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The delay in the delivery of laboratory results can be fatal and can even lead to the death of patients. This study was conducted at the clinical laboratory of the University Hospital of Kinshasa (UHK) from October 2020 to April 2021, aimed to evaluate the laboratory tests’ turnaround time (TAT) and to identify reasons for delay. TAT was quantified using a time and motion analysis approach. The evaluation of TAT consisted of comparing the overall intra-lab TAT with the suggested TAT using student t-test at 95% confidence intervals. Brainstorming was the root cause analysis tool used for identifying reasons for delay. In this study, the laboratory tests’ TATs were significantly higher (p < 0.001) comparing to international guidelines (60 minutes) and customers’ suggested TAT (120 minutes). Only 0.98% of the samples were reported within 60 minutes of patient reception and 1.47% within 120 minutes, i.e. an outlier rate of 98.5%. Root causes of delay related to Machinery, Management, Manpower, Materials, Method and Milieu. Because of many reasons, the laboratory is not meeting the established TAT. Preventive and curative measures must be undertaken to reduce the delay and improve the TAT.

In Democratic Republic of the Congo (DRC), the laboratory TAT is significantly very long and do not comply with either international standards or the suggestions of customers. However, there is neither a national nor a local strategy to improve the laboratory TAT. The aim of the present study is to develop practical management strategies to shorten clinical laboratory tests’ TAT. This was a qualitative study conducted in Kinshasa. Focus groups and Lean tools were used respectively to generate a wide range of views from a variety of laboratory staff and to eliminate several form of waste in the laboratory flow process. Based on the identified root causes of delay, focus groups participants reported that there is a lot of scope for the improvement of TAT in DRC. Consistent attendance and punctuality are essential. The hospital management should implement the Laboratory Information Systems (LIS) and install Middleware. Total laboratory automation, inventory system for all reagents and supplies used in the laboratory, expansion of the sampling area, sufficient number of high-power machine and a clear job description are indispensable. LIS, 3.5 mL BD vacutainer BarricorTM tube and point-of-care testing (POCT) are necessary for workflow improvement. A reduction of 312 minutes was achieved by eliminating or decreasing non-value-added activities. Applying the suggested key strategies, and particularly the new workflow process, is a basis for improving the laboratory tests’ TAT. The algorithm presented can be easily implemented in other laboratories that face this type of problem.

In clinical laboratory, monitoring customers’ satisfaction is required by laboratory quality standards, such as ISO15189:2012 and ISO17025:2017. However, there is no reliable and valid scale to measure clinical laboratory customers’ satisfaction in DRC. This study aims to develop a theoretical and operational instrument for measuring customer satisfaction with clinical laboratory services. In order to develop a reliable and valid measurement tool, the general methodological approach recommended by Churchill was followed. The developed questionnaire was checked for reliability and validity using exploratory and confirmatory factor analyses. Structural Equation Modeling (SEM) was used to determine whether the hypothesis of the conceptual framework is acceptable in measuring customer satisfaction. The Principal Component Analysis (PCA) results showed a three-dimensionality of Customer Satisfaction. Cronbachs alpha coefficients (0.983, 0.981 and 0.981), Joreskog Rho (0.973, 0.970 and 0.967) and composite reliability values (0.95, 0.92 and 0.93) of the latent variables were greater than 0.9, which confirms the very high reliability of the model. Indicator loadings were all greater than the threshold of 0.7 or higher. Also, all the latent variables have average variance extracted (AVE) greater than 0.5, therefore, convergent validity has been achieved. Both the Maximum Shared Variance (0.195, 0.297 and 0.234) and the Average Shared Variance (0.805, 0.703 and 0.766) were lower than the AVE (0.897, 0.839 and 0.875) for all the constructs in the scale. Therefore, Discriminant validity has been achieved. Fit indices used to assess CFA and structural equation model were found to be at an acceptable level for the two- factor model where chi-square/df was 1.6, p = 0.476, GFI = 0.99, AGFI = 0.99, SRMR = 0.069, RMSEA < 0.001, CFI = 1, NFI = 0.98, RFI = 0.98, IFI = 0.98, TLI = 0.98. The instrument demonstrated acceptable psychometric properties and thus it fits for measuring customers’ satisfaction with laboratory services.

Background: In clinical laboratory, monitoring customers’ satisfaction is an important indicator of the quality management system and required by laboratory quality standards, such as ISO 15189: 2012 and ISO17025: 2017. However, there is no reliable and valid scale to measure clinical laboratory customers’ satisfaction in Democratic Republic of the Congo. In this article, an instrument for measuring customer satisfaction with clinical laboratory services is developed and validated.Methods: In order to develop a reliable and valid measurement tool, the general methodological approach recommended by Churchill was followed. Principal component analysis (PCA) with varimax rotation was used to study the dimensionality of the construct. The developed questionnaire was checked for reliability and validity using exploratory and confirmatory analysis. The reliability checks were done using the internal consistency reliability by analyzing the Cronbach’s Alpha, composite reliability and Jöreskog Rhô values. Confirmatory Factor Analysis (CFA) was used to determine whether the hypothesis of the conceptual framework is acceptable in measuring customer satisfaction.Results: The PCA results showed a three-dimensionality of Customer Satisfaction. Cronbachs alpha coefficients (0.983, 0.981 and 0.981), Jöreskog Rhô (0.973, 0.970 and 0.967) and composite reliability values (0.95, 0.92 and 0.93) of the latent variables were greater than 0.9, which confirms the very high reliability of the model. Indicator loadings were all greater than the threshold of 0.7 or higher. Also, all the latent variables have average variance extracted (AVE) greater than 0.5, therefore, convergent validity has been achieved. Both the Maximum Shared Variance (0.195, 0.297 and 0.234) and the Average Shared Variance (0.805, 0.703 and 0.766) were lower than the AVE (0.897, 0.839 and 0.875) for all the constructs in the scale. Therefore, Discriminant validity has been achieved. Fit indices used to assess CFA and structural equation model were found to be at an acceptable level for the two-factor model where chi-square/df was 1.6, p=0.476, GFI = .99, AGFI= .99, SRMR= .069 , RMSEA= .000 , CFI= 1.00, NFI= .98, RFI= .98, IFI= .98, TLI= .98. Conclusion: The instrument demonstrated acceptable psychometric properties and thus the tool is fit for measuring customer satisfaction with laboratory services.

Introduction Parvovirus B19 (PVB19) is one of several viruses transmissible by blood transfusion. Levels of exposure to PVB19 among HIV-infected voluntary blood donors are comparable to those among HIV-negative controls because, in blood donors, the PVB19 infection is transmitted mainly via the respiratory route. Thus, we hypothesize that the seroprevalence of PVB19 in HIV-positive blood donors is equal to the seroprevalence of PVB19 in HIV-negative blood donors. The objective of this study was to compare the seroprevalence of PVB19 between asymptomatic HIV-positive and HIV-negative blood donors. Methods A random sample of 360 eligible blood donors were firstly examined for HIV antibodies by using ELISA automaton and so were categorized as HIV-positive donors and HIV-negative donors. Then the two categories of donors were examined for PVB19 IgG and IgM by using ELISA kits. The seroprevalence of PVB19 in HIV-positive donors was compared to that of HIV-negative donors by using chi-square test or Fisher's exact test. All statistical analyzes were performed with SPSS 21. Results The prevalences of PVB19 IgG and IgM in HIV-positive blood donors were 92.1% (35 of 38) and 44.7% (17 of 38), respectively and those in control group were 89.1% (287 of 322) and 46.3% (149 of 322), respectively. But for both IgG and IgM the difference was not statistically significant (p > 0.05). Conclusion This research confirms our hypothesis: the seroprevalence of PVB19 in HIV-positive blood donors is equal to the seroprevalence of PVB19 in HIV-negative blood donors.