Metrics question

New patients are not showing up for their first telehealth appointment. How would you solve this issue?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Root cause diagnosis for a healthcare specific funnel drop, and designing a fix appropriate to a sensitive, high stakes context.

Segment the no show population, new patients specifically, compared against returning patient no show rates, to confirm this is a first time specific problem.
Hypothesize causes, confusion about how to join a video call, forgetting the appointment, or anxiety about a first telehealth visit.
Investigate via patient surveys or exit interviews with a sample of no show patients to validate the real cause rather than guessing.
Propose fixes matched to the confirmed cause, a test your connection step sent beforehand, or a reminder call the day before for first timers.
Define the metric, first appointment no show rate, tracked before and after the fix, segmented by booking channel.

Segments specifically on new patients since the question already isolates this group, then digs further by booking channel or age group.
Proposes a fix grounded in a likely real cause, a pre appointment tech check reducing could not figure out the link no shows.
Sets a clear before and after metric with a segment specific target, cutting first appointment no shows by 20 percent within a quarter.

Proposing a generic reminder text fix without first validating the actual root cause.
Not comparing new patient no show rate against a baseline like returning patients.
No before and after metric to prove the fix worked.

How would you design the patient survey to find the root cause?
What would you do differently for older patients less comfortable with video calls?