Construction of a precision medical record homepage system for malignant tumors of the tongue based on knowledge graph

doi:10.19439/j.sjos.2026.03.016

Abstract

Abstract: PURPOSE: To address quality issues in the documentation of medical record homepages for malignant tumors of the tongue, such as non-standard diagnostic terminology and inaccurate surgical coding, this study employs knowledge graph technology to construct a clinical coding decision-making workflow for inpatient medical record homepages. METHODS: The quality of 12 201 medical record homepages from the Department of Oromaxillofacial Head and Neck Oncology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, between June 2024 and June 2025 was analyzed, and the existing problems and their causes were summarized. Based on knowledge graph extraction and fusion, combined with expert opinions from clinicians and coding specialists in tongue cancer treatment, a targeted clinical coding decision-making workflow was designed. RESULTS: Among the 12 201 inpatient medical records, totally 8 117 had errors on their homepages (12 889 errors in all). Through Pareto statistical analysis, it was found that incorrect principal diagnosis, omitted additional diagnoses, incorrect principal procedure, and incorrect other procedures were the top four medical record homepage deficiencies, accounting for 87.86%. Addressing these clinical challenges, a knowledge graph encompassing epidemiology and pathology, examination and diagnosis, treatment and medication, and prognosis and follow-up was constructed. Consultations with five clinical experts in tongue cancer treatment and two coding specialists informed the development of a clinician-oriented coding decision-making workflow. CONCLUSIONS: The knowledge graph-based clinical coding decision-making workflow innovatively integrates clinicians into medical record quality management, combining clinical diagnostic logic with homepage coding to improve documentation quality at its source, which provides robust data support for high-quality hospital development.

Key words: Knowledge graph, Malignant tumor of the tongue, Clinical coding decision-making workflow, Medical record quality management, Management system innovation

CLC Number:

Zhou Huining, Yang Yiduo, Wang Yanming, Liu Sutai, He Liu, Wang Yan'an, Xu Hui. Construction of a precision medical record homepage system for malignant tumors of the tongue based on knowledge graph[J]. Shanghai Journal of Stomatology, 2026, 35(3): 319-324.

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