The Collaborative Metadata Repository (CoMetaR) Web App: Quantitative and Qualitative Usability Evaluation

Background In the field of medicine and medical informatics, the importance of comprehensive metadata has long been recognized, and the composition of metadata has become its own field of profession and research. To ensure sustainable and meaningful metadata are maintained, standards and guidelines such as the FAIR (Findability, Accessibility, Interoperability, Reusability) principles have been published. The compilation and maintenance of metadata is performed by field experts supported by metadata management apps. The usability of these apps, for example, in terms of ease of use, efficiency, and error tolerance, crucially determines their benefit to those interested in the data. Objective This study aims to provide a metadata management app with high usability that assists scientists in compiling and using rich metadata. We aim to evaluate our recently developed interactive web app for our collaborative metadata repository (CoMetaR). This study reflects how real users perceive the app by assessing usability scores and explicit usability issues. Methods We evaluated the CoMetaR web app by measuring the usability of 3 modules: core module, provenance module, and data integration module. We defined 10 tasks in which users must acquire information specific to their user role. The participants were asked to complete the tasks in a live web meeting. We used the System Usability Scale questionnaire to measure the usability of the app. For qualitative analysis, we applied a modified think aloud method with the following thematic analysis and categorization into the ISO 9241-110 usability categories. Results A total of 12 individuals participated in the study. We found that over 97% (85/88) of all the tasks were completed successfully. We measured usability scores of 81, 81, and 72 for the 3 evaluated modules. The qualitative analysis resulted in 24 issues with the app. Conclusions A usability score of 81 implies very good usability for the 2 modules, whereas a usability score of 72 still indicates acceptable usability for the third module. We identified 24 issues that serve as starting points for further development. Our method proved to be effective and efficient in terms of effort and outcome. It can be adapted to evaluate apps within the medical informatics field and potentially beyond.

Determining the impact of a clinic coordinator on patient access and clinic efficiency in a pediatric multidisciplinary spina bifida clinic using medical informatics

PURPOSE: The objective of this study was to analyze the effects on patient access by decreasing missed appointments after hiring a clinic coordinator using medical informatics. METHODS: A single-center retrospective analysis of the rates of missed appointments before and after hiring a clinic coordinator in a multidisciplinary spinal differences clinic were analyzed using a commercially available business software system (SAP® Business Objects). The total number of clinic visits was collected for each month to determine the access available for patients. RESULTS: The median number of missed appointments per clinic by month before employing the clinic coordinator was higher than in the two years following implementation (p < 0.0005). No differences were seen in the number of available appointment slots per month indicating no new clinics were needed to improve patient access (p = 0.551). Projected billing amounts prior to hiring the clinic coordinator indicated that $91,520 was lost in the 2 years prior to hiring this coordinator compared to $30,160 lost during the 2 years following the creation of this position (p = 0.0009). CONCLUSION: Hiring a clinic coordinator decreased the rate of missed appointments and was a cost-efficient intervention to improve patient access and provide effective patient care in a multidisciplinary setting.

Interactive Hybrid Medical Conference in Japan

This paper reports medical informatics conference held in November 2020, which is under influence of CoVID-19, in hybrid way. The methods taken to ensure presenters, chairpersons, participants, supporting staffs, vendors seamless infrastructure regardless of on line or on site. This made question answer session rich as usual. Some other outcomes newly made possible are reported, such as demonstration shown on big personal screen, much better than slide projector screen, new participants who became able to participate over prefecture boundaries in challenged times.

Mapeando a dinâmica da informática médica: uma análise bibliométrica do campo científico

A saúde digital é um assunto emergente em fóruns acadêmicos, nas políticas públicas e nas organizações de saúde. Supondo que a saúde digital deriva de conhecimentos da informática médica, este artigo apresenta resultados de uma pesquisa bibliométrica sobre a evolução conceitual e tecnológica do campo da informática médica nas últimas décadas, enfatizando aspectos metodológicos. O trabalho realizou bibliometria em metadados de 100 mil artigos indexados sob a categoria ‘medical informatics’ na base de dados Web of Science entre os anos de 1960 e 2020. Foram realizadas análises longitudinais com utilização dos softwares Bibliometrix e CorText em três eixos: quantidade de publicações, países dos autores e palavras-chave. Conforme a hipótese metodológica que orientou o estudo, as mudanças terminológicas verificadas ao longo do tempo oferecem uma visão aproximativa das mudanças conceituais e tecnológicas do campo de pesquisa da informática médica. Os resultados mostram que esse campo de investigação apresentou crescimento consistente ao longo das últimas seis décadas, expandindo-se para diferentes países. As mudanças terminológicas e conceituais detectadas pela análise de palavras-chave permitiram a identificação de períodos temporais definidos, associados a rótulos genéricos como ‘health informatics’, ‘e-health’. O rótulo ‘medical informatics’ é recorrente como termo mais geral a designar o campo de aplicação, em razão de sua adoção por associações científicas internacionais a partir da década de 1970. Nos últimos cincos anos, pode-se identificar a emergência do termo ‘digital health’, que possivelmente será o conceito dominante na década que se inicia. A análise de palavras-chave também indica a associação entre mudanças terminológicas e de tecnologias, o que reforça as relações entre conceitos e aplicações tecnológicas de cada período.

Analyzing Healthcare Data Using Water Wave Optimization-Based Clustering Technique

The medical informatics field gets wide attention among the research community while developing a disease diagnosis expert system for useful and accurate predictions. However, accuracy is one of the major medical informatics concerns, especially for disease diagnosis. Many researchers focused on the disease diagnosis system through computational intelligence methods. Hence, this paper describes a new diagnostic model for analyzing healthcare data. The proposed diagnostic model consists of preprocessing, diagnosis, and performance evaluation phases. This model implements the water wave optimization (WWO) algorithm to analyze the healthcare data. Before integrating the WWO algorithm in the proposed model, two modifications are inculcated in WWO to make it more robust and efficient. These modifications are described as global information component and mutation operator. Several performance indicators are applied to assess the diagnostic model. The proposed model achieves better results than existing models and algorithms.

One Conference, Three Proceedings – Which Papers Should I Submit and How? A Publication Strategy for Young Scientists Regarding the GMDS Annual Conference and Beyond (Editorial)

The primary intention of any scientific work is to share the gained knowledge and to contribute to the knowledge and progress in the scientific domain. The wide range of journals and conferences, each with specific submission requirements, can be difficult to navigate, especially for young scientists without extensive experience. But a suitable publication strategy can be helpful, especially at the beginning of a scientific career. Using the annual conference of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) e.V. as an example, this editorial highlights fundamental differences, advantages and disadvantages, as well as assistance in selecting the right form of submission.

Hands on the Medical Informatics Initiative Core Data Set — Lessons Learned from Converting the MIMIC-IV

With the steady increase in the connectivity of the healthcare system, new requirements and challenges are emerging. In addition to the seamless exchange of data between service providers on a national level, the local legacy data must also meet the new requirements. For this purpose, the applications used must be tested securely and sufficiently. However, the availability of suitable and realistic test data is not always given. Therefore, this study deals with the creation of test data based on real electronic health record data provided by the Medical Information Mart for Intensive Care (MIMIC-IV) database. In addition to converting the data to the current FHIR R4, conversion to the core data sets of the German Medical Informatics Initiative was also presented and made available. The test data was generated to simulate a legacy data transfer. Moreover, four different FHIR servers were tested for performance. This study is the first step toward comparable test scenarios around shared datasets and promotes comparability among providers on a national level.

German Medical Data Sciences in Studies in Health Technology and Informatics – Reflections on the Fifth Volume

Since 2017, the German Society for Medical Informatics, Biometry and Epidemiology e.V. (GMDS) offers the submission of full papers to the annual meetings, optional in Studies in Health Technologies and Informatics (Stud HIT) or in GMS Medical Informatics, Biometrics, and Epidemiology (MIBE). GMDS’ aim is to increase the attractiveness of the conference and paper submission process in particular for young scientists and to increase the visibility of the conference. A standardized peer review process was established. Since 2017, a 25–35% of the contributions have been submitted as full papers. A total of 177 papers were published in Stud HTI. With an unofficial journal impact factor of 1.088 (2019) and 0.540 (2020), the papers were cited with a frequency similarly to national medical journals or full paper contributions of International medical informatics conferences.

Automated Creation of Expert Systems with the InteKRator Toolbox

Expert systems have a long tradition in both medical informatics and artificial intelligence research. Traditionally, such systems are created by implementing knowledge provided by experts in a system that can be queried for answers. To automatically generate such knowledge directly from data, the lightweight InteKRator toolbox will be introduced here, which combines knowledge representation and machine learning approaches. The learned knowledge is represented in the form of rules with exceptions that can be inspected and that are easily comprehensible. An inference module allows for the efficient answering of queries, while at the same time offering the possibility of providing explanations for the inference results. The learned knowledge can be revised manually or automatically with new evidence after learning.