← Oscar Health Interview Insights
The core constraint is the state licensing restriction, and I spent a decent chunk of time on how to model that cleanly.
Start by clarifying functional and non-functional requirements, then design a high-level architecture that separates patient intake, license-based matching, and physician queues. Focus on the data model for licenses and the matching algorithm, and discuss trade-offs between consistency, latency, and scalability.
Pro tip: Emphasize the importance of real-time license verification and state-specific compliance, and propose a design that can handle license expirations and multi-state physicians gracefully.
Ask questions to understand scale, latency needs, license data sources, and whether matching should be immediate or batched. Confirm that physicians can handle multiple patients and that patients may be in any state.
Outline components: API gateway, patient request service, license service, matching engine, queue manager, and physician dashboard. Use a message queue for asynchronous processing and a database for persistent state.
Design schemas for physicians (with licenses per state), patients (with state), and consultation requests. Consider using a graph or indexed table for fast license lookups.
Describe how to match patients to physicians: filter by state license, then by availability, and use a queue per physician or a priority queue. Discuss fairness and load balancing.
Discuss trade-offs: strong vs. eventual consistency for license data, push vs. pull for queue updates, and how to scale horizontally. Mention monitoring and handling license expirations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.