EISSN: 2980-0749
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2023, Cilt 21, Sayı 3, Sayfa(lar) 134-144
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Corrective Steps in a Total Laboratory Automation: Experience of a University Laboratory
Raziye Yıldız1 Cevval Ulman2
1İzmir Katip Çelebi Üniversitesi Atatürk Eğitim ve Araştırma Hastanesi, Tıbbi Biyokimya İzmir, Türkiye
2Manisa Celal Bayar Üniversitesi, Tıbbi Biyokimya Anabilim Dalı, Manisa, Türkiye
Keywords: Analytical Techniques and Equipment, Automation, Laboratory Organization and Management
Abstract
Aim: The Intra-laboratory Turnaround Time (IR-TAT) serves as a significant measure of overall laboratory efficacy. This study sought to augment laboratory operational productivity and diminish IR-TAT by instating a Total Laboratory Automation (TLA) system, executing stat testing, integrating an additional autoanalyzer, and modifying the sample type.

Material and Methods: The evaluation of IR-TAT was conducted both through the mean TAT and Outlier Percentage (OP), comparing data before and after automation. Seven tests were utilized for this comparison, including Albumin, Alanine Aminotransferase (ALT), Urea, Potassium, Beta Human Chorionic Gonadotropin (β-hCG), Troponin I, and Thyroid Stimulating Hormone (TSH). Statistical analysis was performed using the t-test in the Open Epi program.

Results: Post TLA implementation, IR-TAT demonstrated improvements in routine biochemistry samples. However, a statistically significant elevation was observed in IR-TAT for urgent samples (except β-hCG and TSH), and for β-hCG and TSH within routine samples. To rectify this, stat testing was initiated specifically for the Emergency Department. These stat tests were processed in a separate autoanalyzer outside of TLA, and the sample type for Troponin I was transitioned from serum to plasma. Consequently, a decrease was observed in the mean IR-TAT for stat tests (p<0.001).

Conclusion: The TLA system deployed in our institution has effectively optimized the management of high volumes. Implementing corrective measures such as the inclusion of stat testing and altering the sample type have resulted in definitive improvements in IR-TAT. To maximize the benefits derived from TLA, it is crucial to identify existing issues and implement appropriate corrective measures.

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