Oscar Health Software Engineer Interview Questions

LeetCode #91: Decode Ways. Difficulty: Medium. Topics: String, Dynamic Programming. Asked at Oscar Health in the last 6 months.

## Problem Schedule or query medical appointments, detecting conflicts or finding the earliest available slot. ## Likely LeetCode equivalent Similar to LC 253 Meeting Rooms II. ## Tags heap, intervals, oscar_health

## Problem A hospital needs to schedule `n` medical procedures. Each procedure has a duration, a required room type, and a list of prerequisite procedures that must complete first. Rooms of the same type are interchangeable. Find the minimum total makespan (finish time of the last procedure) using as many rooms as needed. ```python def schedule_procedures( procedures: list[dict], # {id, duration, room_type, prerequisites: list[str]} rooms: dict # {room_type: count} ) -> dict: # {procedure_id: start_time} pass ``` **Example:** ``` procedures = [ {"id":"A", "duration":30, "room_type":"OR", "prerequisites":[]}, {"id":"B", "duration":20, "room_type":"ICU", "prerequisites":["A"]}, {"id":"C", "duration":15, "room_type":"OR", "prerequisites":[]} ] rooms = {"OR": 1, "ICU": 1} Output: {"A": 0, "C": 30, "B": 30} # A and C compete for OR; B waits for A ``` ## Follow-ups 1. How do you detect cycles in the prerequisite graph? 2. This is a generalization of job-shop scheduling — what makes it NP-hard in the general case? 3. For a practical hospital with 20 procedures, what heuristic gives good results quickly? 4. How would you handle emergencies that must preempt a scheduled procedure?

## Problem Determine which patients or regions are covered by a healthcare provider network using graph reachability. ## Likely LeetCode equivalent No confident LC match. ## Tags graph, bfs, oscar_health