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Analysis of Blood Culture Collection and Laboratory Processing Practices in Israel

Key Points Question Are blood cultures collected and processed in Israel in accordance with best practice standards? Findings In this quality improvement study that included 28 hospitals (348 987 blood culture bottles), an estimated 24% of adult bloodstream infections went undetected because of undersampling of patients, use of solitary blood cultures, or lack of anaerobic bottles. Median time from blood draw to pathogen identification was 34 hours longer than best practice. Meaning The findings of this study suggest that interventions to improve blood culturing processes are needed.


Introduction
Blood culturing, the most important diagnostic procedure in treating bacterial infections, comprises both clinical and laboratory processes and is one of the most essential tasks of the clinical microbiology laboratory. 1 The primary goals are maximum detection of true pathogens with minimal contamination and speedy delivery of results. Delays in blood culture (BC) results may delay the initiation of appropriate antibiotic treatment, increasing the risk of death. 2,3 Best practice standards have been proposed for various aspects of blood culturing [4][5][6][7] ; because it is a multistep process involving clinical, ancillary, and laboratory staff across many departments, there are multiple opportunities for failure to meet these standards. Neither clinicians nor microbiologists are solely responsible for overseeing the blood culturing process. As a result, deficiencies in the process may go unnoticed or, if they are noticed, it is unclear whose job it is to correct them. The aim of this study was to evaluate processes related to the diagnosis of bloodstream infection (BSI) in Israeli hospitals and compare them with best practices to detect possible system weaknesses.

Data Collection
In this quality improvement study, data were collected as part of the Israeli Ministry of Health's infection control program. Since 2018, blood culturing practices and processes have been analyzed, with feedback to hospitals to promote improvement. In 2019, hospitals were asked to submit the following data on all BCs performed from January 1 to June 30, 2019: patient identification number; birth date; admission date; department; BC bottle type; and the dates and times of the blood draw, laboratory intake, start of incubation, growth detection, reporting of Gram stain results, reporting of pathogen, and reporting of antibiotic susceptibility testing (AST). The study was approved by the Tel Aviv Sourasky Medical Center Institutional Review Board. The informed consent requirement was waived for this analysis of deidentified data. This study followed the applicable portions of the Standards for Quality Improvement Reporting Excellence (SQUIRE) reporting guideline.

Definitions and Inclusion Criteria
We defined a blood culturing episode as a 24-hour period. 8 If blood draws continued for more than 24 hours, we considered them part of the same episode until there were no blood draws for 24 hours.
For example, if blood samples for cultures were taken repeatedly over 72 hours with no 24-hour period without a blood draw, the 72 hours were considered as 1 episode. We defined a rapid test as organism identification within 4 hours of growth detection. 4 We defined true pathogens and common commensals according to the National Healthcare Safety Network Organisms List. 9 We considered common commensals to cause BSI if they were isolated at least twice on separate occasions. 10 We defined common commensals isolated only once as contaminants; we applied this definition across all sites retrospectively. We classified patients as children if the BC was ordered in a pediatric department or the patient's age was younger than 16 years.
We used the following criteria to overcome documentation errors: the start of incubation had to be 5 minutes to 72 hours after the blood draw. Reporting of Gram stain results had to occur after the positive signal and before reporting of isolate identification. Isolate identification had to occur after Gram stain reporting and within 120 hours of the positive signal. To determine conformity to best practices at the hospital level, we included only hospitals with informative data, defined as having plausible documentation for at least half of all bottles.

Statistical Analysis
Data analysis was performed from April 12, 2021, to September 9, 2022. Hospitals were categorized into group 1 (>700 beds or tertiary care), group 2 (400-700 beds), or group 3 (<400 beds). We used To determine the minimum proportion of adult admissions in which BC should be performed (sampling rate) to prevent underdetection of BSI, we used data from 2018-2020. We used a segmented generalized estimating equation with the proportion of admissions with BSI detected as the outcome and sampling rate, modeled as a spline, as the predictor. We chose as the spline knot (ie, the optimal minimum sampling rate) the value that produced the steepest slope below the knot and a nonsignificant, nonnegative slope above the knot.

JAMA Network Open | Infectious Diseases
To determine whether the number of BC sets obtained per episode reflected confounding by indication (ie, only 1 set was performed because there was a low suspicion of BSI), we compared the proportion of first sets positive for a true pathogen when additional sets were not obtained vs when they were obtained. We expressed these 2 values as a positivity ratio. To estimate the number of BSIs that went undetected because no anaerobic bottle was used, we multiplied the percentage of true pathogens detected only in anaerobic bottles by the number of episodes with no anaerobic bottles.
To estimate BSI that went undetected because only 1 aerobic bottle was taken, we multiplied the percentage of episodes with a true pathogen detected only in subsequent aerobic bottles by the number of negative episodes with single aerobic bottles. Then, to account for the possibility that single bottles were collected in episodes with lower risk of a pathogen in additional bottles, we multiplied this result by the positivity ratio.

Frequency of Collecting Blood Culture Samples
Among adults, the number of BC bottles per 100 patient-days ranged widely between hospitals, from 2.5 to 25.8. The mean (SD) rate was 15.5 (6.7) and did not differ significantly between hospital groups (P = .48). The percentage of adult admissions in which at least 1 BC was performed ranged from 2.7% to 29.0%, with a mean (SD) of 15.7% (6.0%) and no significant difference between hospital groups (P = .43). We found an association between sampling rate and pathogen detection until samples for BCs were obtained in 17% of adult admissions (eFigure in the Supplement). For each additional 1% of admissions in which samples for BC were obtained, the percentage in which a BSI caused by a true pathogen was detected increased by 0.09% (95% CI, 0.08%-0.11%; P < .001). Above 17% of admissions, the finding was no longer significant (β = 0.02%; 95% CI, −0.01% to 0.05%; P = .14).

JAMA Network Open | Infectious Diseases
Bloodstream infection caused by a true pathogen was detected in a mean ( a Single blood sampling occasion: 1 blood draw per episode or 2 blood draws less than 2 minutes apart and none the following day (ie, no opportunity to detect BSIs caused by a common commensal).   Median time from growth detection to reporting of Gram stain results was 4.5 hours (IQR, 1.5-10.7 hours), compared with the best practice of 1 hour or less 12 and the PHE goal of less than or equal to 2 hours to reporting of Gram stain results. 5 Median time from growth detection to Gram stain was less than or equal to 2 hours in 3 of 19 hospitals.

JAMA Network Open | Infectious Diseases
Median time from growth detection to isolate identification was 30.9 hours (IQR, 22.0-41.9), compared with the optimal practice of 4 hours using rapid testing methods. 4 The PHE set a goal of 24

Discussion
In this report that included 96.6% of Israeli hospitals, we found major deficiencies in obtaining and processing of blood cultures. We estimated that almost a quarter of all BSIs went undetected because of undersampling of patients, obtaining solitary BCs, or lack of anaerobic cultures.
Contamination rates were much higher than the recommended threshold. We found delays at all steps, with a median time from blood draw to identification that was 3 times longer than best practices, leading to a 34-hour delay in pathogen identification. Processing times were long despite the fact that more than 90% of laboratories are equipped with automated BC systems and matrix- had the capacity to start incubation at any time, and only 13% had 24-hour service to allow immediate processing of bottles that flagged positive. 13 A US study of laboratory data on more than 165 000 BCs from 13 hospitals in 2015-2016 found turnaround times that were longer than best practice goals: a median of 20.4 hours from collection to Gram stain and 43.9 hours from blood draw to isolate identification. 14 In contrast, another analysis of 36 US hospital laboratories (n = 1586 positive BCs) in 2016 demonstrated that best practice goals are within reach: median preanalytical time was 47 minutes and median time from blood draw to identification was 16.4 hours. 15 We studied 3 practices that could lead to underdetection of BSIs. The first was performing BCs in too few patients. We determined that BSI was likely underdetected in hospitals that performed BCs in less than 17% of adult patients. A study in 223 German intensive care units found a pattern similar to ours: BSI detection increased as the sampling rate increased until reaching a saturation point (80-90 BC sets per 1000 patient-days), after which there was no association between sampling rate and detection. 16 These benchmarks are likely not generalizable to other settings, as they will vary with BSI incidence, which depends on factors such as case mix, antibiotic resistance levels, and infection control practices. We lacked International Classification of Diseases admission codes, which would have allowed us to control for case mix. Friedman et al 17 suggested that BC positivity may be a more useful quality indicator than sampling rate; we did not use this indicator, because it is influenced by blood volume (data that we did not have) and the number of BC sets obtained.
The second reason for underdetection was solitary BCs. We estimated that 7.3% of BSIs were missed because only a single aerobic bottle was obtained. An analysis performed in 1983 found 10% underdetection of BSIs by the first BC set compared with 2 sets. 18 More recently, in a study of patients from whom at least 3 sets were collected, 27% of BSIs were detected after the first set. 8 In our study, the paucity of episodes with multiple BCs and the lack of data on blood volume limited our ability to discern the true yield of subsequent bottles.
The third cause of underdetection was failure to perform anaerobic BCs. Although the ratio of aerobic to anaerobic bottles was close to 1.0 in most hospitals, we estimated that 3% of BSIs went undetected because an anaerobic bottle was not used. One British hospital tried collecting aerobic bottles only, hypothesizing that greater blood volume in a single bottle would enhance detection more than adding an anaerobic bottle. The practice was abandoned after finding higher pathogen detection in the control hospital collecting aerobic-anaerobic pairs. 19 Although we identified aspects of insufficient sampling, there also appears to be oversampling or indiscriminate sampling. One sign of this poor diagnostic stewardship is the low positivity rate 20 : true pathogens were detected in a median of 6.7% of BC bottles in adults and a median of 1.1% of  21 Another possible explanation is that the negligence reflected in performing a solitary BC is coupled with drawing a smaller volume of blood, which results in lower positivity.

JAMA Network Open | Infectious Diseases
Interventions can correct the weaknesses identified in this study. During sample collection, decision support reminders in the electronic medical record can reduce solitary BCs. 22 Contamination can be reduced by initial specimen diversion, 23 using dedicated phlebotomists, 24 and avoiding blood draws from intravenous catheters. 25 Blood culture positivity can be increased by increasing the volume of blood collected through education and feedback for personnel, marking the 10-mL point on bottles, 26 and supplying clinical decision tools to avoid BCs in patients at low risk of BSI. 20 The preanalytical stage can be shortened by staffing the microbiology laboratory 24 hours per day 27 or by operating incubators in other laboratories with 24-hour service 28 or at the point of care. 29 Strategies to shorten the analytical stage include ensuring adequate blood volume, 15 performing Gram stains in the core laboratory when the microbiology laboratory is closed, 12 and adopting rapid testing technology. In a meta-analysis, molecular rapid diagnostic testing was reported to decrease mortality following BSI by 34%, translating into the need to use rapid testing on 20 patients with BSI to prevent 1 death. 30

Limitations
This study has limitations. First, although we excluded samples with illogical documentation, our results may partially reflect documentation errors rather than actual practice. Second, our calculations of processing times included only bottles with proper documentation; they may not be representative of all BCs. Third, we lacked data on blood volume, which is an important variable affecting BC positivity and time to detection. Fourth, we lacked data on whether blood samples for cultures were drawn before or after antibiotics were given. Drawing blood before antibiotics are given is an important element of proper blood culturing practice. Drawing blood after antibiotic therapy has started could contribute to the low culture positivity that we observed.

Conclusions
Our study highlights the complexity and pitfalls of blood culturing. The findings suggest that the blood culturing process is inadequately monitored and managed, resulting in poor detection of BSI and delayed results. The blood culturing process should be continuously monitored and improved through data collection, analysis, and intervention.