Introduction: The impact of workflow changes and total laboratory automation (TLA) on microbiology culture processing time was evaluated in an academic-affiliated regional hospital. Materials and Methods: A retrospective analysis of microbiological data in a research database was performed to compare turnaround time (TAT) for organism identification (ID) before and after implementation of TLA (2013 versus 2016, respectively). TAT was compared using chi-squared test for categorical variables and log-transformed t-test for continuous variables. Results: A total of 9,351 pre-defined common and clinically important positive mono-bacterial culture results were included in the analysis. Shorter TAT (hours) in 2016 compared to 2013 (p<0.0001) for positive result pathogen ID were observed in specimen types including blood (40.7 vs. 47.1), urine (30 vs 44), wound (39.6 vs. 60.2), respiratory (47.7 vs. 67), and all specimen types, combined (43.3 vs. 56.8). Although shorter TAT were not observed from all specimen categories for negative result pathogen ID, TAT for all specimen types, combined, was shorter (p<0.001) in 2016 compared to 2013 (94 vs. 101). Conclusions: Total laboratory automation and workflow changes-including process standardization-facilitate shorter organism ID TAT across specimen sources.

BackgroundUniversity Medical Center in Lubbock, TX is one of few medical centers using Becton Dickinson (BD) Kiestra Total Laboratory Automation (TLA) system since May 2015. The impact on organism-specific turn around time (TAT) in urinary specimens after implementation of TLA was evaluated.MethodsAfter approval from the Quality Improvement Review Board, a retrospective analysis of microbiological data from urinary specimens in BD research database was performed. Before vs. after implementation (2013 vs. 2016) TAT was compared. Ten clinically relevant organisms were analyzed. Statistical analysis was performed with SAS software version 9.2. Data were analyzed using Chi-squared test. A P-value of < 0.05 was considered statistically significant.ResultsOverall, 2282 specimens from 2013 and 2306 specimens from 2016 were analyzed. Compared with before vs. after implementation of TLA, an overall improvement in TAT was observed (expressed as mean hours for each organism): Enterococcus faecalis (55.2 vs. 38.8), Enterococcus faecium (68.4 vs. 43.8), Escherichia coli (44.2 vs. 41.0), Klebsiella pneumoniae (45.0 vs. 44.0), Proteus mirabilis (44.8 vs. 38.6), Pseudomonas aeruginosa (58.9 vs. 37.7), Staphylococcus aureus (49.2 vs. 36.0), Streptococcus agalactiae (49.2 vs. 31.4), Streptococcus pneumoniae (51.7 vs. 61.8), Streptococcus pyogenes (62.6 vs. 26.6). It was also observed that improvement in TAT was more pronounced for Gram-positive organisms than Gram-negative organisms. P-value was < 0.01 for all organisms except Streptococcus pneumoniae (0.7985) and Streptococcus pyogenes (0.2562). The number of specimens with these two organisms was too small to be considered significant.ConclusionAutomation of microbiology laboratory leads to significant TAT improvement in urinary specimens, making early data availability to clinicians. This improves efficiency as well as supporting earlier antibiotic switch, antimicrobial stewardship and optimal patient care in treating urinary tract infections.Disclosures All authors: No reported disclosures.

BackgroundAutomation minimizes hands-on steps and facilitates process improvement in the microbiology laboratory. The impact on the efficiency improvement of the culturing process in an academic regional hospital after implementation of total laboratory automation (TLA) was evaluated.MethodsAfter approval from the Quality Improvement Review Board, a retrospective analysis of microbiological data in Becton Dickenson (BD) Clinical Insights Research Database was performed. Then, laboratory process change and reported microbiological results turnaround time (TAT) before and after implementation of the TLA was compared (2013 vs. 2016). Specimens were classified into blood, respiratory, urine, wound and others. Statistical analysis was performed with SAS software version 9.2. The comparison was done using chi-square test for categorical and log-transformed t-test for continuous variables. A P-value of < 0.05 was considered statistically significant.ResultsA total of 9,351 pre-defined common and clinically important positive mono-microbial culture results were included in the organism identification (ID) TAT analysis. The time of the day at which results were reported in 2016 was more evenly distributed throughout a 24-hour period, rather than delaying to the following morning (P < 0.0001). The definitive positive bacterial pathogen identification TAT was significantly shorter across all sources in 2016 compared with 2013 with overall TAT mean (standard deviation) of 56.8 (24.3) hours in 2013 vs. 43.3 (20.8) hours in 2016 (P < 0.0001). The negative results’ (n = 58,640) TAT was also shortened in 2016 for all (P < 0.05), except for respiratory and other sources.ConclusionAutomation facilitates microbiological laboratory efficiency improvement with shorter definitive organism identification TAT across all specimens as well as shorter TAT for negative results with most specimen sources. This information would facilitate earlier, more accurate and appropriate antibiotic choices which in turn improves clinical decision making and enhances optimal patient care.Disclosures Y. Tabak, Becton, Dickinson and Company: Employee, Salary. L. Vankeepuram, Becton, Dickinson and Company: Employee, Salary. S. Kurtz, Becton, Dickinson and Company: Employee, Salary. D. Sellers, Becton, Dickinson and Company: Employee, Salary.