Product Design

Challenge | Health Record

A two-round design challenge: an electronic health record where doctors and nurses find the right patient among a thousand, and add clinical information by simply talking to it.

Background Line
My role

Product Designer, working solo

Context

Design challenge for a software company, autumn 2023. Two rounds

Scope

Patient search and patient dashboard of an EHR, on desktop and mobile

What I delivered

Research, personas, user journey, sitemap, sketches, wireframes, hi-fi screens, prototype, accessibility check

The problem

Finding one patient among a thousand, fast

Doctors and nurses of a fictional practice platform, Not Ill Co., needed to find a patient by about 20 data points and then read and add clinical information, on a 4K desktop and on a phone.

What I did

Two rounds, and I listened to the feedback

Round one was strategy and research. The reviewers asked for less theory and more interface, so in round two I mapped the journey and the sitemap, then went from sketches to wireframes to hi-fi screens and a prototype.

The outcome

A searchable patient list and a dashboard you can talk to

Search with one filter at a time, cards or table, a patient dashboard ordered by urgency, and "Add with Voice + AI" so clinicians can dictate notes instead of typing them.

01The brief

Not Ill Co. wants to be the best all-in-one platform for medical practices: bookings, reminders, records, everything. The challenge was one part of it, the electronic health record (EHR).

The task was to help create a solution that supports medical practitioners in making better decisions, by accessing and capturing vital clinical information: the patient's history, examination notes, procedures, prescriptions, lab reports and more.

Scenario

About 1,000 patients

Doctors and nurses need a database of all past and current patients.

Task

About 20 search criteria

Find a specific patient by name, surname, gender, e-mail, last visit and more.

Requirements

Desktop and mobile

Work on a 3840 × 2160 desktop and on a 390 × 844 phone.

“How might we help doctors and nurses find the right patient in seconds, and capture what they see without slowing down care?”

My problem statement
02Round one: understanding the people
Round 1 · Strategy

I started with the product, the market and the users. I looked at other EHRs, interviewed a nurse at a large hospital in Vienna and sent a questionnaire to three doctors in Brazil.

Other players

Powerful, but hard to learn

Existing EHRs need training, have a steep learning curve, dated interfaces and too much on screen.

Interview

No time, no attention

Clinicians have no time for training. Older colleagues still prefer paper, and handwriting leads to errors.

Questionnaire

Always on the move

Doctors and nurses walk between rooms all day. Mobile is essential, a phone is small, a tablet fits.

Two personas: Dr. Sarah Matthews, a GP with 22 years of practice, and Mark Johnson, a critical-care nurse with 6 years in the ICU.
What the interview and the questionnaire told me.

I closed round one with goals, success metrics and the main user flow: go to patients → find the patient → open the dashboard → read the history → add information. To keep the scope honest, I left GDPR and HIPAA out on purpose.

03The feedback that shaped round two

The reviewers invited me to a second round, with honest feedback: the thinking was there, the interface wasn't.

Round 1

Strategy

Market, research, personas, goals, metrics and user flows. Mostly text.

Feedback

“Show us the UI”

Too much theory, few visuals, no real journey, no hi-fi, not enough prototyping.

Round 2

Interface

Journey, sitemap, sketches, wireframes, hi-fi on desktop and mobile, and a prototype.

“This time around, we're particularly interested in seeing your wireframing and user interface (UI) design skills in full display.”

The reviewers, inviting me to round two

What they said, and what I did about it

Feedback

No real user journey

Answer: a journey map for doctors (and one for nurses), with pain points and opportunities per phase.

Feedback

A sitemap would help

Answer: a full information architecture, plus a structure for the patient dashboard.

Feedback

Wireframes were weak, no hi-fi

Answer: sketches, then wireframes, then hi-fi screens for the patient list, the dashboard and mobile.

Feedback

Search results in a table felt odd

Answer: cards by default, with a table one click away. A nurse later told me which one she'd use.

Feedback

Research skipped search

Answer: I focused round two on search and filtering instead of business scenarios.

Feedback

Not enough prototyping

Answer: clickable flows on desktop and mobile. You can try the mobile one below.

The feedback slide that opened my round-two presentation.
04A day with the EHR
Round 2 · Interface

I mapped how a doctor uses the EHR through a typical consultation. Each phase showed me where the record slows people down, and what the design could do about it.

Patient examination

Talks to the patient, checks symptoms, examines.

PainTime constraints. Capturing everything.OpportunitySimpler data entry, input on mobile.

Diagnosis & treatment plan

Reviews data and results, diagnoses, plans.

PainData overload. Hard to interpret.OpportunityBetter data visualisation.

Clinical notes & data entry

Writes findings, diagnosis and prescriptions.

PainDocumentation workload. Accuracy.OpportunityFriendlier documentation, voice-to-text.

Lab & imaging orders

Orders tests and imaging.

PainGetting orders right. Input errors.OpportunitySimpler ordering, data validation.

Patient follow-up

Reviews results, adjusts the plan, documents progress.

PainFinding the patient. Keeping up with changing data.OpportunityFind the profile faster, find and edit the right data.

Two opportunities stood out because they appear at both ends of the day: finding the right patient and capturing information without the typing. They became the two pillars of the design.

The doctor's journey, with feelings from frustrated to happy.
The nurse's shift: receiving patients, examinations, medication, monitoring, handover.
05Structure first

Before drawing screens, I placed the patient search inside the whole product, so it wouldn't be designed in a vacuum.

The patient dashboard, ordered by urgency

A patient record holds a lot: demographics, a history timeline, vitals, allergies and alerts, family and social history, consultations, imaging, medications, immunizations, lab results, notes and treatments. I sorted it into three levels, from what you need in the first second to what you do last.

First glance

Urgent context

Demographics, vital signs, allergies and alerts, family and behavioural history.

Then

Timeline and treatments

History timeline, clinical notes, treatments, medications, consultations, imaging, lab, immunizations.

Always at hand

Action to add

Add to any section from its own table, or from one button, including Add with Voice + AI.

The dashboard in three blocks.
Everything a patient record has to hold.
06From sketch to screen

I sketched on paper first, to try ideas fast and throw most of them away, then moved the survivors to wireframes and hi-fi.

Patient list.
Filtering, version 1 and 2.
Patient dashboard.
Wireframe: patient list.
Wireframe: patient dashboard.

Wireframe to hi-fi

Hi-fi: patient list with search, filter chips and patient cards
Wireframe: the same patient list in grey boxes
Wireframe Hi-fi
Drag the handle. The structure stayed, the hierarchy got clearer.
07Finding a patient

Three decisions shaped the patient list, the screen clinicians open many times a day.

Decision 1

Search that shows why a result matched

What I saw

With a thousand patients and many similar names, a list of results isn't enough. You need to see at a glance which one is right.

What I changed
  • Results appear as you type.
  • The matching letters are highlighted.
  • Every result shows MRN and date of birth, the two values that tell people apart.
Why

Picking the wrong patient is a safety problem, not just a usability one. Making the match visible helps people confirm before they click.

Decision 2

One filter at a time

What I saw

My first sketch was an advanced search with conditions you could stack. Powerful, but it looked like a database tool, the kind of interface my research said people avoid.

What I changed
  • Version 2: one row of chips, All, Surname, Name, MRN, DoB, PCP, E-mail and more.
  • One filter per search.
  • Filtering by a field adds that field to the card, so you see what you searched for.
Why

Most searches start with one thing you know: a name, a number, a date. One chip is enough, and it needs no training.

Trade-off: combining criteria takes two searches. I'd validate with clinicians how often that's needed.

Decision 3

Cards by default, a table when you need it

What I saw

The reviewers found search results in a table a bit odd. But a table compares many patients at once.

What I changed
  • Cards by default on desktop, a table one toggle away.
  • Cards only on mobile, where a table doesn't fit.
Why

Two views for two jobs: cards to recognise one person, a table to scan many.

Explore the desktop list

Six states of the patient list. Pick one, or let it play.

Patient list as cards Patient list with a search and highlighted matches Patient list filtered with a chip Patient list filtered by e-mail, cards show the e-mail Patient list as a table with all columns Patient table with a search
1

What a nurse told me later

Cards

Easy to read, easy to tell people apartWork the same on desktop and mobileFewer patients on screen

Table

Many patients and columns at onceFamiliar from other systemsDense, needs a big screen
After the challenge, I showed both views to a nurse: “The cards are beautiful, but the table seems more useful.” For her daily work, density won. I'd test which view should be the default with more clinicians.
08The patient dashboard

Once you find the patient, the dashboard follows the three levels: urgent context on top, the timeline and treatments below, and an add action everywhere.

Demographics, alerts and vitals first. Every table has its own + to add a row.
The add menu, with Voice + AI first.
The full page.
09Mobile, and talking to the record

On a phone, typing a clinical note between rooms is exactly the workload the journey warned about. So the mobile flow lets clinicians say it instead.

On mobile, the patient list stays hidden until you search, cards show five values, sections fold into accordions, and the add button floats over the page. The timeline stays on desktop.

Sketching the Voice + AI flow.
Mobile patient list with search and filter chips
1SearchFind the patient with one filter.
Mobile patient dashboard with accordions and a floating add button
2DashboardUrgent context first, then accordions.
Add menu with Add with Voice + AI and six sections
3AddVoice + AI, or a section by hand.
Add information through Voice + AI, with a record button
4ExplainWhat to say, in one sentence.
Recording with a timer and a waveform
5RecordA timer and a live waveform.
Recorded message with play, delete and continue
6CheckListen again, or record a new one.
AI processing the recording
7ProcessThe AI sorts it into sections.
Review screen: medications and clinical notes to confirm, with edit links
8ReviewEdit, then add to the record.
Principle

The clinician decides

The AI suggests, the clinician confirms. Nothing reaches the record without a review.

Principle

Always a way back

Listen again, delete, edit or cancel at every step.

Principle

Sorted for you

One recording can fill several sections, like medications and clinical notes.

10The prototype

Here's the mobile flow as a prototype you can click through, built from my Figma screens. The search works for real.

Try the tasks on the right: find a patient, filter, and add information with your voice.

Patient list on mobile, with search, filter chips and patient cards
Not Ill Co.
Israel Mesquita Neto's dashboard: MRN, date of birth, allergies and alerts, vital signs, family history, and a floating add button
Add menu: Add with Voice + AI, Clinical notes, Treatments and procedures, Medications, Imaging and radiology, Laboratory and pathology, Immunizations
Add information through Voice + AI. To start, record a voice message explaining clearly what needs to be added.
Recording
Perfect, let's move forward! Your message was recorded. Listen again, delete, or continue.
The AI is processing the recording
Let's review it together: Medications, Aspirin 81 mg once a day and Amoxicillin 500 mg three times a day for 14 days; Clinical notes, stomach pain for three weeks
Interactive prototype

Add a note to Israel's record

You're a doctor between two rooms. Find the patient, then dictate what you just prescribed.

Now on: Patients · list

  1. 1
    Find Israel Mesquita NetoTap the search and type “mes”. Notice the highlighted letters.
  2. 2
    Use one filterPick a chip like MRN or DoB. Try MRN 1010203040.
  3. 3
    Record a voice noteOn his dashboard tap +, then Add with Voice + AI.
  4. 4
    Review and addCheck what the AI understood, then add it to the record.
Figma file ↗
11Accessibility

Clinicians read these screens under harsh light, tired, often at arm's length. I checked every text and background pair in the final UI against WCAG.

Eight pairs pass AA for normal text. Four sit between 3:1 and 4.5:1, so I kept them for large or bold text only, like headings and buttons. In a next iteration I'd darken them so every size passes.

12Next steps and reflection

As a challenge, this wasn't built. This is how I'd take it from Figma to the wards.

Implementation

Hand-off to developers, and check technical constraints, especially for voice and AI.

Training and support

Short in-app help, because clinicians don't have time for courses.

Measure success

Track the metrics below from the first release.

Keep iterating

Test with doctors and nurses, A/B test the defaults, improve.

How I'd measure it

A plan, not results: nothing here was built or measured.

Data accessibility

Time to find a patient, and how often the first search is the right one.

Data capture

How complete records are, and how easy people say capturing is.

Efficiency

Time spent on documentation and on each task.

Error reduction

Fewer medication and documentation errors.

What I learned

Round one taught me that in a design challenge, the reviewers want to see how you think and how you design. Research earns trust only when it shows up in the screens. In round two, every screen traces back to a pain point in the journey.

What I'd do differently

I'd test with clinicians earlier. One nurse changed my mind about cards and tables in a minute. I'd also research search itself, how people look patients up today, before deciding on one filter at a time.

Let’s make it happen.

Whether you’re ready to start a project or just want to chat about your ideas, feel free to reach out! I’m always open to discussing new opportunities.