Adjudicating evolving inpatient diagnoses with a clinical coding agent: a retrospective multicentre study
Abstract
Summary:
Background: International Classification of Diseases (ICD) codes are widely used for reimbursement, health-service planning, and disease surveillance. Automated systems can identify diagnoses and supporting evidence across clinical documents. Yet coding is more than finding diagnoses. Decisions based on isolated information may not fully reflect the evolving clinical picture during admission. Provisional, superseded, or conflicting diagnoses can therefore persist in the final code set, complicating review and correction. We therefore developed and evaluated Clinico, a coding agent that organises evidence by time and clinical relationships to adjudicate diagnoses and update their status during admission.
Methods: We did a retrospective multicentre study with internal and external validation using inpatient records from two Shanghai hospitals. Routine coder-finalised codes served as references. Using 5,000 development stays, we refined Clinico’s prompts and workflow without fine-tuning model parameters. We compared Clinico with three prespecified comparators, two trained on 80,340 stays. Clinico maintained an evidence-linked diagnostic ledger across each admission and reconciled related or conflicting claims before finalising the code set and selecting the principal diagnosis. The primary outcome was principal-diagnosis exact-match agreement; complete code-set micro-F1 was the key secondary outcome.
Findings: Evaluation included 5,000 internal and 4,109 external test…
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