scholarly journals Data Requirements for Electronic Surveillance of Healthcare-Associated Infections

2014 ◽  
Vol 35 (9) ◽  
pp. 1083-1091 ◽  
Author(s):  
Keith F. Woeltje ◽  
Michael Y. Lin ◽  
Michael Klompas ◽  
Marc Oliver Wright ◽  
Gianna Zuccotti ◽  
...  
Keyword(s):  
White Paper ◽  
Specific Information ◽  
Surveillance Systems ◽  
Healthcare Associated Infections ◽  
Electronic Surveillance ◽  
Specific Data ◽  
Healthcare Facilities ◽  
Data Elements ◽  
Healthcare Associated ◽  
Optimal Implementation

Electronic surveillance for healthcare-associated infections (HAIs) is increasingly widespread. This is driven by multiple factors: a greater burden on hospitals to provide surveillance data to state and national agencies, financial pressures to be more efficient with HAI surveillance, the desire for more objective comparisons between healthcare facilities, and the increasing amount of patient data available electronically. Optimal implementation of electronic surveillance requires that specific information be available to the surveillance systems. This white paper reviews different approaches to electronic surveillance, discusses the specific data elements required for performing surveillance, and considers important issues of data validation.Infect Control Hosp Epidemiol 2014;35(9):1083-1091

Managing Our Microbial Mark

2016 ◽  
Vol 42 (2-3) ◽  
pp. 393-428
Author(s):  
Ann Marie Marciarille
Keyword(s):  
United States ◽  
Infection Control ◽  
The United States ◽  
West African ◽  
Healthcare Associated Infections ◽  
Healthcare Facilities ◽  
Quality Reporting ◽  
Reporting Systems ◽  
Control Procedures ◽  
Healthcare Associated

The narrative of Ebola's arrival in the United States has been overwhelmed by our fear of a West African-style epidemic. The real story of Ebola's arrival is about our healthcare system's failure to identify, treat, and contain healthcare associated infections. Having long been willfully ignorant of the path of fatal infectious diseases through our healthcare facilities, this paper considers why our reimbursement and quality reporting systems made it easy for this to be so. West Africa's challenges in controlling Ebola resonate with our own struggles to standardize, centralize, and enforce infection control procedures in American healthcare facilities.

Surveillance for Healthcare associated Infections in Indian NICUs: Researchable Issues

2009 ◽  
Vol 23 (4) ◽  
pp. 331-336
Author(s):  
Ashwani Kumar ◽  
Praveen Kumar
Keyword(s):  
Developed Countries ◽  
Control Measures ◽  
Surveillance Systems ◽  
Healthcare Associated Infections ◽  
Infection Control Measures ◽  
Infection Surveillance ◽  
Healthcare Associated ◽  
Symptoms And Signs ◽  
Local Research ◽  
Underlying Risk

Systematic surveillance is the first and integral step of all infection control measures, especially in intensive care settings. Surveillance systems started evolving in developed countries nearly 40 years ago. With experience and wisdom gained, the surveillance methods have improved and become more standardized. It is now clearly recognized that all patients are not at equal risk. For fair comparisons over time within an unit and in between units, the denominator must take the underlying risk into account. Infection surveillance in the NICU presents a number of unique challenges regarding definitions and differing symptoms and signs in the neonate. Although the importance of surveillance is being increasingly recognized in our country and the methods of developed countries are being adopted, there are numerous issues which need local research. This is in view of the limited manpower and financial resources and different profile of organisms and their epidemiology.

scholarly journals Artificial Intelligence-based tools to control healthcare associated infections: where do we stand

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
A Scardoni ◽  
F Balzarini ◽  
F Cabitza ◽  
A Odone
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Performance Measures ◽  
Performance Outcomes ◽  
Health Concern ◽  
Surveillance Systems ◽  
Healthcare Associated Infections ◽  
Public Health Action ◽  
Practice Performance ◽  
Healthcare Associated

Abstract Background Control of Healthcare associated infections (HAI) is a key public health concern in Europe. Current HAI surveillance systems are based on manual medical records review, vulnerable to misclassification and expensive. Artificial intelligence (AI) offers great potential to public health action and, specifically, to HAI control. Still, scant evidence is available on both its practice and impact. Methods As part of a broader multidisciplinary project, we conducted a systematic review to retrieve, pool and critically apprize all the available evidence on practice, performance and impact of AI-based HAI control programmes. We followed PRISMA guidelines and searched the Medline and Embase databases for relevant studies. Included studies were stratified by HAI type and outcomes of interest, including all possible performance measures, clinical, organizational and economic outcomes. Results We screened 2873 records, resulting in 27 papers included in the review. Studies were carried out in 9 countries, the majority in the US (56%), 18.5% in EU countries, 25.9% published in 2018. Two thirds of studies focused on selected types of infections. Study designs were very diverse and performance observed for HAI detection were very heterogeneous, precluding pooled calculation of summary diagnostic accuracy estimates in most instances, but generally higher than non AI-based models. The highest performance outcomes were Specificity and Negative Predictive Value. Overall performance measures of AI algorithms were: sensitivity range 19%-92%, specificity range 64%-96%, accuracy 70.2%-96.1%. Conclusions Use of AI algorithms for HAI surveillance of HAI has increased reliability compared to traditional surveillance or to automated surveillance models. With ongoing improvements in information technology, implementation of AI models will improve the quality and capacity of surveillance will support hospital HAI surveillance. Key messages Artificial Intelligence (AI) offer great potential to healthcare associated infections (HAI) control. Preliminary evidence show AI-based models have perform better than manual or automated models for HAIs detection.

scholarly journals Disinfectant Wipes Transfer Clostridioides difficile Spores from Contaminated Surfaces to Uncontaminated Surfaces during the Disinfection Process

2020 ◽  
Author(s):  
Carine A. Nkemngong ◽  
Gurpreet K. Chaggar ◽  
Xiaobao Li ◽  
Peter J. Teska ◽  
Haley F Oliver
Keyword(s):  
Hydrogen Peroxide ◽  
Quaternary Ammonium ◽  
Healthcare Associated Infections ◽  
Cross Contamination ◽  
Healthcare Facilities ◽  
Contamination Risk ◽  
Clostridioides Difficile ◽  
Disinfection Process ◽  
The Us ◽  
Healthcare Associated

Abstract Background: Pre-wetted disinfectant wipes are increasingly being used in healthcare facilities to help address the risk of healthcare associated infections (HAI). However, HAIs are still a major problem in the US with Clostridioides difficile being the most common cause, leading to approximately 12,800 deaths annually in the US. An underexplored risk when using disinfectant wipes is that they may cross-contaminate uncontaminated surfaces during the wiping process. The objective of this study was to determine the cross-contamination risk that pre-wetted disinfectant towelettes may pose when challenged with C. difficile spores. We hypothesized that although the tested disinfectant wipes had no sporicidal claims, they will reduce spore loads. We also hypothesized that hydrogen peroxide disinfectant towelettes would present a lower cross-contamination risk than quaternary ammonium products. Methods: We evaluated the risk of cross-contamination when disinfectant wipes are challenged with C. difficile ATCC 43598 spores on Formica surfaces. A disinfectant wipe was used to wipe a Formica sheet inoculated with C. difficile. After the wiping process, we determined log10 CFU on previously uncontaminated pre-determined distances from the inoculation point and on the used wipes. Results: We found that the disinfectant wipes transferred C. difficile spores from inoculated surfaces to previously uncontaminated surfaces. We also found that wipes physically removed C. difficile spores and that hydrogen peroxide disinfectants were more sporicidal than the quaternary ammonium disinfectants. Conclusion: Regardless of the product type, all disinfectant wipes had some sporicidal effect but transferred C. difficile spores from contaminated to otherwise previously uncontaminated surfaces. Disinfectant wipes retain C. difficile spores during and after the wiping process.

scholarly journals Electronically assisted surveillance systems of healthcare-associated infections: a systematic review

2020 ◽  
Vol 25 (2) ◽  
Author(s):  
H Roel A Streefkerk ◽  
Roel PAJ Verkooijen ◽  
Wichor M Bramer ◽  
Henri A Verbrugh
Keyword(s):  
Systematic Review ◽  
Control Programme ◽  
Mature Stage ◽  
Surveillance Systems ◽  
Healthcare Associated Infections ◽  
Medical Specialties ◽  
Specificity And Sensitivity ◽  
Healthcare Associated ◽  
Traditional Surveillance

Background Surveillance of healthcare-associated infections (HAI) is the basis of each infection control programme and, in case of acute care hospitals, should ideally include all hospital wards, medical specialties as well as all types of HAI. Traditional surveillance is labour intensive and electronically assisted surveillance systems (EASS) hold the promise to increase efficiency. Objectives To give insight in the performance characteristics of different approaches to EASS and the quality of the studies designed to evaluate them. Methods In this systematic review, online databases were searched and studies that compared an EASS with a traditional surveillance method were included. Two different indicators were extracted from each study, one regarding the quality of design (including reporting efficiency) and one based on the performance (e.g. specificity and sensitivity) of the EASS presented. Results A total of 78 studies were included. The majority of EASS (n = 72) consisted of an algorithm-based selection step followed by confirmatory assessment. The algorithms used different sets of variables. Only a minority (n = 7) of EASS were hospital-wide and designed to detect all types of HAI. Sensitivity of EASS was generally high (> 0.8), but specificity varied (0.37–1). Less than 20% (n = 14) of the studies presented data on the efficiency gains achieved. Conclusions Electronically assisted surveillance of HAI has yet to reach a mature stage and to be used routinely in healthcare settings. We recommend that future studies on the development and implementation of EASS of HAI focus on thorough validation, reproducibility, standardised datasets and detailed information on efficiency.

scholarly journals Applying Quality Improvement Approaches for the Control of Critical Medical Processes in a Healthcare Facility

2021 ◽  
Vol 18 (2) ◽  
pp. 19-23
Author(s):  
Flaviu Moldovan ◽  
Petruta Blaga
Keyword(s):  
Quality Improvement ◽  
Scientific Literature ◽  
Healthcare Quality ◽  
Healthcare Facility ◽  
Healthcare Associated Infections ◽  
Healthcare Facilities ◽  
Medical Databases ◽  
Ishikawa Diagram ◽  
Healthcare Associated ◽  
Basic Medical

Abstract Healthcare facilities face major challenges as patients require for the continuous improvement of the healthcare quality. We have used as research method the study of the scientific literature from the medical databases, and we have identified the categories of processes that ensure the quality in a healthcare facility. It is drawn a detailed map of the basic medical processes which highlights the sequence and interaction of medical processes that take place on requesting patients until they become resolved patients. The particularization of quality improvement methods for the improvement of critical medical processes is presented. By using the Pareto diagram it is analyzed the adverse events associated with healthcare and by employment of Ishikawa diagram it is analyzed the causes of associated infections highlighting the factors that contributed to the increase of confirmed healthcare associated infections, which are assigned to the hospital information system and the hospital monitoring system.

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