Impact of Automation Process on Microbiological Laboratory Efficiency

Abstract

Background. University Medical Center (UMC) Lubbock made a significant investment to improve the quality and efciency of the microbiology laboratory by implementing the Becton Dickinson (BD) Kiestra Total Laboratory Automation (TLA) system which automates sample setup, incubation and reading. Automation minimizes hands-on steps, increasing efciency, productivity and quality; impacting the rapid identification of pathogens. This system went live in May, 2015. Methods. After approval from the Quality Improvement Review Board, a retrospective analysis of electronically captured microbiological data from a BD research database was used to compare pre-installation (January-December 2013) vs. post-installation period (January-October 2016). Twelve common and clinically important organisms were assessed. The following reporting times were compared: First gram stain, Organism Identification (ID), First antimicrobial susceptibility (AST), and final AST. Reporting time was examined in a 24-hour spectrum divided into day (06:00-17:59) and night (18:00-05:59) shifs. Statistical analysis was performed with SAS sof-ware version 9.2. Data was analyzed using Chi-squared test. A p value of <0.05 was considered statistically significant. Results. Overall 14,179 positive results were reported during the study period. Specimens were collected from inpatient hospital wards, emergency room, critical care units and outpatient locations (35%, 32%, 23%, and 10%, respectively). The most common sources were urine, wound/skin, blood, and respiratory (40%, 25%, 14%, and 10%, respectively). Compared with pre-installation vs. post-installation period, a sig-nifcant change in time to laboratory reporting during night shif in all measures was noted: Time to first gram stain (30% vs. 56%), First organism identification (14% vs. 58%), first AST (8% vs. 62%) and final AST (7% vs. 58%) (P < 0.01) Conclusion. Continued microbiology laboratory efciency efforts lead to significant improvement in impacting time to result which made microbiology data available to clinicians earlier with utilization of TLA. The availability of this information leads to appropriate antibiotic switch in a timely fashion, which in turn supports optimal patient care, antimicrobial stewardship and quality improvements.