Practice in Information Technology Support for Fangcang Shelter Hospital during COVID-19 Epidemic in Wuhan, China

Learning interventions and training methods in health emergencies: A scoping review

BACKGROUND

Keeping the health workforce and the public informed about the latest evolving health information during a health emergency is critical to preventing, detecting and responding to infectious disease outbreaks or other health emergencies. Having a well-informed, ready, willing, and skilled workforce and an informed public can help save lives, reduce diseases and suffering, and minimize socio-economic loss in affected communities and countries. Providing "just in time" support and opportunities for learning in health emergencies is much needed for capacity building. In this paper, 'learning intervention' refers to the provision of ad-hoc, focused, or personalized training sessions with the goal of preparing the health workers for emergencies or filling specific knowledge or skill gaps. We refer to 'training methods' as instructional design strategies used to teach someone the necessary knowledge and skills to perform a task.

METHODS

We conducted a scoping review to map and better understand what learning interventions and training methods have been used in different types of health emergencies and by whom. Studies were identified using six databases (Pubmed/Medline, Embase, Hinari, WorldCat, CABI and Web of Science) and by consulting with experts. Characteristics of studies were mapped and displayed and major topic areas were identified.

RESULTS

Of the 319 records that were included, contexts most frequently covered were COVID-19, disasters in general, Ebola and wars. Four prominent topic areas were identified: 1) Knowledge acquisition, 2) Emergency plans, 3) Impact of the learning intervention, and 4) Training methods. Much of the evidence was based on observational methods with few trials, which likely reflects the unique context of each health emergency. Evolution of methods was apparent, particularly in virtual learning. Learning during health emergencies appeared to improve knowledge, general management of the situation, quality of life of both trainers and affected population, satisfaction and clinical outcomes.

CONCLUSION

This is the first scoping review to map the evidence, which serves as a first step in developing urgently needed global guidance to further improve the quality and reach of learning interventions and training methods in this context.

Effectiveness of Treatment Approaches in COVID-19 Pneumonia: A Comparative Evaluation between a Specialized Center and Conventional Hospitals

BACKGROUND

The early stages of the COVID-19 pandemic overwhelmed general hospitals in Spain. In response, a dedicated hospital for COVID-19 care, the Hospital de Emergencias Enfermera Isabel Zendal (HEEIZ), was established. This study aimed to compare clinical outcomes of COVID-19 patients treated at the specialized HEEIZ with those at conventional general hospitals (CGHs) in Madrid, Spain.

METHODS

The study was a prospective, observational cohort study including COVID-19 patients admitted to the HEEIZ and 14 CGHs (December 2020 to August 2021). Patients were assigned based on hospital preference. Clinical data were collected and analyzed using multivariate regression to assess primary and secondary outcomes, including hospital mortality, need of invasive mechanical ventilation (IMV), and pharmacological treatments.

RESULTS

The HEEIZ cohort (n = 2997) was younger and had lower Charlson comorbidity scores than the CGH cohort (n = 1526). Adjusted HEEIZ hospital mortality was not significantly higher compared with CGHs (OR: 1.274; 95% CI: 0.781-2.079; p = 0.332).

CONCLUSIONS

During the study period, patients admitted to the HEEIZ showed no significant differences in clinical outcomes, compared with patients admitted at CGHs. These results might support the use of specialized centers in managing pandemic surges, allowing CGHs to handle other needs.

Implications for implementation and adoption of telehealth in developing countries: a systematic review of China's practices and experiences

The rapid advancement of telehealth technologies has the potential to revolutionize healthcare delivery, especially in developing countries and resource-limited settings. Telehealth played a vital role during the COVID-19 pandemic, supporting numerous healthcare services. We conducted a systematic review to gain insights into the characteristics, barriers, and successful experiences in implementing telehealth during the COVID-19 pandemic in China, a representative of the developing countries. We also provide insights for other developing countries that face similar challenges to developing and using telehealth during or after the pandemic. This systematic review was conducted through searching five prominent databases including PubMed/MEDLINE, Embase, Scopus, Cochrane Library, and Web of Science. We included studies clearly defining any use of telehealth services in all aspects of health care during the COVID-19 pandemic in China. We mapped the barriers, successful experiences, and recommendations based on the Consolidated Framework for Implementation Research (CFIR). A total of 32 studies met the inclusion criteria. Successfully implementing and adopting telehealth in China during the pandemic necessitates strategic planning across aspects at society level (increasing public awareness and devising appropriate insurance policies), organizational level (training health care professionals, improving workflows, and decentralizing tasks), and technological level (strategic technological infrastructure development and designing inclusive telehealth systems). WeChat, a widely used social networking platform, was the most common platform used for telehealth services. China's practices in addressing the barriers may provide implications and evidence for other developing countries or low-and middle- income countries (LMICs) to implement and adopt telehealth systems.

An approach for joint optimization of probabilistic group test based on cost and time value: taking nucleic acid detection of COVID-19 as an example

In recent years, the world has encountered many epidemic impacts caused by various viruses, COVID-19 has spread and mutated globally since its outbreak in 2019, causing global impact. Nucleic acid detection is an important means for the prevention and control of infectious diseases. Aiming at people who are susceptible to sudden and infectious diseases, considering the control of viral nucleic acid detection cost and completion time, a probabilistic group test optimization method based on the cost and time value is proposed. Firstly, different cost functions to express the pooling and testing costs are used, a probability group test optimization model that considers the pooling and testing costs is established, the optimal combination number of samples for nucleic acid testing is obtained, and the positive probability and the cost functions of the group testing on the optimization result are explored. Secondly, considering the impact of the detection completion time on epidemic control, the sampling ability and detection ability were incorporated into the optimization objective function, then a probability group testing optimization model based on time value is established. Finally, taking COVID-19 nucleic acid detection as an example, the applicability of the model is verified, and the Pareto optimal curve under the minimum cost and shortest detection completion time is obtained. The results show that under normal circumstances, the optimal combination number of samples for nucleic acid detection is about 10. Generally, 10 is used to calculate for the convenience of organization, arrangement and statistics, except for cases where there are special requirements for testing cost and detection completion time.

Hospital architecture in times of crisis

In times of crisis, such as public health emergency, military conflict or natural disaster, health systems face immense pressures. Large-scale crises continue to appear at irregular intervals and healthcare facilities should be prepared to react quickly and flexibly to the increased need for treatment and care. This paper aims to outline key concepts related to healthcare architecture during a mass-scale crisis, discuss challenges, and suggest solutions. Although the field lacks robust research evidence, lessons learned from past and ongoing events clearly indicate that advance planning is essential for effective crisis response. The crisis response has three guiding principles -adaptability, flexibility, and creativity. The interventions can focus on adapting existing healthcare facilities, building new units, and repurposing civil facilities for hospitals. A wide range of building typologies can be utilised, including modular containers, tents, lightweight structures, and repurposing civil buildings and public spaces. These interventions must be quick, economic, durable, and easily deployable. Temporary facilities must ensure an effective spatial platform for patients and staff, establish links with existing services, and consider post-crisis life of interventions. While these principles can be considered for any type of healthcare facility and any type of crisis, end-results will depend on baseline infrastructure and available resources.

Analysis of the Geographic Transmission Differences of COVID-19 in China Caused by Population Movement and Population Density

The coronavirus disease (COVID-19) has led to a global pandemic and caused huge healthy and economic losses. Non-pharmaceutical interventions, especially contact tracing and social distance restrictions, play a vital role in the control of COVID-19. Understanding the spatial impact is essential for designing such a control policy. Based on epidemic data of the confirmed cases after the Wuhan lockdown, we calculate the invasive reproduction numbers of COVID-19 in the different regions of China. Statistical analysis indicates a significant positive correlation between the reproduction numbers and the population input sizes from Wuhan, which indicates that the large-scale population movement contributed a lot to the geographic spread of COVID-19 in China. Moreover, there is a significant positive correlation between reproduction numbers and local population densities, which shows that the higher population density intensifies the spread of disease. Considering that in the early stage, there were sequential imported cases that affected the estimation of reproduction numbers, we classify the imported cases and local cases through the information of epidemiological data and calculate the net invasive reproduction number to quantify the local spread of the epidemic. The results are applied to the design of border control policy on the basis of vaccination coverage.

“Debriefing and Organizational Lessons Learned” (DOLL): A Qualitative Study to Develop a Classification Framework for Reporting Clinical Debriefing Results

Background

The COVID-19 crisis has radically affected our healthcare institutions. Debriefings in clinical settings provide a time for the clinicians to reflect on the successes (pluses) and difficulties (deltas) encountered. Debriefings tend to be well-received if included in the broader management of the unit. The goal of this study was to develop a framework to categorize these debriefings and to assess its worthiness.

Methods

A qualitative approach based on a grounded theory research method was adopted resulting in the “Debriefing and Organizational Lessons Learned” (DOLL) framework. Debriefings were conducted within two Emergency Departments of a Belgian University Hospital during an 8-week period. In the first step, three researchers used debriefing transcripts to inductively develop a tentative framework. During the second step, these three researchers conducted independent categorizations of the debriefings using the developed framework. In step 3, the team analyzed the data to understand the utility of the framework. Chi-square was conducted to examine the associations between the item types (pluses and deltas) and the framework's dimensions.

Results

The DOLL is composed of seven dimensions and 13 subdimensions. Applied to 163 debriefings, the model identified 339 items, including 97 pluses and 242 deltas. Results revealed that there was an association between the frequency of pluses and deltas and the dimensions (p < 0.001). The deltas were mainly related to the work environment (equipment and maintenance) (p < 0.001) while the pluses identified tended to be related to the organization of the unit (communication and roles) (p < 0.001). With leadership's support and subsequent actions, clinicians were more enthusiastic about participating and the researchers anecdotally detected a switch toward a more positive organizational learning approach.

Conclusion

The framework increases the potential value of clinical debriefings because it organizes results into actionable areas. Indeed, leadership found the DOLL to be a useful management tool. Further research is needed to investigate how DOLL may work in non-crisis circumstances and further apply the DOLL into incident reporting and risk management process of the unit.

Emergency Preparedness and Management of Mobile Cabin Hospitals in China During the COVID-19 Pandemic

The healthcare systems in China and globally have faced serious challenges during the coronavirus disease (COVID-19) pandemic. The shortage of beds in traditional hospitals has exacerbated the threat of COVID-19. To increase the number of available beds, China implemented a special public health measure of opening mobile cabin hospitals. Mobile cabin hospitals, also called Fangcang shelter hospitals, refer to large-scale public venues such as indoor stadiums and exhibition centers converted to temporary hospitals. This study is a mini review of the practice of mobile cabin hospitals in China. The first part is regarding emergency preparedness, including site selection, conversion, layout, and zoning before opening the hospital, and the second is on hospital management, including organization management, management of nosocomial infections, information technology support, and material supply. This review provides some practical recommendations for countries that need mobile cabin hospitals to relieve the pressure of the pandemic on the healthcare systems.

Agent-Based Simulation of Virus Testing in Certain-Exposure Time through Community Health Service Centers' Evaluation-A Case Study of Wuhan

Short-term and large-scale full-population virus testing is crucial in containing the spread of the COVID-19 pandemic in China. However, the uneven distribution of health service facilities in terms of space and size may lead to prolonged crowding during testing, thus increasing the chance of virus cross-infection. Therefore, appropriate control of crowd exposure time in large-scale virus testing should be an important goal in the layout of urban community health facilities. This paper uses the Quanta concept and Wells-Riley model to define the "certain-exposure time" under low cross-infection rate. Then, an agent-based simulation model was used to simulate the reasonable screening efficiency of community health service facilities during certain-exposure time at different stages of the COVID-19 pandemic and under different screening processes. Eventually, the screening efficiency was evaluated for all community health service centers in Wuhan. During the early period of the pandemic, 23.13% of communities failed to complete virus testing of community residents within 2 h of certain-exposure time, leaving approximately 56.07% of the population unscreened; during the later period of the COVID-19 pandemic, approximately 53% of communities and 75% of residents could not be screened. The results can pinpoint the distribution of community health service centers with inadequate screening capacity, facilitate targeted policymaking and planning, and effectively curb COVID-19 cross-infection during screening.