Reza Rabiei - Associate Professor at Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Farkhondeh Asadi - Associate Professor at Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Hassan Emami - Assistant Professor at Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Maryam Ahmadi Hosseini - M.Sc. in Health Information Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Background: The quality of coding for diagnoses and external causes of trauma to a great extend contributes to trauma classification, monitoring, and prevention. Objectives: The present study aimed to assess the trauma coding quality using ICD۱۰. Methods: In this descriptive applied study, ۵۹۱ records of trauma patients in educational hospitals affiliated to the Shahid Beheshti University of Medical Sciences (SBUM) were selected to assess coding quality based on ICD۱۰ in ۲۰۱۸. Data were collected using a checklist and analyzed using IBM SPSS Statistics ۲۰.۰. Results: The mean accuracy, completeness, and quality of trauma coding were ۶۴.۵%, ۷۰%, and ۶۷.۵%, respectively. Conclusion: High-quality coding of trauma diagnosis creates a more reliable databank which can be used for planning and policy-making aiming to prevent and reduce traumatic events. The accuracy and completeness of medical diagnoses should be regularly and periodically reviewed to ensure the quality of the codes.

Coding accuracy, coding completeness, coding quality