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Background The dissemination of scientific data on coronavirus disease 2019 (COVID-19) continually builds but, in April 2020, could not keep up with the spread of the disease. Through technology, surgeons in Italy and the UK, representing both peak and pre-peak infective time zones, were able to communicate so that the urgent lessons on the huge expected demands of care learned in Italy could be brought to the UK in advance. This paper specifically discusses the issues related to paediatric surgery, currently under-reported in the literature. Methods The aim of this paper is to conjoin experience from the field to provide a framework for a safe assessment and treatment of paediatric patients by adopting a systemic approach aimed at reducing the risk of contamination. We reviewed the processes and good practices that were undertaken in contexts of emergency such as in Italy and the UK and then adapted them within the Systems Engineering Initiative for Patient Safety (SEIPS) framework to provide an assessment of how to reorganize the services in order to cope with an unexpected situation. The SEIPS model is the adopted theoretical framework, which allows to analyse the system in its main components with a human factors and ergonomics (HFE) perspective. Results The results introduce some of the good practices and recommendations developed during the emergency in the surgical scenario with a focus on the paediatric patients. They represent the lessons learned from the combination of the little existing evidence of literature and the experience from surgical teams who responded in an impromptu and unrehearsed way. Conclusions Lessons learned from the frontline 'on the fly' during COVID-19 emergency should be consolidated and taken into the future. In order to prepare proactively for the next phases and get ahead of the curve of these hospital accesses, there is a need for a risk assessment of the new clinical pathways with a multidisciplinary approach centred on HFE with the adoption of the SEIPS model and an involvement of all the surgical teams. [ABSTRACT FROM AUTHOR]

The importance of clinical supervision, a professional support and clinical governance mechanism, to patients, healthcare workers and organizations has been well documented. Clinical supervision has been shown to support healthcare workers during challenging times, by reducing burnout, enhancing mental health and wellbeing at work, and improving job satisfaction. However, clinical supervision participation and effectiveness are pre-requisites for realising these benefits. During times of stress and increased workloads (e.g. during the Coronavirus pandemic), healthcare workers tend to prioritise clinical duties and responsibilities over clinical supervision. Effective supervision practices can be restored, and healthcare workers can be better supported in their roles during and in the post-pandemic period only if healthcare workers, policy makers, healthcare organizations, clinical supervision trainers and researchers join forces. This paper sheds light on this important topic and offers a number of practical recommendations to reboot effective clinical supervision practices at the point of care. [ABSTRACT FROM AUTHOR]

Background While individual countries have gained considerable knowledge and experience in coronavirus disease of 2019 (COVID-19) management, an international, comparative perspective is lacking, particularly regarding the measures taken by different countries to tackle the pandemic. This paper elicits the views of health system staff, tapping into their personal expertise on how the pandemic was initially handled. Methods From May to July 2020, we conducted a cross-sectional, online, purpose-designed survey comprising 70 items. Email lists of contacts provided by the International Society for Quality in Health Care, the Italian Network for Safety in Health Care and the Australian Institute of Health Innovation were used to access healthcare professionals and managers across the world. We snowballed the survey to individuals and groups connected to these organizations. Key outcome measures were attitudes and information about institutional approaches taken; media communication; how acute hospitals were re-organized; primary health organization; personal protective equipment; and staffing and training. Results A total of 1131 survey participants from 97 countries across the World Health Organization (WHO) regions responded to the survey. Responses were from all six WHO regions; 57.9% were female and the majority had 10 or more years of experience in healthcare; almost half (46.5%) were physicians; and all other major clinical professional groups participated. As the pandemic progressed, most countries established an emergency task force, developed communication channels to citizens, organized health services to cope and put in place appropriate measures (e.g. pathways for COVID-19 patients, and testing, screening and tracing procedures). Some countries did this better than others. We found several significant differences between the WHO regions in how they are tackling the pandemic. For instance, while overall most respondents (71.4%) believed that there was an effective plan prior to the outbreak, this was only the case for 31.9% of respondents from the Pan American Health Organization compared with 90.7% of respondents from the South-East Asia Region (SEARO). Issues with swab testing (e.g. delay in communicating the swab outcome) were less frequently reported by respondents from SEARO and the Western Pacific Region compared with other regions. Conclusion The world has progressed in its knowledge and sophistication in tackling the pandemic after early and often substantial obstacles were encountered. Most WHO regions have or are in the process of responding well, although some countries have not yet instituted widespread measures known to support mitigation, for example, effective swab testing and social control measures. [ABSTRACT FROM AUTHOR]

Objective As the globe endures the coronavirus disease 2019 (COVID-19) pandemic, we developed a hybrid Shewhart chart to visualize and learn from day-to-day variation in a variety of epidemic measures over time. Context Countries and localities have reported daily data representing the progression of COVID-19 conditions and measures, with trajectories mapping along the classic epidemiological curve. Settings have experienced different patterns over time within the epidemic: pre-exponential growth, exponential growth, plateau or descent and/ or low counts after descent. Decision-makers need a reliable method for rapidly detecting transitions in epidemic measures, informing curtailment strategies and learning from actions taken. Methods We designed a hybrid Shewhart chart describing four 'epochs' ((i) pre-exponential growth, (ii) exponential growth, (iii) plateau or descent and (iv) stability after descent) of the COVID-19 epidemic that emerged by incorporating a C -chart and I -chart with a log-regression slope. We developed and tested the hybrid chart using international data at the country, regional and local levels with measures including cases, hospitalizations and deaths with guidance from local subject-matter experts. Results The hybrid chart effectively and rapidly signaled the occurrence of each of the four epochs. In the UK, a signal that COVID-19 deaths moved into exponential growth occurred on 17 September, 44 days prior to the announcement of a large-scale lockdown. In California, USA, signals detecting increases in COVID-19 cases at the county level were detected in December 2020 prior to statewide stay-at-home orders, with declines detected in the weeks following. In Ireland, in December 2020, the hybrid chart detected increases in COVID-19 cases, followed by hospitalizations, intensive care unit admissions and deaths. Following national restrictions in late December, a similar sequence of reductions in the measures was detected in January and February 2021. Conclusions The Shewhart hybrid chart is a valuable tool for rapidly generating learning from data in close to real time. When used by subject-matter experts, the chart can guide actionable policy and local decision-making earlier than when action is likely to be taken without it. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has required health systems to change much faster than normal. Many staff have experienced training in quality improvement and patient safety methods which can be used to support the design of new systems and to accelerate learning about new and adapted practices. This article sets out the principles of quality improvement and patient safety science, applying them in a selection of approaches, methods and tools, which may be useful in crisis situations such as the current pandemic. The article also makes reference to several resources which may be of use to those keen to advance their knowledge. [ABSTRACT FROM AUTHOR]

A human factors and ergonomics (HFE) systems approach offers a model for adjusting work systems and care processes in response to a healthcare crisis such as COVID-19. Using the Systems Engineering Initiative for Patient Safety (SEIPS) model of work system and patient safety, we describe various work system barriers and facilitators experienced by healthcare workers during the COVID-19 crisis. We propose a set of five principles based on this HFE systems approach related to novel pandemic: (i) deferring to local expertise, (ii) facilitating adaptive behaviors, (iii) enhancing interactions between system elements and levels along the patient journey, (iv) re-purposing existing processes and (v) encouraging dynamic continuous learning. [ABSTRACT FROM AUTHOR]

The challenges for health care continue to grow and in the 21st century healthcare policymakers and providers will need to respond to the developing impact of global warming and the environmental impact of healthcare service delivery. This cannot be viewed apart from the current Coronavirus disease (COVID-19) pandemic, which is likely to be linked to the climate crisis. [ABSTRACT FROM AUTHOR]

Epidemiologists frequently adopt statistical process control tools, like control charts, to detect changes in the incidence or prevalence of a specific disease in real time, thereby protecting against outbreaks and emergent health concerns. Control charts have proven essential in instantly identifying fluctuations in infection rates, spotting emerging patterns, and enabling timely reaction measures in the context of COVID-19 monitoring. This study aims to review and select an optimal control chart in epidemiology to monitor variations in COVID-19 deaths and understand pandemic mortality patterns. An essential aspect of the present study is selecting an appropriate monitoring technique for distinct deaths in the USA in seven phases, including pre-growth, growth, and post-growth phases. Stage-1 evaluated control chart applications in epidemiology departments of 12 countries between 2000 and 2022. The study assessed various control charts and identified the optimal one based on maximum shift detection using sample data. This study considered at Shewhart (⁠|$\bar X$|⁠ , |$R$|⁠ , |$C$|⁠) control charts and exponentially weighted moving average (EWMA) control chart with smoothing parameters λ  = 0.25, 0.5, 0.75, and 1 were all investigated in this study. In Stage-2, we applied the EWMA control chart for monitoring because of its outstanding shift detection capabilities and compatibility with the present data. Daily deaths have been monitored from March 2020 to February 2023. Control charts in epidemiology show growing use, with the USA leading at 42% applications among top countries. During the application on COVID-19 deaths, the EWMA chart accurately depicted mortality dynamics from March 2020 to February 2022, indicating six distinct stages of death. The third and fifth waves were extremely catastrophic, resulting in a considerable loss of life. Significantly, a persistent sixth wave appeared from March 2022 to February 2023. The EWMA map effectively determined the peaks associated with each wave by thoroughly examining the time and amount of deaths, providing vital insights into the pandemic's progression. The severity of each wave was measured by the average number of deaths |$W5(1899)\,\gt\,W3(1881)\,\gt\,W4(1393)\,\gt\,W1(1036)\,\gt\,W2(853)\,\gt\,(W6(473)$|⁠. The USA entered a seventh phase (6th wave) from March 2022 to February 2023, marked by fewer deaths. While reassuring, it remains crucial to maintain vaccinations and pandemic control measures. Control charts enable early detection of daily COVID-19 deaths, providing a systematic strategy for government and medical staff. Incorporating the EWMA chart for monitoring immunizations, cases, and deaths is recommended. [ABSTRACT FROM AUTHOR]

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, health services for breast cancer (BC) have been disrupted. Our scoping review examines the impact of the COVID-19 pandemic on BC services, health outcomes, and well-being for women. Additionally, this review identifies social inequalities specific to BC during the pandemic. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews guidelines, the literature search was conducted using scientific databases starting from March 2020 through November 2021. Studies were identified and selected by two researchers based on inclusion criteria, and the relevant data were extracted and charted to summarize the findings. Ninety-three articles were included in this review. Main themes included are as follows: (i) the impact of COVID-19 on BC services; (ii) the impact of COVID-19 on health outcomes and well-being in women with BC; and (iii) any variation in the impact of COVID-19 on BC by social determinants of health. There were apparent disruptions to BC services across the cancer continuum, especially screening services. Clinical repercussions were a result of such disruptions, and women with BC experienced worsened quality of life and psychosocial well-being. Finally, there were social inequalities dependent on social determinants of health such as age, race, insurance status, and region. Due to the disruption of BC services during the COVID-19 pandemic, women were impacted on their health and overall well-being. The variation in impact demonstrates how health inequities have been exacerbated during the pandemic. This comprehensive review will inform timely health-care changes to minimize long-term impacts of the pandemic and improve evidence-based multidisciplinary needs. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has led to huge pressure on not only healthcare systems, but also on healthcare professionals. As the pandemic continues, the aim of this study is to evaluate how 10 reactions of healthcare professionals evolved during the first 18 months of COVID-19.Methods: : A repeated cross-sectional study was performed with eight measurement points between April 2020 and September 2021 in Belgium. Participants were asked how frequently (on a scale of 0 to 10) they experienced positive and negative reactions during normal circumstances and during past week, referred to as before and during COVID-19, respectively. These reactions were stress, fatigue, difficulty sleeping, muscle strain, hypervigilance, leaving profession, headache, doubting knowledge and skills, flashbacks and fear.Results: : In total 13 308 respondents were included in our study. During both the first (March 2020) and second COVID-19 peak (November 2020), the measured personal, professional and physical reactions were significantly higher compared to before COVID-19. The third wave in April 2021 was shorter and less severe with regard to hospital admissions and deaths, yet an important impact on healthcare professionals could still be observed. 'Fatigue', 'stress', 'difficulty sleeping' and 'muscle strain' are the most worrying reactions in September 2021, which are increasing compared to the previous measurements.Conclusion: : Our results showed that acute stress reactions decreased over time but that chronic stress reactions and professional reactions such as 'intent to leave', increased. Healthcare organizations and policy makers should realize that 18 months after the start of COVID-19 almost all of the measured reactions continue to be more prevalent than before COVID-19. Moreover, the continuous increase over the last three measurement periods of the number of healthcare professionals who want to leave their profession is alarming. Continuous follow-up of the personal, professional and physical reactions is more than necessary. [ABSTRACT FROM AUTHOR]

Background Managing high levels of acute COVID-19 bed occupancy can affect the quality of care provided to both affected patients and those requiring other hospital services. Mass vaccination has offered a route to reduce societal restrictions while protecting hospitals from being overwhelmed. Yet, early in the mass vaccination effort, the possible impact on future bed pressures remained subject to considerable uncertainty. Objective The aim of this study was to model the effect of vaccination on projections of acute and intensive care bed demand within a 1 million resident healthcare system located in South West England. Methods An age-structured epidemiological model of the susceptible–exposed–infectious–recovered type was fitted to local data up to the time of the study, in early March 2021. Model parameters and vaccination scenarios were calibrated through a system-wide multidisciplinary working group, comprising public health intelligence specialists, healthcare planners, epidemiologists and academics. Scenarios assumed incremental relaxations to societal restrictions according to the envisaged UK Government timeline, with all restrictions to be removed by 21 June 2021. Results Achieving 95% vaccine uptake in adults by 31 July 2021 would not avert the third wave in autumn 2021 but would produce a median peak bed requirement ∼6% (IQR: 1–24%) of that experienced during the second wave (January 2021). A 2-month delay in vaccine rollout would lead to significantly higher peak bed occupancy, at 66% (11–146%) of that of the second wave. If only 75% uptake was achieved (the amount typically associated with vaccination campaigns), then the second wave peak for acute and intensive care beds would be exceeded by 4% and 19%, respectively, an amount which would seriously pressure hospital capacity. Conclusion Modelling influenced decision-making among senior managers in setting COVID-19 bed capacity levels, as well as highlighting the importance of public health in promoting high vaccine uptake among the population. Forecast accuracy has since been supported by actual data collected following the analysis, with observed peak bed occupancy falling comfortably within the inter-quartile range of modelled projections. [ABSTRACT FROM AUTHOR]

Background: During the COVID-19 pandemic, low- and middle-income countries have rapidly scaled up intensive care unit (ICU) capacities. Doing this without monitoring the quality of care pose risks to patient safety and may negatively affect patient outcomes. While monitoring quality of care is routine in high income countries, it is not systematically implemented in most low- and middle-income countries. In this resource scarce context there is a paucity of feasibly implementable tools to monitor quality of ICU care. Lebanon is an upper middle-income country that during the autumn and winter of 2020-21 has had increasing demands for ICU beds for COVID-19. The World Health Organisation has supported the Ministry of Public Health to increase ICU beds at public hospitals by 300% but no readily available tool to monitor the quality of ICU care was available. The aim of this study was to describe the process of rapidly developing and implementing a tool to monitor quality of ICU care at public hospitals in Lebanon.Methods: In the midst of the escalating pandemic, we applied a systematic approach to develop a realistically implementable quality assurance tool. We conducted a literature review, held expert meetings, and did a pilot study to select among identified quality indicators for ICU care that were feasible to collect during a one-hour ICU visit. In addition, a limited set of the identified indicators that were quantifiable were specifically selected for a scoring protocol to allow comparison over time as well as between ICUs.Results: A total of 44 quality indicators, that, using different methods, could be collected by an external person, were selected for the quality of care tool. Out of these 33 were included for scoring. When tested, the scores showed large difference between hospitals with low versus high resources, indicating considerable variation in quality of care.Conclusion: The proposed tool is a promising way to systematically assess and monitor quality of care in ICUs in the absence of more advanced and resource demanding systems. It is currently in use in Lebanon. The proposed tool may help identifying quality gaps to be targeted and can monitor progress. More studies to validate the tool is needed. [ABSTRACT FROM AUTHOR]

Background Incident reporting (IR) is one of the most used systems to gain knowledge of adverse events (AEs) and to identify sources of risk. During COVID-19 pandemic, several organizational changes have been implemented to respond adequately and effectively to the emergency; this required the suspension of most deferrable activities. Objective The aim of this study is to investigate whether IR attitude of health workers has been reduced during the pandemic event. Method A retrospective analysis was conducted at the Azienda Ospedale – Università di Padova (Italy), considering IR of years 2019 and 2020. To standardize the effects of the decrease in admissions, we considered the number of incidents per 1000 admissions. Results Data shows that during the first (March–May 2020) and second waves (October–December 2020) of the COVID-19 pandemic there was a statistically significant reduction in the rate of IR for every 1000 admissions (P  = 0.001—Wilcoxon test), especially for AEs and in COVID-19 units. Conclusion This study shows a reduction in IR especially during the first and second pandemic waves of COVID-19 in year 2020. Education and training interventions could be fundamental to raise awareness of the importance of IR in health workers, as this could provide opportunities to understand what is impacting on safety in a particular healthcare context and enable continuous improvement. [ABSTRACT FROM AUTHOR]

Background The coronavirus disease 2019 (COVID-19) pandemic is an ongoing severe issue. Objective The aim of this study was to compare the incidence, severity and treatment of acute appendicitis (AA) before and during the COVID-19 pandemic. Methods A retrospective cohort analysis was conducted between January 2019 and April 2020 in one high-volume center. A comparison was performed between two groups (Group A: patients admitted with AA before the COVID-19 pandemic; Group B: patients admitted with AA at the beginning of the pandemic) in terms of the incidence of AA and clinical and pathological outcomes. The incidence of AA was also analyzed in six surrounding peripheral hospitals. Results A total of 94 patients were identified, 54 in Group A and 40 in Group B (57% vs. 43%). Demographic data were comparable between groups. AA in Group B showed a significant higher rate of histological advanced cases (10 (18.5%) Group A vs. 20 (50%) Group B, P  = 0.001) and the need for postoperative antibiotic treatment (6 (11.1%) Group A vs. 11 (27.5%) Group B, P  = 0.045). During the pandemic, a higher percentage of patients were treated at peripheral hospitals (Group A: 54/111 vs. 40/126). Conclusion During the onset of the COVID-19 pandemic there was a significant decrease of patients with AA in a high-volume center, which showed more advanced disease of AA. This significant decrease in the high-volume center correlates with an increase in patients with AA in peripheral hospitals and represents a change in patient flow during the onset of the pandemic. [ABSTRACT FROM AUTHOR]

Background Following the spread of COVID-19, many patients received home care services for recovery. The family is one of the informal caregivers who provide daily physical and psychological support to the patient, and they have the most contributions in the care of patients. Objective This study explains the experiences of home caregivers in the families of patients with COVID-19. Methods This is a qualitative study with a hermeneutic phenomenological approach. Purposeful sampling was applied, and semi-structured interviews in the Center of COVID-19 Control in Khoy, Iran, were used to collect the information. Twenty-three family caregivers, who had already provided care for patients with COVID-19 at home, participated in the study. The themes emerged from interviews. The interviews were recorded and transcripted and then analyzed using Dickelman's interpretive phenomenological approach. Results Thirteen primary concepts, six sub-themes and three main themes were extracted from the data analysis, including 'Irrational fear of disease' with sub-themes: fear of getting infected and indulging in strength of immune system; 'Increasing the burden of care in caregivers' with sub-themes: lack of support and caregiver's family challenges; and 'Self-reinforcement' with sub-themes: highlighting positive features and turning to spirituality. Conclusion Understanding the complexities, experiences and beliefs of family caregivers about living with a COVID-19 patient provides a comprehensive perception of the psychological and physical consequences of care. Executive decision-makers, health care personnel and mental health professionals can also take the necessary strategies to support and manage home caregivers and interdisciplinary cooperation. [ABSTRACT FROM AUTHOR]

Background: New inpatient virtual care models have proliferated in response to the challenges presented by the COVID-19 pandemic, however, few of these programs have yet been evaluated for acceptability and feasibility. We present the results of a survey of feasibility and provider experience with the Virtual Team Rounding Program (VTRP), a quality improvement project developed and rapidly scaled at Brigham and Women's Hospital in Boston, MA, in response to the surge of COVID-19 patients in the spring of 2020.Methods: We surveyed 777 inpatient providers and 41 providers who served as "virtual rounders" regarding their experience with the program. Inpatient providers were asked about their overall satisfaction with the program, whether they the program saved them time, and if so, how much, and their interest in working with a similar program in the future. Providers who had worked as virtual rounders were asked about their overall satisfaction with the program, the overall difficulty of the work, and their interest in participating in a similar program in the future.Results: We find that among both groups the program was well-received, with 72.5% of inpatient providers and 85.7% of virtual rounders reporting they were "satisfied" or "very satisfied" with their experience with the program. Among inpatient providers who worked with the program, two-thirds reported the program saved them time on a daily basis. Inpatient respondents who had worked with virtual rounders were more likely to say that they would be interested in working with the VTRP in the future compared with respondents who never worked with a virtual rounder (75.3% vs 52.5%, p < 0.001).Conclusion: As the pandemic continues, rapidly implementing and studying virtual care delivery programs is crucial for hospitals and health systems. We demonstrate the feasibility and acceptability of a "virtual rounding" program assisting inpatient providers. Future work should examine the impact of these programs on patient outcomes. [ABSTRACT FROM AUTHOR]

Background: COVID-19 is the most informative pandemic in history. These unprecedented recorded data give rise to some novel concepts, discussions and models. Macroscopic modeling of the period of hospitalization is one of these new issues.Methods: Modeling of the lag between diagnosis and death is done by using two classes of macroscopic analytical methods: the correlation-based methods based on Pearson, Spearman and Kendall correlation coefficients, and the logarithmic methods of two types. Also, we apply eight weighted average methods to smooth the time series before calculating the distance. We consider five lags with the least distance. All the computations are conducted on Matlab R2015b.Results: The length of hospitalization for the fatal cases in the USA, Italy and Germany are 2-10, 1-6 and 5-19 days, respectively. Overall, this length in the USA is 2 days more than that in Italy and 5 days less than that in Germany.Conclusion: We take the distance between the diagnosis and death as the length of hospitalization. There is a negative association between the length of hospitalization and the case fatality rate. Therefore, the estimation of the length of hospitalization by using these macroscopic mathematical methods can be introduced as an indicator to scale the success of the countries fighting the ongoing pandemic. [ABSTRACT FROM AUTHOR]

Objective: To identify how features of the community in which a hospital serves differentially relate to its patients' experiences based on the quality of that hospital.Design: A Finite Mixture Model (FMM) is used to uncover a mix of two latent groups of hospitals that differ in quality. In the FMM, a multinomial logistic equation relates hospital-level factors to the odds of being in either group. And a multiple linear regression relates the characteristics of communities served by hospitals to the patients' expected ratings of their experiences at hospitals in each group. Thus, this association potentially varies with hospital quality. The analysis was conducted via Stata.Setting: Hospital Ratings are measured by Hospital Compare using the HCAHPS survey, a patient satisfaction survey required by the Centers for Medicare and Medicaid Services (CMS) for hospitals in the United States. Participants: 2,816 Medicare-certified acute care hospitals across all US states. [ABSTRACT FROM AUTHOR]

Background: COVID-19 pandemic has had a major impact globally, with older people living in aged care homes suffering high death rates.Objectives: We aimed to compare the impact of initial government policies on this vulnerable older population between the UK and Australia during the first wave of attack.Methods: We searched websites of governments in the UK and Australia and media outlets. We examined the key policies including the national lockdown dates and the distribution of some important resources (personal protective equipment and testing) and the effects of these initial policies on the mortality rates in the aged care homes during the first wave of attack of COVID-19.Results: We found that both countries had prioritized resources to hospitals over aged care homes during the first wave of attack. Both countries had lower priority for aged care residents in hospitals (e.g. discharging without testing for COVID-19 or discouraging admissions). However, deaths in aged care homes were 270 times higher in the UK than in Australia as on 7 May 2020 (despite UK having a population only 2.5 times larger than Australia). The lower fatality rate in Australia may have been due to the earlier lockdown strategy when the total daily cases were low in Australia (118) compared to the UK (over 1000), as well as the better community viral testing regime in Australia.Conclusion: In conclusion, the public health policy in Australia aimed towards earlier intervention with earlier national lockdown and more viral testing to prevent new cases. This primary prevention could have resulted in more lives being saved. In contrast, the initial policy in the UK focussed mainly on protecting resources for hospitals, and there was a delay in national lockdown intervention and lower viral testing rate, resulting in more lives lost in the aged care sector. [ABSTRACT FROM AUTHOR]

Objectives To highlight clinical and operational issues, identify factors that shape patient responses in Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) and test the correlations between composite measures and overall hospital ratings. Design Responses to HCAHPS surveys were used in a partial correlation analysis to ascertain those HCAHPS composite measures that most relate to overall hospital ratings. The linear mean scores for the composite measures and individual and global items were analyzed with descriptive analysis and correlation analysis via JMP and SPSS statistical software. Setting HCAHPS is a patient satisfaction survey required by the Centers for Medicare and Medicaid Services for hospitals in the USA. The survey is for adult inpatients, excluding psychiatric patients. Participants 3382 US hospitals. Intervention None. Main Outcome Measure Pearson correlation coefficients for the six composite measures and overall hospital rating. Results The partial correlations for overall hospital rating and three composite measures are positive and moderately strong for care transition (0.445) and nurse communication (0.369) and weak for doctor communication (0.066). Conclusions From a health policy standpoint, it is imperative that hospital administrators stress open and clear communication between providers and patients to avoid problems ranging from misdiagnosis to incorrect treatment. Additional research is needed to determine how the coronavirus of 2019 pandemic influences patients' perceptions of quality and willingness to recommend hospitals at a time when nurses and physicians show symptoms of burnout due to heavy workloads and inadequate personal protective equipment. [ABSTRACT FROM AUTHOR]

Background The health, social and economic consequences of the severe acute respiratory syndrome coronavirus (SARS-CoV-2, henceforth COVID-19) pandemic have loomed large as every national government made decisions about how to respond. The 40 Health Systems, COVID-19 (40HS, C-19) study aimed to investigate relationships between governments' capacity to respond (CTR), their response stringency, scope of COVID-19 testing and COVID-19 outcomes. Methods Data over March and April 2020 were extracted for 40 national health systems on prepandemic government CTR (Global Competitiveness Index), stringency measures (Oxford COVID-19 Government Response Tracker Stringency Index), approach to COVID-19 testing and COVID-19 cases and deaths (Our-World-in-Data). Multidimensional scaling (MDS) and cluster analysis were applied to examine latent dimensions and visualize country similarities and dissimilarities. Outcomes were tested using multivariate and one-way analyses of variances and Kruskal–Wallis H tests. Results The MDS model found three dimensions explaining 91% of the variance and cluster analysis identified five national groupings. There was no association between national governments' prepandemic CTR and the adoption of early stringent public health measures or approach to COVID-19 testing. Two national clusters applied early stringency measures and reported significantly lower cumulative deaths. The best performing national cluster (comprising Australia, South Korea, Iceland and Taiwan) adopted relatively early stringency measures but broader testing earlier than others, which was associated with a change in disease trajectory and the lowest COVID-19 death rates. Two clusters (one with high CTR and one low) both adopted late stringency measures and narrow testing and performed least well in COVID-19 outcomes. Conclusion Early stringency measures and intrinsic national capacities to deal with a pandemic are insufficient. Extended stringency measures, important in the short term, are not economically sustainable. Broad-based testing is key to managing COVID-19. [ABSTRACT FROM AUTHOR]

Objective: Motivated by the coronavirus disease 2019 (covid-19) pandemic, we developed a novel Shewhart chart to visualize and learn from variation in reported deaths in an epidemic.Context: Without a method to understand if a day-to-day variation in outcomes may be attributed to meaningful signals of change-rather than variability we would expect-care providers, improvement leaders, policy-makers, and the public will struggle to recognize if epidemic conditions are improving.Methods: We developed a novel hybrid C-chart and I-chart to detect within a geographic area the start and end of exponential growth in reported deaths. Reported deaths were the unit of analysis owing to erratic reporting of cases from variability in local testing strategies. We used simulation and case studies to assess chart performance and define technical parameters. This approach also applies to other critical measures related to a pandemic when high-quality data are available.Conclusions: The hybrid chart detected the start of exponential growth and identified early signals that the growth phase was ending. During a pandemic, timely reliable signals that an epidemic is waxing or waning may have mortal implications. This novel chart offers a practical tool, accessible to system leaders and frontline teams, to visualize and learn from daily reported deaths during an epidemic. Without Shewhart charts and, more broadly, a theory of variation in our epidemiological arsenal, we lack a scientific method for a real-time assessment of local conditions. Shewhart charts should become a standard method for learning from data in the context of a pandemic or epidemic. [ABSTRACT FROM AUTHOR]

Background: Nursing homes provide long-term care and have residential-oriented hospitalizations characterized by medical, nursing and social-care treatments for a typically geriatric population. In the current emergency phase, the problem of infections in residential structures for the elderly is taking on considerable importance in relation to the significant prevalence rates of coronavirus disease 2019 (COVID-19).Safety Improvement Strategies: Prevention and control measures for severe acute respiratory syndrome coronavirus 2 infection in nursing homes should be planned before a possible outbreak of COVID-19 occurs and should be intensified during any exacerbation of the same. Each facility should identify a properly trained contact person-also external-for the prevention and control of infections, who can refer to a multidisciplinary support committee and who is in close contact with the local health authorities. The contact person should collaborate with professionals in order to prepare a prevention and intervention plan that considers national provisions and scientific evidence, the requirements for reporting patients with symptoms compatible with COVID-19 and the indications for the management of suspected, probable or confirmed cases of COVID-19.Discussion: Adequate risk management in residential structures implies the establishment of a coordination committee with dedicated staff, the implementation of a surveillance program for the rapid recognition of the outbreaks, the identification of suitable premises and equipment, the application of universal precautions, the adaptation of care plans to reduce the possibility of contagion among residents and the protection of operators and staff training initiatives. [ABSTRACT FROM AUTHOR]

Italy was the first country after China to be affected by COVID-19. The wave of the emergency found our country unprepared to cope with the surge of patients going to first aid departments to seek assistance in the almost complete paralysis of community health. Human factors and ergonomics (HFE) can effectively contribute to, and improve the effectiveness of, a pandemic response working on several key areas: training, adapting workflows and processes, restructuring teams and tasks, effective mechanisms and tools for communication, engaging patients and families and learning from failures and successes. In Italy, HFE expertise has been able to provide our healthcare systems with some easy-to-realize solutions (particularly dedicated to improving communication, team work and situational awareness) in order to cope with the need for rapid adaptations to new and unknown scenarios: ensuring information and communication continuity in the different levels of the healthcare system; identifying hazard opportunity through risk management tool; providing training through simulation; organizing regular briefing and debriefing; enhancing the reporting and learning system as an informal way of communicating adverse events and supporting information campaign and education initiatives for the public. [ABSTRACT FROM AUTHOR]

Federated learning (FL) as a distributed machine learning (ML) technique has lately attracted increasing attention of healthcare stakeholders as FL is perceived as a promising decentralized approach to address data privacy and security concerns. The FL approach stores and maintains the privacy-sensitive data locally while allows multiple sites to train ML models collaboratively. We aim to describe the most recent real-world cases using the FL in both COVID-19 and non-COVID-19 scenarios and also highlight current limitations and practical challenges of FL. [ABSTRACT FROM AUTHOR]