Linking antimicrobial prescribing to antimicrobial resistance in the ICU: before and after an antimicrobial stewardship program

An agent-based model on antimicrobial de-escalation in intensive care units: Implications on clinical trial design

Antimicrobial de-escalation refers to reducing the spectrum of antibiotics used in treating bacterial infections. This strategy is widely recommended in many antimicrobial stewardship programs and is believed to reduce patients' exposure to broad-spectrum antibiotics and prevent resistance. However, the ecological benefits of de-escalation have not been universally observed in clinical studies. This paper conducts computer simulations to assess the ecological effects of de-escalation on the resistance prevalence of Pseudomonas aeruginosa-a frequent pathogen causing nosocomial infections. Synthetic data produced by the models are then used to estimate the sample size and study period needed to observe the predicted effects in clinical trials. Our results show that de-escalation can reduce colonization and infections caused by bacterial strains resistant to the empiric antibiotic, limit the use of broad-spectrum antibiotics, and avoid inappropriate empiric therapies. Further, we show that de-escalation could reduce the overall super-infection incidence, and this benefit becomes more evident under good compliance with hand hygiene protocols among health care workers. Finally, we find that any clinical study aiming to observe the essential effects of de-escalation should involve at least ten arms and last for four years-a size never attained in prior studies. This study explains the controversial findings of de-escalation in previous clinical studies and illustrates how mathematical models can inform outcome expectations and guide the design of clinical studies.

A stochastic dynamical model for nosocomial infections with co-circulation of sensitive and resistant bacterial strains

Nosocomial infections (hospital-acquired) has been an important public health problem, which may make those patients with infections or involved visitors and hospital personnel at higher risk of worse clinical outcomes or infection, and then consume more healthcare resources. Taking into account the stochasticity of the death and discharge rate of patients staying in hospitals, in this paper, we propose a stochastic dynamical model describing the transmission of nosocomial pathogens among patients admitted for hospital stays. The stochastic terms of the model are incorporated to capture the randomness arising from death and discharge processes of patients. Firstly, a sufficient condition is established for the stochastic extinction of disease. It shows that introducing randomness in the model will result in lower potential of nosocomial outbreaks. Further, we establish a threshold criterion on the existence of stationary distribution and ergodicity for any positive solution of the model. Particularly, the spectral radius form of stochastic threshold value is calculated in the special case. Moreover, the numerical simulations are conducted to both validate the theoretical results and investigate the effect of prevention and control strategies on the prevalence of nosocomial infection. We show that enhancing hygiene, targeting colonized and infected patients, improving antibiotic treatment accuracy, shortening treatment periods are all crucial factors to contain nosocomial infections.

Microbiome-pathogen interactions drive epidemiological dynamics of antibiotic resistance: A modeling study applied to nosocomial pathogen control

The human microbiome can protect against colonization with pathogenic antibiotic-resistant bacteria (ARB), but its impacts on the spread of antibiotic resistance are poorly understood. We propose a mathematical modeling framework for ARB epidemiology formalizing within-host ARB-microbiome competition, and impacts of antibiotic consumption on microbiome function. Applied to the healthcare setting, we demonstrate a trade-off whereby antibiotics simultaneously clear bacterial pathogens and increase host susceptibility to their colonization, and compare this framework with a traditional strain-based approach. At the population level, microbiome interactions drive ARB incidence, but not resistance rates, reflecting distinct epidemiological relevance of different forces of competition. Simulating a range of public health interventions (contact precautions, antibiotic stewardship, microbiome recovery therapy) and pathogens (Clostridioides difficile, methicillin-resistant Staphylococcus aureus, multidrug-resistant Enterobacteriaceae) highlights how species-specific within-host ecological interactions drive intervention efficacy. We find limited impact of contact precautions for Enterobacteriaceae prevention, and a promising role for microbiome-targeted interventions to limit ARB spread.

Variation in antibiotic use across intensive care units (ICU): A population-based cohort study in Ontario, Canada

OBJECTIVES

Antibiotics are commonly used in intensive care units (ICUs), yet differences in antibiotic use across ICUs are unknown. Herein, we studied antibiotic use across ICUs and examined factors that contributed to variation.

METHODS

We conducted a retrospective cohort study using data from Ontario's Critical Care Information System (CCIS), which included 201 adult ICUs and 2,013,397 patient days from January 2012 to June 2016. Antibiotic use was measured in days of therapy (DOT) per 1,000 patient days. ICU factors included ability to provide ventilator support (level 3) or not (level 2), ICU type (medical-surgical or other), and academic status. Patient factors included severity of illness using multiple-organ dysfunction score (MODS), ventilatory support, and central venous catheter (CVC) use. We analyzed the effect of these factors on variation in antibiotic use.

RESULTS

Overall, 269,351 patients (56%) received antibiotics during their ICU stay. The mean antibiotic use was 624 (range 3-1460) DOT per 1,000 patient days. Antibiotic use was significantly higher in medical-surgical ICUs compared to other ICUs (697 vs 410 DOT per 1,000 patient days; P < .0001) and in level 3 ICUs compared to level 2 ICUs (751 vs 513 DOT per 1,000 patient days; P < .0001). Higher antibiotic use was associated with higher severity of illness and intensity of treatment. ICU and patient factors explained 47% of the variation in antibiotic use across ICUs.

CONCLUSIONS

Antibiotic use varies widely across ICUs, which is partially associated with ICUs and patient characteristics. These differences highlight the importance of antimicrobial stewardship to ensure appropriate use of antibiotics in ICU patients.

Modeling Antibiotic Use Strategies in Intensive Care Units: Comparing De-escalation and Continuation

Antimicrobial de-escalation refers to the treatment mechanism of switching from empiric antibiotics with good coverage to alternatives based on laboratory susceptibility test results, with the aim of avoiding unnecessary use of broad-spectrum antibiotics. In a previous study, we have developed multi-strain and multi-drug models in an intensive care unit setting, to evaluate the benefits and trade-offs of de-escalation in comparison with the conventional strategy called antimicrobial continuation. Our simulation results indicated that for a large portion of credible parameter combinations, de-escalation reduces the use of the empiric antibiotic but increases the probabilities of colonization and infections. In this paper, we first simplify the previous models to compare the long-term dynamical behaviors between de-escalation and continuation systems under a two-strain scenario. The analytical results coincide with our previous findings in the complex models, indicating the benefits and unintended consequences of de-escalation strategy result from the nature of this treatment mechanism, not from the complexity of the high-dimensional systems. By extending the models to three-strain scenarios, we find that de-escalation is superior than continuation in preventing outbreaks of invading strains that are resistant to empiric antibiotics. Thus decisions on antibiotic use strategies should be made specifically according to ICU conditions and intervention objectives.

Long-Term Effects of Phased Implementation of Antimicrobial Stewardship in Academic ICUs: 2007-2015

OBJECTIVES

Antimicrobial stewardship is advocated to reduce antimicrobial resistance in ICUs by reducing unnecessary antimicrobial consumption. Evidence has been limited to short, single-center studies. We evaluated whether antimicrobial stewardship in ICUs could reduce antimicrobial consumption and costs.

DESIGN

We conducted a phased, multisite cohort study of a quality improvement initiative.

SETTING

Antimicrobial stewardship was implemented in four academic ICUs in Toronto, Canada beginning in February 2009 and ending in July 2012.

PATIENTS

All patients admitted to each ICU from January 1, 2007, to December 31, 2015, were included.

INTERVENTIONS

Antimicrobial stewardship was delivered using in-person coaching by pharmacists and physicians three to five times weekly, and supplemented with unit-based performance reports. Total monthly antimicrobial consumption (measured by defined daily doses/100 patient-days) and costs (Canadian dollars/100 patient-days) before and after antimicrobial stewardship implementation were measured.

MEASUREMENTS AND MAIN RESULTS

A total of 239,123 patient-days (57,195 patients) were analyzed, with 148,832 patient-days following introduction of antimicrobial stewardship. Antibacterial use decreased from 120.90 to 110.50 defined daily dose/100 patient-days following introduction of antimicrobial stewardship (adjusted intervention effect -12.12 defined daily dose/100 patient-days; 95% CI, -16.75 to -7.49; p < 0.001) and total antifungal use decreased from 30.53 to 27.37 defined daily doses/100 patient-days (adjusted intervention effect -3.16 defined daily dose/100 patient-days; 95% CI, -8.33 to 0.04; p = 0.05). Monthly antimicrobial costs decreased from $3195.56 to $1998.59 (adjusted intervention effect -$642.35; 95% CI, -$905.85 to -$378.84; p < 0.001) and total antifungal costs were unchanged from $1771.86 to $2027.54 (adjusted intervention effect -$355.27; 95% CI, -$837.88 to $127.33; p = 0.15). Mortality remained unchanged, with no consistent effects on antimicrobial resistance and candidemia.

CONCLUSIONS

Antimicrobial stewardship in ICUs with coaching plus audit and feedback is associated with sustained improvements in antimicrobial consumption and cost. ICUs with high antimicrobial consumption or expenditure should consider implementing antimicrobial stewardship programs.

Clinical Diagnosis of Infection in Surgical Intensive Care Unit: You're Not as Good as You Think!

Background: Because of the everincreasing costs and the complexity of institutional medical reimbursement policies, the necessity for extensive laboratory work-up of potentially infected patients has come into question. We hypothesized that intensivists are able to differentiate between infected and non-infected patients clinically, without the need to pan-culture, and are able to identify the location of the infection clinically in order to administer timely and appropriate treatment. Methods: Data collected prospectively on critically ill patients suspected of having an infection in the surgical intensive care unit (SICU) was obtained over a six-month period in a single tertiary academic medical center. Objective evidence of infection derived from laboratory or imaging data was compared with the subjective answers of the three most senior physicians' clinical diagnoses. Results: Thirty-nine critically ill surgical patients received 52 work-ups for suspected infections on the basis of signs and symptoms (e.g., fever, altered mental status). Thirty patients were found to be infected. Clinical diagnosis differentiated infected and non-infected patients with only 61.5% accuracy (sensitivity 60.3%; specificity 64.4%; p = 0.0049). Concordance between physicians was poor (κ = 0.33). Providers were able to predict the infectious source correctly only 60% of the time. Utilization of culture/objective data and SICU antibiotic protocols led to overall 78% appropriate initiation of antibiotics compared with 48% when treatment was based on clinical evaluation alone. Conclusion: Clinical diagnosis of infection is difficult, inaccurate, and unreliable in the absence of culture and sensitivity data. Infection suspected on the basis of signs and symptoms should be confirmed via objective and thorough work-up.

Population-level mathematical modeling of antimicrobial resistance: a systematic review

BACKGROUND

Mathematical transmission models are increasingly used to guide public health interventions for infectious diseases, particularly in the context of emerging pathogens; however, the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear. Here, we systematically evaluate publications on population-level transmission models of AMR over a recent period (2006-2016) to gauge the state of research and identify gaps warranting further work.

METHODS

We performed a systematic literature search of relevant databases to identify transmission studies of AMR in viral, bacterial, and parasitic disease systems. We analyzed the temporal, geographic, and subject matter trends, described the predominant medical and behavioral interventions studied, and identified central findings relating to key pathogens.

RESULTS

We identified 273 modeling studies; the majority of which (> 70%) focused on 5 infectious diseases (human immunodeficiency virus (HIV), influenza virus, Plasmodium falciparum (malaria), Mycobacterium tuberculosis (TB), and methicillin-resistant Staphylococcus aureus (MRSA)). AMR studies of influenza and nosocomial pathogens were mainly set in industrialized nations, while HIV, TB, and malaria studies were heavily skewed towards developing countries. The majority of articles focused on AMR exclusively in humans (89%), either in community (58%) or healthcare (27%) settings. Model systems were largely compartmental (76%) and deterministic (66%). Only 43% of models were calibrated against epidemiological data, and few were validated against out-of-sample datasets (14%). The interventions considered were primarily the impact of different drug regimens, hygiene and infection control measures, screening, and diagnostics, while few studies addressed de novo resistance, vaccination strategies, economic, or behavioral changes to reduce antibiotic use in humans and animals.

CONCLUSIONS

The AMR modeling literature concentrates on disease systems where resistance has been long-established, while few studies pro-actively address recent rise in resistance in new pathogens or explore upstream strategies to reduce overall antibiotic consumption. Notable gaps include research on emerging resistance in Enterobacteriaceae and Neisseria gonorrhoeae; AMR transmission at the animal-human interface, particularly in agricultural and veterinary settings; transmission between hospitals and the community; the role of environmental factors in AMR transmission; and the potential of vaccines to combat AMR.

Impact of a multimodal strategy combining a new standard of care and restriction of carbapenems, fluoroquinolones and cephalosporins on antibiotic consumption and resistance of Pseudomonas aeruginosa in a French intensive care unit

This study aimed to assess whether post-prescription review and feedback (PPRF) of all antibiotics, with restriction of carbapenems, fluoroquinolones and third-generation cephalosporins (3GCs), along with a change in medical standard of care impacted antibiotic consumption and bacterial antimicrobial resistance in a French medical/surgical intensive care unit (ICU). A 4-year before (2007-2010) and after (2011-2014) retrospective comparative study was performed. Antibiotic consumption was evaluated in defined daily doses per 1000 patient-days. The rates of Pseudomonas aeruginosa resistance to piperacillin, ceftazidime, ciprofloxacin, imipenem and amikacin and of AmpC-hyperproducing group 3 Enterobacteriaceae were assessed. Consumption of fluoroquinolones decreased by -85%, carbapenems by -58%, 3GCs by -50% and glycopeptides by -66% (P ≤ 0.0001). Consumption of penicillins with and without β-lactamase inhibitors increased by +72% and +78%, sulfonamides by +172% and macrolides by +267% (P < 0.0001). Pseudomonas aeruginosa resistance rates for all antibiotics tested and the proportion of AmpC-hyperproducing group 3 Enterobacteriaceae decreased (P ≤ 0.01). The median length of stay, use of vasopressors and invasive mechanical ventilation decreased, and the use of renal replacement therapy increased (P < 0.05). The initial severity score (SAPS II) increased (P < 0.01) due to changes in practice, with no impact on in-hospital mortality (P = 0.07). In conclusion, changes in medical care along with PPRF and a restriction of high ecological impact antibiotics were associated with a shift towards the consumption of low ecological impact antibiotics in an ICU. Rates of resistant P. aeruginosa and of AmpC-hyperproducing group 3 Enterobacteriaceae decreased simultaneously.

Antibiotic Stewardship: Strategies to Minimize Antibiotic Resistance While Maximizing Antibiotic Effectiveness

Empiric therapy of the septic patient in the hospital is challenging. Antibiotic stewardship is concerned with optimizing antibiotic use and minimizing resistance. Clinicians should avoid overcovering and overtreating colonizing organisms in respiratory secretions and urinary catheters. Empiric therapy should take into account the prevalence of multidrug-resistant organisms in the hospital setting. The most effective resistance prevention strategies is to preferentially select a low resistance potential antibiotic, which should be administered in the highest possible dose without toxicity for the shortest duration to eliminate the infection.

Application of dynamic modelling techniques to the problem of antibacterial use and resistance: a scoping review

Selective pressure exerted by the widespread use of antibacterial drugs is accelerating the development of resistant bacterial populations. The purpose of this scoping review was to summarise the range of studies that use dynamic models to analyse the problem of bacterial resistance in relation to antibacterial use in human and animal populations. A comprehensive search of the peer-reviewed literature was performed and non-duplicate articles (n = 1486) were screened in several stages. Charting questions were used to extract information from the articles included in the final subset (n = 81). Most studies (86%) represent the system of interest with an aggregate model; individual-based models are constructed in only seven articles. There are few examples of inter-host models outside of human healthcare (41%) and community settings (38%). Resistance is modelled for a non-specific bacterial organism and/or antibiotic in 40% and 74% of the included articles, respectively. Interventions with implications for antibacterial use were investigated in 67 articles and included changes to total antibiotic consumption, strategies for drug management and shifts in category/class use. The quality of documentation related to model assumptions and uncertainty varies considerably across this subset of articles. There is substantial room to improve the transparency of reporting in the antibacterial resistance modelling literature as is recommended by best practice guidelines.

Antimicrobial stewardship programmes: bedside rationing by another name?

Antimicrobial therapy is a cornerstone of therapy in critically ill patients; however, the wide use of antibiotics has resulted in increased antimicrobial resistance and outbreaks of resistant disease. To counter this, many hospitals have instituted antimicrobial stewardship programmes as a way to reduce the inappropriate use of antibiotics. However, uptake of antimicrobial stewardship programmes has been variable, as many clinicians fear that they may put individual patients at risk of treatment failure. In this paper, I argue that antimicrobial stewardship programmes are indeed a form of bedside rationing, and explore the risks and benefits of such programmes for individual patients in the intensive care unit, and the critically ill population in general. Using Norman Daniels' Accountability for Reasonableness as a framework for evaluating resource allocation policies, I conclude that antimicrobial stewardship programmes are an ethically sound form of bedside rationing.

Optimal control applied to community-acquired methicillin-resistant Staphylococcus aureus in hospitals

Optimal control methods are applied to a deterministic mathematical model to characterize the factors contributing to the replacement of hospital-acquired methicillin-resistant Staphylococcus aureus (HA-MRSA) with community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA), and quantify the effectiveness of three interventions aimed at limiting the spread of CA-MRSA in healthcare settings. Characterizations of the optimal control strategies are established, and numerical simulations are provided to illustrate the results.

Benefits and unintended consequences of antimicrobial de-escalation: Implications for stewardship programs

Sequential antimicrobial de-escalation aims to minimize resistance to high-value broad-spectrum empiric antimicrobials by switching to alternative drugs when testing confirms susceptibility. Though widely practiced, the effects de-escalation are not well understood. Definitions of interventions and outcomes differ among studies. We use mathematical models of the transmission and evolution of Pseudomonas aeruginosa in an intensive care unit to assess the effect of de-escalation on a broad range of outcomes, and clarify expectations. In these models, de-escalation reduces the use of high-value drugs and preserves the effectiveness of empiric therapy, while also selecting for multidrug-resistant strains and leaving patients vulnerable to colonization and superinfection. The net effect of de-escalation in our models is to increase infection prevalence while also increasing the probability of effective treatment. Changes in mortality are small, and can be either positive or negative. The clinical significance of small changes in outcomes such as infection prevalence and death may exceed more easily detectable changes in drug use and resistance. Integrating harms and benefits into ranked outcomes for each patient may provide a way forward in the analysis of these tradeoffs. Our models provide a conceptual framework for the collection and interpretation of evidence needed to inform antimicrobial stewardship.

Impact of Antimicrobial Stewardship on Physician Practice in a Geriatric Facility

BACKGROUND

There is a paucity of literature describing the implementation of antimicrobial stewardship programs (ASPs) in long-term care (LTC) facilities. The current study evaluated the impact of an ASP that was implemented across a geriatric facility, which included an inpatient specialty hospital and an LTC facility. The program included prospective audits with feedback, multidisciplinary education, information technology interventions, and guideline development.

OBJECTIVE

To investigate the impact of the ASP on physicians' prescribing practices in this geriatric facility.

METHODS

Utilization data for antibiotics commonly used to treat urinary tract infections were retrieved for the period September 1, 2011, to August 31, 2013. The study examined whether there were significant changes in overall antibiotic use, ciprofloxacin use, and physician prescribing behaviour after program implementation in September 2012.

RESULTS

There was no significant change in the total number of antibiotic prescriptions for urinary tract infections in the hospital or the LTC facility after ASP implementation. Significant reductions were seen in the average days of therapy initially prescribed and the actual days of therapy after ASP implementation in the LTC facility but not the hospital. Across both facilities, significant reductions were seen in the number of ciprofloxacin prescriptions.

CONCLUSIONS

The current study showed that an ASP can affect physicians' antibiotic prescribing behaviour and antibiotic usage in an LTC environment.

Tobacco Smoking as a Risk Factor for Increased Antibiotic Prescription

INTRODUCTION

Antibiotic resistance is rapidly spreading, affecting millions of people and costing billions of dollars. Potential factors affecting antibiotic prescription, such as tobacco use, could dramatically influence this public health crisis. The study determined the magnitude of impact that tobacco use has on antibiotic prescribing patterns.

METHODS

Pooled data were analyzed in 2015 from the 2006-2010 National Ambulatory Medical Care Survey, a cross-sectional survey describing use of ambulatory medical services in the U.S. via healthcare provider-patient encounters. Patients aged >18 years with documented tobacco use status diagnosed with an infection were included (i.e., all encounters in the analysis included an infectious diagnosis of interest). The analytic sample included 8,307 visits, representing 294 million visits nationally.

RESULTS

Half (49.9%) of encounters that included any infection had an antibiotic prescribed. Adjusted odds of receiving antibiotics among current tobacco users was 1.20 (95% CI=1.02, 1.42), and even higher for encounters of respiratory infections (AOR=1.31, 95% CI=1.05, 1.62). Antibiotic prescription rates were lower among patients aged >65 years, those with comorbid asthma or cancer, non-whites, and those covered by Medicaid and higher for primary care physicians.

CONCLUSIONS

Despite lack of evidence-based rationale, among a national sample of patients with an infectious diagnosis, tobacco users had 20%-30% higher odds of receiving antibiotics than non-tobacco users. This is the first U.S. study to quantify the magnitude of this unsubstantiated practice. Prescribers should understand that tobacco use could be associated with higher antibiotic prescription, which may subsequently increase antimicrobial resistance in the community.

Pros and cons of using biomarkers versus clinical decisions in start and stop decisions for antibiotics in the critical care setting

INTRODUCTION

Patients in the intensive care unit (ICU) frequently receive prolonged or even unnecessary antibiotic therapy, which selects for antibiotic-resistant bacteria. Over the last decade there has been great interest in biomarkers, particularly procalcitonin, to reduce antibiotic exposure.

METHODS

In this narrative review, we discuss the value of biomarkers and provide additional information beyond clinical evaluation in order to be clinically useful and review the literature on sepsis biomarkers outside the neonatal period. Both benefits and limitations of biomarkers for clinical decision-making are reviewed.

RESULTS

Several randomized controlled trials (RCTs) have shown the safety and efficacy of procalcitonin to discontinue antibiotic therapy in patients with severe sepsis or septic shock. In contrast, there is limited utility of procalcitonin for treatment initiation or withholding therapy initially. In addition, an algorithm using procalcitonin for treatment escalation has been ineffective and is probably associated with poorer outcomes. Little data from interventional studies are available for other biomarkers for antibiotic stewardship, except for C-reactive protein (CRP), which was recently found to be similarly effective and safe as procalcitonin in a randomized controlled trial. We finally briefly discuss biomarker-unrelated approaches to reduce antibiotic duration in the ICU, which have shown that even without biomarker guidance, most patients with sepsis can be treated with relatively short antibiotic courses of approximately 7 days.

CONCLUSIONS

In summary, there is an ongoing unmet need for biomarkers which can reliably and early on identify patients who require antibiotic therapy, distinguish between responders and non-responders and help to optimize antibiotic treatment decisions among critically ill patients. Available evidence needs to be better incorporated in clinical decision-making.

What should be considered if you decide to build your own mathematical model for predicting the development of bacterial resistance? Recommendations based on a systematic review of the literature

Acquired bacterial resistance is one of the causes of mortality and morbidity from infectious diseases. Mathematical modeling allows us to predict the spread of resistance and to some extent to control its dynamics. The purpose of this review was to examine existing mathematical models in order to understand the pros and cons of currently used approaches and to build our own model. During the analysis, seven articles on mathematical approaches to studying resistance that satisfied the inclusion/exclusion criteria were selected. All models were classified according to the approach used to study resistance in the presence of an antibiotic and were analyzed in terms of our research. Some models require modifications due to the specifics of the research. The plan for further work on model building is as follows: modify some models, according to our research, check all obtained models against our data, and select the optimal model or models with the best quality of prediction. After that we would be able to build a model for the development of resistance using the obtained results.

Measuring antimicrobial prescribing quality in Australian hospitals: development and evaluation of a national antimicrobial prescribing survey tool

OBJECTIVES

Antimicrobial stewardship (AMS) programmes have been developed with the intention of reducing inappropriate and unnecessary use of antimicrobials, while improving the quality of patient care and locally helping prevent the development of antimicrobial resistance. An important aspect of AMS programmes is the qualitative assessment of prescribing through antimicrobial prescribing surveys (APS), which are able to provide information about the prescribing behaviour within institutions. Owing to lack of standardization of audit tools and the resources required, qualitative methods for the assessment of antimicrobial use are not often performed. The aim of this study was to design an audit tool that was appropriate for use in all Australian hospitals, suited to local user requirements and included an assessment of the overall appropriateness of the prescription.

METHODS

In November 2011, a pilot APS was conducted across 32 hospitals to assess the usability and generalizability of a newly designed audit tool. Following participant feedback, this tool was revised to reflect the requirements of the respondents. A second pilot study was then performed in November 2012 across 85 hospitals.

RESULTS

These surveys identified several areas that can be targets for quality improvement at a national level, including: documentation of indication; surgical prophylaxis prescribed for >24 h; compliance with prescribing guidelines; and the appropriateness of the prescription.

CONCLUSIONS

By involving the end users in the design and evaluation, we have been able to provide a practical and relevant APS tool for quantitative and qualitative data collection in a wide range of Australian hospital settings.

Critical care nephrology: could it be a model of multidisciplinarity in ICU nowadays for other sub-specialities - the jury is out

Emergency and critical care medicine have grown into robust self-supporting disciplines with an increasing demand for dedicated highly-skilled physicians. In the past, “core” specialists were asked to offer bedside advice in acute care wards. In the same regard, critical care medicine and nephrology have been fighting but finally emerged altogether with the concept of critical care nephrology almost 20 years ago. Indeed, polyvalence is no longer a valid option in modern critical care. Uniting forces between disciplines represents the only way to cope with the increasing complexity and cumulating knowledge in the critical care setting. For this reason, the wide array of upcoming acute care sub-specialities must be committed to unrestricted growth and development. This will require competent manpower, a well-designed technical framework, and sufficient financial support. The worldwide success of critical care nephrology proves the feasibility for this concept.