Relationship between specificity of diagnosis writing and accuracy of chronic kidney disease codes

https://doi.org/10.55214/25768484.v9i6.8468

Authors

  • Linda Widyaningrum D3 Medical Records and Health Information Study Program, Faculty of Health Sciences, Universitas Duta Bangsa, Surakarta, Indonesia.
  • Aditya kurniawan D3 Medical Records and Health Information Study Program, Faculty of Health Sciences, Universitas Duta Bangsa, Surakarta, Indonesia.

Inaccurate diagnostic coding in health services often results from incomplete or unclear diagnostic documentation, particularly in chronic conditions like kidney disease. This study aimed to examine the relationship between the specificity of diagnostic writing and the accuracy of chronic kidney disease (CKD) codes in medical records. An analytical retrospective study was conducted at a tertiary hospital, analyzing 110 medical record documents with CKD diagnoses, selected through total sampling from January to December 2024. Data were analyzed using the chi-square test to evaluate the association between diagnostic writing specificity (independent variable) and CKD code accuracy (dependent variable). Results revealed that 78 documents (70.9%) had specific diagnostic writing, while 32 (29.1%) were non-specific. Accurate codes appeared in 98 documents (89%), with 12 (11%) inaccurate. The chi-square test yielded a p-value <0.05, confirming a significant relationship: more specific diagnostic writing enhances code accuracy. These findings highlight the critical role of precise documentation in healthcare coding. To reduce errors, physicians and coding officers should improve ICD-10 comprehension through regular training, strengthen interdisciplinary communication, and adopt standardized documentation protocols, ultimately enhancing diagnostic coding quality and patient care outcomes.

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How to Cite

Widyaningrum, L. ., & kurniawan, A. . (2025). Relationship between specificity of diagnosis writing and accuracy of chronic kidney disease codes. Edelweiss Applied Science and Technology, 9(6), 2731–2742. https://doi.org/10.55214/25768484.v9i6.8468

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Published

2025-06-30