Gayatric C.Gawade - Department of Biochemistry, Bharati Vidyapeeth (DTU) Medical College and Hospital, Pune ۴۱۱۰۴۳, Maharashtra, India
Meghana K.Padwal - Department of Biochemistry, Bharati Vidyapeeth (DTU) Medical College and Hospital, Pune ۴۱۱۰۴۳, Maharashtra, India
Shyam Galsamudre - Central Clinical Laboratory, Bharati Vidyapeeth (DTU) Medical College and Hospital, Pune ۴۱۱۰۴۳, Maharashtra, India
Abdulrahman A.Momin - Department of Biochemistry, Bharati Vidyapeeth (DTU) Medical College and Hospital, Pune ۴۱۱۰۴۳, Maharashtra, India

Background: In the modern era of tremendous automation in analytical processes, reporting errors have been reduced significantly. Therefore, the focus has been shifted to identifying the extra analytical causes of errors in the laboratory. Objectives: This study aimed to audit major clinical decisions affecting quality indicators (i.e., reporting errors and error prevention) by adhering to ISO ۱۵۱۸۹ (۲۰۱۲) and National Accreditation Board for Testing and Calibration Laboratories (NABL) (۱۱۲) requirements. Methods: The records of the reporting errors were maintained from the biochemistry section of the central clinical laboratory (CCL) and analyzed based on the aim of this study. Then, the root cause analysis was performed, and the data was collected and audited from November ۲۰۱۵ to July ۲۰۲۰. Results: The total number of reporting errors between the mentioned periods were ۱۳۲, with an incidence of ۱ error per ۳۸۴ processed samples on the day of observing the reporting error. In general, ۲۲ (۱۶.۶۷%), ۱۶ (۱۲.۱۲%), and ۹۴ (۷۱.۲۱%) cases were pre-analytical, analytical, and post-analytical errors, respectively. The incidence of the post-analytical error was noted to be more since they were all typographical errors. Conclusion: Overall, transcriptional or typographical errors were found to be the main causes of reporting errors. In our clinical laboratory, we are attempting to minimize these errors by pre-validating the results by senior technicians and faculty prior to the typing and approval. These avoidable errors can be minimized by the continuous training of laboratory staff. Up-gradation to automated data collection information management systems are of great hope for preventing such errors.

Reporting errors, Quality indicators, Typographical errors, Post-analytical errors