Independent Research · Primary Research / Generative Study
Role
UX Researcher
Timeline
MAY 2026 - JUNE 2026
METHOD
In-depth Interviews
OUTPUT
Personas, Journey Maps, Concept
Problem Statement
Getting a second medical opinion is supposed to bring clarity. In practice, for many patients it brings something else entirely — a second version of the truth, often contradicting the first, with no one explaining why.
This research set out to understand a very specific moment: when a patient or family member realizes that two doctors don't agree — about a diagnosis, a treatment plan, a prescription, or even how urgent the situation is. Is the difference normal medical nuance? Or is something genuinely being missed? Patients have almost no reliable way to tell. And the emotional, financial, and logistical weight of figuring it out almost always falls on the family — not because they're equipped for it, but because no one else is doing it for them.
Research Approach
This study conducted five in-depth interviews with people who had recently navigated conflicting medical opinions — either as patients themselves, or as the family member coordinating care. Each conversation walked through the full journey: how the situation began, how many doctors got involved, where opinions diverged, how that felt in the moment, and what the person wished had existed.
The situations themselves were different — a stroke recovery, a cancer diagnosis, a chronic condition, a kidney stone. But laid side by side, the affinity map revealed the same handful of patterns showing up almost word for word across every single conversation, regardless of how different the medical situation was.
Key Patterns
Too many doctors, none talking to each other.
4 to 12 doctors were involved per case, each seeing only their own slice. In the stroke case, a discharge instruction for weekly kidney tests was quietly dropped once the patient moved between specialists, and no one caught it.
Doctors disagreed — and no one told the patient.
Every case had two or more meaningfully different opinions on diagnosis, urgency, or treatment. In not one case did a doctor proactively flag the difference — patients found out by accident, often by comparing two reports themselves.The same emotions, every time.
Unprompted, every interview surfaced the same words: confused, scared, helpless, guilty, alone. One participant said it best: "sometimes knowing more only meant understanding more clearly how complicated and uncertain the situation actually is."Trust was based on bedside manner, not accuracy.
Patients couldn't judge who was medically correct, so they trusted whoever explained things simply. A single dismissive remark from one senior doctor — "I've been doing this for 20 years, please trust me" — was enough to push one patient to someone else entirely.
The Confidence Gap
Both patients and both caregivers interviewed rated their own confidence in comparing medical opinions between 2 and 4 out of 10 — regardless of education level, profession, or how organized they were. One participant, who kept meticulous written logs of every appointment, test, and result, still only reached 4/10, because understanding the numbers on a report wasn't the same as understanding what they meant for him personally.
The healthcare coordinator, by contrast, rated her own confidence at 7–8 out of 10 in the same kinds of situations — not because she's a doctor, but because her role gives her access to the full picture across specialists, something none of the other four participants ever had. That gap — between someone with full information and someone without it — is the central finding of this entire study.
Personas
To carry these patterns forward, the five interviews were synthesized into four personas — one for each distinct relationship to the problem. Two interviews (a kidney stone patient and a diabetes patient) became two separate patient personas, since their emotional and behavioral patterns were different enough to need separate treatment. The two caregiver interviews combined into one composite caregiver persona, and the coordinator interview stood entirely on its own, representing what "full access to information" actually looks like in practice.
Each persona was carried into a journey map spanning six stages, from first symptom to resolution — and across all four maps, confidence consistently collapsed at the exact same moment: when a second opinion contradicted the first. Even the coordinator's journey dipped at that point, which is the clearest evidence this is a systems problem, not a knowledge problem — she has the training and the access, and her confidence still drops, because even she has no formal system, only her own manual effort.
Journey Mapping
Each persona was carried into a six-stage journey map, from first symptom to resolution. Across all four maps, confidence consistently collapsed at the exact same moment: when a second opinion contradicted the first. Even the coordinator's journey dipped at that same point — the clearest evidence this is a systems problem, not a knowledge problem. She has the training and the access, and her confidence still drops, because even she has no formal system, only her own manual effort standing between the patient and confusion.
How Might We
Eight How Might We questions came out of this synthesis in total — the five below were the most user-centered and directly actionable, and became the ones carried forward into ideation.
How might we help patients and caregivers compare opinions from multiple doctors confidentily?
How might we help patients understand why diagnoses from different doctors may differ?
How might we help patients make informed treatment decisions when medical opinions confilct?
How might we help patients and caregivers securely store and easily share health records with doctors?
How might we help patients and caregivers ask doctors important questions with confidence?
Ideation — Concept Direction
For all 8 How Might We questions, 3–4 ideas were generated each through brainstorming. From the 5 most user-centered questions, the ideas that most directly solved real user problems were narrowed down to the top 5 overall. These were chosen because they directly solve user problems.
The Opportunity
The most important insight from this research isn’t that the solution needs to be invented. It’s that it already exists, inside hospitals, as a paid role — the healthcare coordinator. Someone whose job is to combine information across specialists, catch conflicts, explain things in plain language, and reduce anxiety.
The gap is access. That support is reserved for a small number of cases formally flagged as complex. Everyone else is left to become their own coordinator — unpaid, untrained, and alone.
“A real, paid role exists for handling exactly this problem — but it’s not available to most patients. Families are doing, unpaid and untrained, a job that hospitals recognise as important enough to create a paid position for.”
SYNTHESIS INSIGHT FROM AFFINITY MAPPING
Closing Thought
Every participant in this study, including the coordinator, agreed on one thing: the individual doctors were competent. Tests were accurate. Equipment worked. The breakdown wasn’t in medical expertise — it was in the space between specialists, where no one was looking at the whole picture, and no one was telling the patient that a gap even existed.
“Good doctors, but a bad system around them. And families like mine fall into the gaps of that bad system.”
CARE GIVER — STROKE CARE
More specialists are often assumed to mean better care. In practice, they also mean more seams — more places where information can fall through. The opportunity isn’t to replace doctors or make diagnoses. It’s to close those seams for the people stuck inside them.
This project's scope was primary UX research, built around a single guiding question: "Why don't patients have tools to compare conflicting diagnoses confidently?" All research activities are complete: five in-depth interviews, affinity mapping, four personas, journey maps across six stages, seven How Might We questions, and five ideation concepts pressure-tested with SCAMPER. The output of this research is a validated problem space and a clear concept direction that emerged directly from these findings.