Personal Protective Equipment Compliance Research Articles

Pose guided anchoring for detecting proper use of personal protective equipment

Ensuring proper use of personal protective equipment (PPE) is essential for improving workplace safety management. The authors present an extensible pose-guided anchoring framework aimed at multi-class PPE compliance detection. The overall approach harnesses a pose estimator to detect worker body parts as spatial anchors and guide the localization of part attention regions using body-knowledge-based rules considering workers' orientations and object scales. Specifically, “part attention regions” are local image patches expecting PPEs based on their inherent relationships with body parts, e.g., (head, hardhat) and (upper-body, vest). Finally, the shallow CNN-based classifiers can reliably recognize both PPE and non-PPE classes within their corresponding part attention regions. Quantitative evaluations tested on the developed construction personal protective equipment dataset (CPPE) show an overall 0.97 and 0.95 F1-score for hardhat and safety vest detection, respectively. Comparative studies with existing methods also demonstrate the higher detection accuracy and advantageous extensibility of the proposed strategy.

Through Their Eyes: Health Care Worker Compliance With Personal Protective Equipment During the COVID-19 Pandemic.

Personal protective equipment (PPE) plays a critical role in protecting health care workers (HCWs). During the coronavirus disease-2019 (COVID-19) pandemic, shortages of PPE supplies drastically changed the way PPE was obtained and used by HCWs. The objective was to investigate the impact of the COVID-19 pandemic and patient isolation type on PPE compliance. This investigation was a survey of HCWs at a level 1 trauma teaching hospital regarding PPE compliance patterns prior to and during the COVID-19 pandemic. HCWs reported an increase in PPE compliance during the COVID-19 pandemic. Nearly half (48.6%) of respondents reported that isolation type impacted the decision to wear PPE, of which most were likely to forgo PPE with contact precautions. HCWs identified multiple barriers to compliance. The underutilization of PPE with contact precautions suggests that the risk of exposure is interpreted as low, and this could be a future target of education.

Correlation of Management Commitment Regarding Occupational Safety and Health and Personal Protective Equipment Compliance in Production Unit Workers of PT. Nitama Galvanizer

Correlation of Management Commitment Regarding Occupational Safety and Health and Personal Protective Equipment Compliance in Production Unit Workers of PT. Nitama Galvanizer

P062 How do our patients feel about face-to-face review in rheumatology clinics since COVID-19? A single tertiary care centre experience

Background/Aims The COVID-19 pandemic has had a significant impact on the management of outpatients. During the first wave of the pandemic, and in common with other departments, almost all our patient consultations happened over the phone. As the rate of infection fell, we felt it was crucial that the patient voice was heard as we re-organised clinical areas and re-opened services. In view of this, we conducted an online survey to better understand patient concerns around visiting our hospital for appointments and how we can adapt the way we work to ensure patient safety and satisfaction. Methods Using our electronic patient record, we identified patients from the clinic lists of 2 adult rheumatology consultants over a 6-week period between June and August 2020. This timeframe was selected as it was towards the end of the UK nationwide shielding period and our department was returning to deliver an increasing proportion of outpatient care face-to-face. Included patients had to have been treated with an immunosuppressive drug and only those on monotherapy hydroxychloroquine, sulfasalazine or prednisolone under 5mg were excluded. We consented each patient via telephone before sending them an email link to an online anonymised survey. This included a combination of 9 multiple choice and white space questions. Results 65 patients were identified of which 16 were excluded as we were unable to contact them or they declined consent. 49 patients were sent the survey of which 31 responses were received. 21/31 (67%) of patients had been shielding. The survey revealed six themes of concern. These include: lack of social distancing in common hospital areas, lack of personal protective equipment compliance amongst staff, prolonged time spent in waiting rooms, lack of knowledge on new hospital policies, logistics of using public transport to come to the hospital, and the importance of retaining virtual consultations going forward. 55% of patients stated they would feel safe in returning to the hospital for face-to-face appointments over the next few months. Conclusion Important themes have emerged from this project that we have presented to our rheumatology multi-disciplinary team, Director of Innovation and Head of Patient Experience. This has reinforced adaptations in our hospital environment such as installing safe distance seating in waiting rooms and scheduled phlebotomy slots. Further, where possible we call patients before face-to-face appointments to inform them of our safety measures and try to schedule these patients for outside peak travel hours. We acknowledge that using an online survey may limit responses from older individuals or those with English as a second language. Despite this, our project has shown the importance of recognising the unique concerns of rheumatology patients and the value in using their opinions to create a “new normal” for our outpatient environment. Disclosure R. Amarnani: None. B. Goulden: None. J. Manson: None. V. Morris: None.

Evaluating Personal Protective Equipment Compliance in the Midst of a Pandemic.

Health care workers wear personal protective equipment (PPE) to protect themselves from any splashes, spray, spatter, droplets of blood, or other potentially infectious materials that may be generated during patient care 1 Examples of PPE include gloves, gowns, eyewear, and masks The tasks listed in the policy as required include * performing respiratory care (eg, intubation, extubation, tracheotomy care, suctioning, assessing patients with active or productive coughs, collecting respiratory specimens);* performing bedside care (when performing tasks likely to generate body fluid splashes);* performing procedures that are likely to generate splashes;* emptying or transporting open containers of fluids or specimens;* participating in traumas or codes;and * caring for patients who spit 3 The tasks listed in the policy as recommended include performing * respiratory care (eg, turning and caring for ventilated patients or patients with a tracheotomy);* bedside care involving body fluids (eg, starting an IV, drawing blood, blood glucose point-of-care testing, dressing changes, stoma or fistula care, changing diapers);and * procedures (eg, lumbar punctures, paracentesis, chest tube insertion, thoracentesis) in any location in the facility 3 Personnel from the Employee Health and Safety and Infection Control Departments determined the required and recommended tasks based on actual body fluid exposure occurrences that staff members documented and submitted to the Employee Health Department In May 2019, unit leaders and educators began discussing ideas for competencies for staff members to complete in 2020 Because the eye and facial protection policy was considered new, a change, problematic, and high risk, unit leaders and educators chose use of eye and facial protection as a 2020 competency for all staff members in procedural areas, including perioperative units, endoscopy, and the cardiac catheterization laboratory, to complete

Review of hygiene adaptations among UK doctors in controlling the spread of SARS-CoV-2 infection

A significant number of healthcare workers around the world have contracted COVID-19 from their workplace, thus there is a need to investigate common hygiene practices. We aimed to describe the common hygiene adaptations of doctors in the hospital and at home. A survey of 110 doctors in UK was carried out to determine their hygiene adaptations and practices. Data were collected on demographics and personal protective equipment compliance. The key findings were frequent hand washing (51%), change of clothing entering and leaving hospital (88% and 92%, respectively), taking a shower upon returning home (85%) and washing work attire at temperatures of 60-80°C (50%). A higher proportion of junior doctors washed their scrubs (p=0.004) and stethoscopes (p=0.014) compared with consultants and seniors. Female doctors cleaned their mobile phones (p=0.022) and work belongings (p=0.01) more frequently. This study signified that junior doctors were more meticulous in hygiene adaptations and female doctors were more fastidious in personal hygiene. The observations of this study may be beneficial in preventing transmission of infection to families of healthcare professionals and are important to implement in the case of a second wave of COVID-19.

489. A Case-Control Approach to an Outbreak of SARS-CoV-2 on an Acute Stroke Unit in the U.S

BackgroundDetailed descriptions of hospital-acquired SARS-CoV-2 infections and transmission chains in healthcare settings are crucial to controlling outbreaks and improving patient safety. However, such reports are scarce. We sought to determine origins and factors associated with nosocomial transmission of SARS-CoV-2 in a 528-bed teaching hospital in Western New York.MethodsThe index patient, who had mental illness, wandered throughout the ward, would not wear a facemask, and was often kept seated at the nursing station, developed COVID-19 on day- 22 of hospitalization. A case-control approach was used, wherein all patients, staff, and 128 randomly selected environmental surfaces on the outbreak unit (case), and randomly selected patients, staff, and environmental surfaces on designated COVID-19 and non-COVID-19 units (control), were tested for SARS-COV-2 by RT-PCR and IgG SARS-COV-2 antibodies (SAR-Ab). Compliance with hand hygiene (HH) and COVID-specific personal protective equipment (PPE) was assessed.Results145 staff and 26 patients were potentially exposed resulting in 25 secondary cases (14 staff and 11 patients). 4/14 (29%) of the staff and 7/11 (64%) of the patients who tested positive, and later became ill, were asymptomatic at the time of testing (Figures 1–2). There was no difference in mean cycle threshold for SARS-COV-2 gene targets between asymptomatic and symptomatic individuals. 0/32 randomly selected staff from the positive and negative control wards tested positive. PPE compliance based on 354 observations was not significantly different between wards. Environmental surface contamination with SARS-COV-2 RNA was not different between outbreak and control wards. Mean monthly HH compliance, based on 20,146 observations, was lower on the outbreak ward (p < 0.006) (Figure 3). 142 staff volunteered for serologic testing. The proportion staff with detectable SAR-Ab was higher on the outbreak ward (OR 3.78: CI 1.01–14.25).Figure 1 Figure 2 Figure 3 ConclusionThe risk of staff exposure was higher in an outbreak setting than on a dedicated COVID-19 unit (Figure 4). Noncompliant patient behavior, decreased hand hygiene, and pre-symptomatic transmission can contribute to nosocomial spread and are important considerations for ongoing infection control efforts.Figure 4 Disclosures All Authors: No reported disclosures

97. Assessment of Personal Protective Equipment Adherence in Red Box Using Remote Video Auditing

Background“Red box (RB)” is a delineated space in the entry way to a patient(pt) room(rm) that facilitates communication between pt and health care provider (HCP) without the latter needing to don/doff personal protective equipment (PPE). It decreases PPE use where unnecessary and increases pt satisfaction ratings. Remote Video Auditing (RVA) is a novel technique used to ensure adherence to isolation precautions. In this study, we used RVA to compare HCP compliance rates with PPE use in isolation rms with or without RB.MethodsA prospective observational study (2/26/19-2/27/20) was designed to evaluate HCP compliance with PPE when entering or exiting droplet/contact isolation rms. RB was demarcated by red tape as a 3-ft area at rm entrance, >6 ft from the head of the bed. Cameras were placed at the entry of 4 rms with RB (RB rms) and 2 isolation rms without RB (control rms). Adherence to gowns, gloves, masks and hand hygiene (HH) was reviewed by trained independent remote observers to maintain uniformity. When HCPs stayed in the RB, compliance at exit was calculated. Compliance was compared between events of HCPs going beyond the RB and those of HCPs entering/exiting control rms using binomial regression models with log link.ResultsRVA captured 6959 pt encounters in 6 rms over a year. Consistent with RB protocol, when HCPs utilized the RB, 69.9% did not practice HH, 91.6% did not utilize gloves and 95.2% did not use gowns (Table 1). When HCPs went beyond the RB, there was significantly increased non-compliance with PPE and HH in RB rms compared with control rms (Table 2). Healthcare-associated infection (HAI) rates for this unit assessed using NHSN criteria demonstrated no increase as compared to prior years.Table 1: Non-Compliance among those who entered Red Box but did not go into the room fully Table 2: Comparison of non-compliance between group that went beyond Red Box Vs. Control group without Red Box ConclusionRVA, a novel, labor-efficient and objective method, was used for observing and comparing PPE compliance in RB rms. Consistent with the purpose of RB, >90% HCPs did not use PPE while confined within it. However, HCPs going beyond the RB were more non-compliant with PPE use as compared to HCPs in control rms. While HAI rates were not increased, this finding is concerning – HCPs going beyond RB may not have used PPE (even in close proximity) due to a false sense of security due to RB. Re-education about optimal use of the RB or discontinuing RB should be considered.Disclosures All Authors: No reported disclosures

Occupational COVID-19 Prevention among Congolese Healthcare Workers: Knowledge, Practices, PPE Compliance, and Safety Imperatives.

The SARS-CoV-2 (COVID-19) pandemic has had a tremendous impact on the functionality of health systems and world affairs. We assessed knowledge, attitudes, and practices (KAPs) of healthcare workers (HCWs) in the Democratic Republic of the Congo (DRC). This was a cross-sectional study conducted in 23 referral hospitals located in three towns of the DRC (Lubumbashi, Kamina, Mbuji-Mayi). In total, 613 HCWs were surveyed using the World Health Organization’s (WHO’s) “Exposure Risk Assessment in the Context of COVID-19” questionnaire. Participants included medical doctors (27.2%) and other categories of HCWs (72.8%). The mean age was 40.3 ± 11.7 years. Over 80% (range: 83–96%) of respondents had sufficient knowledge on each of the three domains: COVID-19 symptoms, disease transmission, and patient care approach. However, attitudes and practices scores were relatively low. Only 27.7% of HCWs were willing to receive a COVID-19 vaccine when it is available, whereas 55% of HCWs complied with good practices; 49.4% wore masks consistently and, surprisingly, only 54.9% used personal protective equipment (PPE) consistently at work and during contact with patients. Knowledge level was positively associated with the use of social media as a primary source of COVID-19-related information and the category of residence, with HCWs from towns already affected by the COVID-19 epidemic being more likely to have positive attitudes (adjusted OR, 1.64; 95%CI, 1.32–2.20) and comply with good practices (aOR, 2.79; 95%CI, 1.93-4.06). This study showed that most Congolese HCWs had sufficient knowledge on COVID-19, whereas the majority did not comply with consistent PPE use. The government of the DRC should urgently take major steps in capacity building for HCWs in outbreak preparedness and supplying hospitals with PPE.

SPARC-ing Change—The Maryland Statewide Prevention and Reduction of Clostridioides difficile (SPARC) Collaborative

Background: In 2018, the Maryland Department of Health, in collaboration with the University of Maryland and Johns Hopkins University, created the Statewide Prevention and Reduction of Clostridioides difficile (SPARC) collaborative to reduce C. difficile as specified in Healthy People 2020. Methods: The SPARC collaborative recruited hospitals contributing most cases to statewide C. difficile standardized infection ratio (SIR), according to data reported to the National Healthcare Safety Network (NHSN). SPARC developed intervention bundles around 4 domains: infection prevention, environmental cleaning, and diagnostic and antimicrobial stewardship. Each facility completed a self-assessment followed by an on-site, day-long, peer-to-peer (P2P) evaluation with 8–12 SPARC subject matter experts (SMEs) representing each domain. The SMEs met with hospital executive leadership and then led 4 domain-based group discussions with relevant hospital team leaders. To identify policy and practice gaps, SMEs visited hospital inpatient units for informal interviews with frontline staff. In a closing session, SPARC SMEs, hospital executives, and team leaders reconvened to discuss preliminary findings. This included review of covert observation data (hand hygiene, personal protective equipment compliance, environmental cleaning) obtained by SPARC team 1–2 weeks prior. Final SPARC P2P written recommendations guided development of customized interventions at each hospital. SPARC provided continuous support (follow up phone calls, educational webinars, technical support, didactic training for antimicrobial stewardship pharmacists) to enhance facility-specific implementation. For every quarter, we categorized C. difficile NHSN data for each Maryland hospital into “SPARC” or “non-SPARC” based on participation status. Using negative binomial mixed models, we analyzed difference-in-difference of pre- and postincidence rate ratios (IRRs) for SPARC and non-SPARC hospitals, which allowed estimation of change attributable to SPARC participation independent of other time-varying factors. Results: Overall, 13 of 48 (27%) hospitals in Maryland participated in the intervention. The baseline SIR for all Maryland hospitals was 0.92, and the post-SPARC SIR was 0.67. The SPARC hospitals had a greater reduction in hospital-onset C. difficile incidence; 8.6 and 4.3 events per 10,000 patient days for baseline and most recent quarter, respectively. For non-SPARC hospitals, these hospital-onset C. difficile incidences were 5.1 preintervention and 4.3 postintervention. We found a statistically significant difference-in-difference between SPARC and non-SPARC hospital C. difficile reduction rates (ratio of IRR, 0.63; 95% CI, 0.44−0.89; P = .01). Conclusions: The Maryland SPARC collaborative, a public health-academic partnership, was associated with a 25% reduction in the Maryland C. difficile SIR. Hospitals participating in SPARC demonstrated significantly reduced C. difficile incidences to match that of high-performing hospitals in Maryland.Funding: NoneDisclosure: Aaron Milstone, BD – consulting.

Availability, Accessibility and Proper Use of Personal Protective Equipment in Wards at Queen Elizabeth Central Hospital (QECH) Blantyre, Malawi: An Observational Study.

The purpose of this study was to evaluate the availability, accessibility and proper use of personal protective equipment (PPE) in the wards at Queen Elizabeth Central Hospital (QECH). We conducted an observational study with a cross-section design. Convenience sampling method was used for selection of healthcare workers (HCWs) in wards. HCWs filled a checklist on accessibility of PPEs and they were observed on proper use of PPE while conducting clinical procedures. Nurse ward in-charge was asked to fill out a checklist on availability of PPE in their ward. PPE was available in 75.8% of wards, not available in 12.5%. Goggles were absent in 70.8% of wards. PPEs were 71.4% accessible and 28.6% inaccessible to healthcare workers in the wards. The most inaccessible PPEs were goggles (83.2%) and footwear (73.7%) while facemasks, sterile and non-sterile gloves and aprons were readily accessible. Non sterile gloves were 100% available and accessible. Only 13.5% of the HCWs had good compliance with PPE standard procedures. The average PPE compliance score of those who had been trained was 6 % greater than those who were not trained. This study identified areas of improvement in healthcare system delivery regarding standard precautions with emphasis on PPE. Improvements in training during professional college education and in-service refresher training could improve compliance with appropriate use of PPE for relatively low cost. Management support could improve availability and accessibility of PPE in the wards at QECH, with active supervision to improve adherence levels to personal protective equipment usage. The study can also help in the development of policies and guidelines regarding PPE usage by showing that most HCWs need to be trained in proper PPE usage.

COVID-19 Intubation Safety: A Multidisciplinary, Rapid-Cycle Model of Improvement.

The COVID-19 pandemic has forced the health care industry to develop dynamic protocols to maximize provider safety as aerosolizing procedures, specifically intubation, increase the risk of contracting SARS-CoV-2. The authors sought to create a quality improvement framework to ensure safe practices for intubating providers, and describe a multidisciplinary model developed at an academic tertiary care facility centered on rapid-cycle improvements and real-time gap analysis to track adherence to COVID-19 intubation safety protocols. The model included an Intubation Safety Checklist, a standardized documentation template for intubations, obtaining real-time feedback, and weekly multidisciplinary team meetings to review data and implement improvements. This study captured 68 intubations in suspected COVID-19 patients and demonstrated high personal protective equipment compliance at the institution, but also identified areas for process improvement. Overall, the authors posit that an interdisciplinary workgroup and the integration of standardized processes can be used to enhance intubation safety among providers during the COVID-19 pandemic.

Human-object interaction recognition for automatic construction site safety inspection

Today, computer vision object detection methods are used for safety inspections from site videos and images. These methods detect bounding boxes and use hand-made rules to enable personal protective equipment compliance checks. This paper presents a new method to improve the breadth and depth of vision-based safety compliance checking by explicitly classifying worker-tool interactions. A detection model is trained on a newly constructed image dataset for construction sites, achieving 52.9% average mean precision for 10 object categories and 89.4% average precision for detecting workers. Using this detector and new dataset, the proposed human-object interaction recognition model achieved 79.78% precision and 77.64% recall for hard hat checking; 79.11% precision and 75.29% recall for safety coloring checking. The new model also verifies hand protection for workers when tools are being used with 66.2% precision and 64.86% recall. The proposed model is superior in these checking tasks when compared with post-processing detected objects with hand-made rules, or applying detected objects only.

Getting Their Attention: Using Human Factors Engineering to Design the Optimal Isolation Sign

<h3>Background</h3> The Centers for Disease Control and Prevention recommends transmission-based precautions for patients with suspected or confirmed infection of select pathogens. Isolation signs are used in healthcare to alert staff of the precautions needed to prevent transmission, including the usage of appropriate personal protective equipment (PPE) prior to entering patients' rooms. However, isolation signs can lack clarity or signal saliency, making it difficult for healthcare staff to process critical information. We sought to apply human factors design principles to isolation signs to increase signage clarity to ultimately improve compliance with isolation precautions. <h3>Methods</h3> We applied human factors design principles to modify existing isolation signs at a quaternary care children's hospital in order to increase saliency of the graphics, and align with how individuals naturally process visual information. Key design changes included converting to a vertical layout, increasing graphic size, and adding number indicators to align with proper donning order. Modified signs were trialed on two pilot units between April and May 2019. Staff feedback was collected using a standardized form to assess sign effectiveness and comprehension. Upon sign implementation on four units in July 2019, direct observations were performed to measure PPE compliance. These observations were compared to the baseline compliance from 2017 and 2018 using chi-square. <h3>Results</h3> Seventy-six staff were surveyed during the trial: 94.7% found the order of donning PPE easy to understand and the majority (71.1%) found the signs to be effective. PPE compliance increased on the four post-implementation units from 87.2% (n=141) in 2017 and 2018 to 100% (n=21) between July and December 2019 (p=0.53). <h3>Conclusions</h3> We found that implementation of human factors principles to isolation sign design improved sign effectiveness and correlated with an increase in PPE compliance. Human factors design principles should be considered by Infection Prevention programs to enhance effectiveness of prevention practices in healthcare.

An innovative quality improvement approach for rapid improvement of infection prevention and control at health facilities in Sierra Leone.

Quality challengeThe Sierra Leone (SL) Ministry of Health and Sanitation’s National Infection Prevention and Control Unit (NIPCU) launched National Infection and Prevention Control (IPC) Policy and Guidelines in 2015, but a 2017 assessment found suboptimal compliance with standards on environmental cleanliness (EC), waste disposal (WD) and personal protective equipment (PPE) use.MethodsICAP at Columbia University (ICAP), NIPCU and the Centers for Disease Control and Prevention (CDC) designed and implemented a Rapid Improvement Model (RIM) quality improvement (QI) initiative with a compressed timeframe of 6 months to improve EC, WD and PPE at eight purposively selected health facilities (HFs). Targets were collaboratively developed, and a 37-item checklist was designed to monitor performance. HF teams received QI training and weekly coaching and convened monthly to review progress and exchange best practices. At the final learning session, a “harvest package” of the most effective ideas and tools was developed for use at additional HFs.ResultsThe RIM resulted in marked improvement in WD and EC performance and modest improvement in PPE. Aggregate compliance for the 37 indicators increased from 67 to 96% over the course of 4 months, with all HFs showing improvement. Average PPE compliance improved from 85 to 89%, WD from 63 to 99% and EC from 51 to 99%.Lessons learnedThe RIM QIC approach is feasible and effective in SL’s austere health system and led to marked improvement in IPC performance. The best practices are being scaled up and the RIM QIC methodology is being applied to other domains.

Deep learning for site safety: Real-time detection of personal protective equipment

The leading causes of construction fatalities include traumatic brain injuries (resulted from fall and electrocution) and collisions (resulted from struck by objects). As a preventive step, the U.S. Occupational Safety and Health Administration (OSHA) requires that contractors enforce and monitor appropriate usage of personal protective equipment (PPE) of workers (e.g., hard hat and vest) at all times. This paper presents three deep learning (DL) models built on You-Only-Look-Once (YOLO) architecture to verify PPE compliance of workers; i.e., if a worker is wearing hard hat, vest, or both, from image/video in real-time. In the first approach, the algorithm detects workers, hats, and vests and then, a machine learning model (e.g., neural network and decision tree) verifies if each detected worker is properly wearing hat or vest. In the second approach, the algorithm simultaneously detects individual workers and verifies PPE compliance with a single convolutional neural network (CNN) framework. In the third approach, the algorithm first detects only the workers in the input image which are then cropped and classified by CNN-based classifiers (i.e., VGG-16, ResNet-50, and Xception) according to the presence of PPE attire. All models are trained on an in-house image dataset that is created using crowd-sourcing and web-mining. The dataset, named Pictor-v3, contains ~1,500 annotated images and ~4,700 instances of workers wearing various combinations of PPE components. It is found that the second approach achieves the best performance, i.e., 72.3% mean average precision (mAP), in real-world settings, and can process 11 frames per second (FPS) on a laptop computer which makes it suitable for real-time detection, as well as a good candidate for running on light-weight mobile devices. The closest alternative in terms of performance (67.93% mAP) is the third approach where VGG-16, ResNet-50, and Xception classifiers are assembled in a Bayesian framework. However, the first approach is the fastest among all and can process 13 FPS with 63.1% mAP. The crowed-sourced Pictor-v3 dataset and all trained models are publicly available to support the design and testing of other innovative applications for monitoring safety compliance, and advancing future research in automation in construction.

Developing a Holistic-Comprehensive Assessment Model: Factors Contributing to Personal Protective Equipment Compliance among Indonesian Cement Workers.

Context:Noncompliance with personal protective equipment (PPE) in industrial workers results in increased injury or illness and is commonly reported worldwide. Numerous guidelines and management policies are employed to prevent work-related health hazards, yet industrial workers still exhibit low rates of PPE compliance, especially in outsourced workers.Aims:The aim of this study was to develop a holistic-comprehensive assessment framework model summarizing the key factors in achieving the stated goals of interventions targeting PPE compliance in Indonesian cement workers.Settings and Design:An analytic observational study was conducted among 183 Indonesian cement workers from a simple random sampling technique.Methods and Material:A self-designed questionnaire was used to investigate factors influencing PPE compliance among cement workers as well as management policies in place.Statistical Analysis Used:Statistical analysis was conducted using SPSS version 24. Results were tabulated using frequency distribution and mean with a standard deviation. The logistic regression model was developed to identify the factors that affect PPE compliance.Results:The highest rate of compliance was 43.7%, a still low figure. Using correlation coefficients and logistic regression, both the behavior of the workers and the existing management policies were found to be significant contributing factors (P < 0.05). Punitive management policies were also found to be a determining factor (OR 5.22; 95% CI 1.01–1.07).Conclusions:Management policy, specifical punishment for noncompliance, was shown to be the strongest influence on PPE compliance in Indonesian cement workers.

Image Detection Model for Construction Worker Safety Conditions using Faster R-CNN

Many accidents occur on construction sites leading to injury and death. According to the Occupational Safety Health Administration (OSHA), falls, electrocutions, being struck-by-objects and being caught in or between an object were the four main causes of worker deaths on construction sites. Many factors contribute to the increase in accidents, and personal protective equipment (PPE) is one of the defense mechanisms used to mitigate them. Thus, this paper presents an image detection model about workers’ safety conditions based on PPE compliance by using the Faster Region-based Convolutional Neural Networks (R-CNN) algorithm. This experiment was conducted using Tensorflow involving 1,129 images from the MIT Places Database (from Scene Recognition) as a training dataset, and 333 anonymous dataset images from real construction sites for evaluation purposes. The experimental results showed 276 of the images being detected as safe, and an average accuracy rate of 70%. The strength of this paper is based on the image detection of the three PPE combinations, involving hardhats, vests and boots in the case of construction workers. In future, the threshold and image sharpness (low resolution) will be two main characteristics of further refinement in order to improve the accuracy rate.

Adherence to personal protective equipment use among nurses in Japanese tertiary care hospitals: what determines variability?

Though nurses have frequent contact with patients, their personal protective equipment (PPE) compliance rate is low, which poses a significant challenge in infection control. To investigate the relative influence of specific factors on PPE compliance. A sequential two-stage mixed-methods design was applied. In a qualitative study, semi-structured interviews were conducted from May to July 2018. In a quantitative study, a nationwide, cross-sectional survey was conducted from January to March 2019, in which a questionnaire was mailed to 735 nurses in 28 tertiary care hospitals in Japan. In the quantitative study, 435 (59.2%) analysable responses were obtained. In the linear regression analysis, the lack of the knowledge that 'standard precaution was the fundamental infection countermeasure applied when patients had signs of infections, and these countermeasures could be terminated if there was no infection found' was significantly associated with decreased PPE adherence, whereas an antimicrobial-resistant bacteria outbreak or a ward shutdown due to an outbreak and the belief 'I must never be the cause of spreading infection' were significantly associated with increased PPE adherence. The β of standard coefficients and t-values of the items were -0.344, -7.784, 0.090, 2.089, 0.088, 2.018, respectively. This survey systematically identified nursing-associated factors that contribute to PPE compliance. As a practical approach to ensure positive outcomes, we suggest educating nurses by providing adequate knowledge on appropriate PPE use and sharing outbreak or ward shutdown experiences.

A qualitative study of factors affecting personal protective equipment use among health care personnel

Health care personnel (HCP) use of personal protective equipment (PPE) reduces infectious disease transmission. However, PPE compliance remains low. The objective of this study was to better understand how HCP perceptions factor into PPE decision making as well as how organizational processes and the environment impact behavior. This qualitative study used observation and focus groups at 2 medical centers. Data were analyzed using thematic analysis. The decision to use PPE and to follow precaution practices was influenced by risk perception as well as organizational and environmental factors. Perceived risk, related to certain organisms and work tasks, was considered by HCP when deciding to use PPE. Organizational processes, such as policies that were not applied uniformly, and environmental factors, such as clean versus contaminated space, also played a role in HCP PPE use. Because HCP seemed focused on organisms and work tasks, education on specific organisms and helping HCP think through their workflow may be more effective in conveying the importance of PPE in reducing transmission. Additionally, isolation practices should be compared across disciplines to ensure they complement, rather than contradict, one another. Assessment of the environment may help protect HCP and patients from infectious organisms. Preventing the spread of infectious organisms should not depend solely on PPE use, but should also be recognized as an organizational responsibility.