Hospital: More Accurate Coding, Higher Revenue

A general hospital with 600 beds closes around 18,000 inpatient cases per year. Revenue depends directly on accurate coding under ICD-10 and procedure codes — incorrect or incomplete codes lead to under-reimbursement, unjustified payer audits, and time-consuming appeal processes.

The coding team of 8 staff was chronically overstretched. Average coding time per case: 18 minutes. Coding quality varied by staff grade and experience level. Around 12% of cases were challenged by payers.

Patient Data Never Leaves the Hospital

Case documentation contains highly sensitive health data — data protection law and healthcare regulations categorically prohibit disclosure to external services. Local processing was non-negotiable.

AI-Supported Coding with SoverIQ

SoverIQ Stack runs on the hospital server, connected to the hospital information system. For each case to be finalised:

• Diagnosis proposals: principal and secondary diagnoses suggested from discharge letter, operative reports, and findings — with coding rules cited
• Procedure proposals: procedure codes derived from operative reports and nursing documentation
• DRG simulation: which DRG does the current coding yield? What additional payments are possible?
• Gap detection: which diagnoses are documented but not yet coded? (complication/comorbidity potential)
• Audit risk flag: flag cases with high review risk and suggest supporting arguments

Results

Coding time per case fell from 18 to 7 minutes. Revenue improvement from more complete coding: average €340 per case — across 18,000 cases a potential of over €6 million per year. Payer challenge rate fell from 12% to 6%. The coding team now processes 40% more cases in the same time.