A Retrospective Observational Study to Assess the Quality Management System in a Molecular Diagnostic Laboratory of a COVID-19 Dedicated Hospital in Delhi, India
Sonali Bhattar, Sukriti Sabharwal, Shikhar Saxena
1. Associate Professor, Department of Microbiology, Institute of Human Behaviour and Allied Sciences, Delhi, India.
2. Senior Resident, Department of Clinical Microbiology, NCRIMS, Meerut, Uttar Pradesh, India.
3. Assistant Professor, Department of Clinical Microbiology, Rajiv Gandhi Super Speciality Hospital, Delhi, India.
Correspondence Address :
Dr. Sukriti Sabharwal,
113 Ram Vihar, Delhi-110092, India.
E-mail: sabharwalsukriti@gmail.com
Abstract
Introduction: A molecular diagnostic laboratory is the cornerstone of Coronavirus Disease-2019 (COVID-19) disease diagnosis, as the patient’s treatment and management protocol depend on molecular results. Therefore, the laboratory conducting these tests must adhere to quality management process to increase the accuracy and validity of the generated reports. Rajiv Gandhi Super Speciality Hospital established its molecular diagnostic set-up at the beginning of the pandemic. Hence, this study aims to generate quality management data to help improve weak points.
Aim: To assess the quality management system for COVID-19 diagnosis.
Materials and Methods: This retrospective observational study was conducted at Rajiv Gandhi Super Speciality Hospital in Delhi, India. A total of 14,561 samples were collected over six months, from February 2021 to July 2021. Data from all samples received during this period for COVID-19 Reverse-Transcriptase Polymerase Chain Reaction (RT-PCR) testing were included. Data were retrospectively collected from the electronic Laboratory Information Management System (LIMS). Quality variables were analysed over six months from July to December 2021 and classified into preanalytical, analytical, and postanalytical variables. Quality Indicators (QIs) were selected from a common model of QIs set by the International Federation of Clinical Chemistry and Laboratory Medicine. The results were presented in percentages, and descriptive statistics were analysed using Statistical Package for Social Sciences (SPSS) software.
Results: During the six-month study period, the molecular laboratory received 14,561 samples. Among the preanalytical variables, sample leakage was the most common cause of sample rejection (134 samples, 0.92%), followed by the non generation of Specimen Referral Form (SRF) identification (76 samples, 0.52%), and non compliance with triple packaging (44 samples, 0.3%). Other preanalytical aspects assessed included incomplete patient identification (17 samples, 0.11%), insufficient sample quantity (12 samples, 0.08%), missing forms/samples (7 samples, 0.04%), samples in the wrong vials/empty Viral Transport Media (VTM) tubes (5 samples, 0.03%), and incomplete LIMS entry (2 samples, 0.01%). Internal Quality Control (QC) was not obtained in 55 samples (0.37%), and two incidents of cross-contamination resulted in false-positive results. Among the postanalytical factors, 11 samples (0.07%) could not be dispatched within the stipulated time frame.
Conclusion: The assessment of the quality management system revealed some areas for improvement, emphasising the importance of adhering to QC processes for the smooth operation of diagnostic laboratories, especially those involved in critical reporting. The assessment of QIs helped monitor laboratory parameters effectively.
Keywords
Laboratory medicine, Quality indicators, Samples
DOI and Others
DOI: 10.7860/JCDR/2024/64986.19228
Date of Submission: May 24, 2023
Date of Peer Review: Jul 15, 2023
Date of Acceptance: Feb 13, 2024
Date of Publishing: Apr 01, 2024
AUTHOR DECLARATION:
• Financial or Other Competing Interests: None
• Was Ethics Committee Approval obtained for this study? No
• Was informed consent obtained from the subjects involved in the study? No
• For any images presented appropriate consent has been obtained from the subjects. No
PLAGIARISM CHECKING METHODS:
• Plagiarism X-checker: May 24, 2023
• Manual Googling: Jul 19, 2023
• iThenticate Software: Feb 10, 2024 (21%)
ETYMOLOGY: Author Origin
EMENDATIONS: 6