Product design question
How can we improve the Real World Data feature in healthcare. Focus on patient engagement.
- Oscar Health
- Product design
- Hard
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
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What this question tests
Product design in a regulated, high stakes domain: can you improve a healthcare data feature while centering the actual patient, not just clinicians.
How to approach it
- Clarify what Real World Data means here, assume it refers to patient outcomes and treatment data collected outside clinical trials.
- Identify the patient engagement gap: patients rarely know their own data contributes to research or how it benefits them, so they disengage from data sharing requests.
- Prioritize building trust and transparency before adding features, since consent and clarity are prerequisites in healthcare.
- Design a feature: a simple dashboard showing patients how their shared data has been used, for example contributing to studies on their condition.
- Add a light engagement loop, like relevant health insights back to the patient, so sharing feels reciprocal not extractive.
- Define success as opt in rate for data sharing and patient reported trust score, alongside data completeness for researchers.
What a strong answer includes
- Centers patient trust and consent, which is the real constraint in health data products, not just a UI feature.
- Proposes reciprocity, giving something back to patients, as the core engagement mechanism.
- Picks metrics that matter in healthcare specifically, opt in rate and trust, not generic DAU.
Common mistakes
- Designing a data dashboard for clinicians and calling it patient engagement.
- Ignoring consent and privacy, which are central constraints for health data.
Likely follow-up questions
- How would you handle patients who are uncomfortable with any data sharing?
- How would you measure engagement without compromising data privacy?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop