Trends in infection-related patient safety incident reporting before and during the COVID-19 pandemic in Korea.

Purpose: The purpose of this study was to analyze the trends and characteristics of infection-related patient safety incident reporting before and during the coronavirus disease 2019 (COVID-19) pandemic in Korea, and to provide basic data for preventing infection-related patient safety incidents and improving their management. Methods: A cross-sectional analysis of secondary national data (Patient Safety Reporting Data) was conducted. In total, 517 infection-related patient safety incidents reported from 2018 to 2021 were analyzed. Changes in the number of reports before and during the COVID-19 pandemic and differences in variables related to infection-related patient safety incidents were analyzed using the chi-square test and independent t-test in SPSS 29.0. Results: This study found that infection-related patient safety incidents decreased during the COVID-19 pandemic compared to before the pandemic. Furthermore, incident-related characteristics, such as the type of healthcare organization, severity of harm, and post-incident actions, changed during the COVID-19 pandemic. Conclusion: The many changes in the infection control system and practices during the COVID-19 pandemic may have contributed to a decrease in the reporting of infection-related patient safety incidents. It is hoped that longitudinal studies on patient safety incidents related to the pandemic and analytical studies on factors influencing patient safety incidents will continue to be conducted to prevent and improve patient safety incidents. [ FROM AUTHOR] Copyright of Journal of Korean Biological Nursing Science is the property of Korean Society of Biological Nursing Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Telemedicine in the Era of Covid-19: Teleconsultation Architecture Platform

Teleconsultation is a type of medical practice similar to face-to-face consultations, and it allows a health professional to give a consultation remotely through information and communication technologies. In the context of the management of the coronavirus epidemic, the use of teleconsultation practices can facilitate healthcare access and limit the risk of avoidable propagation in medical cabinets. This paper presents the monitoring of international teleconsultation referrals in the era of Covid-19 to facilitate and prevent the suspension of access to care, the most common architecture for teleconsultation, communication technologies and protocols, vital body signals, video transmission, and the conduct of teleconsultation. The aim is to develop a teleconsultation platform to diagnose the patient in real time, transmit data from the remote location to the doctor, and provide a teleconsultation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

The smart city and COVID-19

Smart cities are concepts much loved by politicians and technologists but are very difficult to bring about in practice. There are many isolated applications in cities such as operating streetlamps, but very few, if any, examples of integrated applications sharing data and managing the city as a holistic entity rather than a set of disparate and unconnected applications. This is despite hundreds of trials and indicates how difficult bringing about a smart city will be. The key challenge is the wide range of interested parties in a city including the elected city authority, subcontractors and suppliers to the authority, emergency services, transport providers, businesses, residents, workers, tourists, and other visitors. Some of these entities will be primarily driven by finance, such as businesses and transport providers. Some will be driven by political considerations. Some will be concerned with the quality of life as well as financial costs. In some cases, there will be conflicting interests-the city may want as much information as possible on people in the city, whereas individuals may want privacy and the minimum data stored concerning their movements and attributes. COVID-19 does not change any of these issues, but it does increase the importance of some applications such as smart health, logistics, people surveillance, data security, and crisis management, while reducing the importance of others such as traffic management. It may result in more willingness for monitoring and data sharing if this can be shown to result in better control of the virus. © 2023 the authors.

Billing basics and fundamentals

Prior to the public health emergency (PHE), there were efforts to advance telemedicine. The hurdles posed by reimbursement were one of the elements limiting its expansion. Billing rules varied pre PHE between private and governmental payers. The major billing changes during PHE sustained the health care system and provided access to care. Anticipated changes in billing post PHE will determine the future of telehealth. The aim of the chapter is to provide an overview of fundamentals of telehealth billing. First, we will focus on providing a basic understanding of all key stake holder payers, and the telehealth billing code system. Subsequently, we will outline telehealth services and coverage prior to and during the PHE. Finally, we attempt to review a sample of the current bills introduced to congress, shaping the future post PHE. © 2023 Elsevier Inc. All rights reserved.

Recent Trends in Remote Healthcare Applications and Futuristic Approach

Remote healthcare is a well-accepted telemedicine service that renders efficient and reliable healthcare to patients suffering from chronic diseases, neurological disorders, diabetes, osteoporosis, sensory organs, and other ailments. Artificial intelligence, wireless communication, sensors, organic polymers, and wearables enable affordable, non-invasive healthcare to patients in all age groups. Telehealth services and telemedicine are beneficial to people residing in remote locations or patients with limited mobility, rehabilitation treatment, and post-operative recovery. Remote healthcare applications and services proved to be significant during the COVID-19 pandemic for both patients and doctors. This study presents a detailed study of the use of artificial intelligence and the internet of things in applications of remote healthcare in many domains of health, along with recent patents. This research also presents network diagrams of documents from the Scopus database using the tool VOSViewer. The paper highlights gap which can be undertaken by future researchers. © 2023 IEEE.

Social Distance and Face Mask Detection using vision-based sensors and IP cameras

Healthcare systems all over the world are strained as the COVID-19 pandemic's spread becomes more widespread. The only realistic strategy to avoid asymptomatic transmission is to monitor social distance, as there are no viable medical therapies or vaccinations for it. A unique computer vision-based framework that uses deep learning is to analyze the images that are needed to measure social distance. This technique uses the key point regressor to identify the important feature points utilizing the Visual Geometry Group (VGG19) which is a standard Convolutional Neural Network (CNN) architecture having multiple layers, MobileNetV2 which is a computer vision network that advances the-state-of-art for mobile visual identification, including semantic segmentation, classification and object identification. VGG19 and MobileNetV2 were trained on the Kaggle dataset. The border boxes for the item may be seen as well as the crowd is sizeable, and red identified faces are then analyzed by MobileNetV2 to detect whether the person is wearing a mask or not. The distance between the observed people has been calculated using the Euclidian distance. Pretrained models like (You only look once) YOLOV3 which is a real-time object detection system, RCNN, and Resnet50 are used in our embedded vision system environment to identify social distance on images. The framework YOLOV3 performs an overall accuracy of 95% using transfer learning technique runs in 22ms which is four times fast than other predefined models. In the proposed model we achieved an accuracy of 96.67% using VGG19 and 98.38% using MobileNetV2, this beats all other models in its ability to estimate social distance and face mask. © 2023 IEEE.

The impact of the COVID-19 pandemic on the healthcare of patients with type 2 diabetes mellitus in the department of veterans affairs

The novel coronavirus (COVID-19) pandemic and strategies meant to mitigate infections caused disruptions to healthcare services across the globe. To evaluate the impact of the COVID-19 pandemic on the healthcare of patients with type 2 diabetes in the VA healthcare system, this work enumerated a cohort of patients with type 2 diabetes who utilized care in the VA across all months between March 2018 and February 2022 and analyzed service utilization, medication adherence, and diabetes-related short-term outcomes.The first objective was to determine the effect of the pandemic's interruption on the utilization of diabetes-related outpatient encounters. Results showed that the share of patients with diabetes with at least one virtual care visit increased from 3.4% in the pre- COVID year (March 2019 to February 2020) to 16.4% in the first year during COVID (March 2020 to February 2021) while the percent of patients with diabetes with an in- person diabetes-related outpatient visit fell from 89.8% to 72.3%.Second, large changes in oral antidiabetic medication use, adherence (i.e., proportion of days (PDC) covered >=80%), and discontinuation (zero days covered) were discovered during the pandemic among patients with treated type 2 diabetes. The mean percent adherent was 23.4%, 11.6%, and 30.1% during the pre-pandemic (i.e., March 2018-February 2020), pre-vaccine pandemic (i.e., March 2020-December 2020), and post-vaccine pandemic (i.e., January 2021-February 2020) periods, respectively.Finally, this study evaluated changes in average A1C measurement, glycemic control, and preventable diabetes outcomes before and during the COVID-19 pandemic. The percent of eligible patients with A1C measurement decreased by 8.6% when the pandemic began, trending back to pre-pandemic levels by January 2021, at which point it fell by about 1% per month to end of study. The rate of uncontrolled diabetes averaged 400 per 100,000 before the pandemic, but rose to almost 550 per 100,000 patients during the pandemic. Likewise, the rate of short-term complications averaged 30 per 100,000, but rose to 49 per 100,000 at its high during the pandemic.The pandemic's interruptions caused vast differences in the healthcare routines of patients with diabetes, which initially led to more negative outcomes than before the pandemic. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Smart Healthcare: Future Applications & Challenges

After the outbreak of corona virus, all counties are paying special attention to their healthcare infrastructure. During second phase of covid-19, entire world has seen health care crisis. Large number of people died globally. Entire world was affected mentally or physically. There is a great need to strengthen the healthcare infrastructure, to vaccinate the population against covid virus infection and to take proper precaution to avoid spread of the virus, so that the world will not see such deadly days again. This paper discusses how technologies like Internet of Things (IoT), Artificial Intelligence (AI), Drones etc can help in remote monitoring of patients, judicious hospital admission, conscious distribution of lifesaving drugs etc. Investment in technology with not only help in the reduction of spread of the virus but will also help in fighting with all other future pandemics. All the countries must have to invest more on latest technologies in their healthcare to make themselves ready for such future pandemics. When the things will improve, the new normal will be very much different from the life that was before pandemic. IoT, AI and other technologies will become the non-separatable part of our life. © 2023 Bharati Vidyapeeth, New Delhi.

Automatic Detection of Lung Ultrasound Artifacts using a Deep Neural Networks approach

The COVID-19 pandemic has challenged many of the healthcare systems around the world. Many patients who have been hospitalized due to this disease develop lung damage. In low and middle-income countries, people living in rural and remote areas have very limited access to adequate health care. Ultrasound is a safe, portable and accessible alternative;however, it has limitations such as being operator-dependent and requiring a trained professional. The use of lung ultrasound volume sweep imaging is a potential solution for this lack of physicians. In order to support this protocol, image processing together with machine learning is a potential methodology for an automatic lung damage screening system. In this paper we present an automatic detection of lung ultrasound artifacts using a Deep Neural Network, identifying clinical relevant artifacts such as pleural and A-lines contained in the ultrasound examination taken as part of the clinical screening in patients with suspected lung damage. The model achieved encouraging preliminary results such as sensitivity of 94%, specificity of 81%, and accuracy of 89% to identify the presence of A-lines. Finally, the present study could result in an alternative solution for an operator-independent lung damage screening in rural areas, leading to the integration of AI-based technology as a complementary tool for healthcare professionals. © 2023 SPIE.

The quality of medical care in a round-the-clock hospital during the COVID-19 pandemic

Violations in the provision of medical care are detected by controlling the volume, timing, quality and conditions of medical care. The objective of the work is assessment of the activities of the round-the-clock hospital from the standpoint of the quality of medical care during the COVID-19 pandemic. Material and methods. A database of indicators reflecting the activity of round-the-clock hospital for four years, from 2017 to 2020 (Omsk) was formed. Analytical, statistical methods and the method of expert assessments were used to analyze the required indicators. Results. Evaluation of inpatient hospital activities during the COVID-19 pandemic compared to the "pre-pandemic” years showed a 1.9-fold and 2.9-fold decrease in the total number of quality examinations performed and the number of defects detected, respectively. The number of defects that were grounds for denial or reduction of payment for medical care found in the "before-COVID-19” years was 2.1 times higher than in 2020. In 2020, the weight of the share of those defects that directly reflect the quality of medical care increased significantly. The quantitative composition of the inpatient hospital staff changed insignificantly during the analyzed period – the number of physicians increased by only 5% over four years, with no dynamics in the qualitative characteristics of the staff. The number of medical equipment increased by 27.6%. Due to re-profiling in 2020, there was a decrease in the number of hospitalized patients, with an increase in the proportion of patients admitted by emergency care (up to 91%) and an increase in mortality by 2.7 times. Conclusions. One of the conditions for maintaining high quality of medical care is a balance between the main components of quality: accessibility, timeliness, sufficiency, efficiency and safety and the speed of its achievement, which in turn depends on the amount of resources and reserves. © 2023, Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences. All rights reserved.

Emotional risk work during the pandemic: Healthcare professionals' perceptions from a COVID-19 ward

In March 2020, COVID-19 wards were established in hospitals in Denmark. Healthcare professionals from a variety of specialities and wards were transferred to these new wards to care for patients admitted with severe COVID-19 infections. Based on ethnographic fieldwork in a COVID-19 ward at a hospital in Copenhagen, Denmark, including focus group interviews with nursing staff, we intended to explore practices in a COVID-19 ward by seeking insight into the relation between the work carried out and the professionals' ways of talking about it. We used a performative approach of studying how the institutional ways of handling pandemic risk work comes into being and relates to the health professionals' emerging responses. The empirical analysis pointed at emotional responses by the nursing staff providing COVID-19 care as central. To explore these emotional responses we draw on the work of Mary Douglas and Deborah Lupton's concept of the ‘emotion-risk-assemblage'. Our analysis provides insight into how emotions are contextually produced and linked to institutional risk understandings. We show that work in the COVID-19 ward was based on an institutional order that was disrupted during the pandemic, producing significant emotions of insecurity. Although these emotions are structurally produced, they are simultaneously internalised as feelings of incompetence and shame.

Modelling COVID-19 effect on the performance of MENA Health-care sector

PurposeThis study models the effects of the COVID-19 pandemic on the performance of the private health-care sector in the Middle East and North Africa (MENA) countries. This paper aims to address the economic, societal and sustainability of the health-care sector.Design/methodology/approachData were collected from Bloomberg and the sample consists of 534 firm-year observations from 55 firms listed over 2010–2020. The authors apply panel data and control for the country and governance effects.FindingsThe authors found heterogeneous results regarding the three sub-sectors. The pandemic has a negative effect on the accounting and market performances of the "Pharmaceutical companies” and an insignificant impact on "Healthcare Management and Facilities Services.” Moreover, the impact of COVID-19 on health-care firms' performance depends on the country's economic classification and the degree of regulatory and governance frameworks.Research limitations/implicationsFurther studies may consider a larger sample and other regions. It is recommended to address the health-care sector's challenges to invest in new technologies such as "digital twin” and predictive and personalized medicine. It is worth testing model development theory and its effects on speeding up and designing models to ensure the proper functioning and developing mathematics to determine uncertainties in patient data and model predictions.Originality/valueTo the best of the authors' knowledge, this paper is novel as it is unique in modeling the impact of COVID-19 on the health-care public companies in the MENA region. The findings pinpoint firms' and countries' heterogeneous impacts on financial and market performances.

Health Tourism Prevalence among Western Balkans Citizens During the COVID-19 Pandemic Period

Background: This study seeks to evaluate the prevalence of and the association between receiving medical care abroad and the level of trust that citizens from the Western Balkans-Albania, Bosnia and Herzegovina, Kosovo and Montenegro-have in their healthcare systems. Method(s): The study is cross-sectional and was carried out during three months (July 25-October 30, 2021) through a self-reported questionnaire administered through the Google Forms platform. The study included approximately two-thousand citizens (N=2,356) aged eighteen (18) to seventy (70). Result(s): More than one-third (37.2%) of respondents stated that they or a relative had received healthcare services abroad during the last twelve (12) months. Citizens of Montenegro had the highest prevalence of receiving healthcare services abroad at 43.8%, followed by those from Bosnia and Herzegovina at 39%. No statistically significant difference was found in the level of trust in the healthcare system in the country between those who received healthcare services abroad (4.41+/-2.88) (out of 10) and those who did not (4.48+/-2.81) (t=-0.587, p=0.557). Conclusion(s): We ultimately conclude that more than one-third of the participants in our study have traveled abroad for healthcare purposes, with females, those living in urban areas, and those who have previously had a negative healthcare experience in their home country all being more likely to rely on health tourism.Copyright © 2023 Maljichi et al.

Applying Machine Learning and Model-Driven Approach for the Identification and Diagnosis of Covid-19

Ubiquitous environments are not fixed in time. Entities are constantly evolving;they are dynamic. Ubiquitous applications therefore have a strong need to adapt during their execution and react to the context changes, and developing ubiquitous applications is still complex. The use of the separation of needs and model-driven engineering present the promising solutions adopted in this approach to resolve this complexity. The authors thought that the best way to improve efficiency was to make these models intelligent. That's why they decided to propose an architecture combining machine learning with the domain of modeling. In this article, a novel tool is proposed for the design of ubiquitous applications, associated with a graphical modeling editor with a drag-drop palette, which will allow to instantiate in a graphical way in order to obtain platform independent model, which will be transformed into platform specific model using Acceleo language. The validity of the proposed framework has been demonstrated via a case study of COVID-19. © 2023 IGI Global. All rights reserved.

Effect of COVID-19 pandemic on sleep quality of frontline healthcare workers

Background: The 2019 coronavirus disease (COVID-19) outbreak, which was brought on by the SARS-CoV-2 novel coronavirus, has had a significant negative influence on our environment and exposed health-care personnel to a new level of risk. Very few studies have addressed the disturbances in the sleep quality of healthcare workers during COVID-19 pandemic. Aim and Objectives: The primary objective of the study was to examine the sleep quality of frontline healthcare workers during COVID-19 pandemic in a tertiary care center in northern Kerala. Material(s) and Method(s): Healthcare workers belonging to a tertiary care center were invited to participate in the study. An online questionnaire including sociodemographics, Pittsburgh sleep quality index, and Insomnia severity index was used to evaluate sleep disturbances in healthcare workers. Univariate and bivariate analysis of the results were done to identify the predictors of poor sleep quality. Result(s): A total of 250 frontline healthcare workers were enrolled in the study, out of which 243 participants provided usable responses. About 27.6% of health workers showed features of poor sleep quality. The prevalence rate of poor sleep quality was highest among nurses, 55.2% followed by doctors and ambulance drivers, 22.4% and 11.9%, respectively. About 17.7% of the study population had subthreshold insomnia and 1.2% had clinical insomnia of moderate intensity. Conclusion(s): The prevalence of poor sleep quality is high among healthcare workers confronting COVID pandemic. This study emphasizes the need to implement specific protective measures for maintaining the sleep quality and decreasing stress among frontline health care workers during pandemics.Copyright © 2023, Mr Bhawani Singh. All rights reserved.

IoT Coupled Healthcare Systems: A Bibliometric Analysis

The adoption of the Internet of Things (IoT) has revolutionized the way the health care industry works. IoT en-abled smart and connected solutions like smart sensors, wearable devices, and smart health monitoring systems are used to unleash the potential growth of the health care industry. IoT based health care solutions are on greater priority among IoT service providers since the disruptions caused by the COVID-19. According to experts, there still exist white spots in research studies on the Internet of Things (IoT) and health care Systems. The study conducted in this paper aims to explore emerging global research trends and topical focus in the field of IoT in health care System. Bibliometric analysis is used to analyze the research articles on 'Internet of Things' and 'Health care Systems' extracted from SCOPUS and WoS database using VoS Viewer tool;the analysis used to assess the growth and research trends of different research fields over a period of time. The parameters considered during analysis include year-wise citations, year-wise publications, keyword clustering analysis, author-wise analysis, country-wise research trends and publication trend over the years. The results showcased that there has been significant change in utilization of IoT in healthcare systems continuously during the period under study conducted. © 2022 IEEE.

Impact of Biomedical Engineering on Human & social Dynamics: A Review on Recent Approaches Through Bioengineering from Recent Past to Post-Covid-19

INTRODUCTION: The paper aims to discuss the various issues/ problems that people face in day to day life. Using diverse scenarios ranging from mental health issues to common grafting procedures, the author here strives to link these issues to bioengineering and how they are being impacted by modern technology. Most methods and procedures discussed attempt to utilize day-to-day activities and ease of access. The paper has adopted rapid review method. For literature collection, Google scholar database has been used with a scope of specific keywords and time frame of 5 weeks to complete the study © COPYRIGHT RED FLOWER PUBLICATIONS PVT LTD

Regional Survey of HealthWorkers' Opinions on the COVID-19 Pandemic

The emergence, spread, and development of COVID-19 has become a serious challenge and a test of the professional, organizational, and technological capabilities of the global medical community. The specific nature of the profession puts health workers at the forefront of responding to a COVID-19 outbreak and exposes them to a particularly high risk of infection. Hazards include contact with the pathogen, long work hours, psychological distress, fatigue, occupational burnout, and several others. Simultaneously, as members of society, health workers are also exposed to the general risks and influences of a difficult epidemiological situation (e.g., anxiety from uncertainty, lack of information, and general social and economic problems and constraints). As professionals, health workers must demonstrate the unity of opinion, attitude, and action and act as experts for patients on various issues, implementing the state's health care policy. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Preheal: Forming a Start-up Team Post-COVID-19

The Indian government had been making efforts to foster an innovative business culture by incorporating design thinking and innovation in b-school curricula. Substantial investments had also helped aspiring entrepreneurs pursue their ambitions. One such beneficiary of these initiatives was Preheal Innovations Private Limited, which aimed to build an online platform catering to the healthcare, beauty, and wellness needs of customers throughout India. Mr. Vikrant, founder and CEO of Preheal, had built a robust network of contacts in the healthcare sector after 20 years of experience and this, combined with the company's unique business model catering to customers in both urban (tier-2 and tier-3 cities) and rural areas in India, played a key role in attracting the initial start-up team. However, efforts were interrupted due to COVID-19, which lead to the departure of team members. Post lockdown, Mr. Vikrant had to decide how to relaunch the new venture with either full or partial staffing, in a changed business environment. © 2022 NeilsonJournals Publishing.

COMPARATIVE ANALYSIS OF THE FEATURES OF ORGANIZING MEASURES TO COMBAT THE COVID-19 PANDEMIC IN THE HEALTH SYSTEMS OF THE RUSSIAN FEDERATION AND FOREIGN COUNTRIES

The study analyzed available literatures covering the organization of measures to combat the COVID-19 pandemic in the healthcare systems of the Russian Federation and several foreign countries. For the comprehensive assessment of the specifics of organizing measures to combat the COVID-19 pandemic, countries were chosen based on geographical distances from China (the closest is Korea, and the most remote are the Great Britain and Haiti), maximum population on their continent (the United States is in North America, and Brazil in South America), and significant differences in the functioning of the healthcare systems. The peculiarities of organizing measures to combat the COVID-19 pandemic in the considered countries were associated with a complex of political, financial, economic, demographic, and organizational factors, the individual combination of which determined the peculiarities of the development of the epidemic process in each specific case. Moreover, as a priority manifestation of the severity of these factors, the capabilities of the healthcare system, including the availability of services of medical workers, sufficient number of testing equipment, medical protection equipment, hospital beds, and other parameters, should be considered. The main role was played by global state strategies implemented in the healthcare systems of the analyzed countries at the pre-epidemic stage and, in most cases, aimed at optimizing the financial and economic provisions of state guarantees of medical care. The general criteria for the differential diagnosis of COVID-19 in the national recommendations of all the states considered were respiratory symptoms and general infectious intoxication. In addition, fever and respiratory symptoms were accepted as priority criteria for COVID-19 screening. © 2023 Vestnik Rossijskoj Voenno-Medicinskoj Akademii. All rights reserved.