Ebook: Health Informatics Vision: From Data via Information to Knowledge

This volume contains the accepted full papers of the ICIMTH (International Conference on Informatics, Management, and Technology in Healthcare). The Scientific Programme Committee presents to the academic and professional community of Biomedical and Health Informatics the scientific outcomes of the ICIMTH 2019 Conference, which is being held from 5 to 7 July 2019 in Athens, Greece.

The ICIMTH 2019 Conference is the 17th Annual Conference in this series of scientific events, gathering scientists working in the field of Biomedical and Health Informatics from all continents as well as from the hosting country.

This year the Conference is focusing on increasing and improving our Knowledge of Healthcare in applications spanning the whole spectrum from Clinical Informatics, Health Informatics to Public Health Informatics as applied in the healthcare domain. Since Management and Organisational issues play an important role in the implementation phase of Biomedical and Health Informatics applications, topics related to the above themes are also included as an integral part of the overall theme of the Conference. We are examining the field of Biomedical and Health Informatics in a very broad framework presenting the research and application outcomes of Informatics from cell to populations, including a number of Technologies such as Imaging, Sensors, and Biomedical Equipment and Management and Organisational aspects, including legal and social issues and setting research priorities in Health Informatics. In essence, Data, Informatics, and Technology inspires health professionals and informaticians to improve healthcare for the benefit of patients.

This volume incorporates only the full papers accepted for oral presentation. It should be noted that the Proceedings are published in this series of the Conference as an e-book with e-access for ease of use and browsing without losing any of the advantages of indexing and citation in the biggest Scientific Literature Databases, such as Medline and Scopus that the series of Studies in Health Technology and Informatics (SHTI) of IOS Press provides.

At the end of the deadline we had 150 submissions, from which after reviewing we have accepted 95 as full papers to be included in the volume proceedings.

The Editors would like to thank the Members of the Scientific Programme Committee, the Organising Committee, and all Reviewers, who have performed a very professional thorough and objective refereeing of the scientific work in order to achieve a high-quality publishing achievement for a successful scientific event.

Athens, 30.05.2019

The Editors,

John Mantas, Arie Hasman, Parisis Gallos, Katia Kolokathi, Mowafa S. Househ, and Joseph Liaskos

This lecture is dealing with new, future forms of collaboration and with its (hopefully existing) extended synergies, which may now will come in our era of digitization. Entities in this collaboration are we, the human beings, and other living entities such as animals with ‘natural intelligence’ as well as non-living entities, in particular functionally comprehensive machines, with ‘artificial intelligence’. Based on lessons learned during the last years, among others in a task force on synergy and intelligence (SYnENCE) of the Braunschweig Scientific Society, five consequences for future health care with respect to this collaboration are put for discussion: (1) functional comprehensive ‘intelligent’ machines should be regarded as entities, not as modalities, (2) such machines have to become users of information systems in health, in addition to human entities, appropriate (3) legal and (4) ethical frameworks have to be developed, (5) extended collaboration in medicine and health care needs to be evaluated in accordance with good scientific practice. The statements of Karl Jaspers, made in 1946 on medicine and on technology, may help us to find a good way.

Execution of multiple computer-interpretable guidelines (CIGs), enables the creation of patient-centered care plans for multimorbidity, which can be monitored by clinical decision support systems. This paper introduces an execution framework to manage multiple, concurrently implemented CIGs, also discussing the approaches used such as constraint satisfaction.

We conducted a literature review on the use of accelerometers in medical context, on Pubmed and IEEEXplore. This includes 440 relevant articles. The subsequently identified publications were classified with regard to the medical context (prevention, diagnostics, therapy) as well as according to medical-informatics field of application, e.g. activity-tracking, fall prevention/detection and gait analysis. Furthermore, we analyzed their clinical integration or potential for the clinical usage, including both the technical integration into the clinical structures and respective claims and requirements, e.g. privacy or hygiene. This analysis shows five categories (“without indication” to “concrete implementation”). In 90% no statement was made on clinical integration. Only two articles could be found with concrete implementations, but these descriptions are limited to a more conceptual technical side. This poor situation in final clinical integration has to change in the future, because only by the premise “from workbench to bedside” the medical benefit is given.

Access to mentors for education in surgical subspecialties is a challenge in many hospitals. Videoconferencing (VC) provides real-time communication between mentors and mentees despite dispersed geographical locations. In Norway, an educational pathway of a specific laparoscopic surgical procedure was carried out using VC. The surgical training lasted for three months and was video recorded. The dataset covers the educational procedure, constituting of a trajectory of eight patient cases. During a model of stepwise distancing of the physical presence of the mentor, the collaborative work using VC leads the mentee to become an expert. VC is a tool for both collaboration and representation, as the picture on the VC offers the same information to both the mentor and the mentee. The communication is characterized by guidance and explanations of why specific actions are necessary for problem-solving. The use of VC was a presumption for becoming an expert in this procedure.

This paper provides a summary of the Privacy Management Analysis method followed for the analysis of the International Patient Summary exchange use cases of Trillium II Project. The objective is to recommend the required security and privacy measures by providing traceability from Regulations/Principles/Preferences to the recommended Security & Privacy Measures that needs to be implemented in pilots.

Nowadays, the great majority of the healthcare organizations has been criticized due to the high costs and low efficiency and are facing a critical situation aggravated by unmet demand and aging population. Availability of medicines is one of the clearest indicators that a healthcare organization is working efficiently. Medicines represent a large portion of the costs in the health services due to the significant value of these products and their storage and control requirements. Shortages of inventory have become a severe problem at the Brazilian healthcare organizations. The purpose of this work is to present the deployment of a Decision Support System which supports real-time inventory control and medicine tracking providing transparency and accessibility of this critical information at the Brazilian National Cancer Institute.

‘Research through innovation’ is the current demand echoing throughout the healthcare industry, healthcare institutions tend to invest heavily in technology. Data Science being the major disruptor across industries is being incepted through establishment of innovation and R&D centers within their respective organizations. Data Science has become a critical component for the healthcare industry, supporting innovative approaches towards advanced clinical practice, clinical research and corporate management, serving to build an intelligent enterprise. Every healthcare institution maintains a good number of technical staffs with IT, Software, data management, BI and analytical capabilities, aiding the institutions to manage report and publish its data in some or the other way, grossly covering most aspects of data science knowingly or unknowingly. Setting up a new entity within the organization by recruitment of staff with Data Science based skill sets would be the first thought to strike the management, which in contrast would end up as disaster when it comes to understanding the organizational culture, processes, infrastructure, platforms, data etc. Hence in order to setup a data science hub, regrouping or realigning some of the existing institutional resources is crucial. With this approach, the Data Science hub would carry out three primary functions. The “Project Management & Data Sourcing”, the “Data Management & General Analytics” and “Advanced Analytics”. Current resources can be reorganized within the first two functions, further; it would be about establishing an advanced analytics group within the hub which would perform the Machine learning and AI functions.

Even if, English is generally used for international communication, it is essential to keep in mind that research is running at the local level by local teams generally communicating in their local/national language. Bearing these in mind, the “European Federation for Medical Informatics Working Group on Health Informatics for Inter-regional Cooperation” has as one of its objectives, to develop a multilingual dictionary focusing on Health Informatics as a collaboration tool allowing improving international and more particularly European cooperation. This dictionary is implemented as a part of HeTOP (Health Terminology/Ontology Portal) which is currently integrating more than 70 terminologies and ontologies in 32 languages. The EFMI Dictionary main aims are helping medical librarians, translators, academic and industrial researchers understanding better one another and supporting students self-learning.

Brazil has a complex situation in cancer treatment services. The incidence rates have reached around 600.000 new cases each year. The development of an Oncology Decision Support System (ODSS) that support cancer treatment is amongst the priorities in the cancer control program. The purpose of this article is to study the ODSS deployment at the Brazilian National Cancer Institute. The implementation of this Clinical Decision Support System employed on the management, processing, and analysis of Brazilian cancer clinical data can be considered a disruptive innovation which changes the clinical decision-making process radically.

Gestational Diabetes Mellitus (GDM) has been associated with a plethora of maternal and neonatal comorbidities as well as adverse pregnancy outcomes. Evidence supports that identifying women with GDM and tight controlling of blood glucose (BG) levels are the fundamental steps for an effective management and prevention of risks associated with GDM. Recent advances in mobile phone applications have shown that they may offer personalized health care services, improve patient’s care, independence and self-management as well as enhance patient’s compliance to BG monitoring and treatment. Our aim was to identify and appraise main mobile phone applications that were evaluated by published clinical studies. Therefore, mobile applications that were accepted and deployed by healthcare providers, mainly hospitals, such as MobiGuide (Spain), Pregnant+ (Norway) and GDm-Health (UK) were reviewed herein.

The buzz words ‘Data Science’ and ‘Data Scientist’ are trending high in this age of information. The boundaries are still undefined, the exact skill sets are unclear, and the job description is still murky. This is an attempt to identify some mandatory or desired skills based on what data science demands from a data scientist. A very generic job description for a data scientist is ‘A person who can perform advanced analytics on the institutional data’, this gives a very unclear picture to the decision maker to identify the right resources within their data science activity. Practically the data scientist should be the one who can understand and moreover be involved with the data life cycle starting from inception > collection > operation > extraction > observation > preparation > description > prediction > prescription > Archival. Each of these aspects of data has a science behind it. An old team ‘Jack of all trades’ briefly defines this job description. A good data scientist essentially needs to be a good programmer, a good business/system/data analyst, a good statistician, one who can seamlessly visualize data, and is empowered with a vision to use and apply the necessary tools, techniques and methodologies in a scientific and applicable realistic way. Healthcare/Research environment is a complicated vertical when it comes to data, hence having domain knowledge is almost critical, complying with aspects of data governance such as patient privacy, consent, ethics etc.

The use of automated dispensing cabinets (ADCs) to enhance medication processes in hospitals has been increasing recently. Studies evaluated the effects of this technology on patient safety, workflow efficiency and cost reduction. To evaluate factors affecting nurses’ attitudes and acceptance of using ADCs, an online survey, including seven categories with closed-ended questions and one open-ended question, was developed based on technology acceptance model and instruments used in previous studies. Response rate was 29.4% of 1,062 nurses at King Faisal Specialist Hospital and Research Centre, Jeddah, Saudi Arabia. Perceived usefulness, perceived ease of use, perceived usefulness to enhance control systems and training have positive effects on improving nurses’ attitudes and increasing acceptance of using ADCs. Perceived risks had negative effects. The qualitative analysis of the open-ended responses supported these results and helped to identify many areas for improvement, especially in addressing perceived risks associated with the use of this technology.

Medical data are being generated in large quantities. However, these data are rarely used beyond their primary purpose. Big data methods to medical data offer the opportunity to transform healthcare. The healthcare industry has been a lot less successful than other industries in applying these new tools. Main reasons are privacy concerns and the fact that medical data in Germany are scattered across institutions. The method of data donation can offer a solution. The first aim of the proposed Medical Data Donation Enabler (MADE) project is to investigate ethical, legal and socio-technical barriers to data donation. The second aim is to develop a concept of a medical data donation process model that addresses the barriers by providing a data donation process model. The process model concept created through MADE could be provided for this purpose.

The last four decades witnessed a huge progress in digitizing health information, representing an unmatched opportunity for utilizing health analytics in improving the quality of healthcare and reducing its costs. To learn more about different challenges facing the successful utilization of health analytics, a careful review of literature was conducted, and a qualitative analysis was used to explore and classify these challenges. Three main categories of challenges were identified. 1) Technological challenges; hardware, software, and data content, 2) Human challenges; knowledge, experiences, beliefs and attitudes, and end user behaviors, and 3) Organizational challenges; managerial, financial, and legal barriers to optimal utilization of health analytics. The non-technological problems seem to be harder to solve as well as more time consuming, including the existence of a specific business need and a clear vision to guide the project. In addition, health analytics should always be built with the end users in mind.

Medical laboratories process and store sensitive data during four major phases: arrival of patients in the laboratory premises and registration of their data, pre-analytical, analytical and post-analytical phases. ISO 15189 has specific requirements concerning the management of the laboratory data in terms of security, availability and protection. The aim of the present study was to examine major aspects of the General Data Protection Regulation (GDPR) integration in medical laboratories that comply with the ISO 15189 standard, including data breach and informed consent. To the best of our knowledge, this is the first study dealing with this subject in the healthcare sector. Accredited medical laboratories need to modify their ISO 15189 Quality System documentation and processes applying appropriate additions and adjustments in order to incorporate GDPR requirements in a clear manner.

Clinical Research is a complicated process within a research institution or a tertiary care hospital, almost all research project proposal needs to get an institutional review board (IRB) approval before any research activity takes place. IRB approval involves various processes, in form of sub-committees through which the proposal is reviewed. It is of utmost importance to understand the complete functioning of an IRB, in order to automate the various processes using a management system. The Research office entity forms the central body managing the IRB functions. It provides all sorts of administrative support as far as guidelines, documentation, communication and co-ordination is concerned; hence the research office forms the administrative wing of the IRB. Further the IRB has several sub-committees such as the Ethics Committee, Basic Research committee and the Animal Care and Use Committee. Each committee has a chairperson and several members from different specialty to cover all the aspects of research. Each committee may have its own process/workflow of approval, but usually the process of each committee is somewhat similar to each other. Apart from these workflows process the things that needs to be digitized would include researcher’s profile, pre-award and post-award management, publication management, graduate student management and research analytics for the organization.

Emergencies involving children are rare events. Due to the associated lack of routine and special features in pediatric resuscitation, it is prone to errors and the results are unsatisfactory. One way of tackling this problem is to use assistance services. However, due to the process, these services cannot be easily integrated. One possibility is the use of Head Mounted Displays. These are often controlled via voice commands. With medical terms, the voice control implemented as standard can quickly become unusable. A wearable app was therefore developed for this paper and evaluated according to ISO/IEC 30122-2:2017 to determine the extent to which the voice control of a state-of-the-art smartglass works in quiet and noisy conditions for use during a resuscitation. Since the commands were well understood and the app could be reliably controlled, the use of voice control in an assistance service is conceivable.

Although adherence is a key factor for successful treatment of chronic diseases, only about 50% of patients achieve good adherence. However, health enabling technologies and gamification offer new possibilities to enhance patient’s motivation. In physical rehabilitation, various applications exist. As these often stress a specific part of the rehabilitation process, we introduce a six-step new holistic approach to apply game design elements in the entire rehabilitation process, while focusing on patients with musculoskeletal diseases of the shoulder.

Surgery cancellation is a well-recognized quality problem within hospitals. The e-Team Surgery project addressed the problem of elective surgery cancellation at a Norwegian hospital and explored the potential to reduce surgery cancellation by providing a tool for secure online communication between the hospital and the patient. This communication would occur before surgery while the patient was still at home. The causes of elective surgery cancellation are divided into two major categories: hospital- and patient-related reasons. As part of the e-Team Surgery project, this study addressed patient reasons for cancelling surgery through qualitative interviews with 11 patients who fit these criteria. The study found that most patients called the hospital to reschedule, not to cancel, their upcoming surgery. The patient interviews had significant implications for the e-Team Surgery project. They affected the overall understanding of the surgery cancellation problem and made more clear the data and information needed when developing sustainable systems to reduce elective surgery cancellation.

In the field of oncology, survival analysis is one of the most important tools in terms of measuring therapy success, evaluating risk or prognostic factors. Within this work, a variety of common survival analyses were embedded into a real-time analysis platform based on a comprehensive oncological dataset. The analysis platform utilizes an in-memory database, therefore allowing spontaneous adjustments of the survival curves to selections and stratifications. In contrast to classical statistics, where individual scripts have to be formulated for every possible request, the running system allows the deduction of instantaneous results.

Medication errors are a significant health problem and a serious threat to patient safety. In Norway, an estimated one-third of the elderly population has been exposed to potentially inappropriate medications. The Norwegian government has assumed a pivotal role in reducing medication errors and providing safer medication management for its citizens, particularly through the national eHealth system’s e-prescription and Summary Care Record. In the present study, we depart from the governmental eHealth initiatives and examine why access to pharmaceutical information is not sufficient to solve the problem with medication errors. Empirical data were collected from 2015 to 2019 through the conduction of 56 qualitative interviews that were transcribed, thematically coded and analysed. The results illustrate how eHealth systems are helpful, at the same time, we emphasise changed work practices and professional knowledge-sharing as a basis for solving the issue of medication errors.

Socio-constructive instructional designs for online-based learning focus on interaction and communication of students to allow in-depth learning. The objective of this study is to analyze whether increased interaction of students in online-based learning settings may contribute to better outcome. We developed indicators for presence, participation, and interactivity of students. We extracted log data from the learning management system for 31 students in 10 online courses (n=123 course attendances). We correlated indicators to final grades and also applied a decision tree based machine learning approach. We found only weak to moderate correlations between the indicators and final grades, but acceptable results concerning prediction of students’ success based on the indicators. Our results support the theory that student presence and participation in online-based courses is related to learning outcome.

The purpose of this study is to ascertain the readiness of the public hospital in Greece to comply with the new Regulation for protecting personal data (GDPR). A qualitative research was carried out by using structured interview with experts and relevant hospital executives of the 2nd Health Region for collecting the data. Despite the mandatory application of the new Regulation by Hospitals, the right to be forgotten and the other rights on personal data in healthcare are virtually not applicable.

To understand the home-based difficulties encountered in the health care pathways of patients with Amyotrophic Lateral Sclerosis (ALS), we must annotate a large amount of textual data, from a database created by the ALS Île de France coordination network. For this purpose, we have developed a modular ontology, consisting of four modules, and a semantic annotation tool integrating the created ontology. The specificity of our approach is the creation of equivalent classes at different levels of the ontology. These equivalent classes represent variables of interest allowing a statistical approach and a clinical analysis of comprehension of care pathways ruptures causing.