Concise healthcare-associated infection reporting and benchmarking with minimal staff resources.

We report on intelligent information technology tools that produce fully-automated surveillance reports of high precision for 12 intensive care units (ICUs) without relevant time expenditure of infection control or ICU staff. This is accomplished by MONI-ICU, a computerized system for automated identification and continuous monitoring of ICU-associated infections, which makes surveillance data readily accessible and presents them in easily perceptible reporting format.

Clinical impact of antimicrobial resistance in European hospitals: excess mortality and length of hospital stay related to methicillin-resistant Staphylococcus aureus bloodstream infections.

Antimicrobial resistance is threatening the successful management of nosocomial infections worldwide. Despite the therapeutic limitations imposed by methicillin-resistant Staphylococcus aureus (MRSA), its clinical impact is still debated. The objective of this study was to estimate the excess mortality and length of hospital stay (LOS) associated with MRSA bloodstream infections (BSI) in European hospitals. Between July 2007 and June 2008, a multicenter, prospective, parallel matched-cohort study was carried out in 13 tertiary care hospitals in as many European countries. Cohort I consisted of patients with MRSA BSI and cohort II of patients with methicillin-susceptible S. aureus (MSSA) BSI. The patients in both cohorts were matched for LOS prior to the onset of BSI with patients free of the respective BSI. Cohort I consisted of 248 MRSA patients and 453 controls and cohort II of 618 MSSA patients and 1,170 controls. Compared to the controls, MRSA patients had higher 30-day mortality (adjusted odds ratio [aOR] = 4.4) and higher hospital mortality (adjusted hazard ratio [aHR] = 3.5). Their excess LOS was 9.2 days. MSSA patients also had higher 30-day (aOR = 2.4) and hospital (aHR = 3.1) mortality and an excess LOS of 8.6 days. When the outcomes from the two cohorts were compared, an effect attributable to methicillin resistance was found for 30-day mortality (OR = 1.8; P = 0.04), but not for hospital mortality (HR = 1.1; P = 0.63) or LOS (difference = 0.6 days; P = 0.96). Irrespective of methicillin susceptibility, S. aureus BSI has a significant impact on morbidity and mortality. In addition, MRSA BSI leads to a fatal outcome more frequently than MSSA BSI. Infection control efforts in hospitals should aim to contain infections caused by both resistant and susceptible S. aureus.

Electronic surveillance of healthcare-associated infections with MONI-ICU--a clinical breakthrough compared to conventional surveillance systems.

Surveillance of clinical entities such as healthcare-associated infections (HCAI) by conventional techniques is a time-consuming task for highly trained experts. Such are neither available nor affordable in sufficient numbers on a permanent basis. Nevertheless, expert surveillance is a key parameter for good clinical practice, especially in intensive care medicine. MONI-ICU (monitoring of nosocomial infections in intensive care units) has been developed methodically and practically in a stepwise manner over the last 20 years and is now a reliable tool for clinical experts. It provides an almost real-time view of clinical indicators for HCAI--at the cost of almost no additional time on the part of surveillance staff or clinicians. We describe the use of this system in clinical routine and compare the results generated automatically by MONI-ICU with those generated in parallel by trained surveillance staff using patient chart reviews and other available information ("gold standard"). A total of 99 ICU patient admissions representing 1007 patient days were analyzed. MONI-ICU identified correctly the presence of an HCAI condition in 28/31 cases (sensitivity, 90.3%) and their absence in 68/68 of the non-HCAI cases (specificity, 100%), the latter meaning that MONI-ICU produced no "false alarms". The time taken for conventional surveillance at the 52 ward visits was 82.5 hours. MONI-ICU analysis of the same patient cases, including careful review of the generated results required only 12.5 hours (15.2%).

Data correction pre-processing for electronically stored blood culture results: implications on microbial spectrum and empiric antibiotic therapy.

BACKGROUND: The outcome of patients with bacteraemia is influenced by the initial selection of adequate antimicrobial therapy. The objective of our study was to clarify the influence of different crude data correction methods on a) microbial spectrum and ranking of pathogens, and b) cumulative antimicrobial susceptibility pattern of blood culture isolates obtained from patients from intensive care units (ICUs) using a computer based tool, MONI. METHODS: Analysis of 13 ICUs over a period of 7 years yielded 1427 microorganisms from positive results. Three different data correction methods were applied. Raw data method (RDM): Data without further correction, including all positive blood culture results. Duplicate-free method (DFM): Correction of raw data for consecutive patient's results yielding same microorganism with similar antibiogram within a two-week period. Contaminant-free method (CFM): Bacteraemia caused by possible contaminants was only assumed as true bloodstream infection, if an organism of the same species was isolated from > 2 sets of blood cultures within 5 days. RESULTS: Our study demonstrates that different approaches towards raw data correction - none (RDM), duplicate-free (DFM), and a contaminant-free method (CFM) - show different results in analysis of positive blood cultures. Regarding the spectrum of microorganisms, RDM and DFM yielded almost similar results in ranking of microorganisms, whereas using the CFM resulted in a clinically and epidemiologically more plausible spectrum. CONCLUSION: For possible skin contaminants, the proportion of microorganisms in terms of number of episodes is most influenced by the CFM, followed by the DFM. However, with exception of fusidic acid for gram-positive organisms, none of the evaluated correction methods would have changed advice for empiric therapy on the selected ICUs.

Artificial-intelligence-based hospital-acquired infection control.

Nosocomial or hospital-acquired infections (NIs) are a frequent complication in hospitalized patients. The growing availability of computerized patient records in hospitals permits automated identification and extended monitoring for signs of NIs. A fuzzy- and knowledge-based system to identify and monitor NIs at intensive care units (ICUs) according to the European Surveillance System HELICS (NI definitions derived from the Centers of Disease Control and Prevention (CDC) criteria) was developed and put into operation at the Vienna General Hospital. This system, named Moni, for monitoring of nosocomial infections contains medical knowledge packages (MKPs) to identify and monitor various infections of the bloodstream, pneumonia, urinary tract infections, and central venous catheter-associated infections. The MKPs consist of medical logic modules (MLMs) in Arden syntax, a medical knowledge representation scheme, whose definition is part of the HL7 standards. These MLM packages together with the Arden software are well suited to be incorporated in medical information systems such as hospital information or intensive-care patient data management systems, or in web-based applications. In terms of method, Moni contains an extended data-to-symbol conversion with several layers of abstraction, until the top level defining NIs according to HELICS is reached. All included medical concepts such as "normal", "increased", "decreased", or similar ones are formally modeled by fuzzy sets, and fuzzy logic is used to process the interpretations of the clinically observed and measured patient data through an inference network. The currently implemented cockpit surveillance connects 96 ICU beds with Moni and offers the hospital's infection control department a hitherto unparalleled NI infection survey.

Augmenting Analytics Software for Clinical Microbiology by Man-Machine Interaction.

In the present study, we intended to solve identification problems in analyzing the results of microbiology by proactive man-machine interaction. We modified the analytics software MOMO so that it flags laboratory results containing textual elements unknown to the thesaurus, and a human expert assigns the elements to the respective existing thesaurus elements or creates new ones. In 773,309 laboratory results, roughly 2.6% contained unassigned elements and would have been ignored in thesaurus-based analyses for purposes other than simply reporting microbiological findings to physicians. In current use, the thesaurus is kept up to date with synonyms, syntactic deviations, misspellings, and entries not contained earlier, with man-machine interaction of 2-3 hours per week. This approach helps to accommodate both up-to-date clinical reporting for immediate patient care as well as up-to-date queries for infection surveillance and epidemiology, outbreak management, quality control and benchmarking, and antimicrobial stewardship.

Arden Syntax MLM Building Blocks for Microbiological Concepts and Their Application in Infection Surveillance.

BACKGROUND: The diagnosis - and hence definitions - of healthcare-associated infections (HAIs) rely on microbiological laboratory test results in specific constellations. OBJECTIVES: To construct a library that provides interoperable building blocks for the analysis of microbiological laboratory test results. METHODS: We used Java for preprocessing raw microbiological laboratory test results and Arden Syntax for knowledge-based querying of data based on microbiology information elements used in European surveillance criteria for HAIs. To test the library and quantify how often these information elements occur in the data, we performed a retrospective cohort study on adult patients admitted for at least 24 hours to an intensive care unit at the Vienna General Hospital in 2013. RESULTS: We identified eleven information elements for which information was electronically available. These elements were identified positively 1,239 times in 1,184 positive microbiology tests from 563 patients. DISCUSSION: The availability of a library for the analysis of microbiology laboratory test results in HAI terms facilitates electronic HAI surveillance.

Arden Syntax Clinical Foundation Framework for Event Monitoring in Intensive Care Units: Report on a Pilot Study.

The creation of clinical decision support systems has received a strong impulse over the last years, but their integration into a clinical routine has lagged behind, partly due to a lack of interoperability and trust by physicians. We report on the implementation of a clinical foundation framework in Arden Syntax, comprising knowledge units for (a) preprocessing raw clinical data, (b) the determination of single clinical concepts, and (c) more complex medical knowledge, which can be modeled through the composition and configuration of knowledge units in this framework. Thus, it can be tailored to clinical institutions or patients' caregivers. In the present version, we integrated knowledge units for several infection-related clinical concepts into the framework and developed a clinical event monitoring system over the framework that employs three different scenarios for monitoring clinical signs of bloodstream infection. The clinical event monitoring system was tested using data from intensive care units at Vienna General Hospital, Austria.

Context-Sensitive Clinical Alert Packages Written in Arden Syntax.

An increasing body of raw patient data is generated on each day of a patient's stay at a hospital. It is of paramount importance that critical patient information be extracted from these large data volumes and presented to the patient's clinical caregivers as early as possible. Contemporary clinical alert systems attempt to provide this service with moderate success. The efficacy of the systems is limited by the fact that they are too general to fit specific patient populations or healthcare institutions. In this study we present an extendable alerting framework implemented in Arden Syntax, which can be configured to the needs and preferences of healthcare institutions and individual patient caregivers. We illustrate the potential of this alerting framework via an alert package that analyzes hematological laboratory results with data from intensive care units at the Vienna General Hospital, Austria. The results show the effectiveness of this alert package and its ability to generate key alerts while avoiding over-alerting.

Detecting borderline infection in an automated monitoring system for healthcare-associated infection using fuzzy logic.

BACKGROUND: Many electronic infection detection systems employ dichotomous classification methods, classifying patient data as pathological or normal with respect to one or several types of infection. An electronic monitoring and surveillance system for healthcare-associated infections (HAIs) known as Moni-ICU is being operated at the intensive care units (ICUs) of the Vienna General Hospital (VGH) in Austria. Instead of classifying patient data as pathological or normal, Moni-ICU introduces a third borderline class. Patient data classified as borderline with respect to an infection-related clinical concept or HAI surveillance definition signify that the data nearly or partly fulfill the definition for the respective concept or HAI, and are therefore neither fully pathological nor fully normal. OBJECTIVE: Using fuzzy sets and propositional fuzzy rules, we calculated how frequently patient data are classified as normal, borderline, or pathological with respect to infection-related clinical concepts and HAI definitions. In dichotomous classification methods, borderline classification results would be confounded by normal. Therefore, we also assessed whether the constructed fuzzy sets and rules employed by Moni-ICU classified patient data too often or too infrequently as borderline instead of normal. PARTICIPANTS AND METHODS: Electronic surveillance data were collected from adult patients (aged 18 years or older) at ten ICUs of the VGH. All adult patients admitted to these ICUs over a two-year period were reviewed. In all 5099 patient stays (4120 patients) comprising 49,394 patient days were evaluated. For classification, a part of Moni-ICU's knowledge base comprising fuzzy sets and rules for ten infection-related clinical concepts and four top-level HAI definitions was employed. Fuzzy sets were used for the classification of concepts directly related to patient data; fuzzy rules were employed for the classification of more abstract clinical concepts, and for top-level HAI surveillance definitions. Data for each clinical concept and HAI definition were classified as either normal, borderline, or pathological. For the assessment of fuzzy sets and rules, we compared how often a borderline value for a fuzzy set or rule would result in a borderline value versus a normal value for its associated HAI definition(s). The statistical significance of these comparisons was expressed in p-values calculated with Fisher's exact test. RESULTS: The results showed that, for clinical concepts represented by fuzzy sets, 1-17% of the data were classified as borderline. The number was substantially higher (20-81%) for fuzzy rules representing more abstract clinical concepts. A small body of data were found to be in the borderline range for the four top-level HAI definitions (0.02-2.35%). Seven of ten fuzzy sets and rules were associated significantly more often with borderline values than with normal values for their respective HAI definition(s) (p<0.001). CONCLUSION: The study showed that Moni-ICU was effective in classifying patient data as borderline for infection-related concepts and top-level HAI surveillance definitions.

Characterization of clinically isolated Ralstonia mannitolilytica strains using random amplification of polymorphic DNA (RAPD) typing and antimicrobial sensitivity, and comparison of the classification efficacy of phenotypic and genotypic assays.

Ralstonia mannitolilytica strains isolated between February 2002 and March 2004 from 30 episodes of infection in 26 patients at Vienna University Hospital were characterized. Twenty-four of the episodes occurred within a 7 month period, suggesting they were outbreak-related, although no common source of infection was identified. The isolates were assayed using PCR to confirm species identification. Random amplification of polymorphic DNA (RAPD) typing classified the R. mannitolilytica isolates into four distinct genotypes: A/I, B/II, C/III and D/IV (15, 13, 1 and 1 isolates, respectively). API 20NE, VITEK Gram-negative Identification Card plus (GNI+) and VITEK Gram Negative Bacillus Identification (GNB) yielded negative or no acceptable biochemical profile for 4, 11 and 11 isolates, respectively. None of the isolates acidified D-arabitol or mannitol. Two isolates (7 %) were positive for nitrate reduction. All 30 R. mannitolilytica isolates were resistant to desferrioxamine, and 29 were able to grow on BCSA. The most active compounds in vitro were ciprofloxacin and cefepime, whilst only the genotype D/IV isolate was sensitive to gentamicin and amikacin (the remaining 29 isolates being resistant to both).

Advances In Infection Surveillance and Clinical Decision Support With Fuzzy Sets and Fuzzy Logic.

By the use of extended intelligent information technology tools for fully automated healthcare-associated infection (HAI) surveillance, clinicians can be informed and alerted about the emergence of infection-related conditions in their patients. Moni--a system for monitoring nosocomial infections in intensive care units for adult and neonatal patients--employs knowledge bases that were written with extensive use of fuzzy sets and fuzzy logic, allowing the inherent un-sharpness of clinical terms and the inherent uncertainty of clinical conclusions to be a part of Moni's output. Thus, linguistic as well as propositional uncertainty became a part of Moni, which can now report retrospectively on HAIs according to traditional crisp HAI surveillance definitions, as well as support clinical bedside work by more complex crisp and fuzzy alerts and reminders. This improved approach can bridge the gap between classical retrospective surveillance of HAIs and ongoing prospective clinical-decision-oriented HAI support.

Influence of selective bowel decontamination on the organisms recovered during bacteremia in neutropenic patients.

OBJECTIVE: To assess the influence of prophylactic selective bowel decontamination (SBD) on the spectrum of microbes causing bloodstream infection (BSI). DESIGN: The microbes causing BSI in neutropenic patients of a hematologic ward (HW) and a bone marrow transplantation unit (BMTU), respectively, were compared by retrospective analysis of blood culture results from January 1996 to June 2003. SETTING: A 30-bed HW (no SBD) and a BMTU including a 7-bed normal care ward and an 8-bed intensive care unit (SBD used) of a 2,200-bed university teaching hospital. RESULTS: The overall incidences of bacteremia in the HW and the BMTU were similar (72.6 vs 70.6 episodes per 1,000 admissions; P = .8). Two hundred twenty episodes of BSI were recorded in 164 neutropenic patients of the HW and 153 episodes in 127 neutropenic patients of the BMTU. Enterobacteriaceae (OR, 3.14; CI95, 1.67-5.97; P= .0002) and Streptococcus species (OR, 2.04; CI95, 1.14-3.70; P = .015) were observed more frequently in HW patients and coagulase-negative staphylococci more frequently in BMTU patients (OR, 0.15; CI95, 0.09-0.26; P < .00001). No statistically significant differences were found for gram-negative nonfermentative bacilli (P = .53), Staphylococcus aureus (P = .21), Enterococcus species (P = .48), anaerobic bacteria (P = .1), or fungi (P = .50). CONCLUSIONS: SBD did not lead to a significant reduction in the incidence of bacteremia, but significant changes in microbes recovered from blood cultures were observed. SBD should be considered when empiric antimicrobial therapy is prescribed for suspected BSI.

Sensor-operated faucets: a possible source of nosocomial infection?

Recently, contamination of sensor-operated faucets (SOFs) with Pseudomonas aeruginosa was observed. To evaluate odds ratios, we conducted a case-control study in which handle-operated faucets served as controls. No statistically significant difference in P. aeruginosa counts was observed between SOFs and regular faucets in our study (odds ratio, 0.0; 95% confidence interval, 0.0 to 39.0; two-sided P exact = .99).

Prophylaxis of ophthalmia neonatorum--a nationwide survey of the current practice in Austria.

UNLABELLED: The aim of this study was to analyze the current practice of Ophthalmia neonatorum prophylaxis in Austria. Questionnaires were sent to 107 hospitals with obstetric units, as well as to 490 registered community midwives, together looking after a yearly total of approximately 70,000 births. The overall return of the hospitals and midwives was 91.6% and 7.6%, respectively. RESULTS: Ophthalmia neonatorum prophylaxis is being applied by 93.8% of all respondents (hospitals 96.9%, and community midwives 82.3%). The three most frequently applied substances were Erythromycin (41.8%), Gentamicin (21.3%) and Silver nitrate (19.7%). Other substances were Tetracycline, Povidone-Iodine, Neomycin and Chloramphenicol. The reported overall-observation of chemical conjunctivitis after application of a prophylactic agent was 42.3% (55/133), typically after the use of Silver nitrate, Erythromycin or Tetracycline. The agent was determined by pediatricians (29%), in accordance to governmental decree (15%), by hospital policy (12%), effectiveness against Chlamydia and Gonococci (9%), by pharmacists (3%) and ophthalmologists (3%). 18% did not give any reason for the choice of agent. CONCLUSION: The rationale for prophylaxis and the substances used in Austria show heterogeneity. Seven prophylactic agents are used, two antiseptics and five antibiotics. 25% of the routine applicants are using substances (Gentamicin, Neomycin or Chloramphenicol) for which no evidence based efficacy for prophylaxis of Ophthalmia neonatorum has been demonstrated through clinical trials. However, 83.5% of the maternity units do not want changes in their current routine, unless there is a nation-wide agreement for Ophthalmia neonatorum prophylaxis.

Healthcare-associated infection surveillance and bedside alerts.

Expectations and requirements concerning the identification and surveillance of healthcare-associated infections (HAIs) are increasing, calling for differentiated automated approaches. In an attempt to bridge the "definition swamp" of these infections and serve the needs of different users, we improved the monitoring of nosocomial infections (MONI) software to create better surveillance reports according to consented national and international definitions, as well as produce infection overviews on complex clinical matters including alerts for the clinician's ward and bedside work. MONI contains and processes surveillance definitions for intensive-care-unit-acquired infections from the European Centre for Disease Prevention and Control, Sweden, as well as the Centers for Disease Control and Prevention, USA. The latest release of MONI also includes KISS criteria of the German National Reference Center for Surveillance of Nosocomial Infections. In addition to these "classic" surveillance criteria, clinical alert criteria--which are similar but not identical to the surveillance criteria--were established together with intensivists. This is an important step to support both infection control and clinical personnel; and--last but not least--to foster co-evolution of the two groups of definitions: surveillance and alerts.

Effectiveness of an automated surveillance system for intensive care unit-acquired infections.

This study assessed the effectiveness of a fully automated surveillance system for the detection of healthcare-associated infections (HCAIs) in intensive care units. Manual ward surveillance (MS) and electronic surveillance (ES) were performed for two intensive care units of the Vienna General Hospital. All patients admitted for a period longer than 48 h between 13 November 2006 and 7 February 2007 were evaluated according to HELICS-defined rules for HCAI. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and personnel time spent per surveillance type were calculated. Ninety-three patient admissions were observed, whereby 30 HCAI episodes were taken as a reference standard. Results with MS versus ES were: sensitivity 40% versus 87%, specificity 94% versus 99%, PPV 71% versus 96%, NPV 80% versus 95%, and time spent per surveillance type 82.5 h versus 12.5 h. In conclusion, ES was found to be more effective than MS while consuming fewer personnel resources.

Validation of fuzzy sets in an automated detection system for intensive-care-unit-acquired central-venous-catheter-related infections.

Central venous catheters play an important role in patient care in intensive care units (ICUs), but their use comes at the risk of catheter-related infections (CRIs). Electronic surveillance systems can detect CRIs more accurately than manual surveillance, but these systems often omit patients that do not exhibit all infection signs to their full degree, the so-called borderline group. By extending an electronic surveillance system with fuzzy constructs, the borderline group can be identified. In this study, we examined the size of the borderline group for systemic CRIs (CRI2) by calculating the frequency of fuzzy values for CRI2 and related infection parameters in patient data involving ten ICUs (75 beds) over one year. We also validated the expert-defined fuzzy constructs by comparing overall and CRI2-specific support. The study showed that more than 86% of the data contained fuzzy values, and that the borderline group for CRI2 consisted of 2% of the study group. It was also confirmed that most fuzzy constructs were good representatives of the borderline CRI2 patient group.

Can we bridge the definition diversity in healthcare-associated infection surveillance? From IT-supported surveillance to IT-supported infection prevention and control.

Expectations and requirements of the surveillance of healthcare-associated infections (HAIs) trigger a growing differentiation of HAI surveillance approaches. In an attempt to bridge this diversity of definitions and to serve the needs of different user groups, we have enhanced MONI (identification, monitoring, and reporting of nosocomial infections) not only to create better reports, but also to output overviews on complex clinical matters, as well as to generate alerts and reminders for the clinicians' bedside work.

Concordance between European and US case definitions of healthcare-associated infections.

BACKGROUND: Surveillance of healthcare-associated infections (HAI) is a valuable measure to decrease infection rates. Across Europe, inter-country comparisons of HAI rates seem limited because some countries use US definitions from the US Centers for Disease Control and Prevention (CDC/NHSN) while other countries use European definitions from the Hospitals in Europe Link for Infection Control through Surveillance (HELICS/IPSE) project. In this study, we analyzed the concordance between US and European definitions of HAI. METHODS: An international working group of experts from seven European countries was set up to identify differences between US and European definitions and then conduct surveillance using both sets of definitions during a three-month period (March 1st -May 31st, 2010). Concordance between case definitions was estimated with Cohen's kappa statistic (κ). RESULTS: Differences in HAI definitions were found for bloodstream infection (BSI), pneumonia (PN), urinary tract infection (UTI) and the two key terms "intensive care unit (ICU)-acquired infection" and "mechanical ventilation". Concordance was analyzed for these definitions and key terms with the exception of UTI. Surveillance was performed in 47 ICUs and 6,506 patients were assessed. One hundred and eighty PN and 123 BSI cases were identified. When all PN cases were considered, concordance for PN was κ = 0.99 [CI 95%: 0.98-1.00]. When PN cases were divided into subgroups, concordance was κ = 0.90 (CI 95%: 0.86-0.94) for clinically defined PN and κ = 0.72 (CI 95%: 0.63-0.82) for microbiologically defined PN. Concordance for BSI was κ = 0.73 [CI 95%: 0.66-0.80]. However, BSI cases secondary to another infection site (42% of all BSI cases) are excluded when using US definitions and concordance for BSI was κ = 1.00 when only primary BSI cases, i.e. Europe-defined BSI with "catheter" or "unknown" origin and US-defined laboratory-confirmed BSI (LCBI), were considered. CONCLUSIONS: Our study showed an excellent concordance between US and European definitions of PN and primary BSI. PN and primary BSI rates of countries using either US or European definitions can be compared if the points highlighted in this study are taken into account.