Assessment of hematology laboratory performance in the total testing process using quality indicators and sigma metrics in the northwest of Ethiopia: A cross‐sectional study

Abstract

Abstract Background and Aims Assuring laboratory quality by minimizing the magnitude of errors is essential. Therefore, this study aimed to assess hematology laboratory performance in the total testing process using quality indicators and sigma metrics. Methods A cross‐sectional study was conducted from April to June 2022. The study included a total of 13,546 samples. Data on included variables were collected using a checklist. Descriptive statistics were used to present the overall distribution of errors. Binary logistic regression models were applied. Furthermore, using a Sigma scale, the percentage of errors was converted to defects per million opportunities to assess laboratory performance. Finally, the defect per million opportunities was converted to a sigma value using a sigma calculator. Results Of the 13,546 samples and corresponding requests, the overall error rate was 123,296/474,234 (26%): 93,412/47,234 (19.7%) pre‐analytical, 2364/474,234 (0.5%) analytical, and 27,520/474,234 (5.8%) post‐analytical. Of the overall errors, 93,412/123,296 (75.8%), 2364/123,296 (1.9%), and 27,520/123,296 (22.3%) were pre‐analytical, analytical, and post‐analytical errors, respectively. The overall sigma value of the laboratory was 2.2. The sigma values of the pre‐analytical, analytical, and post‐analytical phases were 2.4, 4.1, and 3.1, respectively. The sample from the inpatient department and collected without adherence to the standard operating procedures (SOPs) had a significantly higher (p < 0.05) rejection rate as compared to the outpatient department and collected with adherence to SOPs, respectively. In addition, an association between prolonged turnaround times and manual recording, inpatient departments, and morning work shifts was observed. Conclusion The current study found that the overall performance of the laboratory was very poor (less than three sigma). Therefore, the hospital leadership should change the manual system of ordering tests and release of results to a computerized system and give need‐based training for all professionals involved in hematology laboratory sample collection and processing.

Keywords

• hematology
• laboratory
• quality indicators
• sigma metrics
• testing process