Washing hands is one of the most important ways to prevent infectious diseases, including COVID-19. The World Health Organization (WHO) has published hand-washing guidelines. This paper presents a large real-world dataset with videos recording medical staff washing their hands as part of their normal job duties in the Pauls Stradins Clinical University Hospital. There are 3185 hand-washing episodes in total, each of which is annotated by up to seven different persons. The annotations classify the washing movements according to the WHO guidelines by marking each frame in each video with a certain movement code. The intention of this “in-the-wild” dataset is two-fold: to serve as a basis for training machine-learning classifiers for automated hand-washing movement recognition and quality control, and to allow to investigation of the real-world quality of washing performed by working medical staff. We demonstrate how the data can be used to train a machine-learning classifier that achieves classification accuracy of 0.7511 on a test dataset.

An individual's knowledge and skills, also known as human capital, shape its professional quality and become a valuable resource for the organization when entering an employment relationship. Investment in human capital, promoting the formal and non-formal lifelong learning of the workforce while implementing targeted capital monitoring, is essential to achieve the strategic goals of the organisation. In addition, in particularly critical areas such as healthcare, human capital management can play a crucial role in ensuring the quality of healthcare and patient safety. The study aims to analyse the research carried out on the aspects of human capital management of the healthcare workforce and its role in the health sector. To achieve the goal, a rapid review was performed by including articles indexed in the databases Scopus and Web of Science in the period 2017-2021, according to search strategy. The study shows - human capital is mostly analysed at the national or regional level as an indicator of a country's level of development (macro-dimension). At the same time, relatively little research has been conducted at the micro-dimension, where management of human capital of the healthcare workforce has been studied at the institutional or sectoral level. Research on human capital management in the healthcare sector at the institutional level only fragmentarily reflects its importance and does not provide a comprehensive picture of effective management methods or systems, as well as benefits or barriers to implementation. There is a significant lack of research on the interaction of human capital management with specific factors in the healthcare sector, such as the quality of health care and the safety of patients and healthcare professionals.

The competence of healthcare professionals is crucial in ensuring patient safety and the quality of healthcare. Skills are one of the most important aspects of competence, but often health care employers, when assessing the readiness of young professionals, point out that the ability to implement skills in a real work environment are unclear, insufficient and even inadequate.The paradigm shift in education intends bringing skills to the foreground. In order to promote skills management, Rīga Stradiņš University (RSU) already in 2016 started work on the institutional level project “Skills Monitoring System” (hereinafter - SMS), focusing primarily on work and profession specific skills in the field of health care studies.Visible and demonstrable monitoring of skills in education is an innovation. The aim of this article is to analyze and reflect the coherence of the RSU Skills Monitoring System concept with the current principles of education policy development, legal framework and basic principles of higher education pedagogy in skills acquisition and evaluation in health care education, as well as to evaluate the initial results of the newly developed system.In order to achieve the goal, an interdisciplinary, qualitative study was conducted, where analytical and descriptive, inductive, deductive and synthesis research and legal (translation) norm methods were implemented, as well as interviews to evaluate initial results.The results of the research show that the components and solutions included in SMS have been developed in accordance with the legal framework and the main educational guidelines, in accordance with the theoretical concepts of pedagogy. An education approach based on simulation integrated in the acquisition of skills allows to systematically evaluate the amount and quality of theoretical knowledge, to determine the actual level of abilities and to predict the quality of performance and compliance with the real work environment. The management of skills acquisition in Higher Education Institutions should be supported and promoted from the point of view of educators, employees and sectoral professional associations and employers.

Background: Thousands of people die every day around the world from infections acquired in a hospital. Hands are the main pathways of germ transmission during healthcare. Hand hygiene monitoring can be performed using various methods. One of the latest techniques that can combine all is a neural network-based hand hygiene monitoring system. Methods/Design: Each participant performed 3 hand-washing trials, each time receiving different type of feedback. The order in which each participant of the study used the developed applications was strictly defined, thus each hand-washing study session started with performing hand washing using application A, B and C accordingly. All captured videos of hand-wash episodes were saved and later analysed with neural networks. In the end, both evaluation results were compared and evaluated. Results show that when the participants use Application Type A, they perform hand washing much faster, as well as in comparison of Application Type A versus application type C. However, the longest time spent for the hand washing was detected while using the application type B. Conclusion: Study shows that structured guidance provided during the real time hand washing could be associated with better overall performance. The Application C has confirmed its effectiveness. Proving its advantage among other applications, the Application C can be integrated into the clinical environment