Background and Aims As a core data source in the development of medical informatization, the front page of inpatient medical records plays a crucial role in determining the usability of research data and the scientific quality of clinical decision-making. Given the relatively standardized diagnostic and treatment protocols for thyroid malignancies, this disease serves as a representative model for evaluating the data quality of medical record front sheets. This study aimed to systematically assess the accuracy of diagnostic and surgical procedure coding for thyroid malignancies on the medical record front page, identify existing problems, and explore strategies for improvement and the potential for future application in clinical research.Methods A total of 3 361 patients who underwent initial surgical treatment and were pathologically confirmed with thyroid cancer at the Department of Thyroid Surgery, the First Affiliated Hospital of Kunming Medical University from January 2018 to December 2020 were retrospectively included. Postoperative pathology reports and surgical records were used as reference standards to evaluate the accuracy of primary and secondary diagnosis codes, as well as primary and secondary surgical procedure codes on the medical record front page.Results The accuracy rate of primary diagnosis coding reached 98.8%. However, among 1 368 patients with cervical lymph node metastasis, only 31.2% had correctly recorded secondary diagnosis codes and metastatic sites, with an omission rate as high as 67.8%. The overall accuracy rate for primary surgical procedure coding was 90.4%, with thyroid lobectomy (TL) and total thyroidectomy (TT) coding accuracies of 85.5% and 96.0%, respectively. Among the coding errors, 70.0% involved TL procedures being incorrectly coded as TT. Secondary surgical procedure codes—mainly for lymph node dissection—were highly inconsistent, with up to 14 different coding types, reflecting a lack of standardization and unified input criteria. Notably, the error rate for primary surgical coding in 2020 increased significantly compared with the previous two years, suggesting subjectivity and variability in manual data entry.Conclusion This study highlights major accuracy deficiencies in surgical procedure coding for thyroid malignancies on the medical record front page, which may compromise the scientific validity of real-world data. Going forward, leveraging artificial intelligence technologies to support structured documentation and automated coding, alongside establishing a proactive quality control system through multidisciplinary collaboration, may significantly improve data accuracy. These efforts are essential for strengthening data foundations for precision treatment, performance evaluation, insurance payment, and clinical research on thyroid cancer.