Imaging and plate counting to quantify the effect of an antimicrobial: A case study of a photo-activated chlorine dioxide treatment.

AIM: To assess removal versus kill efficacies of antimicrobial treatments against thick biofilms with statistical confidence. METHODS AND RESULTS: A photo-activated chlorine dioxide treatment (Photo ClO2 ) was tested in two independent experiments against thick (>100 µm) Pseudomonas aeruginosa biofilms. Kill efficacy was assessed by viable plate counts. Removal efficacy was assessed by 3D confocal scanning laser microscope imaging (CSLM). Biovolumes were calculated using an image analysis approach that models the penetration limitation of the laser into thick biofilms using Beer's Law. Error bars are provided that account for the spatial correlation of the biofilm's surface. The responsiveness of the biovolumes and plate counts to the increasing contact time of Photo ClO2 were quite different, with a massive 7 log reduction in viable cells (95% confidence interval [CI]: 6.2, 7.9) but a more moderate 73% reduction in biovolume (95% CI: [60%, 100%]). Results are leveraged to quantitatively assess candidate CSLM experimental designs of thick biofilms. CONCLUSIONS: Photo ClO2 kills biofilm bacteria but only partially removes the biofilm from the surface. To maximize statistical confidence in assessing removal, imaging experiments should use fewer pixels in each z-slice, and more importantly, at least two independent experiments even if there is only a single field of view in each experiment. SIGNIFICANCE AND IMPACT OF STUDY: There is limited penetration depth when collecting 3D confocal images of thick biofilms. Removal can be assessed by optimally fitting Beer's Law to all of the intensities in a 3D image and by accounting for the spatial correlation of the biofilm's surface. For thick biofilms, other image analysis approaches are biased or do not provide error bars. We generate unbiased estimates of removal and assess candidate CSLM experimental designs of thick biofilms with different pixilations, numbers of fields of view and number of experiments using the included design tool.

Symmetry-Breaking Bifurcations of the Information Bottleneck and Related Problems.

In this paper, we investigate the bifurcations of solutions to a class of degenerate constrained optimization problems. This study was motivated by the Information Bottleneck and Information Distortion problems, which have been used to successfully cluster data in many different applications. In the problems we discuss in this paper, the distortion function is not a linear function of the quantizer. This leads to a challenging annealing optimization problem, which we recast as a fixed-point dynamics problem of a gradient flow of a related dynamical system. The gradient system possesses an SN symmetry due to its invariance in relabeling representative classes. Its flow hence passes through a series of bifurcations with specific symmetry breaks. Here, we show that the dynamical system related to the Information Bottleneck problem has an additional spurious symmetry that requires more-challenging analysis of the symmetry-breaking bifurcation. For the Information Bottleneck, we determine that when bifurcations occur, they are only of pitchfork type, and we give conditions that determine the stability of the bifurcating branches. We relate the existence of subcritical bifurcations to the existence of first-order phase transitions in the corresponding distortion function as a function of the annealing parameter, and provide criteria with which to detect such transitions.

Guide Swap enables genome-scale pooled CRISPR-Cas9 screening in human primary cells.

CRISPR-Cas9 screening allows genome-wide interrogation of gene function. Currently, to achieve the high and uniform Cas9 expression desirable for screening, one needs to engineer stable and clonal Cas9-expressing cells-an approach that is not applicable in human primary cells. Guide Swap permits genome-scale pooled CRISPR-Cas9 screening in human primary cells by exploiting the unexpected finding that editing by lentivirally delivered, targeted guide RNAs (gRNAs) occurs efficiently when Cas9 is introduced in complex with nontargeting gRNA. We validated Guide Swap in depletion and enrichment screens in CD4+ T cells. Next, we implemented Guide Swap in a model of ex vivo hematopoiesis, and identified known and previously unknown regulators of CD34+ hematopoietic stem and progenitor cell (HSPC) expansion. We anticipate that this platform will be broadly applicable to other challenging cell types, and thus will enable discovery in previously inaccessible but biologically relevant human primary cell systems.

Evaluation of the Antimicrobial Efficacy of N-Acetyl-l-Cysteine, Rhamnolipids, and Usnic Acid-Novel Approaches to Fight Food-Borne Pathogens.

In the food industry, the increasing antimicrobial resistance of food-borne pathogens to conventional sanitizers poses the risk of food contamination and a decrease in product quality and safety. Therefore, we explored alternative antimicrobials N-Acetyl-l-cysteine (NAC), rhamnolipids (RLs), and usnic acid (UA) as a novel approach to prevent biofilm formation and reduce existing biofilms formed by important food-borne pathogens (three strains of Salmonella enterica and two strains of Escherichia coli, Listeria monocytogenes, Staphylococcus aureus). Their effectiveness was evaluated by determining minimum inhibitory concentrations needed for inhibition of bacterial growth, biofilm formation, metabolic activity, and biofilm reduction. Transmission electron microscopy and confocal scanning laser microscopy followed by image analysis were used to visualize and quantify the impact of tested substances on both planktonic and biofilm-associated cells. The in vitro cytotoxicity of the substances was determined as a half-maximal inhibitory concentration in five different cell lines. The results indicate relatively low cytotoxic effects of NAC in comparison to RLs and UA. In addition, NAC inhibited bacterial growth for all strains, while RLs showed overall lower inhibition and UA inhibited only the growth of Gram-positive bacteria. Even though tested substances did not remove the biofilms, NAC represents a promising tool in biofilm prevention.

Measuring Antimicrobial Efficacy against Biofilms: a Meta-analysis.

Through a statistical meta-analysis of published data on antimicrobial efficacy against biofilms formed by two common bacterial species, it was concluded that the particular experimental method used is the most important factor determining the outcome of the test. An expected dose-response relationship (greater killing with higher doses or longer treatment times) was observed for data sets derived from a single method but was not observed when data from multiple studies using diverse methods were pooled. Method-specific properties such as the surface area/volume ratio, areal biofilm cell density, and microbial species were shown to influence quantitative measurements of biofilm killing. A better appreciation of the method characteristics that affect antibiofilm efficacy tests could aid decision-making related to investment in research and development and regulatory approvals for biofilm control strategies. The following recommendations are offered to those working in research and development related to biofilm control: (i) report the log reduction, surface area/volume ratio, and biofilm areal cell density; (ii) include data for a benchmark agent, making sure that this agent performs competitively at the dose tested; (iii) measure the dose-response relationship, i.e., make measurements at multiple treatment concentrations or dose durations; and (iv) use a standardized method in addition to research methods.

Quorum sensing inhibition as a promising method to control biofilm growth in metalworking fluids.

Microbial contamination in metalworking systems is a critical problem. This study determined the microbial communities in metalworking fluids (MWFs) from two machining shops and investigated the effect of quorum sensing inhibition (QSI) on biofilm growth. In both operations, biofilm-associated and planktonic microbial communities were dominated by Pseudomonadales (60.2-99.7%). Rapid recolonization was observed even after dumping spent MWFs and meticulous cleaning. Using Pseudomonas aeruginosa PAO1 as a model biofilm organism, patulin (40 µM) and furanone C-30 (75 µM) were identified as effective QSI agents. Both agents had a substantially higher efficacy compared to α-amylase (extracellular polymeric substance degrading enzyme) and reduced biofilm formation by 63% and 76%, respectively, in MWF when compared to untreated controls. Reduced production of putatively identified homoserine lactones and quinoline in MWF treated with QS inhibitors support the effect of QSI on biofilm formation. The results highlight the effectiveness of QSI as a potential strategy to eradicate biofilms in MWFs.

Inactivation of Pseudomonas aeruginosa biofilms formed under high shear stress on various hydrophilic and hydrophobic surfaces by a continuous flow of ozonated water.

The inactivation of Pseudomonas aeruginosa biofilms grown on glass under high shear stress and exposed to a range of dissolved ozone concentrations (2, 5 and 7 ppm) at 10 and 20 min was investigated. The regression equation, log reduction (biofilm) = 0.64 + 0.59×(C - 2) + 0.33×(T - 10), described the dependence of biofilm inactivation on the dissolved ozone concentration (C, ppm) and contact time (T, min). The predicted D-values were 11.1, 5.7 and 2.2 min at 2, 5 and 7 ppm, respectively. Inactivation of biofilms grown on various surfaces was tested at a single dissolved ozone concentration of 5 ppm and a single exposure time of 20 min. Biofilms grown on plastic materials showed inactivation results similar to that of biofilms on glass, while biofilms grown on ceramics were statistically significantly more difficult to inactivate, suggesting the importance of utilizing non-porous materials in industrial and clinical settings.

Physiological and proteomic analysis of Escherichia coli iron-limited chemostat growth.

Iron bioavailability is a major limiter of bacterial growth in mammalian host tissue and thus represents an important area of study. Escherichia coli K-12 metabolism was studied at four levels of iron limitation in chemostats using physiological and proteomic analyses. The data documented an E. coli acclimation gradient where progressively more severe iron scarcity resulted in a larger percentage of substrate carbon being directed into an overflow metabolism accompanied by a decrease in biomass yield on glucose. Acetate was the primary secreted organic by-product for moderate levels of iron limitation, but as stress increased, the metabolism shifted to secrete primarily lactate (∼70% of catabolized glucose carbon). Proteomic analysis reinforced the physiological data and quantified relative increases in glycolysis enzyme abundance and decreases in tricarboxylic acid (TCA) cycle enzyme abundance with increasing iron limitation stress. The combined data indicated that E. coli responds to limiting iron by investing the scarce resource in essential enzymes, at the cost of catabolic efficiency (i.e., downregulating high-ATP-yielding pathways containing enzymes with large iron requirements, like the TCA cycle). Acclimation to iron-limited growth was contrasted experimentally with acclimation to glucose-limited growth to identify both general and nutrient-specific acclimation strategies. While the iron-limited cultures maximized biomass yields on iron and increased expression of iron acquisition strategies, the glucose-limited cultures maximized biomass yields on glucose and increased expression of carbon acquisition strategies. This study quantified ecologically competitive acclimations to nutrient limitations, yielding knowledge essential for understanding medically relevant bacterial responses to host and to developing intervention strategies.

The relative influences of product volume, delivery format and alcohol concentration on dry-time and efficacy of alcohol-based hand rubs.

BACKGROUND: Alcohol-based hand rubs (ABHR) range in alcohol concentration from 60-95% and are available in a variety of delivery formats, such as rinses, gels, and foams. Recent studies suggest that some ABHR foams dry too slowly, thereby encouraging the use of inadequate volumes. This study investigates the influence of product volume, delivery format, and alcohol concentration on dry-time and antimicrobial efficacy of ABHR foams, gels and rinses. METHODS: ABHR dry-times were measured using volunteers to determine the influences of product volume, delivery format, and alcohol concentration. ABHR efficacies were evaluated according to the European Standard for Hygienic Hand Disinfection (EN 1500) using 3-mL application volumes rubbed for 30 s, and additionally, using volumes of the products determined to rub dry in 30 s. RESULTS: Volumes of six ABHR determined to rub dry in 30 s ranged from 1.7 mL to 2.1 mL, and the rate of drying varied significantly between products. ABHR dry-times increased linearly with application volume and decreased linearly with increasing alcohol concentration, but were not significantly influenced by product format. An ABHR foam (70% EtOH), rinse (80% EtOH), and gel (90% EtOH) each met EN 1500 efficacy requirements when tested at a volume of 3 mL, but failed when tested at volumes that dried in 30 s. CONCLUSIONS: Application volume is the primary driver of ABHR dry-time and efficacy, whereas delivery format does not significantly influence either. Although products with greater alcohol concentration dry more quickly, volumes required to meet EN 1500 can take longer than 30 s to dry, even when alcohol concentration is as high as 90%. Future studies are needed to better understand application volumes actually used by healthcare workers in practice, and to understand the clinical efficacy of ABHR at such volumes.

A statistical model for assessing performance standards for quantitative and semiquantitative disinfectant test methods.

A performance standard for a disinfectant test method can be evaluated by quantifying the (Type I) pass-error rate for ineffective products and the (Type II) fail-error rate for highly effective products. This paper shows how to calculate these error rates for test methods where the log reduction in a microbial population is used as a measure of antimicrobial efficacy. The calculations can be used to assess performance standards that may require multiple tests of multiple microbes at multiple laboratories. Notably, the error rates account for among-laboratory variance of the log reductions estimated from a multilaboratory data set and the correlation among tests of different microbes conducted in the same laboratory. Performance standards that require that a disinfectant product pass all tests or multiple tests on average, are considered. The proposed statistical methodology is flexible and allows for a different acceptable outcome for each microbe tested, since, for example, variability may be different for different microbes. The approach can also be applied to semiquantitative methods for which product efficacy is reported as the number of positive carriers out of a treated set and the density of the microbes on control carriers is quantified, thereby allowing a log reduction to be calculated. Therefore, using the approach described in this paper, the error rates can also be calculated for semiquantitative method performance standards specified solely in terms of the maximum allowable number of positive carriers per test. The calculations are demonstrated in a case study of the current performance standard for the semiquantitative AOAC Use-Dilution Methods for Pseudomonas aeruginosa (964.02) and Staphylococcus aureus (955.15), which allow up to one positive carrier out of a set of 60 inoculated and treated carriers in each test. A simulation study was also conducted to verify the validity of the model's assumptions and accuracy. Our approach, easily implemented using the computer code provided, offers a quantitative decision-making tool for assessing a performance standard for any disinfectant test method for which log reductions can be calculated.

Use of statistical modeling to reassess the performance standard for the AOAC use-dilution methods (955.15 and 964.02).

The AOAC Use-dilution methods (UDM) 955.15 (Staphylococcus aureus) and 964.02 (Pseudomonas aeruginosa) are laboratory methods used to substantiate antimicrobial efficacy claims for liquid disinfectants on inanimate surfaces. The UDM is accepted by the U.S. Environmental Protection Agency for the purpose of product registration. To attain a hospital-level claim, testing against S. aureus and P. aeruginosa is required, and the product must pass against both microbes. Currently, the UDM's performance standard for a single 60-carrier test is the same for both microbes, and allows up to one positive carrier for the product to be considered as a pass. In this paper, the performance standards for these methods are reassessed using data from a 2009 five-laboratory collaborative study and a recently published statistical model. The reassessment focuses on the pass-error rate for ineffective products and the fail-error rate for highly effective products. The calculations indicate that the pass-error rate is between 9 and 24% and the fail-error rate between 18 and 23% when the current performance standard is used for a single test. For product registration, a smaller pass-error rate (1%) historically has been maintained by requiring that a disinfectant pass three UDM tests for each of the two microbes; however, the calculations also indicate that the fail-error rate is between 42 and 45%. This large fail-error rate is a compelling reason to consider a new performance standard for the two UDM methods, 955.15 (S. aureus) and 964.02 (P. aeruginosa). One alternative performance standard allows no more than six positive carriers out of 60 as a pass when using P. aeruginosa and no more than three positive carriers out of 60 when using S. aureus. In addition, the new performance standard requires that three UDM tests be performed with each of the two microbes, and the disinfectant must pass all six tests to be considered efficacious. The statistical calculations for this alternative performance standard indicate that the pass-error rate is no more than 3%, while the fail-error rate is as small as 5%. Based on these error rate calculations, proposed revisions to the performance standards for AOAC Methods 955.15 and 964.02 are provided.

Coupon position does not affect Pseudomonas aeruginosa and Staphylococcus aureus biofilm densities in the CDC biofilm reactor.

The CDC Biofilm Reactor method is the standard biofilm growth protocol for the validation of US Environmental Protection Agency biofilm label claims. However, no studies have determined the effect of coupon orientation within the reactor on biofilm growth. If positional effects have a statistically significant impact on biofilm density, they should be accounted for in the experimental design. Here, we isolate and quantify biofilms from each possible coupon surface in the reactor to quantitatively determine the positional effects in the CDC Biofilm Reactor. The results showed no statistically significant differences in viable cell density across different orientations and vertical positions in the reactor. Pseudomonas aeruginosa log densities were statistically equivalent among all coupon heights and orientations. While the Staphylococcus aureus cell growth showed no statistically significant differences, the densities were not statistically equivalent among all coupon heights and orientations due to the variability in the data. Structural differences were observed between biofilms on the high-shear baffle side of the reactor compared to the lower shear glass side of the reactor. Further studies are required to determine whether biofilm susceptibility to antimicrobials differs based on structural differences attributed to orientation.

The effect of a prospective intervention program with automated monitoring of hand hygiene performance in long-term and acute-care units at a Veterans Affairs medical center.

OBJECTIVE: To measure the impact of an automated hand hygiene monitoring system (AHHMS) and an intervention program of complementary strategies on hand hygiene (HH) performance in both acute-care and long-term care (LTC) units. DESIGN: Prospective, nonrandomized, before-and-after intervention study. SETTING: Single Veterans Affairs Medical Center (VAMC), with 2 acute-care units and 6 LTC units. METHODS: An AHHMS that provides group HH performance rates was implemented on 8 units at a VAMC from March 2021 through April 2022. After a 4-week baseline period and 2.5-week washout period, the 52-week intervention period included multiple evidence-based components designed to improve HH compliance. Unit HH performance rates were expressed as the number of dispenses (events) divided by the number of patient room entries and exits (opportunities) × 100. Statistical analysis was performed with a Poisson general additive mixed model. RESULTS: During the 4-week baseline period, the median HH performance rate was 18.6 (95% CI, 16.5-21.0) for all 8 units. During the intervention period, the median HH rate increased to 21.6 (95% CI, 19.1-24.4; P < .0001), and during the last 4 weeks of the intervention period (exactly 1 year after baseline), the 8 units exhibited a median HH rate of 25.1 (95% CI, 22.2-28.4; P < .0001). The median HH rate increased from 17.5 to 20.0 (P < .0001) in LTC units and from 22.9 to 27.2 (P < .0001) in acute-care units. CONCLUSIONS: The intervention was associated with increased HH performance rates for all units. The performance of acute-care units was consistently higher than LTC units, which have more visitors and more mobile veterans.

Influence of season and plant species on the abundance and diversity of sulfate reducing bacteria and ammonia oxidizing bacteria in constructed wetland microcosms.

Constructed wetlands offer an effective means for treatment of wastewater from a variety of sources. An understanding of the microbial ecology controlling nitrogen, carbon and sulfur cycles in constructed wetlands has been identified as the greatest gap for optimizing performance of these promising treatment systems. It is suspected that operational factors such as plant types and hydraulic operation influence the subsurface wetland environment, especially redox, and that the observed variation in effluent quality is due to shifts in the microbial populations and/or their activity. This study investigated the biofilm associated sulfate reducing bacteria and ammonia oxidizing bacteria (using the dsrB and amoA genes, respectively) by examining a variety of surfaces within a model wetland (gravel, thick roots, fine roots, effluent), and the changes in activity (gene abundance) of these functional groups as influenced by plant species and season. Molecular techniques were used including quantitative PCR and denaturing gradient gel electrophoresis (DGGE), both with and without propidium monoazide (PMA) treatment. PMA treatment is a method for excluding from further analysis those cells with compromised membranes. Rigorous statistical analysis showed an interaction between the abundance of these two functional groups with the type of plant and season (p < 0.05). The richness of the sulfate reducing bacterial community, as indicated by DGGE profiles, increased in planted vs. unplanted microcosms. For ammonia oxidizing bacteria, season had the greatest impact on gene abundance and diversity (higher in summer than in winter). Overall, the primary influence of plant presence is believed to be related to root oxygen loss and its effect on rhizosphere redox.

Guidelines for the statistical analysis of a collaborative study of a laboratory method for testing disinfectant product performance.

This paper presents statistical techniques suitable for analyzing a collaborative study (multilaboratory study or ring trial) of a laboratory disinfectant product performance test (DPPT) method. Emphasis is on the assessment of the repeatability, reproducibility, resemblance, and responsiveness of the DPPT method. The suggested statistical techniques are easily modified for application to a single laboratory study. The presentation includes descriptions of the plots and tables that should be constructed during initial examination of the data, including a discussion of outliers and QA checks. The statistical recommendations deal with evaluations of prevailing types of DPPTs, including both quantitative and semiquantitative tests. The presentation emphasizes tests in which the disinfectant treatment is applied to surface-associated microbes and the outcome is a viable cell count; however, the statistical guidelines are appropriate for suspension tests and other test systems. The recommendations also are suitable for disinfectant tests using any microbe (vegetative bacteria, virus, spores, etc.) or any disinfectant treatment. The descriptions of the statistical techniques include either examples of calculations based on published data or citations to published calculations. Computer code is provided in an appendix.

Sample sizes for estimating the sensitivity of a monitoring system that generates repeated binary outcomes with autocorrelation.

Sample size formulas are provided to determine how many events and how many patient care units are needed to estimate the sensitivity of a monitoring system. The monitoring systems we consider generate time series binary data that are autocorrelated and clustered by patient care units. Our application of interest is an automated hand hygiene monitoring system that assesses whether healthcare workers perform hand hygiene when they should. We apply an autoregressive order 1 mixed effects logistic regression model to determine sample sizes that allow the sensitivity of the monitoring system to be estimated at a specified confidence level and margin of error. This model overcomes a major limitation of simpler approaches that fail to provide confidence intervals with the specified levels of confidence when the sensitivity of the monitoring system is above 90%.

Calculating the limit of detection for a dilution series.

AIMS: Microbial samples are often serially diluted to estimate the number of microbes in a sample, whether as colony-forming units of bacteria or algae, plaque forming units of viruses, or cells under a microscope. There are at least three possible definitions for the limit of detection (LOD) for dilution series counts in microbiology. The statistical definition that we explore is that the LOD is the number of microbes in a sample that can be detected with high probability (commonly 0.95). METHODS AND RESULTS: Our approach extends results from the field of chemistry using the negative binomial distribution that overcomes the simplistic assumption that counts are Poisson. The LOD is a function of statistical power (one minus the rate of false negatives), the amount of overdispersion compared to Poisson counts, the lowest countable dilution, the volume plated, and the number of independent samples. We illustrate our methods using a data set from Pseudomonas aeruginosa biofilms. CONCLUSIONS: The techniques presented here can be applied to determine the LOD for any counting process in any field of science whenever only zero counts are observed. SIGNIFICANCE AND IMPACT OF STUDY: We define the LOD when counting microbes from dilution experiments. The practical and accessible calculation of the LOD will allow for a more confident accounting of how many microbes can be detected in a sample.

Bacterial transfer and biofilm formation in needleless connectors in a clinically simulated in vitro catheter model.

OBJECTIVE: Although needleless connectors (NCs) are widely used in clinical practice, they carry significant risk of bloodstream infection (BSI). In this study, we quantified differences in bacterial transfer and biofilm formation between various NCs. DESIGN: Prospective, clinically simulated in vitro experimental study. METHODS: We tested 20 NCs in a 5-day clinical simulation of Staphylococcus aureus inoculations onto NC septum surfaces, which were then flushed with saline and cultured for bacterial transfer. Biofilm formation was measured through destructive sampling of the connector-catheter system. Moreover, 8 NC design factors were evaluated for their influence on bacterial transfer and biofilm formation. This study was designed without a disinfection protocol to ascertain the intrinsic risk of each NC. RESULTS: Clave Neutron and MicroClave had the lowest overall mean log density of bacteria in the flush compared to other NCs (P < .05), except there were no statistically significant differences between Clave Neutron, Microclave, SafeTouch, and SafeAccess (P ≥ .05). The amount of biofilm in the NC was positively associated with bacteria in the flush (P < .0005). Among 8 design factors, flow path was most important, with the internal cannula associated with a statistically significant 1 log reduction (LR) in bacteria in the flush (R2 = 49%) and 0.5-2 LR in the connector (R2 = 34%). All factors together best explained bacteria in the flush (R2 = 65%) and biofilm in the connector (R2 = 48%). CONCLUSIONS: Bacterial transfer and biofilm formation in the connector-catheter system varied statistically significantly between the 20 NCs, suggesting that NC choice can lower the risk of developing catheter-related BSIs.

Comparison of quantification methods for an endoscope lumen biofilm model.

Biofilm has been implicated in multi-drug resistant organism outbreaks following endoscopic procedures. Automated Endoscope Reprocessors (AER) are devices validated to clean and disinfect endoscopes per applicable standards. The ISO 15883 part 4 standard guides performance testing validation of AERs, including cleaning performance using a biofilm test soil. The standard recommends assessment of biofilm reduction using protein or carbohydrate quantification methods. The aim of this study was to assess the suitability of various quantification methods using the ISO biofilm model. The ISO 15883 part 5 biofilm test soil method was used to grow biofilm within lumens representative of endoscopes channels. The biofilm was then quantified using five methods: Crystal Violet (CV), Colony Forming Units (CFU), Total Organic Carbon (TOC), protein assay with Orthophtalaldehyde (OPA), and protein assay by micro bicinchoninic acid (µBCA). The five methods were statistically analyzed for their ability to assess biofilm reduction on samples accurately and precisely. In addition, the quantification methods were compared to demonstrate statistical equivalency, and thus their suitability for assessing biofilm cleaning performance testing of AERs.

The impact of automated hand hygiene monitoring with and without complementary improvement strategies on performance rates.

OBJECTIVE: To determine how engagement of the hospital and/or vendor with performance improvement strategies combined with an automated hand hygiene monitoring system (AHHMS) influence hand hygiene (HH) performance rates. DESIGN: Prospective, before-and-after, controlled observational study. SETTING: The study was conducted in 58 adult and pediatric inpatient units located in 10 hospitals. METHODS: HH performance rates were estimated using an AHHMS. Rates were expressed as the number of soap and alcohol-based hand rub portions dispensed divided by the number of room entries and exits. Each hospital self-assigned to one of the following intervention groups: AHHMS alone (control group), AHHMS plus clinician-based vendor support (vendor-only group), AHHMS plus hospital-led unit-based initiatives (hospital-only group), or AHHMS plus clinician-based vendor support and hospital-led unit-based initiatives (vendor-plus-hospital group). Each hospital unit produced 1­2 months of baseline HH performance data immediately after AHHMS installation before implementing initiatives. RESULTS: Hospital units in the vendor-plus-hospital group had a statistically significant increase of at least 46% in HH performance compared with units in the other 3 groups (P ≤ .006). Units in the hospital only group achieved a 1.3% increase in HH performance compared with units that had AHHMS alone (P = .950). Units with AHHMS plus other initiatives each had a larger change in HH performance rates over their baseline than those in the AHHMS-alone group (P < 0.001). CONCLUSIONS: AHHMS combined with clinician-based vendor support and hospital-led unit-based initiatives resulted in the greatest improvements in HH performance. These results illustrate the value of a collaborative partnership between the hospital and the AHHMS vendor.