01Spreadsheet audit
Case details, insurer information, clinic coordination and status tracking lived in one dense operational sheet.
Design implication
The product needed a traceable case model rather than a digital copy of the spreadsheet.
DoctorAnywhere
A spreadsheet was holding an entire care journey together.
I transformed a fragile GP-to-specialist concierge workflow into a case-and-ticket platform that reduced manual effort while preserving the judgement agents need in complex care situations.
Service DesignProduct DesignB2B SaaS
- My role
- Lead Product Designer — product strategy, research, service blueprinting, MVP definition, interaction design and validation
- Scope
- MVP → launch
- Focus
- Healthcare · Workflow · MVP
- Evidence status
- The 90% error reduction and 80% manual-workload reduction are the verified operational outcomes used in this portfolio; usability evidence came from an eight-task test.
Verified operational and usability impact
−90%human error
−80%manual workload
77.5System Usability Scale
What I owned—and the environment around the work
A concise project brief that makes my individual contribution, collaborators and definition of success clear before the detailed process.
- 01Service context
- A concierge team coordinated GP referrals, insurer requirements, clinics, appointments and patient updates through a spreadsheet-heavy workflow.
- 02My ownership
- I led discovery, reconstructed the current service, defined the case-and-ticket MVP, designed the agent workspace and validated the critical workflow.
- 03Core collaborators
- Three concierge agents and two stakeholders informed discovery, with Product and Engineering involved in scope, rules and delivery feasibility.
- 04Success definition
- Reduce manual effort and preventable errors while keeping complex clinical and operational exceptions visible to the agent.
The decision behind the screens
The concierge team managed referrals, insurer details, clinic coordination and patient updates in one complex spreadsheet. Errors, slow case completion and unclear hand-offs affected both patients and staff.
- A single spreadsheet created a high risk of human error.
- Patient complaints averaged 32% daily.
- Slow case completion contributed to 48% patient drop-off.
- Only 10.5% of requested appointments were secured and proceeded.
The product worked because we modelled the service around it—not just the spreadsheet on top of it.
Three signals changed the shape of the problem
I connected behavioural, operational and qualitative evidence before choosing a solution. Each signal created a concrete design implication.
02Frontline interviews
Three agents and two stakeholders described different needs across case creation, assessment, follow-up and hospitalisation scenarios.
Design implication
The workflow needed clear common stages with room for exception tickets and agent judgement.
03Journey mapping
GP referral and cashless-insurance journeys shared work but diverged at key hand-offs, evidence requirements and escalation points.
Design implication
One platform needed to support multiple service paths without forcing them into an identical sequence.
The experience only works when the backstage works
The blueprint keeps the customer journey, visible product behaviour and operational responsibilities connected across the same sequence.
StageCustomerFrontstageBackstage
1 · Receive
A referral or specialist request enters the concierge service.
The patient receives acknowledgement and clear next-step expectations.
An agent creates a structured case with source, insurer and referral context.
2 · Assess
Provides missing information when required.
Requests are specific rather than repeated or ambiguous.
The agent validates eligibility, documents and urgency before progressing.
3 · Coordinate
Waits for a suitable clinic or specialist option.
Progress communication reduces uncertainty during coordination.
Tickets track clinic, insurer and internal follow-ups inside the case.
4 · Confirm
Reviews and accepts an appointment option.
Appointment details and requirements are made clear.
The agent records confirmation and closes dependent follow-ups.
5 · Close or escalate
Completes the hand-off or receives support for an exception.
The outcome and next owner are visible.
The case history remains traceable for closure, complaint or escalation.
Scroll horizontally on smaller screens to follow the complete service.
Complexity, compressed into three decisions
The artefacts were useful because they helped the team make choices. This is the evidence-to-decision trail behind the final experience.
Question
What should replace the spreadsheet?
Evidence
A flat row mixed a patient journey, many follow-ups and several owners.
Decision
Use a parent case for the patient request and linked tickets for actionable follow-ups.
Question
How much should the MVP automate?
Evidence
Rules repeated, but exceptions still required agent interpretation and coordination.
Decision
Automate structure, states and traceability first while keeping judgement with the concierge team.
Question
Where should scope stop?
Evidence
Referral, insurer, appointment and hospitalisation paths could make a first release too broad.
Decision
Prioritise the smallest coherent case lifecycle and validate eight critical tasks before scaling scenarios.
Service Design and Product Design, deliberately connected
I treated the operating experience and the interface as one system. Each lens solved a different part of the same problem.
Service Design
Shaping the ecosystem, hand-offs and operating model.
- Mapped GP referral, cashless insurance and escalation journeys
- Combined stakeholder hypotheses with frontline interviews
- Designed current- and future-state service journeys
- Clarified roles, states and hand-offs across the concierge operation
Product Design
Turning service decisions into clear, usable product behaviour.
- Defined the MVP around cases, tickets and status stages
- Translated service rules into end-to-end task flows
- Designed and tested low- and high-fidelity prototypes
- Built a scalable agent workspace using the design system
From ambiguity to a decision the team could act on
Understand the real service
Mapped referral, insurance, patient-source and escalation paths, then analysed the team’s working spreadsheet to see how the service actually operated—not how process documents said it worked.
Validate the hypotheses
Facilitated stakeholder mapping, created a 15-question research guide and interviewed three concierge agents plus two stakeholders to test assumptions about case creation, assessment and hospitalisation.
Move from journey to MVP
Used current- and future-state maps to define the target experience. Converted the hand-offs into a case-and-ticket model, then prioritised the smallest coherent workflow for launch.
Test before scaling
Validated the flow with stakeholders and agents, iterated low-fidelity wireframes, then ran an eight-task usability study on the high-fidelity product before delivery.
Three connected views for the complete concierge workflow
The high-fidelity design turned the service model into a practical agent workspace. Read together, these screens show how an agent creates a structured case, coordinates the referral and closes the loop with a confirmed appointment and traceable history.
01 · Structured intake
Create a case without recreating the spreadsheet
A stepped intake captures GP, patient and insurer information in the order agents need it. Policy benefits and exclusions remain visible at the point of entry, reducing rework before the referral progresses.
02 · Active coordination
Manage the referral from one operational view
The case header, appointment ticket, supporting documents, ownership and suggested specialists sit in one workspace. Agents can move the request forward without reconstructing context across separate tools.
03 · Confirmed outcome
Close the loop while preserving the case history
The booked state keeps the chosen specialist, appointment time, follow-up actions and status trail together. Agents can change or cancel the appointment while retaining a clear record of how the case reached its outcome.
What made the work difficult—and how I responded
These constraints shaped the solution, the order of work and the compromises I made with the wider team.
Exception-heavy healthcare work
The tension
Standardising the workflow risked hiding urgent or unusual patient situations.
My response
I standardised the case lifecycle while using tickets, notes and escalation states to keep exceptions explicit.
Operational continuity
The tension
The team still had to manage active patients while moving away from a familiar spreadsheet.
My response
The MVP followed the agents’ mental model, used recognisable status stages and focused first on the highest-risk manual work.
Sensitive, multi-party information
The tension
Patient, referral, insurer and clinic data needed to be visible without overwhelming the workspace.
My response
Information was grouped around the task and case stage, with traceable ownership rather than one dense all-purpose view.
Evidence that moved the work forward
8critical tasks tested
83.3%error-free completion
5agents and stakeholders interviewed
2service journeys mapped
The 90% error reduction and 80% manual-workload reduction are the verified operational outcomes used in this portfolio; usability evidence came from an eight-task test.
What changed
01
Digitised a fragile spreadsheet-heavy operation.
02
Reduced manual workload without automating away agent judgement.
03
Created one traceable view of patient requests, clinic updates and statuses.
04
Established a foundation for later provider-recommendation capabilities.
Looking back and ahead
I translated a complex human service into a scalable product model without automating away the judgement that made the service safe and workable.
The right abstraction was not a better spreadsheet; it was a case lifecycle supported by smaller accountable tickets.
I would instrument time-in-stage, reopened tickets, exception categories and patient communication gaps to guide the next automation priorities.