Implementation of an automated cluster alert system into the routine work of infection control and hospital epidemiology: experiences from a tertiary care university hospital.

BACKGROUND: Early detection of clusters of pathogens is crucial for infection prevention and control (IPC) in hospitals. Conventional manual cluster detection is usually restricted to certain areas of the hospital and multidrug resistant organisms. Automation can increase the comprehensiveness of cluster surveillance without depleting human resources. We aimed to describe the application of an automated cluster alert system (CLAR) in the routine IPC work in a hospital. Additionally, we aimed to provide information on the clusters detected and their properties. METHODS: CLAR was continuously utilized during the year 2019 at Charité university hospital. CLAR analyzed microbiological and patient-related data to calculate a pathogen-baseline for every ward. Daily, this baseline was compared to data of the previous 14 days. If the baseline was exceeded, a cluster alert was generated and sent to the IPC team. From July 2019 onwards, alerts were systematically categorized as relevant or non-relevant at the discretion of the IPC physician in charge. RESULTS: In one year, CLAR detected 1,714 clusters. The median number of isolates per cluster was two. The most common cluster pathogens were Enterococcus faecium (n = 326, 19 %), Escherichia coli (n = 274, 16 %) and Enterococcus faecalis (n = 250, 15 %). The majority of clusters (n = 1,360, 79 %) comprised of susceptible organisms. For 906 alerts relevance assessment was performed, with 317 (35 %) alerts being classified as relevant. CONCLUSIONS: CLAR demonstrated the capability of detecting small clusters and clusters of susceptible organisms. Future improvements must aim to reduce the number of non-relevant alerts without impeding detection of relevant clusters. Digital solutions to IPC represent a considerable potential for improved patient care. Systems such as CLAR could be adapted to other hospitals and healthcare settings, and thereby serve as a means to fulfill these potentials.

The quality of antimicrobial prescribing in acute care hospitals: results derived from a national point prevalence survey, Germany, 2016.

BackgroundRobust data on the quality of antimicrobial prescriptions in German acute care hospitals are scarce. To establish and implement antimicrobial stewardship (AMS) measures and to increase prudent antimicrobial use (AMU), the identification of appropriate process and quality indicators is pertinent.AimOur main objective was to identify parameters associated with adequate AMU and inadequate AMU by analysing point prevalence data. Our secondary goal was to describe the current state of AMS implementation in Germany.MethodsA national point prevalence survey for healthcare-associated infections and AMU was conducted in German hospitals in 2016. Data on structure and process parameters were also collected. Recorded antimicrobial prescriptions were divided into adequate, inadequate and undefinable AMU. A multivariable linear regression analysis was performed to examine the correlation of selected structure and process parameters with the adequacy of recorded antimicrobials.ResultsData from 218 acute care hospitals, 64,412 patients and 22,086 administered antimicrobials were included. Multivariable linear regression analysis revealed that documentation of a reason for AMU in the patient notes increased the likelihood of adequate AMU and decreased the likelihood of inadequate AMU significantly (p < 0.001), while tertiary care hospital type had the opposite effect (p < 0.001).ConclusionThrough associating structural and process parameters with adequacy of AMU, we identified parameters that increased the odds of prudent AMU. Documentation was a key element for improving AMU. Revealed deficits regarding the implementation of AMS in German hospitals concerning dedicated staff for AMS activities and establishment of regular AMU training and AMU audits should be tackled.

Antibiotic consumption in Germany: first data of a newly implemented web-based tool for local and national surveillance.

Objectives: The features of a newly established, web-based surveillance system for hospital antibiotic consumption are described and data on broad-spectrum antibiotic use in German acute care hospitals are presented. Methods: The watch- and reserve-group antibiotics, two categories of antibiotics derived from the WHO Essential Medicines List comprising key agents for antimicrobial stewardship, were used as a framework for data analysis. The median antibiotic consumption densities (ACDs; DDD/100 patient days) for the years 2015/16 based on data from 137 acute care hospitals have been calculated for whole facilities, ICUs and medical and surgical departments, stratified by type of care. Results: The new web-based system provides real-time surveillance at unit and facility levels, accessible to all relevant stakeholders. User-defined reports are available via an interactive database, various report types support different approaches to analysis, and different complementing quantification measures of antimicrobial consumption are available. Watch- and reserve-group antibiotics accounted for 42% and 2% of total antibiotic use, respectively. Surgical services presented with considerably lower median ACDs of the watch-group antibiotics compared with medical services. Tertiary care hospitals exhibited higher ACDs of the reserve-group antibiotics and carbapenems than primary/secondary care hospitals, while the ACDs of the watch-group antibiotics as a whole did not differ significantly. Comparing the proportional use with other European countries revealed a relatively high use of the watch-group, ranking beyond the 75th percentile. Conclusions: Because of its particular features the new web-based surveillance system is a valuable tool for antimicrobial stewardship. The WHO categories of watch- and reserve-group antibiotics proved to be a useful framework for the analysis of hospital antibiotic consumption data.

Antimicrobial usage in German acute care hospitals: results of the third national point prevalence survey and comparison with previous national point prevalence surveys.

Objectives: Previous point prevalence surveys (PPSs) revealed the potential for improving antimicrobial usage (AU) in German acute care hospitals. Data from the 2016 German national PPS on healthcare-associated infections and AU were used to evaluate efforts in antimicrobial stewardship (AMS). Methods: A national PPS in Germany was organized by the German National Reference Centre for Surveillance of Nosocomial Infections in 2016 as part of the European PPS initiated by the ECDC. The data were collected in May and June 2016. Results were compared with data from the PPS 2011. Results: A total of 218 hospitals with 64 412 observed patients participated in the PPS 2016. The prevalence of patients with AU was 25.9% (95% CI 25.6%-26.3%). No significant increase or decrease in AU prevalence was revealed in the group of all participating hospitals. Prolonged surgical prophylaxis was found to be common (56.1% of all surgical prophylaxes on the prevalence day), but significantly less prevalent than in 2011 (P < 0.01). The most frequently administered antimicrobial groups were penicillins plus ß-lactamase inhibitors (BLIs) (23.2%), second-generation cephalosporins (12.9%) and fluoroquinolones (11.3%). Significantly more penicillins plus BLIs and fewer second-generation cephalosporins and fluoroquinolones were used in 2016. Overall, an increase in the consumption of broad-spectrum antimicrobials was noted. For 68.7% of all administered antimicrobials, the indication was documented in the patient notes. Conclusions: The current data reaffirm the points of improvement that previous data identified and reveal that recent efforts in AMS in German hospitals require further intensification.

Healthcare-Associated Infections and the Use of Antibiotics in German Hospitals.

BACKGROUND: A national point prevalence survey (PPS) of healthcare-associated infections (HAI) and antibiotic use (AU) was carried out in Germany in 2022 in the framework of the European PPS conducted by the European Centre for Disease Prevention and Control (ECDC). The objective was to determine the prevalence of HAI and AU in German hospitals and to compare the obtained values with those of the most recent previous PPS, which was carried out in 2016. METHODS: The German National Reference Center for the Surveillance of Nosocomial Infections was entrusted with the organization of the PPS of 2022. As recommended by the ECDC, each hospital in a representative sample of 50 hospitals was invited to participate, and all other interested hospitals in Germany were also able to participate if desired. The data were collected by specially trained hospital staff in May, June, and July 2022. The definitions and methods put forth by the ECDC were used. RESULTS: Data from 66 586 patients in 252 hospitals were included. The prevalence of HAI in all participating hospitals was 4.9%, and that of AU was 26.9%. The HAI and AU prevalences were essentially unchanged in comparison to 2016. The most common types of HAI were surgical site infection (23.5%), lower respiratory tract infection (21.6%), and urinary tract infection (19.0%). CONCLUSION: HAI were just as frequent in 2022 as in 2016, affecting approximately one in twenty hospitalized patients on any given day.

Risk factors for nosocomial SARS-CoV-2 infections in patients: results from a retrospective matched case-control study in a tertiary care university center.

BACKGROUND: Factors contributing to the spread of SARS-CoV-2 outside the acute care hospital setting have been described in detail. However, data concerning risk factors for nosocomial SARS-CoV-2 infections in hospitalized patients remain scarce. To close this research gap and inform targeted measures for the prevention of nosocomial SARS-CoV-2 infections, we analyzed nosocomial SARS-CoV-2 cases in our hospital during a defined time period. METHODS: Data on nosocomial SARS-CoV-2 infections in hospitalized patients that occurred between May 2020 and January 2021 at Charité university hospital in Berlin, Germany, were retrospectively gathered. A SARS-CoV-2 infection was considered nosocomial if the patient was admitted with a negative SARS-CoV-2 reverse transcription polymerase chain reaction test and subsequently tested positive on day five or later. As the incubation period of SARS-CoV-2 can be longer than five days, we defined a subgroup of "definite" nosocomial SARS-CoV-2 cases, with a negative test on admission and a positive test after day 10, for which we conducted a matched case-control study with a one to one ratio of cases and controls. We employed a multivariable logistic regression model to identify factors significantly increasing the likelihood of nosocomial SARS-CoV-2 infections. RESULTS: A total of 170 patients with a nosocomial SARS-CoV-2 infection were identified. The majority of nosocomial SARS-CoV-2 patients (n = 157, 92%) had been treated at wards that reported an outbreak of nosocomial SARS-CoV-2 cases during their stay or up to 14 days later. For 76 patients with definite nosocomial SARS-CoV-2 infections, controls for the case-control study were matched. For this subgroup, the multivariable logistic regression analysis revealed documented contact to SARS-CoV-2 cases (odds ratio: 23.4 (95% confidence interval: 4.6-117.7)) and presence at a ward that experienced a SARS-CoV-2 outbreak (odds ratio: 15.9 (95% confidence interval: 2.5-100.8)) to be the principal risk factors for nosocomial SARS-CoV-2 infection. CONCLUSIONS: With known contact to SARS-CoV-2 cases and outbreak association revealed as the primary risk factors, our findings confirm known causes of SARS-CoV-2 infections and demonstrate that these also apply to the acute care hospital setting. This underscores the importance of rapidly identifying exposed patients and taking adequate preventive measures.

Lean back and wait for the alarm? Testing an automated alarm system for nosocomial outbreaks to provide support for infection control professionals.

INTRODUCTION: Outbreaks of communicable diseases in hospitals need to be quickly detected in order to enable immediate control. The increasing digitalization of hospital data processing offers potential solutions for automated outbreak detection systems (AODS). Our goal was to assess a newly developed AODS. METHODS: Our AODS was based on the diagnostic results of routine clinical microbiological examinations. The system prospectively counted detections per bacterial pathogen over time for the years 2016 and 2017. The baseline data covers data from 2013-2015. The comparative analysis was based on six different mathematical algorithms (normal/Poisson and score prediction intervals, the early aberration reporting system, negative binomial CUSUMs, and the Farrington algorithm). The clusters automatically detected were then compared with the results of our manual outbreak detection system. RESULTS: During the analysis period, 14 different hospital outbreaks were detected as a result of conventional manual outbreak detection. Based on the pathogens' overall incidence, outbreaks were divided into two categories: outbreaks with rarely detected pathogens (sporadic) and outbreaks with often detected pathogens (endemic). For outbreaks with sporadic pathogens, the detection rate of our AODS ranged from 83% to 100%. Every algorithm detected 6 of 7 outbreaks with a sporadic pathogen. The AODS identified outbreaks with an endemic pathogen were at a detection rate of 33% to 100%. For endemic pathogens, the results varied based on the epidemiological characteristics of each outbreak and pathogen. CONCLUSION: AODS for hospitals based on routine microbiological data is feasible and can provide relevant benefits for infection control teams. It offers in-time automated notification of suspected pathogen clusters especially for sporadically occurring pathogens. However, outbreaks of endemically detected pathogens need further individual pathogen-specific and setting-specific adjustments.

Pandemic influenza A(H1)pdm09 in hospitals and intensive care units - results from a new hospital surveillance, Germany 2009/2010.

OBJECTIVES: The pandemic influenza A(H1)pdm09 (PI) was introduced to Germany in April 2009. The Robert Koch Institute (RKI) implemented a nationwide voluntary hospital sentinel surveillance for to assess the burden and severity of PI. SETTING: Three modules were offered: a hospital module collected aggregated data from all hospital units on admissions and fatalities with and without PI; an intensive care module data on admissions, patient-days, and ventilated patient-days with and without PI; and a case-based module retrieved clinical patient data of PI cases. A in-patient with a PCR confirmation was defined as a PI case. Descriptive, trend, uni-, and multivariable analysis were performed. RESULTS: Between week 49/2009 and 13/2010, the hospitals reported 103 (0.07%) PI cases among 159181 admissions and 59/16728 (0.35%) PI-related admissions in intensive care units (ICUs). The weekly average incidence decreased in hospitals by 21.5% and in ICUs by 19.2%. In ICUs, 1848/85559 (2.2%) patient-days were PI-related, 94.8% of those with mechanical ventilation. Case-based data on 43 recovered and 16 fatal PI cases were reported. Among recovered, 61% were admitted to ICUs, 51% were mechanically ventilated, and 16% received extracorporeal membrane oxygenation (ECMO). All fatal cases were admitted to ICUs and received mechanical ventilation, 75% ECMO. Fatal outcome was rather associated with complications than with underlying medical conditions. CONCLUSION: The surveillance started shortly after the PI peak, which explains the small number of PI cases. The burden of PI disease was low, but higher in ICUs with a high proportion of severe cases needing ventilation and ECMO treatment. A continuous hospital surveillance system could be helpful to measure the burden of severe community-acquired infections.