Claims and billing analytics for a hospital group

The client is a UK hospital group whose claims and billing data was scattered across departments, leaking revenue through rejected claims. Recovered revenue here funds frontline care, so the stakes are more than financial.

Rejections were reworked by hand with no visibility into why they happened, so the same mistakes recurred.

Claims data was scattered across departments, so rejected claims were reworked by hand and revenue quietly leaked. The manual rework was costly and never addressed the underlying causes.

Nobody could see why claims were being rejected at a pattern level, so the same mistakes recurred. Without root-cause visibility, the group was treating symptoms indefinitely.

The group needed to stop the leakage at its source, not just process rejections faster. Prevention, not faster rework, was the real objective.

We unified claims and billing onto a governed data model, giving one reliable view across departments. A single joined-up view is what makes systemic patterns visible.

On top of it we surfaced rejection root-causes, so systemic issues became visible and fixable rather than recurring. Seeing the patterns is the first step to stopping them.

We built checks that flag at-risk claims before submission, catching problems while they are still cheap to correct, and FHIR alignment kept the model consistent with the clinical data estate. The leakage was tackled at source.