plan, dosage, or transition schedule to follow at home.

PAIN 03

Prescribing was unstructured

Medication, take-home vs in-hospital, dosing, refills, and ordering were fragmented. Without structure and validation, errors and omissions slipped through.

◇ 04 · Process

From wireframe to working screen

Smart Reco went through several iterations. I started in low fidelity to settle the hard question, what does a vet need to enter and how should three recommendations be presented and compared, before committing to the visual layer. The structure held; the polish followed.

Early wireframe of the nutrition recommendation screen: filter inputs and three placeholder product cards
wireframe: settling the inputs and the three-up comparison first
Final nutrition recommendation screen: clinical filters and three matched products with scores
final: same structure, dressed in the product's clinical UI
◇ 05 · The Solution

Two modules, two decisions, both inside the practice system

Two modules, two decisions. Smart Reco answers "what should this animal eat?" from its clinical picture. The Inventory and medication flow answers "what am I prescribing, and how is it dispensed?" Both structured, both inside the practice software.

TWO MODULES Smart Reco · nutrition + Inventory · medication
SMART RECO · RECOMMEND

Clinical inputs in, top-three products out

The vet sets a patient's clinical picture: diagnosis, sensitivity, body condition, breed, lifestyle, weight, activity, reproduction, then runs the recommendation. Smart Reco returns the three best-fit nutrition products, each with a match breakdown so the vet can compare and choose, not just accept. It reads as part of the medical record, not a bolted-on calculator.

Why it matters: a memory task becomes a structured, comparable, defensible recommendation in seconds.

Nutrition recommendation: clinical filter inputs and three matched products with scores and Select
set the patient's clinical inputs, run it, and compare the three best-fit products
SMART RECO · EDGE CASE

When nothing matches, say so clearly

Decision support must be honest about its limits. When no product matches the inputs, the screen says "No matching products" and asks the vet to adjust the criteria. Empty and edge states received the same attention as the happy path.

Why it matters: a clear "no answer" keeps the vet in control and the tool credible.

No matching products state: the recommendation returns no results and prompts the vet to adjust criteria
the no-match state is honest about its limits and gives a clear next step
SMART RECO · SHARE

A report the owner takes home

The recommendation exports to a clean, branded PDF the vet can hand the pet owner: the chosen foods, daily allowance, a day-by-day dietary transition schedule, the doctor's instructions, and feeding advice. The decision leaves the exam room as a plan the owner can actually follow.

Why it matters: the recommendation becomes a take-home plan that helps owners follow through after checkout.

Exported nutrition report: foods, daily allowance, dietary transition schedule, doctor's instructions and feeding advice
INVENTORY · PRESCRIBE

Prescribing, structured and validated

The medication flow keeps each prescription on one record. A Take-Home / In-Hospital toggle changes the context, while inline validation checks the dose, frequency, duration, refills, quantity, dispenser, and printed label before filling.

Why it matters: structure plus validation turns prescribing from a free-text risk into a checked, repeatable step.

Medication list, Take-Home context: prescribe with dose, frequency, duration, refill and label, with validation
take-home: dose, frequency, refills, and label validated before filling
Medication list, In-Hospital context for medication given during the visit
in-hospital: the same record, switched to medication given during the visit
INVENTORY · ORDER

From prescription to ordering build plan

Prescribing connects to ordering: what's needed for the visit rolls into an ordering build plan, so stock and dispensing stay tied to the actual care given rather than tracked on the side. It closes the loop from the decision to the supply.

Why it matters: ordering reflects real care, so inventory and dispensing don't drift apart from what was actually prescribed.

Ordering build plan: items needed for the visit assembled for ordering and dispensing
the ordering build plan ties supply to the care provided
◇ 06 · Reflection

Surface the rationale, keep the human in control

Decision support supports, never decides

The recommendation gives a vet three options and the reasoning, then gets out of the way. Same principle I'd later lean on for AI in financial systems: surface the rationale, keep the human in control.

Edge states are the real work

A clinical tool earns credibility by handling no-match results, validation errors, and take-home versus in-hospital cases clearly.

Wireframe the hard question first

Settling inputs and the three-up comparison in low fidelity, before any visual polish, is what kept the final screen coherent. Structure before surface.

Honest about the scope

This was early-career module work inside a large product, not the full research-to-impact arc. It's where the habits the rest of my portfolio is built on started to form.

FINAL REFLECTION

Banfield taught me how to design for high-stakes, time-pressured work. Give clinicians a fast, defensible recommendation and a structured way to act, while keeping judgment and responsibility with them. I have carried that principle into every system I have designed since.

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