Workflow Modifications and Addition of MALDI-TOF Technology Significantly Improved Turn-Around-Time to Identification of Common Urine Pathogens

Background: In order to improve the identification of common aerobic urine cultures as well as antimicrobial susceptibility testing (AST) setup at an Academic Medical Center, work-flow modifications and MALDI-TOF technology were incorporated. Previously, the majority of species identification was achieved with conventional identification/antimicrobial susceptibility combo panels. All urine cultures, regardless of laboratory receipt time, were previously read once per day on 1st shift. Methods: The initial workflow modification involved addition of a 2nd shift urine culture reading. Urine specimens received from 8:00 AM to 4:00 PM were read on 1st shift, while urine specimens received from 4:00 PM to 8:00 AM were read on 2nd shift. Additionally, urine cultures were sorted into categories: no growth (NG) at 24 hours, no growth at \u3c24 hours, single colonies of growth, multiple colonies of growth, and potential contaminants. No growth cultures were signed out at 24 hours. No growth cultures at \u3c 24 hours were reincubated to be read on subsequent shift. Cultures with growth were set aside as either single colony types or multiple colony types. Cultures of probable contaminants were signed out. Once cultures were sorted, the isolated colonies underwent MALDI-TOF analysis (Bruker) and antimicrobial susceptibility testing (AST) as appropriate. Individual technologists setup the MALDITOF target plate map and spotted the associated target plate. AST was setup at the same time. The MALDI-TOF was then operated by a central technologist and results reported by the original technologist reading the culture. Results: Retrospective pre-workflow (September-November 2013) and post-workflow (May, June, October 2014) modification turn-around-times were compared for 16 commonly isolated pathogens. These pathogens consisted of common urine pathogens as noted in Table 1. Staphylococcus aureus was previously identified in our laboratory by a positive coagulase test and not included in this analysis. The average turn-around-times, standard deviations and the p-values for each organism are indicated in Table 1. Conclusion: Converting from conventional identification methods to MALDI-TOF, in conjunction with workflow modifications such as a 2nd culture reading, notably improved urine culture turn-around-time for identification and AST

Assessment of utility of daily patient results averages as adjunct quality control in a weekday-only satellite chemistry laboratory

ABSTRACT Background: Our department operates a weekday-only (8AM-5PM) satellite laboratory in an infusion center with a menu of 18 chemistry tests on a Roche c501 analyzer. We examined whether daily patient results averages (PRA) in this setting might be useful as a patient-based quality control (PBQC) adjunct to standard daily liquid quality control (LQC) measurements. First, we evaluated the reproducibility (coefficient of variation, CV) of daily PRAs for each analyte, and compared these to CVs of LQC. Second, for select analytes found to have relatively low PRA CVs, we evaluated the extent to which use of daily PRA measurements could improve detection of analytical errors when combined with LQC. Methods: Patient results data for approximately one month (21 weekdays) were obtained from the Sunquest laboratory information system. For calculation of patient results averages (PRA), qualifying results were restricted to those within the reference range for each analyte. PRA and standard deviation (S) of PRA across 21 days was calculated for each analyte. Coefficients of variation for PRA (CV-PRA) were compared to those observed for standard liquid quality control (LQC) measurements (CV-LQC). For those analytes for which CV-PRA was less than CV-LQC, we evaluated the potential advantage of addition of PRA to daily LQC. For each analyte, a presumed PRA shift was determined such that probability of detection (P) was 0.5 when using LQC alone (viz., using high LQC and low LQC measurements), according to criterion that at least one 1-2S deviation from mean was obtained. For this same PRA shift, P = 0.5 for LQC alone was compared to P obtained for LQC + PRA (viz., using high LQC, low LQC, and PRA measurements), according to the same criterion. Results: Across 21 days, the number of results per day per assay ranged from 23 ±4 (uric acid) to 75 ±21 (electrolytes). Qualifying results (results within the reference range) ranged from 70 ± 6 % (LDH) to 99 ± 1 % (Cl). Seven analytes had CV-PRA \u3c CV-LQC (analyte, CV%): albumin, 1.25%; Ca, 0.67%; Cl, 0.62%; CO2, 1.13%; creatinine, 3.44%; K, 1.14%; Na, 0.65%. The remainder did not meet this criterion: ALP, 3.7%; ALT, 5.2%; AST, 5.1%; BUN, 4.6%; glucose, 1.4%; LDH, 2.0%; Mg, 1.4%; P, 2.5%; protein, 0.9%; TBIL, 6.1%; uric acid, 4.3%. Among the seven analytes for which CV-PRA \u3c CV-LQC, probability (P) of shift detection by LQC for circumstances as described in Methods (LQC P = 0.5) was increased substantially by inclusion of PRA (analyte, shift in analyte concentration, P): CO2, ±1.07 mmol/L, 0.97; creatinine, ±0.099 mg/dL, 0.93; albumin, ±0.126 g/dL, 0.85; Ca, ±0.14 mg/dL, 0.80; K, ±0.097 mmol/L, 0.76; Cl, ±1.24 mmol/L, 0.74; Na, ±1.48 mmol/L, 0.68. Conclusions: For 7 analytes, daily PRA demonstrated CVs less than those for LQC. For these analytes, calculations demonstrated that daily PRA can increase probability of detection of small results shifts when used as an adjunct to LQC. Daily PRA is a simple and essentially cost-free form of PBQC that may be useful for certain analytes in part-time laboratory settings