The accuracy of diagnostic codes refers to the proper classification of diseases according to ICD-10; a code is considered accurate if it complies with the applicable classification rules. This study employed a qualitative research design, utilizing the following data collection methods: interviews—from which the researcher obtained information—direct field observations, a review of documentation, and the use of a checklist for patient referral documents. The results included 44 patient referral documents from 2022–2024; of these, 26 (59%) medical records were found to be accurate, while 18 (41%) were inaccurate. Upon reviewing the inaccuracies through the 5M framework (Man, Money, Method, Material, Machine), it was found that the individuals coding patient diagnoses lacked a medical records background, had not received coding training, there were no specific SOPs regarding patient referrals, and they still relied on Google for assistance when encountering new cases. There is a need to improve the quality of diagnostic coding accuracy and to conduct periodic coding audits to address potential inaccuracies in diagnostic codes, ensuring greater consistency and accuracy in the future and enhancing existing quality standards.
Copyrights © 2026