RESUMO
Implementation of Quality indicators (QIs) plays an imperative role in improving the total testing process, as it provides a quantitative basis for evaluating the laboratory performance. Besides monitoring of analytical quality specifications, several lines of experimental and clinical evidence have alluded a pivotal role of extra-analytical phases in improving the quality of laboratory services and therefore a relevance of pre- and post-analytical steps have been speculated on the overall quality in the total testing process and consequently on clinical decision-making. This was a retrospective study designed to evaluate and review different extra-analytical quality indicators in NABL accredited clinical biochemistry laboratory at BJ Medical College and Civil Hospital, Ahmedabad, Gujarat in an endeavour to ameliorate the performance of the laboratory. All Clinical Chemistry Laboratory test requests with their respective samples from January 2018 to December 2021 were included in the study. A total of 1,439,011samples were processed, and were evaluated for seven QIs [(% of number of suitable samples not received; QI-8), (% of number of samples received in inappropriate container; QI-9), (% of number of samples hemolysed; QI-10), (% of number of samples with inadequate sample volume; QI 12) (% of number of samples received mismatched; QI 15), (% of number of samples reported after turnaround time; QI 21) and (% of number of samples with critical values informed; QI 22)] based on defined criteria of Quality Specification given by International Federation of Clinical Chemistry. Total number of preanalytical errors was 53,669 (3.72%). Among the preanalytical errors, inadequate sample volume (2.37% of total samples; 63.49% of total pre-analytical errors) was the most common anomaly followed by Not received samples (24.18%) hemolysis (8.26%) mismatched (3.91%) and 0.14% samples were received in Inappropriate container; manifesting that the error frequency was unacceptable for QI 21 and QI 8, acceptable for QI 10, minimally acceptable for QI 15 and optimum for QI QI 9. Furthermore, there was year-wise progressive decline in error rate of inadequate sample volume, hemolysed sample received and mismatched samples. Total number of post analytical errors were 19,002 (1.32%). TAT outlier and critical values communicated were the two QIs evaluated for this phase and results of both QI were within acceptable limits. Quality indicators serve as a tool to monitor process performance and consequently derived error rates warrant active intervention to improve the laboratory services and patient health care. Dissemination of certified documents, regular staff training and evaluation needs to be conducted.
RESUMO
INTRODUCTION: The interpretation of quantitative test results requires the availability of appropriate reference intervals (RIs). Every laboratory has been advised by scientific literature and reagent manufacturers to establish RIs for all analytes. Measuring RIs using direct methods is very costly, and it poses ethical and practical challenges. To overcome these challenges, indirect methods, such as Hoffman, and newer automated approaches, such as KOSMIC and refineR, are used to verify RIs for thyroid hormones. OBJECTIVE: To verify RIs for thyroid hormones in adult patients using Hoffman, KOSMIC and refineR methods and to compare these with reference ranges given in kit literature or standard textbooks. MATERIALS AND METHODS: The observed values (results) of thyroid hormone were collected from the LIS (Laboratory Information System) of the Biochemistry Department at the B. J. Medical College and Civil Hospital in Ahmedabad between 1 January 2021 and 31 May 2022. Hoffman, KOSMIC and refineR methods were used to verify the RIs. The computerised Hoffman approach, which Katayev et al. describe, is a simple method for determining RI from hospital data. Zierk et al. pre-validated and suggested the KOSMIC method based on Python programming, whereas refineR was proposed by Tatjana et al. based on R programming language. RESULTS: Hoffman, KOSMIC and refineR's indirect RI techniques revealed comparable results with kit literature in free T3 and T4, whereas higher upper reference limits of thyroid-stimulating hormone (TSH) compared to kit literature were observed with KOSMIC and refineR methods. However, the computerised Hoffman method revealed comparable results with TSH also. CONCLUSION: Indirect approaches, such as Hoffman, KOSMIC and refineR, provide reliable RI verification for free T3 and T4 utilising patient samples obtained from LIS. However, the manual Hoffman method provides reliable RI verification for TSH data derived from the hospital population as compared to automated approaches, such as KOSMIC and refineR.
