Auburn Community Hospital

Auburn Community Hospital's coding team was overwhelmed by inpatient volume that had outpaced capacity, causing a growing discharged-not-final-billed (DNFB) backlog with revenue sitting uncollected. Coders under time pressure were systematically undercoding case complexity — the hospital was treating sicker patients than its billing reflected, leaving reimbursement on the table.

Auburn partnered with AGS Health to implement AI-assisted medical coding combined with robotic process automation (RPA). The AI analyzed clinical documentation and suggested appropriate codes while RPA handled repetitive data-entry tasks such as navigating between systems, pulling records, and populating billing fields — freeing human coders to focus on validation, complex cases, and quality review.

The implementation generated $1.03 million in additional revenue through improved coding accuracy and reduced revenue leakage. DNFB cases dropped 50%, coder productivity increased over 40%, case mix index improved 4.6%, and total ROI exceeded 10x — meaning every dollar invested returned at least ten.

• AI coding tools act as a first-pass research assistant, enabling human coders to focus on validation and complex cases rather than initial code lookup — this is augmentation, not replacement.
• Undercoding under time pressure is a systemic and measurable problem; AI catches documentation-supported complexity that coders miss when rushed, directly improving CMI.
• Even a 99-bed community hospital with no dedicated innovation team can achieve 10x ROI from AI-assisted coding with the right implementation partner.