<![CDATA[This bibliometric research aims to map the most researched disease trends globally and their implications for preventing or reducing the risk of hospitals experiencing financial losses by strengthening the role of coders in DRG-based financing systems. The study applied a bibliometric analysis to literature collected from the PubMed database using structured keywords related to clinical coders, DRG/case-mix, and reimbursement, with inclusion criteria limiting article types to only English-language articles. The data reduction yielded 4,280 final articles, which were exported to .txt format and analyzed using VOSviewer and Microsoft Excel. Network map analysis reveals that treatment outcomes keywords dominate the network's central metrics. The knowledge structure is divided into four main clusters: (1) chronic multimorbidity profile and economic impact evaluation; (2) complex oncology target therapy and prognosis; (3) treatment of genetically mutation-based non-small cell lung cancer; and (4) mitigation of the global pandemic of health insurance. The analysis of time trends shows a clear evolution in research, from the adaptation phase of the pandemic crisis to the precise management of modern diseases and the use of internal hospital governance instruments, such as severity-of-illness indices and risk assessment. Implications: The accuracy of the clinical coder's codification of clinical variables (cancer stage, comorbidities, and complications) affects the appropriate severity level, helping prevent financial losses for the hospital due to under-coding and underpayment. The novelty of this research lies in providing a transparent, systematic, and replicable scientific mapping of the direction of research on the relationship between clinical coding and the DRG financing system.]]>
