Development and Evaluation of a Virtual Research Environment to Improve Quality of Care in Overcrowded Emergency Departments: Observational Study

A scoping review of metaverse in emergency medicine

BACKGROUND

Interest in the metaverse has been growing worldwide as the virtual environment provides opportunities for highly immersive and interactive experiences. Metaverse has gradually gained acceptance in the medical field with the advancement of technologies such as big data, the Internet of Things, and 5 G mobile networks. The demand for and development of metaverse are different in diverse subspecialties owing to patients with varying degrees of clinical disease. Hence, we aim to explore the application of metaverse in acute medicine by reviewing published studies and the clinical management of patients.

METHOD

Our review examined the published articles about the concept of metaverse roadmap, and four additional domains were extracted: education, prehospital and disaster medicine, diagnosis and treatment application, and administrative affairs.

RESULTS

Augmented reality (AR) and virtual reality (VR) integration have broad applications in education and clinical training. VR-related studies surpassed AR-related studies in the emergency medicine field. The metaverse roadmap revealed that lifelogging and mirror world are still developing fields of the metaverse.

CONCLUSION

Our findings provide insight into the features, application, development, and potential of a metaverse in emergency medicine. This study will enable emergency care systems to be better equipped to face future challenges.

Metaverse applied to musculoskeletal pathology: Orthoverse and Rehabverse

The Metaverse is 'an integrated network of 3D virtual worlds.' It incorporates digitally created realities into the real world, involves virtual copies of existing places and changes the physical reality by superimposing digital aspects, allowing its users to interact with these elements in an immersive, real-time experience. The applications of the Metaverse are numerous, with an increasing number of experiences in the field of musculoskeletal disease management. In the field of medical training, the Metaverse can help facilitate the learning experience and help develop complex clinical skills. In clinical care, the Metaverse can help clinicians perform orthopedic surgery more accurately and safely and can improve pain management, the performance of rehabilitation techniques and the promotion of healthy lifestyles. Virtualization can also optimize aspects of healthcare information and management, increasing the effectiveness of procedures and the functioning of organizations. This optimization can be especially relevant in departments that are under significant care provider pressure. However, we must not lose sight of the fundamental challenges that still need to be solved, such as ensuring patient privacy and fairness. Several studies are underway to assess the feasibility and safety of the Metaverse.

Game Experience and Learning Effects of a Scoring-Based Mechanic for Logistical Aspects of Pediatric Emergency Medicine: Development and Feasibility Study

Background

Using serious games for learning in operations management is well established. However, especially for logistics skills in health care operations, there is little work on the design of game mechanics for learning engagement and the achievement of the desired learning goals.

Objective

This contribution presents a serious game design representing patient flow characteristics, systemic resource configurations, and the roles of the players based on a real Swedish emergency ward. The game was tested in a set of game-based learning practices in the modalities of a physical board game and an online multiplayer serious game that implemented the same game structure.

Methods

First, survey scores were collected using the Game Experience Questionnaire Core and Social Presence Modules to evaluate the experience and acceptance of the proposed design to gamify real processes in emergency care. Second, lag sequential analysis was applied to analyze the impact of the game mechanics on learning behavior transitions. Lastly, regression analysis was used to understand whether learning engagement attributes could potentially serve as significant predicting variables for logistical performance in a simulated learning environment.

Results

A total of 36 students from courses in engineering and management at KTH Royal Institute of Technology participated in both game-based learning practices during the autumn and spring semesters of 2019 and 2020. For the Core Module, significant differences were found for the scores for negative affect and tension compared with the rest of the module. For the Social Presence Module, significant differences were found in the scores for the psychological involvement – negative feelings dimension compared with the rest of the module. During the process of content generation, the participant had access to circulating management resources and could edit profiles. The standard regression analysis output yielded a ΔR² of 0.796 (F1_4,31=2725.49, P<.001) for the board version and 0.702 (F2_4,31=2635.31, P<.001) for the multiplayer online version after the learning engagement attributes.

Conclusions

The high scores of positive affect and immersion compared to the low scores of negative feelings demonstrated the motivating and cognitive involvement impact of the game. The proposed game mechanics have visible effects on significant correlation parameters between the majority of scoring features and changes in learning engagement attributes. Therefore, we conclude that for enhancing learning in logistical aspects of health care, serious games that are steered by well-designed scoring mechanisms can be used.

On the Logical Design of a Prototypical Data Lake System for Biological Resources

Biological resources are multifarious encompassing organisms, genetic materials, populations, or any other biotic components of ecosystems, and fine-grained data management and processing of these diverse types of resources proposes a tremendous challenge for both researchers and practitioners. Before the conceptualization of data lakes, former big data management platforms in the research fields of computational biology and biomedicine could not deal with many practical data management tasks very well. As an effective complement to those previous systems, data lakes were devised to store voluminous, varied, and diversely structured or unstructured data in their native formats, for the sake of various analyses like reporting, modeling, data exploration, knowledge discovery, data visualization, advanced analysis, and machine learning. Due to their intrinsic traits, data lakes are thought to be ideal technologies for processing of hybrid biological resources in the format of text, image, audio, video, and structured tabular data. This paper proposes a method for constructing a practical data lake system for processing multimodal biological data using a prototype system named ProtoDLS, especially from the explainability point of view, which is indispensable to the rigor, transparency, persuasiveness, and trustworthiness of the applications in the field. ProtoDLS adopts a horizontal pipeline to ensure the intra-component explainability factors from data acquisition to data presentation, and a vertical pipeline to ensure the inner-component explainability factors including mathematics, algorithm, execution time, memory consumption, network latency, security, and sampling size. The dual mechanism can ensure the explainability guarantees on the entirety of the data lake system. ProtoDLS proves that a single point of explainability cannot thoroughly expound the cause and effect of the matter from an overall perspective, and adopting a systematic, dynamic, and multisided way of thinking and a system-oriented analysis method is critical when designing a data processing system for biological resources.