Uniform national numerator definitions for infection control clinical indicators: surgical site infection and health-care related bloodstream infection

1999 ◽  
Vol 4 (4) ◽  
pp. 12-14 ◽  
Author(s):  
E. Auricht ◽  
J. Borgert ◽  
M. Butler ◽  
H. Cadwallader ◽  
P. Collignon ◽  
...  
Keyword(s):  
Health Care ◽  
Infection Control ◽  
Surgical Site Infection ◽  
Bloodstream Infection ◽  
Site Infection ◽  
Clinical Indicators

scholarly journals Knowledge and practices of health care professionals to prevent surgical site infection in a tertiary health care centre

2018 ◽  
Vol 5 (6) ◽  
pp. 2248 ◽  
Author(s):  
Vaibhav B. Patil ◽  
Ravi M. Raval ◽  
Ganesh Chavan
Keyword(s):  
Health Care ◽  
Infection Control ◽  
Surgical Site Infection ◽  
Health Care Professionals ◽  
Staff Nurses ◽  
P Value ◽  
Site Infection ◽  
Health Care Centre ◽  
Interns And Residents ◽  
Control Protocols

Background: In spite of advanced operative techniques, availability of higher antibiotics, modern sterilization techniques, higher rate of SSI in government set up after major surgeries is quiet worrisome. Present study is an attempt to assess knowledge and practices of health care professionals to decrease incidence of SSI and to determine their relationship with each other.Methods: This is cross sectional study conducted in one of the tertiary institute in western Maharashtra. Data collection was done by using pre-tested, structured questionnaire. We assessed knowledge and practices followed in wards and operation theatre and compared with standard practices according to WHO infection control protocols. We analyzed data according to Low (<60%), moderate or good (60-80%) and >80% means high knowledge and practices using 3-point Likert scale (never practiced, sometimes practiced, and always practiced). Subgroup analysis will be made by dividing participants in 3 groups mainly consultants (faculty), residents and interns, and staff nurses.Results: Authors found poor knowledge among all three subgroups and in assessment of level of practices, we found that 68.75 % of consultants were following very high level of practices followed by staff nurses (64.51%) and then Interns and residents (49.15%) and while assessing relationship between knowledge and practices in each subgroup by calculating spearman’s Rho coefficient (R), authors found that for interns and residents, P value is 0.025, so association is statistically significant.Conclusions: It can be concluded that health care professionals in the current study have good practices level regarding infection control but knowledge of surgical site infection prevention activities among those was found low. It emphasizes importance of providing training programs for newly joined students, staff nurses and for consultants about infection control protocols at regular intervals.

USE OF AN ELECTRONIC DATA WAREHOUSE TO ENHANCE CARDIAC SURGICAL SITE SURVEILLANCE AT A LARGE CANADIAN CENTRE

2008 ◽  
Vol 31 (4) ◽  
pp. 21 ◽  
Author(s):  
G W Rose ◽  
V R Roth ◽  
K N Suh ◽  
M Taljaard ◽  
C Van Walraven ◽  
...  
Keyword(s):  
Infection Control ◽  
Surgical Site Infection ◽  
Data Warehouse ◽  
Stepwise Logistic Regression ◽  
Site Infection ◽  
Electronic Data ◽  
Trigger Mechanism ◽  
Trigger Tool ◽  
Infection Surveillance ◽  
Trigger Mechanisms

Background/Purpose: Surgical site infection surveillance to determineincidence is a key infection control activity. Case detection is labour-intensive, therefore most infection control programs use manual or simple electronic mechanisms to “trigger” chart review. However, such “trigger” mechanisms are also labour-intensive, and often of poor specificity. Our objective is to develop a complex trigger mechanism using data from an electronic data warehouse, to improve specificity of surveillance of surgical site infection compared to current trigger mechanisms. Methods: We will derive an electronic trigger tool for cardiac surgical site infection surveillance using a nested case-control design, among a cohort of all patients undergoing coronary artery bypass grafting, cardiac valve repairor replacement, or heart transplant at the University of Ottawa Heart Institute, from July 1 2004 to June 30 2007. We will perform a systematic literature review to identify potential trigger factors to include in the model, then construct the trigger tool by backwards stepwise logistic regression. The best-fit model will be used to calculate the probability of surgical site infection. We will select the threshold probability to use in surveillance by visual inspection of receiver-operator-characteristic curves. The accuracy of this electronic trigger mechanism will be compared to pre-existing manual and simple electronic mechanisms using relative true positive ratios and relative false positive ratios. Results/Conclusions: We have selected 200 cases of surgical site infection and 541 controls from among 3744 procedures performed during the study period. As of the date ofthis abstract we are still undertaking the systematic review.

scholarly journals 907. Technology and Medicine: Prediction of Surgical Site Infection in Clean Surgeries using Artificial Neural Networks

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S487-S487
Author(s):  
Flávio Henrique Batista de Souza ◽  
Braulio Roberto Gonçalves Marinho Couto ◽  
Felipe Leandro Andrade da Conceição ◽  
Gabriel Henrique Silvestre da Silva ◽  
Igor Gonçalves Dias ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Data Collection ◽  
Infection Control ◽  
Surgical Site Infection ◽  
Predictive Power ◽  
Hospital Infection ◽  
Automated System ◽  
Site Infection ◽  
Average Hospital ◽  
Hospital Infection Control

Abstract Background In Belo Horizonte, a city with 3,000,000 inhabitants, a survey was performed in six hospitals, between July 2016 and June 2018, about surgical site infection (SSI) in patients undergoing clean surgery procedures. The main objective is to statistically evaluate such incidences and enable an analysis of the SSI predictive power, through MLP (Multilayer Perceptron) pattern recognition algorithms. Methods Through the Hospital Infection Control Committees (CCIH) of the hospitals, a data collection on SSI was carried out through the software SACIH - Automated System for Hospital Infection Control. So, three procedures were performed: a treatment of the collected database for use of intact samples; a statistical analysis on the profile of the collected hospitals; an evaluation of the predictive power of five types of MLPs (Backpropagation Standard, Momentum, Resilient Propagation, Weight Decay and Quick Propagation) for SSI prediction. The MLPs were tested with 3, 5, 7 and 10 neurons in the hidden layer and with a division of the database for the resampling process (65% or 75% for testing, 35% or 25% for validation). They were compared by measuring the AUC (Area Under the Curve - ranging from 0 to 1) presented for each of the configurations. Results From 45,990 records, 12,811 were able for analysis. The statistical analysis results were: the average age is 49 years old (predominantly between 30 and 50); the surgeries had an average time of 134.13 minutes; the average hospital stay is 4 days (from 0 to 200 days), the death rate reached 1% and the SSI 1.49%. A maximum prediction power of 0.742 was found. Conclusion There was a loss of 60% of the database samples due to the presence of noise. However, it was possible to have a relevant sample to assess the profile of these six hospitals. The predictive process, presented some configurations with results that reached 0.742, what promises the use of the structure for the monitoring of automated SSI for patients submitted to surgeries considered clean. To optimize data collection, enable other hospitals to use the prediction tool and minimize noise from the database, two mobile application were developed: one for monitoring the patient in the hospital and other for monitoring after hospital discharge. The SSI prediction analysis tool is available at www.nois.org.br. Disclosures All Authors: No reported disclosures

scholarly journals Automated Risk Analysis of Surgical Site Infection in Hip Arthroplasty Surgeries

2020 ◽  
Vol 41 (S1) ◽  
pp. s135-s136
Author(s):  
Flávio Souza ◽  
Braulio Couto ◽  
Felipe Leandro Andrade da Conceição ◽  
Gabriel Henrique Silvestre da Silva ◽  
Igor Gonçalves Dias ◽  
...  
Keyword(s):  
Data Collection ◽  
Infection Control ◽  
Surgical Site Infection ◽  
Hip Arthroplasty ◽  
Hospital Infection ◽  
Site Infection ◽  
Weight Decay ◽  
Hospital Infection Control ◽  
Belo Horizonte ◽  
Arthroplasty Surgery

Background: In 7 hospitals in Belo Horizonte, a city with >3,000,000 inhabitants, a survey was conducted between July 2016 and June 2018, focused on surgical site infection (SSI) in patients undergoing arthroplasty surgery procedures. The main objective is to statistically evaluate such incidences and enable a study of the prediction power of SSI through pattern recognition algorithms, the MLPs (multilayer perceptron). Methods: Data were collected on SSI by the hospital infection control committees (CCIHs) of the hospitals involved in the research. All data used in the analysis during their routine SSI surveillance procedures were collected. The information was forwarded to the NOIS (Nosocomial Infection Study) Project, which used SACIH automated hospital infection control system software to collect data from a sample of hospitals participating voluntarily in the project. After data collection, 3 procedures were performed: (1) a treatment of the database collected for the use of intact samples; (2) a statistical analysis on the profile of the hospitals collected; and (3) an assessment of the predictive power of 5 types of MLP (backpropagation standard, momentum, resilient propagation, weight decay, and quick propagation) for SSI prediction. MLPs were tested with 3, 5, 7, and 10 hidden layer neurons and a database split for the resampling process (65% or 75% for testing and 35% or 25% for validation). The results were compared by measuring AUC (area under the curve; range, 0–1) presented for each of the configurations. Results: Of 1,246 records, 535 were intact for analysis. We obtained the following statistics: the average surgery time was 190 minutes (range, 145–217 minutes); the average age of the patients was 67 years (range, 9–103); the prosthetic implant index was 98.13%; the SSI rate was 1.49%, and the death rate was 1.21%. Regarding the prediction power, the maximum prediction power was 0.744. Conclusions: Despite the considerable loss rate of almost 60% of the database samples due to the presence of noise, it was possible to perform relevant sampling for the profile evaluation of hospitals in Belo Horizonte. For the predictive process, some configurations have results that reached 0.744, which indicates the usefulness of the structure for automated SSI monitoring for patients undergoing hip arthroplasty surgery. To optimize data collection and to enable other hospitals to use the SSI prediction tool (available in www.sacihweb.com ), a mobile application was developed.Funding: NoneDisclosures: None

Uniform national denominator definitions for infection control clinical indicators: surgical site and health care associated blood stream infection

2001 ◽  
Vol 6 (2) ◽  
pp. 47-53 ◽  
Author(s):  
E. Auricht ◽  
J. Borgert ◽  
M. Butler ◽  
H. Cadwallader ◽  
P. Collignon ◽  
...  
Keyword(s):  
Health Care ◽  
Infection Control ◽  
Blood Stream Infection ◽  
Blood Stream ◽  
Clinical Indicators

Infection Control in Surgical Practice

2017 ◽  
Author(s):  
Caroline E. Reinke ◽  
Rachel R. Kelz ◽  
Elizabeth A Bailey
Keyword(s):  
Health Care ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Clostridium Difficile ◽  
Tract Infection ◽  
Infection Control ◽  
Central Line ◽  
Ventilator Associated Pneumonia ◽  
Site Infection ◽  
Preventive Strategies

Health care–associated infections (HAIs) are those that are acquired while patients are being treated for another condition in the health care setting. HAIs are associated with substantial morbidity and mortality, with 75,000 deaths attributable to HAIs each year. This review outlines the evolution of HAI as a quality metric and introduces key governmental and professional organization stakeholders. The role of the local infection control program is also discussed. Using the example of surgical site infection, we detail the multitude of factors that contribute to the occurrence of an HAI, evidence-based preventive strategies, and systems-based programs to reduce preventable infections. Specific diagnostic criteria and preventive strategies are also introduced for catheter-associated urinary tract infection, central line–associated bloodstream infection, ventilator-associated pneumonia, Clostridium difficile infection, and various multidrug-resistant organisms. This review contains 3 figures, 9 tables, and 74 references. Key words: catheter-associated urinary tract infection, central line–associated bloodstream infection, Clostridium difficile, hospital-acquired infection, infection, quality, surgical site infection, ventilator-associated pneumonia 

Infection Control in Surgical Practice

2017 ◽  
Author(s):  
Caroline E. Reinke ◽  
Rachel R. Kelz ◽  
Elizabeth A Bailey
Keyword(s):  
Health Care ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Clostridium Difficile ◽  
Tract Infection ◽  
Infection Control ◽  
Central Line ◽  
Ventilator Associated Pneumonia ◽  
Site Infection ◽  
Preventive Strategies

Health care–associated infections (HAIs) are those that are acquired while patients are being treated for another condition in the health care setting. HAIs are associated with substantial morbidity and mortality, with 75,000 deaths attributable to HAIs each year. This review outlines the evolution of HAI as a quality metric and introduces key governmental and professional organization stakeholders. The role of the local infection control program is also discussed. Using the example of surgical site infection, we detail the multitude of factors that contribute to the occurrence of an HAI, evidence-based preventive strategies, and systems-based programs to reduce preventable infections. Specific diagnostic criteria and preventive strategies are also introduced for catheter-associated urinary tract infection, central line–associated bloodstream infection, ventilator-associated pneumonia, Clostridium difficile infection, and various multidrug-resistant organisms. This review contains 3 figures, 9 tables, and 74 references. Key words: catheter-associated urinary tract infection, central line–associated bloodstream infection, Clostridium difficile, hospital-acquired infection, infection, quality, surgical site infection, ventilator-associated pneumonia 

scholarly journals Variation in the Type and Frequency of Postoperative Invasive Staphylococcus aureus Infections According to Type of Surgical Procedure

2010 ◽  
Vol 31 (7) ◽  
pp. 701-709 ◽  
Author(s):  
Deverick J. Anderson ◽  
Jean Marie Arduino ◽  
Shelby D. Reed ◽  
Daniel J. Sexton ◽  
Keith S. Kaye ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Surgical Site Infection ◽  
Bloodstream Infection ◽  
Surgical Procedures ◽  
Tertiary Care ◽  
Orthopedic Procedures ◽  
Neurosurgical Procedures ◽  
Site Infection ◽  
Incisional Surgical Site Infection ◽  
Epidemiological Characteristics

Objective.To determine the epidemiological characteristics of postoperative invasive Staphylococcus aureus infection following 4 types of major surgical procedures.Design.Retrospective cohort study.Setting.Eleven hospitals (9 community hospitals and 2 tertiary care hospitals) in North Carolina and Virginia.Patients.Adults undergoing orthopedic, neurosurgical, cardiothoracic, and plastic surgical procedures.Methods.We used previously validated, prospectively collected surgical surveillance data for surgical site infection and microbiological data for bloodstream infection. The study period was 2003 through 2006. We defined invasive S. aureus infection as either nonsuperficial incisional surgical site infection or bloodstream infection. Nonparametric bootstrapping was used to generate 95% confidence intervals (CIs). P values were generated using the Pearson x2 test, Student t test, or Wilcoxon rank-sum test, as appropriate.Results.In total, 81,267 patients underwent 96,455 procedures during the study period. The overall incidence of invasive S. aureus infection was 0.47 infections per 100 procedures (95% CI, 0.43–0.52); 227 (51%) of 446 infections were due to methicillin-resistant S. aureus. Invasive S. aureus infection was more common after cardiothoracic procedures (incidence, 0.79 infections per 100 procedures [95% CI, 0.62–0.97]) than after orthopedic procedures (0.37 infections per 100 procedures [95% CI, 0.32–0.42]), neurosurgical procedures (0.62 infections per 100 procedures [95% CI, 0.53–0.72]), or plastic surgical procedures (0.32 infections per 100 procedures [95% CI, 0.17¬0.47]) (P < .001). Similarly, S. aureus bloodstream infection was most common after cardiothoracic procedures (incidence, 0.57 infections per 100 procedures [95% CI, 0.43–0.72]; P < .001, compared with other procedure types), comprising almost three-quarters of the invasive S. aureus infections after these procedures. The highest rate of surgical site infection was observed after neurosurgical procedures (incidence, 0.50 infections per 100 procedures [95% CI, 0.42–0.59]; P < .001, compared with other procedure types), comprising 80% of invasive S. aureus infections after these procedures.Conclusion.The frequency and type of postoperative invasive S. aureus infection varied significantly across procedure types. The highest risk procedures, such as cardiothoracic procedures, should be targeted for ongoing preventative interventions.

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