Ebook: Data, Informatics and Technology: An Inspiration for Improved Healthcare

The current volume presents the accepted papers of the ICIMTH (International Conference on Informatics, Management and Technology in Healthcare). The Organising Committee and the Scientific Programme Committee would like to present to the academic community the scientific outcomes of the ICIMTH 2018 Conference, which is being held from 6 to 8 July 2018 in Athens, Greece.

The ICIMTH 2018 Conference is the 16th Annual Conference in this series of scientific events, gathering scientists from all continents as well as from the hosting country in the field of Biomedical and Health Informatics.

The Conference is focusing on Improving Healthcare by the use of Data in Biomedical Informatics applications spanning the whole spectrum from Clinical Informatics, Health Informatics to Public Health Informatics as applied in the Healthcare domain. Considering that Management and organisational issues play an important role in the implementation phase of Biomedical Informatics applications, topics related to the above themes are also included as an integral part of the overall theme of the Conference. We are treating the field of Biomedical Informatics in a very broad framework, examining the research and applications outcomes of Informatics from cell to populations, including a number of Technologies such as Imaging, Sensors, and Biomedical Equipment and Management and Organisational aspects, such as 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 and is published in the Studies in Health Technology and Informatics (HTI) book series which has the advantage of being indexed in some of the major indexing services, such as Medline and Scopus.

At the end of the deadline we had 130 submissions, from which after reviewing we have accepted 80 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 done a very professional, thorough and objective refereeing of the scientific work to produce a high quality publishing achievement for a successful scientific event.

Athens, 4.06.2018

The Editors,

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

Depression is the most common psychiatric disorder worldwide, which affects more than 300 million people. We aimed to detect depressed patients and healthy people automatically. We work on the PHQ-9 questionnaires and reduced it to a PHQ-5 questionnaires with a new cut-off value of 8 to detect depressed patients. We trained a Neural Network with 70% of our dataset. Then, the proposed classifier was tested with two datasets. The first one consists of 30% of PHQ-5 datasets, which could achieve 85.69%, 99.11% and 90.56% for accuracy, sensitivity and specificity respectively. The second test dataset consists of physical patient's parameters which recorded during a study in the Hanover Medical School. This classifier has shown good results in the detection of depression based on these two datasets.

The characteristics of the “blockchain” technology and especially its decentralized nature lead to the notion of neutrality, censorship resistance, and absolute truths, which makes the concept interesting for many different domains, such as finance, supply chain management, or the energy sector – of course also for the healthcare area (eHealth). Blockchains also offer the possibility for well-known access points for a distributed system with easy to use and simple to integrate programming interfaces, which makes it interesting as a central point for electronic healthcare data exchange in a distributed environment. This paper presents a concept for integrating and sharing distributed personal healthcare records based on smart contracts implemented on an Ethereum blockchain.

Wearable and mobile devices are now commonly used in our daily activities, giving users instant access to various information. One the one hand, wearable and mobile technologies are developing at a fast rate and have been increasingly ubiquitous. On the other hand, the potential of their application in health is yet to be fully explored. This paper attempts to sketch an overview of wearable and mobile applications in the healthcare domain. We first review how various wearable and mobile applications are being used to monitor and manage health conditions. Then how connections between physiological factors and psychological factors can help with disease prevention is presented. Finally, challenges and future directions for further developments of these emerging technologies in health are discussed.

The use of new technology seems to be an important factor that contributes to the overall ability to adapt and achieve higher independence. Technologies using digital games have gained the great interest of the scientific community as there are many advantages for both effectiveness and benefits, physically and mentally, providing the opportunity for essential and enjoyable training. This study presents an important initial step utilizing the LLM Care service which focuses on the needs and challenges for the health and daily living of people with Down syndrome (DS) by applying new technology hardware and software. People with cognitive impairments, such as memory, attention and motivation problems may also benefit from this kind of cognitive support that assistive technology offers.

Classification of a continuous risk score into risk levels is common. However, while the absolute risk score is essential, it is arguably unethical to label anyone at ‘high, moderate or low risk’ of a serious event, simply because management based on a single criterion (e.g. avoiding the target condition) has been determined to be effective or cost-effective at a population level. Legally, mono-criterial risk labeling can inhibit the obtaining of a fully-informed, preference-based consent, since multiple considerations (various benefits and harms) matter to most individuals, not only the single criterion that is the basis of the provided risk category. These ethical and legal challenges can be met by preference-sensitive multi-criteria decision support tools. In this future vision paper, we demonstrate, at a conceptual proof-of-method level, how such decision support can and should be developed without reference to risk-level classifications. The statin decision is used as illustration, without any empirical claims.

Accelerating progress in screening technologies, e.g. genetic testing, means more individuals are facing the stressful decision of whether to request the test. Fully-informed and preference-based consent, as well as ethical practice, requires the full range of benefits and harms from any test or treatment to be identified and assessed from the individual's point of view. For both ethical and legal reasons, we see the decision on whether to undertake a genetic screening test being increasingly seen, in future, as calling for a personalised analysis of the full range of subsequent management options. The conventional dissociation of ‘risk assessment’ and ‘risk management’ phases is thereby ruled out. One way of addressing the resulting challenge is through personalised multi-criterial decision support tools. In this vision paper we provide conceptual proof of method of how such an interactive online tool could function. The polygenetic genetic screening decision is used, solely as illustration.

Introduction: Interoperability of health information systems is one of the key challenges of modern healthcare systems. A weak spot in this technology stack of interoperability protocols as defined by HL7 and IHE is cross affinity domain exchange of access control information and policies. In several industries the Blockchain technology had a major breakthrough. The goal of this paper is to elaborate how to exchange cross affinity domain access information enhancing well established IHE networks with block chain technology.

Methods: Using literature analysis and research on current interoperability standards the state of the art of securely exchanging medical information was elaborated. We enhanced this system with the capabilities of the peer2peer based Blockchain network elaborating the workflows of exchanging the access control specific information.

Results: We extended an IHE based affinity domain by adding a block chain ledger to the deployment. This ledger is fed with XACML based policies which are propagated through the peer2peer based system. Using the Blockchain protocol other affinity domains are informed of the change and can retrieve the information. Acting as an additional source of policies and consents the policy decision point is capable of querying this network and building a decision based on the retrieved information.

The ever-increasing flood of information, especially in the medical-clinical field, inter alia due to the increase of data-intensive mobile/wearable devices, is one of the biggest challenges of medical informatics. In this work different possibilities of the integration of wearable devices on the example of the development of a fall prevention system are presented and classified. We started with a commercial off-the-shelf one-on-one system (Shimmer/Arduino) using a Bluetooth connection, integrated via nurse call system as Human-Machine-Interface. During the evaluation of the system we mentioned several new requirements and optimization possibilities. Thus, we adjusted the hardware-software-system; the near-field communication was realized by IEEE802.15.4, we replaced commercial off-the-shelf devices with highly-specialized open hardware in-house developments and we transferred the nurse call integration by setting up our own network and integrating this into an existing (wireless) local area network. With this development, the energy-efficient, simple and intuitive mechanisms of proximity communication via IEEE802.15.4 can be combined with the benefits broadband functionalities, e.g. of Wi-Fi, with both worlds benefits and the compensation of some disadvantages.

Cloud computing is a reality in most business sectors. Hospitals have been more reluctant to adopt cloud technology due to strict data security regulations. Cloud could provide economies of scale reducing Information Technology spending in the Greek state-owned hospitals, while giving the opportunity to the hospitals to upgrade their profile offering web-based services. We propose a simple, robust and easy to apply approach for the Greek hospitals, focusing on clinical and laboratory data in order to move to the cloud environment. To the best of our knowledge, there is no other study regarding the adoption of cloud infrastructure in the Greek hospital sector. This innovative method could transform the business model of the hospitals.

This paper reviews several architectures of Computer-Based Speech Therapy (CBST) systems and solutions and describes an architecture for an Entropy-Based Sound Speech Disorder (SSD) Screening System aimed at by our research project. The proposed architecture and data flow scenario aim to provide a fully-automated Entropy-based SSD Screening System, to be connected with CBSTs and to be used as a research infrastructure for further refinement of the objectives of our research project.

The paper presents a 3D healthcare informatics support for Hand Rehabilitation after injury. As a novelty, the application uses the Leap Motion sensor for patient's gestures recognition, and videos to illustrate to the users the hand exercise to perform. The implemented application provides feedback to users regarding the correctness of the performed recovery gestures/exercises. The data related to hand rehabilitation is saved in a database and offers to the Medical Rehabilitation Experts the possibility to monitor the patients in a more consistent manner. To assess the efficiency and accuracy of the application the application will be tested following a usability plan.

The alpine space is characterized with rural regions, often hard to reach for mobile care. As part of the EU-funded INTESI project, a mobile platform for vital sign self-monitoring for patients who receive mobile care was developed. Based on a thorough analysis of user requirements and available technology a platform was established, that integrates several Bluetooth low energy devices for measuring vital signs. The developed VITAMO app further enables clients and nurses to easily govern measurements and jointly take control of a client's health during the care process. In addition, the system supports the communication of clients and nurses electronically. The internal data structure adheres to current healthcare standards e.g. FHIR and offers easy interfaces for future applications. The complete system was applied in a pilot study and got formally evaluated.

Current medical systems need to be able to communicate complex and detailed medical data securely and efficiently. However, the quantity of available healthcare data is rising rapidly, far exceeding the capacity to deliver personal or public health benefits from analyzing this data. Thus, a substantial overhaul of methodology is required to address the real complexity of health. This can be achieved by constructing medical domain ontologies for representing medical terminologies, considered to be a difficult task, requiring a profound analysis of the structure and the concepts of medical terminologies. In this paper, a mechanism is presented for constructing healthcare ontologies, while matching them to HL7 FHIR Resources ontologies both in terms of syntactic and semantic similarity, in order to understand their nature and translate them into a common standard to improve the quality of patient care, research, and health service management.

Rehabilitation aims at brain rewiring through intensive practice following brain injury. This paper presents a new supportive mechanism that will be used to isolate wrist movement and in combination to the use of serious games, to act as a motivational tool to improve adherence during home-based practice. The paper describes the proposed methodology employed to carry out the home-based programme while leap motion is used to monitor and evaluate these exercises.

BMI Investigator (BMII) is an interactive web-based tool with a learning knowledge base, which provides a way for researchers to query structured, unstructured, genomic and image data contained in a data warehouse. We demonstrate how development of an efficient, usable, and learnable web interface for a diverse group of research stakeholders benefits from an iterative human-centered participatory design process utilizing a team of clinicians, students, programmers, and informatics experts.

In rehabilitation, exergames and serious games are widely usedin order to motivate patients in the therapeutic procedure. Patients are asked to modify their incorrect motor patterns or reinforce the proper ones through activity rather than exercise. Interactive applications as such, can have a huge impact on a patient's motivation making repetitive physical exercises into pleasant experiences, thus maximizing the gains of therapy. In this paper we present the design and implementation of a serious game platform based on virtual 3D game environment and leap motion controller for interaction. For each session, achieved goals and response to stimuli is recorded and analyzed. Preliminary analysis results from evaluating the game with healthy subjects are encouraging.

A Urine Monitoring Device (UMOD) has been designed and implemented for monitoring postoperative urination. This device has been created primarily to assist nurses and doctors monitor patients during their postoperative and recovery period. Furthermore, to reduce the burden of the nursing staff required to regularly monitor and empty the urine bags saving them precious time. The device consists of a stand and a load cell where the urine bag is attached. The stand is light and can easily move shall the patient require to move. An ESP Wi-Fi microprocessor module is used to calculate the rate of flow of urine in real time, identify and ignore any false readings due to accidental movements of the urine bag using an accelerometer and transmit the readings to a server / cloud through the local Wi-Fi.

Life is changing after recognizing a pregnancy. Then the future parents, who are often healthy individuals, need to change their lifestyles, meet different healthcare institutions, follow new rules, and reschedule their everyday activities. This paper illustrates the design and development of a novel mobile application supporting future parents in planning their activities after recognizing the pregnancy. The focus is on identifying and sharing relevant data between future-parents, healthcare institutions, and the supporting social groups. First, the design and development of the application are sketched, and then we present early evaluation results with major stakeholders: future parents and responsible actors from healthcare institutions, based on data from interviews. The results contribute to increased understanding of developing mobile applications for future parents, considering temporal, situation dependent needs during the pregnancy process, but also after having given birth. To handle temporal and longer-term needs, and provide contextualized information, considering patient-pathways are beneficial.

The healthcare domain requires security against possible threats, such as viruses to defend the integrity of the health and patient records. During the system analysis, different parts of the sub systems are connected under a main system. Under these connections into the Internet, malicious programs are spread into the system network and damages to vital information have been appearing. For that reason, it is crucial to model the spreading of the computer virus using dynamic equation systems and the solution of these systems will be presented. In this work an epidemiological model SIR is presented, and the analysis of its performance is illustrated.

Parkinson's disease (PD) is a neurodegenerative disorder that affects more than 10 million people worldwide. Assistive technology and exergames come to play a beneficial role in positive mood and socialization improvement, overall quality of life and improved confidence with everyday functional activities. More and more Exergames inserts in the market but how many of that are fitting the patient's needs? How many of that took into consideration theirs's opinion. This study describes the Minimum Viable Product (MVP) model “Develop-measure-learn” circle in a co-creation way with the PD patients to develop and improve Exergames for them, and the tools that are needed to accomplish. The most important outcome of this procedure was the proposed development of more realistic games, giving the researchers the step of starting the investigation of 3D solutions.

Augmented Realty (AR) technology has a significant contribution in healthcare sector by offering valuable solutions the last two decades. The aim of this paper is to investigate the implementations of Augmented Reality technologies in healthcare, which include wearable devices such as AR Glasses and Optical Head-Mounted Display Devices (OHMD), by searching the international scientific literature. Relevant studies were retrieved online from scientific databases using keywords related to Augmented Reality in healthcare. The results indicate the numerous applications of these technologies in healthcare procedures, like diagnosis, treatment, and rehabilitation, as well as in the education of healthcare professionals. The international scientific community encourages the usage of the AR wearable technologies like AR glasses in Healthcare.

Drug safety is an important aspect in healthcare, resulting in a number of inadvertent events, which may harm the patients. IT based Clinical Decision Support (CDS), integrated in electronic-prescription or Electronic Health Records (EHR) systems, can provide a means for checking prescriptions for errors. This requires expressing prescription guidelines in a way that can be interpreted by IT systems. The paper uses Natural Language Processing (NLP), to interpret drug guidelines by the UK NICE BNF offered in free text. The employed NLP component, MetaMap, identifies the concepts in the instructions and interprets their semantic meaning. The UMLS semantic types that correspond to these concepts are then processed, in order to understand the concepts that are needed to be implemented in software engineering for a CDS engine.