The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Implementation of total laboratory automation at a tertiary care hospital in Saudi Arabia: effect on turnaround time and cost efficiency
Open accessAbstract
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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“Establishing stat laboratories or rapid response teams within or near high-acuity areas like the ED or ICU can decentralize testing for a select menu of critical tests (e.g., ABG, lactate, troponin), eliminating transportation delays.”
From Impact of Laboratory Turnaround Time on Clinical Decision-Making and Patient Outcomes (2024) · cites this paper as [27]
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“Such improvements have been shown to reduce the TAT [26–30].”
From Shorter laboratory turnaround time is associated with shorter emergency department length of stay: a retrospective cohort study (2022) · cites this paper as [29]
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“Implementing single-piece flow for stat samples, where they are processed immediately upon arrival rather than batched, is another effective tactic.”
From Impact of Laboratory Turnaround Time on Clinical Decision-Making and Patient Outcomes (2024) · cites this paper as [27]
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In the citing paper
“Standardizing collection protocols and investing in continuous training for all staff involved in the pre-analytical phase reduces sample rejection rates [27].”
From Impact of Laboratory Turnaround Time on Clinical Decision-Making and Patient Outcomes (2024) · cites this paper as [27]
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Citations
Cites
Total laboratory automation: Do stat tests still matter?
Dolci, A., Giavarina, D., Pasqualetti, S., Szőke, D., & Panteghini, M. (2017) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2017.04.002 · Cited by 66
Clinical Laboratory Automation: A Case Study
Archetti, C., Montanelli, A., Finazzi, D., Caimi, L., & Garrafa, E. (2017) · Journal of Public Health Research · doi:10.4081/jphr.2017.881 · Cited by 57
Evaluation of the impact of a total automation system in a large core laboratory on turnaround time
Lou, A. H., Elnenaei, M. O., Sadek, I., Thompson, S., Crocker, B., & Nassar, B. A. (2016) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2016.08.018 · Cited by 47
Lou, A. H., Elnenaei, M. O., Sadek, I., Thompson, S., Crocker, B., & Nassar, B. A. (2017) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2017.04.019 · Cited by 34
Nonanalytic Laboratory Automation: A Quarter Century of Progress
Hawker, C. D. (2017) · Clinical Chemistry · doi:10.1373/clinchem.2017.272047 · Cited by 32
Designing and evaluating autoverification rules for thyroid function profiles and sex hormone tests
Li, J., Cheng, B., Ouyang, H., Xiao, T., Hu, J., & Cai, Y. (2017) · Annals of Clinical Biochemistry International Journal of Laboratory Medicine · doi:10.1177/0004563217712291 · Cited by 27
The impact of automating laboratory request forms on the quality of healthcare services
Dogether, M. A., Muallem, Y. A., Househ, M. S., Saddik, B. A., & Khalifa, M. (2016) · Journal of Infection and Public Health · doi:10.1016/j.jiph.2016.09.003 · Cited by 16
Cited by
Sorted by citations
Nonanalytic Laboratory Automation: A Quarter Century of Progress
Hawker, C. D. (2017) · Clinical Chemistry · doi:10.1373/clinchem.2017.272047 · Cited by 32
Kim, K., Lee, S., Kim, T. H., & Lee, S. G. (2021) · Annals of Laboratory Medicine · doi:10.3343/alm.2022.42.1.89 · Cited by 30
The Impact of Total Automaton on the Clinical Laboratory Workforce: A Case Study
Alnaam, Y., Elsafi, S. H., Aljahdali, M. H., Shaman, R. S. A., Al-Qurouni, B. H., & Zahrani, E. M. A. (2022) · Journal of Healthcare Leadership · doi:10.2147/jhl.s362614 · Cited by 28
Vrijsen, B. E. L., Haitjema, S., Westerink, J., Hulsbergen-Veelken, C. A. R., van Solinge, W. W., & ten Berg, M. J. (2022) · BMC Emergency Medicine · doi:10.1186/s12873-022-00763-w · Cited by 20
Rupp, N., Ries, R., Wienbruch, R., & Züchner, T. (2023) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-023-05038-2 · Cited by 19
Metadata
- Authors
- Ellison, T. L., Alharbi, M., Alkaf, M., Elimam, S., Alfaries, M., Al Nounou, R., Nasr, R., & Owaidah, T.
- Affiliations
- King Faisal Specialist Hospital & Research Centre (SA)
- From the Department of Pathology and Laboratory Medicine, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
- Corresponding author
- Owaidah, Tarek
- Venue
- Annals of Saudi Medicine
- Published
- 2018-09
- Volume
- 38
- Issue
- 5
- Pages
- 352-357
- ISSN
- 0256-4947 (ISSN-L)
- 0975-4466
- PMC
- PMC6180219
- OpenAlex
- W2897284165
- Cited by
- 22
- References
- 7
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 7 · 2023: 1 · 2022: 5 · 2021: 1 · 2020: 2 · 2019: 2
- FWCI
- 0.86
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Annals of Saudi Medicine (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › Medical Laboratory Technology › Clinical Laboratory Practices and Quality Control
- Health Sciences › Health Professions › General Health Professions › Healthcare cost, quality, practices
- Social Sciences › Decision Sciences › Management Science and Operations Research › Healthcare Operations and Scheduling Optimization
- Keywords
- total laboratory automation, turnaround time, cost efficiency, random blood glucose, troponin T, routine assay, tertiary care hospital
- MeSH terms
- Contract Services, Cost-Benefit Analysis, Direct Service Costs, Humans, Laboratories, Hospital, Personnel Staffing and Scheduling, Saudi Arabia, Time Factors, Efficiency, Organizational, Automation, Laboratory, Tertiary Care Centers
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