Inspiration

A dental treatment plan can leave patients with difficult financial questions: What does insurance cover? How much will I pay? Could a different treatment date make care more affordable?

We created CareWindow to help patients understand their options and plan dental expenses around their benefits, while respecting their dentist’s treatment guidance.

What it does

CareWindow organizes the experience into three steps: Gather Information --> Analyze ---> Recommend.

Patients can review their dental benefits, claims, and prescribed treatment information before exploring treatment costs and timing.

How we built it

We built the frontend using Next.js, React, and TypeScript.

Our TypeScript backend connects to MongoDB Atlas, which stores synthetic member profiles, dental plans, claims, providers, pricing, appointments, and treatment cards.

We developed adapters to translate database records into frontend review inputs and established a deterministic optimizer foundation for evaluating treatment schedules.

What we learned

We learned that successful integration requires agreement on the meaning of data, not just its format.

A dentist’s estimated charge is different from a contracted fee. A pending claim is different from a settled insurance payment. Those distinctions must remain visible when presenting financial information.

We also learned to treat missing values as unknown and require review before using imported information as confirmed calculation inputs.

Challenges we faced

Our biggest challenge was connecting independently developed frontend and backend components with different data contracts.

Dental benefits also introduce complex rules involving deductibles, annual maximums, network status, and treatment timing. We worked to preserve those details without overwhelming the user.

Along the way, we resolved merge conflicts, diagnosed a network issue affecting MongoDB connectivity, and separated working database features from simulated demo behavior.

What we’re proud of

We built a clear review workflow backed by a structured synthetic dataset.

We also created a foundation for explainable calculations through shared contracts, validation, and automated tests.

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