VOLUME 38 | ISSUE 5 | SEPTEMBER-OCTOBER 2018

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Implementation of total laboratory automation at a tertiary care hospital in Saudi Arabia: effect on turnaround time and cost efficiency

Tracy Louise Ellison, Maha Alharbi, Morad Alkaf, Shamad Elimam, Mariam Alfaries, Randa Al Nounou, Rasheed Nasr, Tarek Owaidah

From the Department of Pathology and Laboratory Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia

How to cite this article:

Ellison TL, Alharbi M, Alkaf M, Elimam S, Alfaries M, Al Nounou R, et al. Implementation of total laboratory automation at a tertiary care hospital in Saudi Arabia: effect on turnaround time and cost efficiency. Ann Saudi Med 2018; 38(5): 352-357. 

Abstract

BACKGROUND: Total laboratory automation (TLA) is a relatively new way of improving the management of high volume clinical laboratories. TLA may reduce staff, reduce operating costs, decrease testing time and provide enhanced process control.

 

OBJECTIVES: Establish a cost efficient TLA that is less labor intensive, improves productivity and reduces turnaround time (TAT).

 

DESIGN: Implementation of TLA for random glucose and troponin-T as sentinel tests to compare change in TAT.

 

SETTING: Tertiary hospital with high volume of laboratory tests.

 

METHODS: Routine patient samples for random glucose and troponin-T were used to capture TAT. Information on staff grades and schedules before and after implementing the TLA, and cost of contracts to deliver the service were collected.

 

MAIN OUTCOME MEASURES: TAT, cost efficiency, and reduction in labor. 

 

RESULTS: The consolidation of contracts resulted in a reduction of 28.8 million SAR in direct costs. Staffing cost was reduced by 1.14 million SAR with less senior staff required; there were reductions in staff at both senior and junior level. The overall TAT for all tests was reduced by 32% in 2016 (after TLA implementation) compared to 2012 (before TLA implementation). The median TAT for random glucose tests was reduced by 21% (to 55.7 minutes in 2016 from 70.1 minutes in 2012). Evidence of test optimization by exploring the impact of stat tests, auto-dilutions and reruns on the overall TAT of the TLA is shown by comparing troponin T TATs after reclassifying stat tests (in 2016) to routine (in 2017). At the 75th percentile, there was a 27% reduction in TAT when comparing August 2016 to March 2017 with a 19% reduction in median TAT. 

 

CONCLUSION: By moving from stat to routine assays, the TAT was reduced, which is counter-intuitive. The use of stat assays slowed down the performance of the TLA. A careful review of the mix of assays should be conducted to maximize performance and to ensure that the system delivers what is required.

 

LIMITATIONS: Room for improvement by systematically analyzing and reviewing the impact of making minor changes that could have significant impact on TAT. 

 

CONFLICT OF INTEREST: None. 

 

 

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