Hand hygiene expectations in radiography: A critical evaluation of the opportunities for and barriers to compliance

2019 ◽  
Vol 20 (3) ◽  
pp. 122-131
Author(s):  
Annette Jeanes ◽  
Fiona Henderson ◽  
Nick Drey ◽  
Dinah Gould
Keyword(s):  
Hand Hygiene ◽  
Critical Evaluation ◽  
Evidence Base ◽  
Risk Process ◽  
World Health ◽  
X Ray ◽  
Chest X Ray ◽  
Hygiene Compliance ◽  
Control Knowledge ◽  
Health Organization

Introduction: Good hand hygiene practices reduce the risk of transmission of infection in healthcare. In common with other areas of healthcare, infection control knowledge and practice in radiography has potential for improvement. Regular hand hygiene compliance (HHC) monitoring indicated poor compliance in radiology which did not accurately reflect practice in one organisation. Using a quality improvement cycle, the process and context of work undertaken in radiology were examined in order to improve the validity and utility of HHC monitoring data collection process in the department. Methods: Following examination of the evidence base and with agreement from the radiology team, the chest X-ray process was observed and actions notated. This was then scored using the organisation and the World Health Organization five moments of hand hygiene tool. An alternative risk-based scoring system was developed. Results: The HHC score of 22% was obtained using standard measurements. Achievement of 100% compliance would require the radiographer to clean their hands nine times for each X-ray. The sequence of taking a chest X-ray was examined and two points in the process were identified as key points at which hand cleaning should take place to reduce the risk of transmission of infection. Conclusions: Cleaning hands frequently to achieve compliance expectations in this short low-risk process is neither feasible nor beneficial. A pragmatic risk-based approach to hand hygiene expectations in predictable procedures such as taking a chest X-ray reduces ambiguity and potentially increases compliance.

scholarly journals Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks

Proceedings ◽  
2020 ◽  
Vol 54 (1) ◽  
pp. 31
Author(s):  
Joaquim de Moura ◽  
Lucía Ramos ◽  
Plácido L. Vidal ◽  
Jorge Novo ◽  
Marcos Ortega
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Clinical Symptoms ◽  
Early Stage ◽  
World Health ◽  
Complete Analysis ◽  
Screening Process ◽  
X Ray ◽  
Chest X Ray ◽  
Health Organization

The new coronavirus (COVID-19) is a disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). On 11 March 2020, the coronavirus outbreak has been labelled a global pandemic by the World Health Organization. In this context, chest X-ray imaging has become a remarkably powerful tool for the identification of patients with COVID-19 infections at an early stage when clinical symptoms may be unspecific or sparse. In this work, we propose a complete analysis of separability of COVID-19 and pneumonia in chest X-ray images by means of Convolutional Neural Networks. Satisfactory results were obtained that demonstrated the suitability of the proposed system, improving the efficiency of the medical screening process in the healthcare systems.

scholarly journals Pathways to clean hands: highlights of successful hand hygiene implementation strategies in Europe

2010 ◽  
Vol 15 (18) ◽  
Author(s):  
A P Magiorakos ◽  
E Leens ◽  
V Drouvot ◽  
L May-Michelangeli ◽  
C Reichardt ◽  
...  
Keyword(s):  
Hand Hygiene ◽  
Implementation Strategies ◽  
World Health ◽  
Surveillance Systems ◽  
The European Union ◽  
Hygiene Practices ◽  
Governmental Support ◽  
Hygiene Compliance ◽  
Health Organization ◽  
Healthcare Associated

Hand hygiene is the most effective way to stop the spread of microorganisms and to prevent healthcare-associated infections (HAI). The World Health Organization launched the First Global Patient Safety Challenge - Clean Care is Safer Care - in 2005 with the goal to prevent HAI globally. This year, on 5 May, the WHO’s initiative SAVE LIVES: Clean Your Hands, which focuses on increasing awareness of and improving compliance with hand hygiene practices, celebrated its second global day. In this article, four Member States of the European Union describe strategies that were implemented as part of their national hand hygiene campaigns and were found to be noteworthy. The strategies were: governmental support, the use of indicators for hand hygiene benchmarking, developing national surveillance systems for auditing alcohol-based hand rub consumption, ensuring seamless coordination of processes between health regions in countries with regionalised healthcare systems, implementing the WHO's My Five Moments for Hand Hygiene, and auditing of hand hygiene compliance.

scholarly journals Hand hygiene compliance monitoring in anaesthetics: Feasibility and validity

2018 ◽  
Vol 19 (3) ◽  
pp. 116-122 ◽  
Author(s):  
A Jeanes ◽  
J Dick ◽  
P Coen ◽  
N Drey ◽  
DJ Gould
Keyword(s):  
Hand Hygiene ◽  
Hand Hygiene Compliance ◽  
Care Delivery ◽  
Compliance Rate ◽  
Significant Risk ◽  
World Health ◽  
Compliance Monitoring ◽  
Infection Control Practitioner ◽  
Hygiene Compliance ◽  
Health Organization

Background: Hand hygiene compliance scores in the anaesthetic department of an acute NHS hospital were persistently low. Aims: To determine the feasibility and validity of regular accurate measurement of HHC in anaesthetics and understand the context of care delivery, barriers and opportunities to improve compliance. Methods: The hand hygiene compliance of one anaesthetist was observed and noted by a senior infection control practitioner (ICP). This was compared to the World Health Organization five moments of hand hygiene and the organisation hand hygiene tool. Findings: In one sequence of 55 min, there were approximately 58 hand hygiene opportunities. The hand hygiene compliance rate was 16%. The frequency and speed of actions in certain periods of care delivery made compliance measurement difficult and potentially unreliable. During several activities, taking time to apply alcohol gel or wash hands would have put the patients at significant risk. Discussion: We concluded that hand hygiene compliance monitoring by direct observation was invalid and unreliable in this specialty. It is important that hand hygiene compliance is optimal in anaesthetics particularly before patient contact. Interventions which reduce environmental and patient contamination, such as cleaning the patient and environment, could ensure anaesthetists encounter fewer micro-organisms in this specialty.

scholarly journals Hand hygiene compliance among rural healthcare workers of Nepal

2018 ◽  
Vol 5 (1) ◽  
pp. 90-95
Author(s):  
Ajay Kumar Rajbhandari ◽  
Reshu Agrawal Sagtani ◽  
Kedar Prasad Baral
Keyword(s):  
Health Care ◽  
Hand Hygiene ◽  
Healthcare Workers ◽  
Compliance Rate ◽  
Hand Washing ◽  
World Health ◽  
Cross Sectional ◽  
Hygiene Compliance ◽  
Health Organization ◽  
Healthcare Associated

Introductions: Transmission of healthcare associated infections through contaminated hands of healthcare workers are common. This study was designed to explore the existing compliance of hand hygiene among the healthcare workers workings in different level of health care centers of Makwanpur district of Nepal. Methods: This was a cross sectional observational study conducted in Makwanpur district, Nepal, during 2015. Healthcare workers from nine healthcare centers were selected randomly for the study. Standard observation checklists and World Health Organization guidelines on hand hygiene were used to assess the compliance of hand hygiene during patient care. Results: There were 74 participants. Overall compliance for hand washing was 24.25% (range 19.63 to 45.56). Complete steps of hand washing were performed by 38.3% of health care workers. The factors associated for noncompliance were lack of time (29.3%), example set by seniors (20%), absence or inadequate institution protocol (20%) and unfavourable health care setting (> 20%). Conclusions: Overall hand washing compliance rate amongst the healthcare workers in rural health facilities of Nepal were low (24.25%).

scholarly journals A Deep Learning Approach to Detect COVID-19 Patients from Chest X-ray Images

AI ◽  
2020 ◽  
Vol 1 (3) ◽  
pp. 418-435
Author(s):  
Khandaker Haque ◽  
Ahmed Abdelgawad
Keyword(s):  
Deep Learning ◽  
World Health ◽  
X Rays ◽  
X Ray ◽  
Global Pandemic ◽  
Proposed Model ◽  
Dental Diseases ◽  
Chest X Ray ◽  
Artery Disease ◽  
Health Organization

Deep Learning has improved multi-fold in recent years and it has been playing a great role in image classification which also includes medical imaging. Convolutional Neural Networks (CNNs) have been performing well in detecting many diseases including coronary artery disease, malaria, Alzheimer’s disease, different dental diseases, and Parkinson’s disease. Like other cases, CNN has a substantial prospect in detecting COVID-19 patients with medical images like chest X-rays and CTs. Coronavirus or COVID-19 has been declared a global pandemic by the World Health Organization (WHO). As of 8 August 2020, the total COVID-19 confirmed cases are 19.18 M and deaths are 0.716 M worldwide. Detecting Coronavirus positive patients is very important in preventing the spread of this virus. On this conquest, a CNN model is proposed to detect COVID-19 patients from chest X-ray images. Two more CNN models with different number of convolution layers and three other models based on pretrained ResNet50, VGG-16 and VGG-19 are evaluated with comparative analytical analysis. All six models are trained and validated with Dataset 1 and Dataset 2. Dataset 1 has 201 normal and 201 COVID-19 chest X-rays whereas Dataset 2 is comparatively larger with 659 normal and 295 COVID-19 chest X-ray images. The proposed model performs with an accuracy of 98.3% and a precision of 96.72% with Dataset 2. This model gives the Receiver Operating Characteristic (ROC) curve area of 0.983 and F1-score of 98.3 with Dataset 2. Moreover, this work shows a comparative analysis of how change in convolutional layers and increase in dataset affect classifying performances.

scholarly journals Identifying the World Health Organization’s fifth moment for hand hygiene: Infection prevention in the operating room

2019 ◽  
Vol 21 (1) ◽  
pp. 28-34
Author(s):  
Fiona Smith ◽  
Karen Lee ◽  
Eleanor Binnie-McLeod ◽  
Mark Higgins ◽  
Elizabeth Irvine ◽  
...  
Keyword(s):  
Hand Hygiene ◽  
Operating Room ◽  
Direct Contact ◽  
Phase 1 ◽  
World Health ◽  
Phase 2 ◽  
Frontline Staff ◽  
The World ◽  
Hygiene Compliance ◽  
Health Organization

Background: The World Health Organization have designed the fifth of their ‘5 moments’ for hand hygiene to account for microbial transfer from patients to equipment in a narrow area around that patient, known as the patient zone. The study was prompted by emerging local confusion about application of the patient zone in the operating room (OR). Aim/Objectives: In two phases, we aimed to create a ‘5 moments’ style poster displaying an OR patient zone: phase 1, quantify equipment, in direct contact with the patient and, touched by non-scrubbed staff immediately after touching the patient; and phase 2, categorise equipment identified in phase 1 into patient zone and healthcare zone. An objective is to produce a ‘5 moments’ poster for the OR. Methods: The first phase used non-participant direct overt observation. In phase 2, phase 1 data were collaboratively assigned to patient zone or healthcare zone. Photography and graphic design were used to produce the OR ‘5 moments’ poster. Results: In 11 full-length surgeries, 20 pieces of equipment were in direct contact with the patient and 57 pieces of equipment were touched. In phase 2, a ‘5 moments’ poster showing an OR patient zone was designed. Discussion: Content of the patient zone was identified and displayed in a novel resource. Having shared understanding of the patient zone has potential to sustain hand hygiene compliance and equipment cleaning in the OR. Conclusion: Limitations in methods were balanced by collaboration with frontline staff. The study has been used as a teaching tool in the OR and similar settings.

scholarly journals Determinants of success and sustainability of the WHO multimodal hand hygiene promotion campaign, Italy, 2007–2008 and 2014

2017 ◽  
Vol 22 (23) ◽  
Author(s):  
Maria Luisa Moro ◽  
Filomena Morsillo ◽  
Simona Nascetti ◽  
Mita Parenti ◽  
Benedetta Allegranzi ◽  
...  
Keyword(s):  
Hand Hygiene ◽  
Hand Hygiene Compliance ◽  
World Health ◽  
Absolute Increase ◽  
Italian Regions ◽  
Hygiene Promotion ◽  
Before And After ◽  
Hygiene Compliance ◽  
Health Organization ◽  
Implementation Progress

A national hand hygiene promotion campaign based on the World Health Organization (WHO) multimodal, Clean Care is Safer Care campaign was launched in Italy in 2007. One hundred seventy-five hospitals from 14 of 20 Italian regions participated. Data were collected using methods and tools provided by the WHO campaign, translated into Italian. Hand hygiene compliance, ward infrastructure, and healthcare workers’ knowledge and perception of healthcare-associated infections and hand hygiene were evaluated before and after campaign implementation. Compliance data from the 65 hospitals returning complete data for all implementation tools were analysed using a multilevel approach. Overall, hand hygiene compliance increased in the 65 hospitals from 40% to 63% (absolute increase: 23%, 95% confidence interval: 22–24%). A wide variation in hand hygiene compliance among wards was observed; inter-ward variability significantly decreased after campaign implementation and the level of perception was the only item associated with this. Long-term sustainability in 48 of these 65 hospitals was assessed in 2014 using the WHO Hand Hygiene Self-Assessment Framework tool. Of the 48 hospitals, 44 scored in the advanced/intermediate categories of hand hygiene implementation progress. The median hand hygiene compliance achieved at the end of the 2007–2008 campaign appeared to be sustained in 2014.

scholarly journals CHEST X-RAY FINDINGS IN COVID-19 PNEUMONIA: A PICTORIAL REVIEW

2020 ◽  
pp. 9-11
Author(s):  
Zohra Ahmad ◽  
Parul Dutta ◽  
Deepjyoti Das Choudhury ◽  
Satabdi Kalita ◽  
Zohaib Hussain ◽  
...  
Keyword(s):  
Virus Disease ◽  
Vital Role ◽  
World Health ◽  
Thoracic Imaging ◽  
X Ray ◽  
Pictorial Review ◽  
Care Workers ◽  
The World ◽  
Chest X Ray ◽  
Health Organization

Corona Virus Disease 19 or COVID-19, was first detected in Wuhan province in China in December 2019 and reported to the World Health Organization (WHO) on December 31, 2019 [1]. It was declared a pandemic on March 11th, 2020 [2] and has till now affected 40 million people all around the world resulting in 1.1 million deaths (as of 18th Oct, 2020) [3]. As the world is reeling under the burden of the disease, it has been imperative for the radiologists to be familiar with the imaging appearance of the disease. Thoracic imaging with chest X-ray and CT is the key modality for the diagnosis and management of respiratory diseases. Although CT is more sensitive, the immense challenge of disinfection control in the modality may disrupt the service availability and portable X-ray may be considered to minimize the risk [4]. Use of portable X-ray has played a vital role in all the areas around the world during this pandemic. The purpose of this pictorial review is to represent the frequently encountered features and abnormalities in chest X-ray and strengthen the knowledge of the health-care workers in this war against the pandemic.

Identifikasi Penderita COVID-19 Berdasarkan Chest X-Ray Menggunakan Algoritma Jaringan Syaraf Tiruan Backpropagation

2021 ◽  
pp. 195-200
Author(s):  
Heru Rahmat Wibawa Putra ◽  
Y Yuhandri
Keyword(s):  
Virus Disease ◽  
Imaging Techniques ◽  
Training Data ◽  
World Health ◽  
X Ray ◽  
Initial Stage ◽  
The World ◽  
Chest X Ray ◽  
Artificial Neural Network Ann ◽  
Health Organization

Corona Virus Disease 2019 (COVID-19) is an infectious respiratory disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV2). This disease first appeared in Wuhan, China and spread throughout the world. COVID-19 has had a major impact on public health around the world. On March 9, 2020, the World Health Organization (WHO) declared COVID-19 a pandemic. Early identification of people with COVID-19 can help limit the wider spread. One of the factors behind the rapid spread of the disease is the long clinical trial time. Rapid clinical testing is a challenge facing the spread of COVID-19. Most countries, including Indonesia, face the problem of lack of detection equipment and experts in diagnosing this disease. Chest X-Ray is one of the medical imaging techniques and also an alternative to identify the symptoms of pneumonia caused by COVID-19. This study aims to identify pneumonia caused by COVID-19 and other diseases based on Chest X-Ray. 107 Chest X-Ray images used as material for this study were obtained from the General Hospital of Ibnu Sina Padang Indonesia, which consisted of 27 images of pneumonia caused by COVID-19, 51 images with other diseases and 29 images of normal lungs. Then pre-processing is carried out as an initial stage and then feature extraction is carried out. Furthermore, the learning and identification process is carried out using the Backpropagation Artificial Neural Network (ANN) algorithm. In this study, 92 images were used as training data, and 15 images were used as test data. The results of calculations carried out using a network with a pattern of 16-100-100-100-2 obtained an accuracy value of 73%. The results of the identification prediction can be used as consideration in establishing a diagnosis of COVID-19 sufferers, but cannot be used as an absolute reference.

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