A Web-based multidrug-resistant organisms surveillance and outbreak detection system with rule-based classification and clustering

Electronic information systems for One Health surveillance of antimicrobial resistance: a systematic scoping review

INTRODUCTION

Electronic information systems (EIS) that implement a 'One Health' approach by integrating antimicrobial resistance (AMR) data across the human, animal and environmental health sectors, have been identified as a global priority. However, evidence on the availability, technical capacities and effectiveness of such EIS is scarce.

METHODS

Through a qualitative synthesis of evidence, this systematic scoping review aims to: identify EIS for AMR surveillance that operate across human, animal and environmental health sectors; describe their technical characteristics and capabilities; and assess whether there is evidence for the effectiveness of the various EIS for AMR surveillance. Studies and reports between 1 January 2000 and 21 July 2021 from peer-reviewed and grey literature in the English language were included.

RESULTS

26 studies and reports were included in the final review, of which 27 EIS were described. None of the EIS integrated AMR data in a One Health approach across all three sectors. While there was a lack of evidence of thorough evaluations of the effectiveness of the identified EIS, several surveillance system effectiveness indicators were reported for most EIS. Standardised reporting of the effectiveness of EIS is recommended for future publications. The capabilities of the EIS varied in their technical design features, in terms of usability, data display tools and desired outputs. EIS that included interactive features, and geospatial maps are increasingly relevant for future trends in AMR data analytics.

CONCLUSION

No EIS for AMR surveillance was identified that was designed to integrate a broad range of AMR data from humans, animals and the environment, representing a major gap in global efforts to implement One Health approaches to address AMR.

Chlorhexidine bathing to prevent healthcare-associated vancomycin-resistant Enterococcus infections: A cluster quasi-experimental controlled study at intensive care units

BACKGROUND/PURPOSE

Vancomycin-resistant Enterococcus (VRE), a multidrug-resistant, difficult-to-treat pathogen of healthcare-associated infections (HAIs), is now endemic at many intensive care units (ICUs). Chlorhexidine (CHG) bathing is a simple and highly effective intervention to decrease VRE acquisition, but its effect on VRE-HAIs has not been assessed in prospective studies at ICUs.

METHODS

This is a cluster quasi-experimental controlled study. Under active VRE surveillance and contact isolation of all identified VRE carriers, four ICUs were assigned to provide 2% CHG bathing for all patients on a daily basis (CHG group) during the intervention period, while another four ICUs were assigned to provide standard care without CHG bathing for all patients (standard care group) during the same period.

RESULTS

The CHG group (n = 1501) had a 62% lower crude incidence of VRE-HAIs during the intervention period, compared with the baseline period (1.0 vs. 2.6 per thousand patient-days, P = 0.009), while VRE-HAIs incidence did not change in standard care group (n = 3299) (1.1 vs. 0.5 per thousand patient-days, P = 0.139). In multivariable analyses, CHG bathing was independently associated with a 70% lower risk of VRE-HAIs (adjusted odds ratio [OR] 0.3, 95% confidence interval [CI], 0.2 to 0.7, P = 0.006). In contrast, standard care during the same period had no effect on the risk of VRE-HAIs (adjusted OR 1.8, 95% CI: 0.7 to 4.7, P = 0.259).

CONCLUSION

CHG bathing is a highly effective approach to prevent VRE-HAIs at ICUs, in the context of active VRE surveillance with contact isolation.

Healthcare Associated Infections: An Interoperable Infrastructure for Multidrug Resistant Organism Surveillance

Prevention and surveillance of healthcare associated infections caused by multidrug resistant organisms (MDROs) has been given increasing attention in recent years and is nowadays a major priority for health care systems. The creation of automated regional, national and international surveillance networks plays a key role in this respect. A surveillance system has been designed for the Abruzzo region in Italy, focusing on the monitoring of the MDROs prevalence in patients, on the appropriateness of antibiotic prescription in hospitalized patients and on foreseeable interactions with other networks at national and international level. The system has been designed according to the Service Oriented Architecture (SOA) principles, and Healthcare Service Specification (HSSP) standards and Clinical Document Architecture Release 2 (CDAR2) have been adopted. A description is given with special reference to implementation state, specific design and implementation choices and next foreseeable steps. The first release will be delivered at the Complex Operating Unit of Infectious Diseases of the Local Health Authority of Pescara (Italy).

Healthcare-associated infections in intensive care units in Taiwan, South Korea, and Japan: recent trends based on national surveillance reports

Background

Sustainable systematic interventions are important for infection prevention and control (IPC). Data from surveillance of healthcare-associated infections (HAI) provides feedback for implementation of IPC programs. To address the paucity of such data in Asia, we searched for national HAI surveillance and IPC programs in this region.

Methods

Data were analysed from open access national surveillance reports of three Asian countries: Taiwan, South Korea and Japan from 2008 to 2015. National IPC programs were identified.

Results

There were differences among the countries in surveillance protocols, hospital coverage rates, and national IPC policies and programs. Nevertheless, there was a 53.0% reduction in overall HAI over the 8-year period. This consisted of a decrease from 9.34 to 5.03 infections per 1000 patient-days in Taiwan, from 7.56 to 2.76 in Korea, and from 4.41 to 2.74 in Japan (Poisson regression, all p < 0.05). Across the three countries, Escherichia coli and Candida albicans were the major pathogens for urinary tract infection. Staphylococcus aureus, Acinetobacter baumannii and Enterococcus faecium were common bloodstream pathogens. For pneumonia, S. aureus, A. baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae were the predominant pathogens, with considerable country differences. There was a 64.6% decrease in the number of isolates of methicillin-resistant S. aureus, 38.4% decrease in carbapenem-resistant P. aeruginosa and 49.2% decrease in carbapenem-resistant A. baumannii (CRAB) in Taiwan (all p < 0.05), and similarly in Korea with the exception of CRAB (30.5 and 50.4% reduction, respectively, both p < 0.05).

Conclusion

We found a significant decrease in HAI across the three countries in association with sequential multifaceted interventions such as hand hygiene, care bundles, and antimicrobial stewardships. Further regional collaboration could be forged to develop joint strategies to prevent HAI.

Automated detection of hospital outbreaks: A systematic review of methods

OBJECTIVES

Several automated algorithms for epidemiological surveillance in hospitals have been proposed. However, the usefulness of these methods to detect nosocomial outbreaks remains unclear. The goal of this review was to describe outbreak detection algorithms that have been tested within hospitals, consider how they were evaluated, and synthesize their results.

METHODS

We developed a search query using keywords associated with hospital outbreak detection and searched the MEDLINE database. To ensure the highest sensitivity, no limitations were initially imposed on publication languages and dates, although we subsequently excluded studies published before 2000. Every study that described a method to detect outbreaks within hospitals was included, without any exclusion based on study design. Additional studies were identified through citations in retrieved studies.

RESULTS

Twenty-nine studies were included. The detection algorithms were grouped into 5 categories: simple thresholds (n = 6), statistical process control (n = 12), scan statistics (n = 6), traditional statistical models (n = 6), and data mining methods (n = 4). The evaluation of the algorithms was often solely descriptive (n = 15), but more complex epidemiological criteria were also investigated (n = 10). The performance measures varied widely between studies: e.g., the sensitivity of an algorithm in a real world setting could vary between 17 and 100%.

CONCLUSION

Even if outbreak detection algorithms are useful complementary tools for traditional surveillance, the heterogeneity in results among published studies does not support quantitative synthesis of their performance. A standardized framework should be followed when evaluating outbreak detection methods to allow comparison of algorithms across studies and synthesis of results.

A Web-Based, Hospital-Wide Health Care-Associated Bloodstream Infection Surveillance and Classification System: Development and Evaluation

Background

Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent.

Objective

To develop an automatic surveillance and classification system for health care-associated bloodstream infection (HABSI), and to evaluate its performance by comparing it with a conventional infection control personnel (ICP)-based surveillance system.

Methods

We developed a Web-based system that was integrated into the medical information system of a 2200-bed teaching hospital in Taiwan. The system automatically detects and classifies HABSIs.

Results

In this study, the number of computer-detected HABSIs correlated closely with the number of HABSIs detected by ICP by department (n=20; r=.999 P<.001) and by time (n=14; r=.941; P<.001). Compared with reference standards, this system performed excellently with regard to sensitivity (98.16%), specificity (99.96%), positive predictive value (95.81%), and negative predictive value (99.98%). The system enabled decreasing the delay in confirmation of HABSI cases, on average, by 29 days.

Conclusions

This system provides reliable and objective HABSI data for quality indicators, improving the delay caused by a conventional surveillance system.

Data elements and validation methods used for electronic surveillance of health care-associated infections: a systematic review

BACKGROUND

We describe the primary data sources, data elements, and validation methods currently used in electronic surveillance systems (ESS) for identification and surveillance of health care-associated infections (HAIs), and compares these data elements and validation methods with recommended standards.

METHODS

Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a PubMed and manual search was conducted to identify research articles describing ESS for identification and surveillance of HAIs published January 1, 2009-August 31, 2014. Selected articles were evaluated to determine what data elements and validation methods were included.

RESULTS

Among the 509 articles identified in the original literature search, 30 met the inclusion criteria. Whereas the majority of studies (83%) used recommended data sources and validated the numerator (80%), only 10% of studies performed external and internal validation. In addition, there was variation in the ESS data formats used.

CONCLUSIONS

Our findings suggest that the majority of ESS for HAI surveillance use standard definitions, but the lack of widespread internal data, denominator, and external validation in these systems reduces the reliability of their findings. Additionally, advanced programming skills are required to create, implement, and maintain these systems and to reduce the variability in data formats.