A Better ICD Shortlist Is Not Yet a Better Coding Workflow
TL;DR for operators Hospital coding teams must identify appropriate diagnosis codes from clinical notes, laboratory results, and admission records. The first automation decision is whether software should predict codes directly or retrieve a shortlist that a coding professional can examine. Bohra and Bohra’s Multimodal Dual-Encoder Retrieval for Automated ICD Coding1 provides evidence for the retrieval approach. On MIMIC-III, its model achieves 66.75% Precision@3 versus 62.12% for the strongest multimodal classification baseline, and 62.44% versus 59.73% Micro-F1@8. A separate LLM stage improves the ordering of retrieved candidates, raising NDCG@8 from 65% to 71% on 2,000 human-annotated cases. ...