Sharing datasets of the COVID-19 epidemic in the Czech Republic.

At the time of the COVID-19 pandemic, providing access to data (properly optimised regarding personal data protection) plays a crucial role in providing the general public and media with up-to-date information. Open datasets also represent one of the means for evaluation of the pandemic on a global level. The primary aim of this paper is to describe the methodological and technical framework for publishing datasets describing characteristics related to the COVID-19 epidemic in the Czech Republic (epidemiology, hospital-based care, vaccination), including the use of these datasets in practice. Practical aspects and experience with data sharing are discussed. As a reaction to the epidemic situation, a new portal COVID-19: Current Situation in the Czech Republic (https://onemocneni-aktualne.mzcr.cz/covid-19) was developed and launched in March 2020 to provide a fully-fledged and trustworthy source of information for the public and media. The portal also contains a section for the publication of (i) public open datasets available for download in CSV and JSON formats and (ii) authorised-access-only section where the authorised persons can (through an online generated token) safely visualise or download regional datasets with aggregated data at the level of the individual municipalities and regions. The data are also provided to the local open data catalogue (covering only open data on healthcare, provided by the Ministry of Health) and to the National Catalogue of Open Data (covering all open data sets, provided by various authorities/publishers, and harversting all data from local catalogues). The datasets have been published in various authentication regimes and widely used by general public, scientists, public authorities and decision-makers. The total number of API calls since its launch in March 2020 to 15 December 2020 exceeded 13 million. The datasets have been adopted as an official and guaranteed source for outputs of third parties, including public authorities, non-governmental organisations, scientists and online news portals. Datasets currently published as open data meet the 3-star open data requirements, which makes them machine-readable and facilitates their further usage without restrictions. This is essential for making the data more easily understandable and usable for data consumers. In conjunction with the strategy of the MH in the field of data opening, additional datasets meeting the already implemented standards will be also released, both on COVID-19 related and unrelated topics.

Control Centre for Intensive Care as a Tool for Effective Coordination, Real-Time Monitoring, and Strategic Planning During the COVID-19 Pandemic.

In the Czech Republic, the strategic data-based and organizational support for individual regions and for providers of acute care at the nationwide level is coordinated by the Ministry of Health. At the beginning of the COVID-19 pandemic, the country needed to very quickly implement a system for the monitoring, reporting, and overall management of hospital capacities. The aim of this viewpoint is to describe the purpose and basic functions of a web-based application named "Control Centre for Intensive Care," which was developed and made available to meet the needs of systematic online technical support for the management of intensive inpatient care across the Czech Republic during the first wave of the pandemic in spring 2020. Two tools of key importance are described in the context of national methodology: one module for regular online updates and overall monitoring of currently free capacities of intensive care in real time, and a second module for online entering and overall record-keeping of requirements on medications for COVID-19 patients. A total of 134 intensive care providers and 927 users from hospitals across all 14 regions of the Czech Republic were registered in the central Control Centre for Intensive Care database as of March 31, 2021. This web-based application enabled continuous monitoring and decision-making during the mass surge of critical care from autumn 2020 to spring 2021. The Control Center for Intensive Care has become an indispensable part of a set of online tools that are employed on a regular basis for crisis management at the time of the COVID-19 pandemic.

Development of the Czech Childhood Cancer Information System: Data Analysis and Interactive Visualization.

BACKGROUND: The knowledge of cancer burden in the population, its time trends, and the possibility of international comparison is an important starting point for cancer programs. A reliable interactive tool describing cancer epidemiology in children and adolescents has been nonexistent in the Czech Republic until recently. OBJECTIVE: The goal of this study is to develop a new web portal entitled the Czech Childhood Cancer Information System (CCCIS), which would provide information on childhood cancer epidemiology in the Czech Republic. METHODS: Data on childhood cancers have been obtained from the Czech National Cancer Registry. These data were validated using the clinical database of childhood cancer patients and subsequently combined with data from the National Register of Hospitalised Patients and with data from death certificates. These validated data were then used to determine the incidence and survival rates of childhood cancer patients aged 0 to 19 years who were diagnosed in the period 1994 to 2016 (N=9435). Data from death certificates were used to monitor long-term mortality trends. The technical solution is based on the robust PHP development Symfony framework, with the PostgreSQL system used to accommodate the data basis. RESULTS: The web portal has been available for anyone since November 2019, providing basic information for experts (ie, analyses and publications) on individual diagnostic groups of childhood cancers. It involves an interactive tool for analytical reporting, which provides information on the following basic topics in the form of graphs or tables: incidence, mortality, and overall survival. Feedback was obtained and the accuracy of outputs published on the CCCIS portal was verified using the following methods: the validation of the theoretical background and the user testing. CONCLUSIONS: We developed software capable of processing data from multiple sources, which is freely available to all users and makes it possible to carry out automated analyses even for users without mathematical background; a simple selection of a topic to be analyzed is required from the user.

Complex Reporting of the COVID-19 Epidemic in the Czech Republic: Use of an Interactive Web-Based App in Practice.

BACKGROUND: The beginning of the coronavirus disease (COVID-19) epidemic dates back to December 31, 2019, when the first cases were reported in the People's Republic of China. In the Czech Republic, the first three cases of infection with the novel coronavirus were confirmed on March 1, 2020. The joint effort of state authorities and researchers gave rise to a unique team, which combines methodical knowledge of real-world processes with the know-how needed for effective processing, analysis, and online visualization of data. OBJECTIVE: Due to an urgent need for a tool that presents important reports based on valid data sources, a team of government experts and researchers focused on the design and development of a web app intended to provide a regularly updated overview of COVID-19 epidemiology in the Czech Republic to the general population. METHODS: The cross-industry standard process for data mining model was chosen for the complex solution of analytical processing and visualization of data that provides validated information on the COVID-19 epidemic across the Czech Republic. Great emphasis was put on the understanding and a correct implementation of all six steps (business understanding, data understanding, data preparation, modelling, evaluation, and deployment) needed in the process, including the infrastructure of a nationwide information system; the methodological setting of communication channels between all involved stakeholders; and data collection, processing, analysis, validation, and visualization. RESULTS: The web-based overview of the current spread of COVID-19 in the Czech Republic has been developed as an online platform providing a set of outputs in the form of tables, graphs, and maps intended for the general public. On March 12, 2020, the first version of the web portal, containing fourteen overviews divided into five topical sections, was released. The web portal's primary objective is to publish a well-arranged visualization and clear explanation of basic information consisting of the overall numbers of performed tests, confirmed cases of COVID-19, COVID-19-related deaths, the daily and cumulative overviews of people with a positive COVID-19 case, performed tests, location and country of infection of people with a positive COVID-19 case, hospitalizations of patients with COVID-19, and distribution of personal protective equipment. CONCLUSIONS: The online interactive overview of the current spread of COVID-19 in the Czech Republic was launched on March 11, 2020, and has immediately become the primary communication channel employed by the health care sector to present the current situation regarding the COVID-19 epidemic. This complex reporting of the COVID-19 epidemic in the Czech Republic also shows an effective way to interconnect knowledge held by various specialists, such as regional and national methodology experts (who report positive cases of the disease on a daily basis), with knowledge held by developers of central registries, analysts, developers of web apps, and leaders in the health care sector.

Similarity Detection Between Virtual Patients and Medical Curriculum Using R.

This paper presents the domain of information sciences, applied informatics and biomedical engineering, proposing to develop methods for an automated detection of similarities between two particular virtual learning environments - virtual patients at Akutne.cz and the OPTIMED curriculum management system - in order to provide support to clinically oriented stages of medical and healthcare studies. For this purpose, the authors used large amounts of text-based data collected by the system for mapping medical curricula and through the system for virtual patient authoring and delivery. The proposed text-mining algorithm for an automated detection of links between content entities of these systems has been successfully implemented by the means of a web-based toolbox.

Medical and Healthcare Curriculum Exploratory Analysis.

In the recent years, medical and healthcare higher education institutions compile their curricula in different ways in order to cover all necessary topics and sections that the students will need to go through to success in their future clinical practice. A medical and healthcare curriculum consists of many descriptive parameters, which define statements of what, when, and how students will learn in the course of their studies. For the purpose of understanding a complicated medical and healthcare curriculum structure, we have developed a web-oriented platform for curriculum management covering in detail formal metadata specifications in accordance with the approved pedagogical background, namely outcome-based approach. Our platform provides a rich database that can be used for innovative detailed educational data analysis. In this contribution we would like to present how we used a proven process model as a way of increasing accuracy in solving individual analytical tasks with the available data. Moreover, we introduce an innovative approach on how to explore a dataset in accordance with the selected methodology. The achieved results from the selected analytical issues are presented here in clear visual interpretations in an attempt to visually describe the entire medical and healthcare curriculum.

Curriculum Mapping with Academic Analytics in Medical and Healthcare Education.

BACKGROUND: No universal solution, based on an approved pedagogical approach, exists to parametrically describe, effectively manage, and clearly visualize a higher education institution's curriculum, including tools for unveiling relationships inside curricular datasets. OBJECTIVE: We aim to solve the issue of medical curriculum mapping to improve understanding of the complex structure and content of medical education programs. Our effort is based on the long-term development and implementation of an original web-based platform, which supports an outcomes-based approach to medical and healthcare education and is suitable for repeated updates and adoption to curriculum innovations. METHODS: We adopted data exploration and visualization approaches in the context of medical curriculum innovations in higher education institutions domain. We have developed a robust platform, covering detailed formal metadata specifications down to the level of learning units, interconnections, and learning outcomes, in accordance with Bloom's taxonomy and direct links to a particular biomedical nomenclature. Furthermore, we used selected modeling techniques and data mining methods to generate academic analytics reports from medical curriculum mapping datasets. RESULTS: We present a solution that allows users to effectively optimize a curriculum structure that is described with appropriate metadata, such as course attributes, learning units and outcomes, a standardized vocabulary nomenclature, and a tree structure of essential terms. We present a case study implementation that includes effective support for curriculum reengineering efforts of academics through a comprehensive overview of the General Medicine study program. Moreover, we introduce deep content analysis of a dataset that was captured with the use of the curriculum mapping platform; this may assist in detecting any potentially problematic areas, and hence it may help to construct a comprehensive overview for the subsequent global in-depth medical curriculum inspection. CONCLUSIONS: We have proposed, developed, and implemented an original framework for medical and healthcare curriculum innovations and harmonization, including: planning model, mapping model, and selected academic analytics extracted with the use of data mining.

Practical use of medical terminology in curriculum mapping.

BACKGROUND: Various information systems for medical curriculum mapping and harmonization have been developed and successfully applied to date. However, the methods for exploiting the datasets captured inside the systems are rather lacking. METHOD: We reviewed the existing medical terminologies, nomenclatures, coding and classification systems in order to select the most suitable one and apply it in delivering visual analytic tools and reports for the benefit of medical curriculum designers and innovators. RESULTS: A formal description of a particular curriculum of general medicine is based on 1347 learning units covering 7075 learning outcomes. Two data-analytical reports have been developed and discussed, showing how the curriculum is consistent with the MeSH thesaurus and how the MeSH thesaurus can be used to demonstrate interconnectivity of the curriculum through association analysis. CONCLUSION: Although the MeSH thesaurus is designed mainly to index medical literature and support searching through bibliographic databases, we have proved its use in medical curriculum mapping as being beneficial for curriculum designers and innovators. The presented approach can be followed wherever needed to identify all the mandatory components used for transparent and comprehensive overview of medical curriculum data.

OPTIMED Platform: Curriculum Harmonisation System for Medical and Healthcare Education.

This contribution introduces a new web-based OPTIMED platform for an effective harmonisation of medical and healthcare curriculum. Behind the engineering background stays an original methodology covering planning model based on formal parameterisation of curriculum, which fully support the outcome-based approach to education. With the use of developed system curriculum, designers and senior guarantors can provide a clear and transparent composition of compulsory and optional courses, and easily identify potential duplicities and overlaps across a domain of medical and healthcare education. For students, it means an absolutely new way of how to understand what is really taught during a learning period, including all necessary meta information. All members across the academic community are able to search and consequently display in detail the most important domains related to the particular year, term, course, medical discipline or topic. The presented solution significantly enhances the transparency and continuity of the environment in which the authors of the teaching materials as well as their consumers work daily. Suggestions for future improvements of the OPTIMED platform are discussed.

Interactive algorithms for teaching and learning acute medicine in the network of medical faculties MEFANET.

BACKGROUND: Medical Faculties Network (MEFANET) has established itself as the authority for setting standards for medical educators in the Czech Republic and Slovakia, 2 independent countries with similar languages that once comprised a federation and that still retain the same curricular structure for medical education. One of the basic goals of the network is to advance medical teaching and learning with the use of modern information and communication technologies. OBJECTIVE: We present the education portal AKUTNE.CZ as an important part of the MEFANET's content. Our focus is primarily on simulation-based tools for teaching and learning acute medicine issues. METHODS: Three fundamental elements of the MEFANET e-publishing system are described: (1) medical disciplines linker, (2) authentication/authorization framework, and (3) multidimensional quality assessment. A new set of tools for technology-enhanced learning have been introduced recently: Sandbox (works in progress), WikiLectures (collaborative content authoring), Moodle-MEFANET (central learning management system), and Serious Games (virtual casuistics and interactive algorithms). The latest development in MEFANET is designed for indexing metadata about simulation-based learning objects, also known as electronic virtual patients or virtual clinical cases. The simulations assume the form of interactive algorithms for teaching and learning acute medicine. An anonymous questionnaire of 10 items was used to explore students' attitudes and interests in using the interactive algorithms as part of their medical or health care studies. Data collection was conducted over 10 days in February 2013. RESULTS: In total, 25 interactive algorithms in the Czech and English languages have been developed and published on the AKUTNE.CZ education portal to allow the users to test and improve their knowledge and skills in the field of acute medicine. In the feedback survey, 62 participants completed the online questionnaire (13.5%) from the total 460 addressed. Positive attitudes toward the interactive algorithms outnumbered negative trends. CONCLUSIONS: The peer-reviewed algorithms were used for conducting problem-based learning sessions in general medicine (first aid, anesthesiology and pain management, emergency medicine) and in nursing (emergency medicine for midwives, obstetric analgesia, and anesthesia for midwifes). The feedback from the survey suggests that the students found the interactive algorithms as effective learning tools, facilitating enhanced knowledge in the field of acute medicine. The interactive algorithms, as a software platform, are open to academic use worldwide. The existing algorithms, in the form of simulation-based learning objects, can be incorporated into any educational website (subject to the approval of the authors).

Medical faculties educational network: multidimensional quality assessment.

Today, World Wide Web technology provides many opportunities in the disclosure of electronic learning and teaching content. The MEFANET project (MEdical FAculties NETwork) has initiated international, effective and open cooperation among all Czech and Slovak medical faculties in the medical education fields. This paper introduces the original MEFANET educational web portal platform. Its main aim is to present the unique collaborative environment, which combines the sharing of electronic educational resources with the use tools for their quality evaluation. It is in fact a complex e-publishing system, which consists of ten standalone portal instances and one central gateway. The fundamental principles of the developed system and used technologies are reported here, as well as procedures of a new multidimensional quality assessment.