Key Success Factors of Total Laboratory Automation and Their Impact on the Turnaround Time of Patient Results in Qatar
DOI:
https://doi.org/10.70301/Keywords:
Laboratory Automation, Turnaround time, Laboratory Workflow, Pre-analytical, Specimen transportationAbstract
The Qatar healthcare laboratories have considerable challenges with regard to effective realization of laboratory automation systems. The positivist philosophy and the quantitative, cross sectional research design used in the study examines the empirical associations of these variables. The research design is the investigation of the key success factors (independent variables) total laboratory automation (mediation variable) and the effect on the turnaround time of patient results (dependent variable) in Qatar. Laboratories, which depend on large automation systems, are highly complex and there are high chances of failures in the system that can considerably discontinue the laboratory activities. The purpose of the study is to identify and analyze the impact of the main success factors on the laboratory performance and turnaround time related to providing patient results. A questionnaire was created to do this, and it was sent to the professionals of the laboratories using email and LinkedIn through Qualtrics. A 7-point Likert scale was used to obtain more than 400 answers in an attempt to obtain valid and reliable data to do further analysis. The focus on EFA in order to recognize underlying factors. The structural model was affirmed by using Confirmatory Factor Analysis (CFA). Structural Research hypotheses and mediation effects were tested by Equation Modelling (SEM). Using Indirect effect, SEM, is the path relationships that are not direct subsidiary to P1 × P2 where P1 represents the path coefficient of the path from<|human|>Indirect effect, SEM, is the relationship paths that were not direct as subsidiaries of P1 × P2 where P1 is the path coefficient of the path between. The path coefficient of MV to DV, IV to MV and P2, were tested whether they were statistically significant. using the formula C ′ = P1 × P2 + P3. The findings revealed that there are substantial indirect effects (p < 0.05). of six of the six IVs which means that it was the IVs which affected the DV using the MV therefore endorsing partial mediation in five cases on main and case study sample.
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