Large language models for extraction of OPS-codes from operative reports in meningioma surgery.

ABSTRACT:

Background

In the German medical billing system, surgical departments encode their procedures in OPS-codes. These OPS-codes have major impact on DRG grouping and thus mainly determine each case´s revenue. In our study, we investigate the ability of the Large Language Model (LLM) GPT to derive correct OPS codes from the surgical report.

Methods

For our study, 100 patients who underwent meningioma surgery at our clinic between 2023 and 2024 were examined. We recorded the OPS codes assigned by the surgeon after the procedure, as well as the final coding by the hospital´s coders before case closure. In addition, the surgical report was extracted and anonymously provided to GPT-4o and GPT CodeMedic together with the current OPS-catalogue. The coding of each group was analyzed des

SUBMITTER: Lehmann S 

PROVIDER: S-EPMC12313760 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature