Use of Computer Simulation to Study Impact of Increasing Routine Test Volume on Turnaround Times of STAT Samples on ci8200 Integrated Chemistry and Immunoassay Analyzer

摘要

Automated clinical chemistry analyzers were first introduced as single- and multichannel continuous flow analyzers in the 1960s (1)(2). Ongoing evolution of analyzers has been driven by two factors: ( a ) increased demand by clinicians for rapid turnaround times (TATs); and ( b ) a need to decrease the cost of producing laboratory results and to consolidate laboratory testing into fewer workstations. The diagnostic industry has responded to this need by developing analyzers that have high throughput and expanded test menus, and perform both clinical chemistry assays and immunoassays on a single platform. As a result of these technical innovations, analyzer throughput and assay TAT are now dependent on such factors as ( a ) tests ordered on samples, ( b ) the number of samples loaded on a analyzer, and ( c ) the STAT-vs-routine ratio. Selection of the most appropriate analyzer to meet laboratory TAT consistently is no longer a trivial exercise of dividing the total number of daily tests by an analyzer’s hourly throughput to determine whether it will meet laboratory needs. The goals of this study were to determine the feasibility of using MedModel 2001 (Promodel Corporation) software to develop a simulation model of the ci8200 integrated chemistry and immunoassay analyzer manufactured by Abbott Diagnostics, to estimate the percentage error in the model’s predictions of test TAT, and finally, to use the validated model to evaluate the impact of increased routine test volumes on the TAT of STAT samples.A simulation model of a clinical analyzer uses computer software specifically designed to imitate and capture an analyzer’s dynamic behavior to study its performance under different conditions. Researchers in Europe and the United States have used computer simulations to study various aspects of clinical laboratory operation, including staff assignments, evaluating the queue length, and priority handling and processing TAT for different sample types (3) …