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Research on the Primary Factors Influencing the Quality of Clinical Coding Under DRG Payment Systems: A Survey
Yinghong Fu1,2, Guangying Gao1, Huiying Xing2
1School of Public Health, Capital Medical University, No. 10 Xitoutiao, Fengtai District, Beijing 100069, China.
Abstract:
Background: The main data basis for the Diagnosis-Related Group (DRG) payment methodology is the disease diagnosis and clinical codes in the Medical Record (MR). Problems such as up-coding have arisen during implementation in many countries, and problems with MR quality and solutions have been studied mostly from the physician's perspective. We investigated and analyzed the main influences on clinical coding from the perspectives of directors and coders in Medical Records Section (MRS) to provide recommendations for improvements in data quality. Methods: The questionnaire was developed, revised and improved using literature research and expert consultation methods. From 13 to 19 June 2024, the electronic questionnaire survey was conducted among the directors and coders of medical records department in healthcare organization. A total of 484 directors and coders were included in this study. And relevant statistics were computed and analyzed by non-parametric tests. Results: Coders should possess strong job responsibilities (92.36%), coding skills (91.33%), knowledge of clinical medicine (90.70%), and other comprehensive qualities and abilities. When encountering difficult problems, the clinical coders should first communicate with clinical doctors (91.95%). The two main factors affecting the quality of MR and clinical coding are the individual factors of doctors (88.84%) and the individual factors of coders (85.54%). Conclusions: Doctors and coders are the primary factors influencing the quality of clinical coding. It is recommended to establish a systematic training program for doctors to enhance the connotative quality of MR, for coders to solidify professional coding skills, strengthen communication and exchange, adopt reasonable behaviors, avoid moral hazards, and effectively improve the quality of clinical coding.
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