Innovation in Health Informatics: A Smart Healthcare Primer

By Miltiadis Lytras

Innovation in Health Informatics: A Smart Healthcare Primer explains how the most recent advances in information and communication technologies have paved the way for new breakthroughs in healthcare. The book showcases current and prospective applications in a context defined by an imperative to deliver efficient, patient-centered and sustainable healthcare systems. Topics discussed include big data, medical data analytics, artificial intelligence, machine learning, virtual and augmented reality, 5g and sensors, Internet of Things, nanotechnologies and biotechnologies. Additionally, there is a discussion on social issues and policy- making for the implementation of smart healthcare.

This book is a valuable resource for undergraduate and graduate students, practitioners, researchers, clinicians and data scientists who are interested in how to explore the intersections between bioinformatics and health informatics.

• Provides a holistic discussion on the new landscape of medical technologies, including big data, analytics, artificial intelligence, machine learning, virtual and augmented reality, 5g and sensors, Internet of Things, nanotechnologies and biotechnologies
• Presents a case study driven approach, with references to real-world applications and systems
• Discusses topics with a research-oriented approach that aims to promote research skills and competencies of readers

• Language: English
• Publisher: Academic Press
• Release date: Nov 13, 2019
• ISBN: 9780128190449

Book preview

examinations.

Section A

Smart Healthcare in the Era of Bid Data and Data Science

Outline

Chapter 1 Smart Healthcare: emerging technologies, best practices, and sustainable policies

Chapter 2 Syndromic surveillance using web data: a systematic review

Chapter 3 Natural Language Processing, Sentiment Analysis, and Clinical Analytics

Chapter 1

Smart Healthcare: emerging technologies, best practices, and sustainable policies

Miltiadis D. Lytras¹,², Paraskevi Papadopoulou¹ and Akila Sarirete²,    ¹Deree College—The American College of Greece, Athens, Greece,    ²Effat College of Engineering, Effat University, Jeddah, Saudi Arabia

Abstract

The integration of innovation within healthcare is a key aspect of the so-called next generation medical systems. Toward this direction the contribution of this volume is multifold. First demystifies the new wave of emerging and streamline technologies and uncovers the added value of their components. Second underlines a new policy-based era of health governance, since the integration of innovation within healthcare must be understood from the key stakeholders and needs to be implemented taking into account various limitations. Last but not least, innovation in healthcare must be seen as a human-centric process where complicated and sophisticated, distributed medical services and processes are utilized. The adoption of advanced Healthcare Information Systems and Medical Informatics requires an integrated approach sensitive to various social, economic, political, and cultural factors. The challenges that the adoption and use sophisticated information and communication technologies (ICTs) generate need to be considered too. Smart Data and Data Analytics along with cognitive computing are the promising technologies with great value added for the domain of healthcare. The focus of this edited volume is to examine the social, economic, political, and cultural impacts, and challenges emerging sophisticated ICT bear for patient-centric systems in healthcare. By offering a detailed comprehensive and comparative insight into diverse advances in ICT and their application across issues and domains, this edited volume occupies a unique position on the market. This is because it brings together not only a discussion on the most promising technologies and their current and prospective uses, but also dwells on managerial and policymaking challenges and opportunities this process creates.

Keywords

Innovation; Smart Healthcare; resilient smart city; applications; services; medical informatics

1.1 Introduction

The integration of innovation within healthcare is a key aspect of the so-called next generation medical systems. Toward this direction the contribution of this volume is multifold. First, it demystifies the new wave of emerging and streamline technologies and uncovers the added value of their components. Second, it underlines a new policy-based era of health governance, since the integration of innovation within healthcare must be understood from the key stakeholders and needs to be implemented taking into account various limitations. Last but not least, innovation in healthcare must be seen as a human-centric process where complicated and sophisticated, distributed medical services and processes are utilized.

The adoption of advanced Healthcare Information Systems and Medical Informatics requires an integrated approach sensitive to various social, economic, political, and cultural factors. The challenges that the adoption and use of sophisticated information and communication technologies (ICTs) generate need to be considered too. Smart Data and Data Analytics along with cognitive computing are the promising technologies with great value added for the domain of healthcare.

The focus of this edited volume is to examine the social, economic, political, and cultural impacts, and challenges emerging from the use of sophisticated ICTs for patient-centric systems in healthcare. By offering a detailed comprehensive and comparative insight into diverse advances in ICT and their application across issues and domains, this edited volume occupies a unique position on the market. This is because it brings together not only a discussion on the most promising technologies and their current and prospective uses, but also dwells on managerial and policymaking challenges and opportunities this process creates.

1.2 Bridging innovative technologies and smart solutions in medicine and healthcare

Major advances and breakthroughs in science and technology are transforming our world. More specifically, incredible developments in biology and technology have broad ramifications in the ways the world population increases and how our health and life spans will be affected. An increased world population, of currently more than 7.7 billion people, together with the expected increasing life spans, which were made possible by scientific and technological advances, create new challenges. The High-level Political Forum on Sustainable Development is the central UN platform adopted at the United Nations on September 2015 as a plan of action for people, the planet as a whole and prosperity. It is expected that their goals and targets will stimulate action up to 2030. Within the 17 Sustainable Development Goals and 169 targets, Goal 3 aims to ensure healthy lives and promote well-being for all ages (United Nations, 2019). Healthcare sciences, therefore, will be essential for interpreting the genetic variation in comparison with the gene/environment interactions which seem to be at the core of most diseases and biological phenomena. Improved sanitary conditions and hygiene, the use of vaccines and antibiotics, improved understanding of diseases, and innovative treatments have helped keep many hereditary and infectious diseases in check. Moreover, improved home and work conditions have contributed to healthy aging and longer life spans as well as provided access to better quality food and nutrients. In fact, the booming population of older adults, in mostly the developed countries, is a testament to the incredible developments in science and technology. According to the World Bank, the public expenditure on healthcare in the EU could jump from 8% of GDP in 2000 to 14% in 2030. How effectively will we be able to explore such advances and innovations in regard to health both locally and globally? How will we manage to tackle our disease burden to improve our day-to-day well-being especially if in developed countries The global population of people over 80 will be more than triple by 2050 and in the less-developed countries the youth profile will escalate? Will Europeans, for example, find ways to balance budgets and restrain spending and come up with a sustainable survival strategy for Europe’s healthcare systems? Will all the children born in less-developed countries have access to clean water, good quality food, and receive good medical care?

We have already taken the first step toward tackling genetic and infectious diseases at the root. Largely we have managed to integrate genetic, environmental, and behavioral factors in the hope to prevent and treat illnesses and diseases. Many of the techniques used are still in their early stages, but the promise is remarkable. To a point, we have managed to strengthen prevention. We have also recognized the heterogeneity that exists among patients and various populations of the world. The ultimate goal would be to successfully make healthcare and community health services predictive, preventive, and personal.

1.2.1 From genomics to proteomics to bioinformatics and health informatics

The contribution of genomics to our understanding of disease and health has expanded significantly the last few years especially after the publication of the reference Human Genome in 2001. Genomics as an interdisciplinary field of biology aims at the collective characterization and quantification of genes focusing on their structure and function, and also evolution and mapping.

The next field that emerged is the field of proteomics which through gene expression directs the production of proteins with the assistance of enzymes and various types of RNA molecules and other translational factors. In turn, proteins, generally speaking, are structural components of cells, tissues, and organs, or serve as enzymes in most chemical reactions and carry signals in and between cells. With the advent of Next Generation Sequencing and other high throughput technologies, Whole Genome Sequencing became possible including Whole Exome Sequencing as well as Genome-Wide Association Studies. Similarly, metabolomics emerged as the scientific systematic study of chemical processes involving metabolites with their unique chemical fingerprints and metabolite profiles more like a snapshot of the physiological state of cells and of organisms.

Then came the use of the exposome in the practice of epidemiology. Wild in his 2005 paper stated, At its most complete, the exposome encompasses life-course environmental exposures (including lifestyle factors), from the prenatal period onwards. Exposome has been defined as the totality of exposure individuals experience over their lives and how those exposures affect health (DeBord et al., 2016). The Exposome, could conceptually and practically speaking, provide a holistic view of human health and disease. Genome sequence information needs to be linked with information about our diets and nutrition including variation in metabolism; our behaviors and lifestyles; our disease profile and medications; and our microbial, chemical, and physical exposures to understand the environmental/genetic interactions that ultimately affect human health. Measuring the exposome though is a major challenge, yet, it is obvious it plays a critical role in understanding chronic disease formation and progression. Exposure assessments require the integration of different types of exposure information, and by managing to identify stressors and their actions we could improve our understanding of various diseases and ultimately improve disease prevention. All these advances in genomics and proteomics have triggered a revolution in discovery-based research. Pharmacogenomics became the study of genetic material in relationship with drug targets. Currently, there is growing attention toward personalized medicine and precision medicine. Systems biology facilitates our understanding of even the most complex biological systems such as the brain.

Bioinformatics became a highly interdisciplinary field of storing, retrieving, and analyzing large amounts of biological information. Bioinformatics deals with research data and uses it for research purposes, medical informatics deals with data from individual patients for the purposes of clinical management (diagnosis, treatment, and prevention), and biomedical informatics is the bridge between the two as it leads to effective use of biomedical data. The emerging advances of bioinformatics in fact and the need to improve healthcare and the management of Medical Systems have already contributed toward the establishment of better next generation medicine and medical systems by putting emphasis on improvement of prognosis, diagnosis, therapy, and prevention of diseases (Lytras & Papadopoulou, 2018).

Health informatics is another common term used. Health informatics is also known as clinical informatics, medical informatics, and biomedical informatics with the most inclusive term being biomedical informatics. Health informatics is the field of information science concerned with mainly the management of healthcare data and information. All these terms may cause confusion but it is useful to remember that in reality, technology serves as means of transportation, not of destination.

Health informatics, nevertheless, has helped to promote research collaborations of researchers from the field of Bioinformatics and Health Informatics together with administrators, clinicians, and data scientists. Having access to high-speed computers, mobile technology, voice recognition, and more, healthcare professionals have begun to examine ways to incorporating the latest computational intelligence with Big Data Analytics as well as Data Mining and Machine Learning Methodologies.

The increased need to improve healthcare, and the welfare of patients and people, in general, requires that we fast improve prognosis, diagnosis, and therapies to advance personalized medicine and targeted drug/gene therapy (Alyass, Turcotte, & Meyre, 2015; Chen, Qian, & Yan, 2013; Tenenbaum, 2016). Since technology is advancing faster then professionals can follow there is a new need for investing on education and translation of emerging technologies and the data/information they generate into healthcare information (Greene, Giffin, Greene, & Moore, 2015). There are lots of data but less information, knowledge, and wisdom. Information is data with meaning. Again, it is always up to Humans to provide knowledge and wisdom.

We expect that the 100,000 genome project will help bridge the gaps between these disciplines by combining genomic sequence data with medical records and that this will be a groundbreaking resource on how to best interpret the data for the benefit of patients.

The original 4–5 Big Data Vs such as data volume, data velocity, data veracity, data validity, and data value (see Fig. 1.1; Papadopoulou, Lytras, & Marouli, 2018) were expanded to 10 Big Data Vs to include in addition data variability, data vulnerability, data volatility, data variety, and data variety (Firican, 2017). Those 10 Big Data characteristics are examined in terms of usefulness and importance as to which is the most decisive criterion turning data from big to smart as a real-time assistance for the improvement of living conditions. Fig. 1.1 depicts the 10 Big Data Vs and main characteristics as they could apply to healthcare as well. For a more extensive coverage on the 10 Vs, see Firican (2017) and Suwinski et al. (2019). It is important to note that it is not enough to manage to filter structured or unstructured Big Data into smart data but to also use it to make wise decisions which will serve both the individual and society as a whole.

Figure 1.1 The 10 Vs of Big Data as they contribute to smart and wise data.

1.2.2 Ways of developing intelligent and personalized healthcare interventions

Massive amounts of Big Data both structured and unstructured have been collected in the healthcare industry. To filter Big Data and turn it into smart data is not an easy task. Even more so, to analyze it for insights that would lead to smarter operations and more efficient decision-making. Whether it is Big Data originating from smart sensors then to be sent to collection points and from there to analytic platforms within Internet of Thing (IoT) systems or Big Data that is processed waiting to be turned into actionable information is very challenging indeed.

Electronic health records (EHRs), for example, and multiple other healthcare information systems provide the ability and the need to collate and analyze large amounts of data to improve health and financial decisions.

As genetic information collection grows, datasets are huge (Big Data) and part of EHRs. Mining the Data becomes a major task. All large healthcare organizations will collect and analyze a variety of clinical, financial, and administrative data to make wise clinical and business decisions. Therefore Data Analytics is very important and it requires well-educated individuals. There is high need for Informaticians (or informaticists) who can manage to harness the power of information technology to expedite the transfer and analysis of data, leading to improved efficiencies and knowledge.

Here are some examples of top Healthcare innovations (https://getreferralmd.com/):

• Payer–Provider Analytics/Data Software

• Artificial Intelligence

• BlockChain for Healthcare

• Internet of Medical Things

• Patient Engagement

• Centralized Monitoring of Hospital Patients

• Gene Therapy for Inherited Retinal Diseases

• Hybrid Closed-Loop Insulin Delivery System

• Noninvasive Diabetes Monitoring

• 5G Mobile Technology

1.2.3 Advancing medicine and healthcare: insights and wise solutions

It is evident that the driving forces behind Health Informatics are strong. Intensive training is needed, which includes in addition to good understanding of biological systems, IT knowledge about networks and systems, usability, process reengineering, workflow analysis, and redesign. This should be followed by focusing on proper training and quality improvement, efficient project management, wise leadership, and teamwork so as to ensure medical excellence and proper implementation (see Fig. 1.2).

Figure 1.2 Content management resilient Smart Healthcare systems cluster.

1.2.4 Ways of disseminating our healthcare experience

Health Informatics is a relatively new and exciting field with many new job opportunities including in the Academia world. Research in health informatics is being published at an increasing rate so hopefully new approaches and tools will be evaluated more often and more objectively.

Although technology holds great promise, it is not the solution for every problem facing medicine today. We must continue to focus on improved patient care as the single most important goal of this new field.

Table 1.1 outlines a number of ICT solutions and managerial issues pertaining to healthcare, the type of educational training, and citizen engagement.

Table 1.1

1.3 Visioning the future of resilient Smart Healthcare

The constitutional technological parts, of smart healthcare, including numerous emerging and streamline technologies, are summarized in the following table together with some policy implications that will be discussed further in Chapter 17, Policy implications for Smart Healthcare: the international collaboration dimension.

In the next section, we elaborate on selective applications and services for smart healthcare.

1.4 Content management resilient Smart Healthcare systems cluster

Even though the content management cluster is not the most sophisticated in terms of computing complexity, it provides though a significant number of value adding services of massive use, which are critical for the realization of any Resilient Smart Healthcare Computing Vision. While there are many diverse IT vendors and provides of services, including open source cloud solutions and integrated content workflow systems, it is important to understand from the beginning the main characteristics of these applications. The following list of features is representative for the capacities of content management systems to support greater scenarios of engagement and services.

• They enable the modular integration of textual data found in policies, official documents, digital archives.

• They can be enriched with advances metadata schemas, taxonomies, ontologies, and semantics enabling complementary views of the same content based on some well-defined criteria.

• They can adopt advanced matching and similarity algorithms, challenging the exploration of content based on user preferences and needs.

• They can be integrated with collaborative platforms and social media or networks, enabling a superficial artificial meta-context of exploitation. The integration of content with social networks or human networks in general sets an amazing new context for exploitation especially for resilient Smart Healthcare applications.

• They can support different cloud computing scenarios based on document as a service, promoting a paper free, trusted resilient Smart Healthcare computing culture in different context that will be applied.

All these characteristics are significant, although they cannot be realized in value adding services without creativity in perceptions. This is to our opinion the critical challenge for resilient Smart Healthcare applications. There must be a concrete vision and a scalable approach of incremental diffused value for the establishment of simple, fully functional, and sustainable services. In the next section, we discuss some ideas for many applications or clusters of resilient Smart Healthcare applications in which the content management component is the main value integrator.

1.4.1 Resilient Smart Healthcare learning management systems cluster

This cluster is related to the developmental aspect of the Smart Healthcare ecosystem. It is critical in the context of resilient Smart Healthcare design to integrative innovative, collaborative learning infrastructures that cultivate a learning culture in the context of the Smart City, engaging citizens and visitors in a developmental process. Promoting the knowledge, the skills, the competencies, and the talents of inhabitants should be a key strategic objective in modern cities. In the next paragraphs, we are discussing seven areas of interest for resilient Smart Healthcare LMSs. Each of these areas represents a context of application as well as a context of inquiry a public dialogue for the various services and underlying philosophy of implementations. For sure there are many more application areas (Fig. 1.3).

• Lifelong learning integrated resilient Smart Healthcare university: The idea of establishing an Open Informal educational space accessible by the Smart Cities Inhabitants sounds as a very promising area. Different implementation scenarios could be adopted. For example, the integration of Massive Open Online Courses in a simple access point, or a community-based open approach where stakeholders in the resilient Smart Healthcare can contribute content and lectures in such an infrastructure. This Smart Open University should serve as an open space of dialogue for the key issues of modern living in cities. It can be also used as a community platform for knowledge diffusion between the youth generation and policy makers. The lifelong learning and distributed perspective are also of great significance.

• Community-based professional training at large scale: Thinking about learning initiatives at a large scale, it is given that one of the main aspects should be the collaborative engagement of a great number of resilient Smart Healthcare citizens. Community-based professional training refers to the capacity of a relevant infrastructure to diffuse learning content and programs in formal or informal modes to a great number of people. Consider for example a Teachers community to use a relevant service or application for interacting and collaboration.

• Massive open online courses (MOOCs) technologies and paradigm: The adoption of MOOCs paradigm in the context of resilient Smart Healthcare design can be a very good approach. Implementing MOOCs integrated with social mining capabilities and analytics can enhance significantly the capacity of an urban area to learn and evolve.

• Hubs of connected medical schools: The integration through LMSs or other ICTS of various Schools at an urban district or at a large, it is a key movement. The scenarios can be different. For example, the development of a cloud, open accessible infrastructure with open source technologies, promoting the feeling of belonging and learning in the same resilient Smart Healthcare area. Capabilities related to advanced profiling, collaborative projects between schools, flipped classrooms can provide additional value perceptions.

• Collaborative, exploratory, constructivist, active learning for resilient Smart Healthcare inhabitants: One of the key value propositions of resilient Smart Healthcare learning applications should be the promotion of a collaborative, active learning approach. The use of available ICTs should be made on a creative engaging way, so that the participants in these experimental approaches should feel the impact and the added value of resilient Smart Healthcare open distributed community-based education. For example, consider an open system where active citizen organize campaigns, seminar interactions for key societal challenges such as the Climate Change, The Energy Consumption, The Public Safety, a community-based social entrepreneurship model.

• Global integration/smart global alliance for learning: Modern resilient Smart Healthcare areas should adopt an openness to the globe. They must build synergetic services, some applications that promote multicultural interactions, and create advanced mechanisms for social integration of diversity. Toward this direction resilient Smart Healthcare learning management systems can serve as a vehicle for learning content diffusion between smart cities, associations, social coalitions, and political ideas. This idea of Global Integration must find supporters at the policymaking level and should be a continuous improvement process rather than a per-case standalone implementation. Consider for example a resilient Smart Healthcare LMS that brings together Medical Experts from China and Saudi Arabia and delivers learning content related to the cultural understanding of doing business in these areas.

• Inclusion, diversity, equality through smart learning: This application domain is maybe one of the most critical for the furnishing of a multicultural, diverse, and inclusive resilient Smart Healthcare culture. There are many propositions of services and projects in this area. Consider for example an application for smartphones which will integrate citizens and will connect them on a basis of social inquiry. For example, LMSs will aggregate microcontent contributed by various inhabitants on a case of disease treatment, diversity, and equality.

The previous mentioned are only few exemplary cases of application related to resilient Smart Healthcare learning management systems. We must emphasize that even though these cases represent meaningful solutions for certain problems, the real value of this category of application can be expanded by mixing more enabling technologies. In the next section, we elaborate on another content management technology that enables the so-called Resilient Smart Healthcare Document Management applications.

Figure 1.3 Resilient Smart Healthcare open distributed community-based education applications (I).

1.4.2 Resilient Smart Healthcare document management systems cluster

The provision of an integrated approach that promotes the vision of Document as a Service is critical toward the resolve of many inefficiencies especially in the interactions of citizens with authorities and offices. Current Document Management Technologies, provide a variety of services and features that meet most of the requirements of value services. The development of a fully functional infrastructure for the issuing, signing, commenting, integration, collaborative authoring, annotation, extraction, merge and management of documents in different formats it is a bold initiative toward the realization of smart cities vision. Given also the fact that documents represent the so-called explicit knowledge it is more than critical to support their entire life cycle from creation, to distribution, use, store, etc., with policies and relevant tools. In the next paragraphs, very briefly we present six main ideas for applications related to resilient Smart Healthcare document management value adding services. This list is not exhaustive but rather representative of the capacities of document management systems to be problem solvers (Fig. 1.4).

• Smart cities digital signatures integrated framework—trust and advanced encryption: One of the most critical aspects for the provision of advanced document-based services is the design implementation and provision of digital signatures infrastructures. This will facilitate several dynamic content and document exchanges and will for sure enhance a document-based business processes automation. For example, an integrated resilient Smart Healthcare application that will manage the issuing of digital signatures and will link human entities with different privileges and signature grants over documents could be an excellent proposition in this category.

• Large-scale accessible archives—accessibility applications for documents: Accessibility must be one of the key priorities in resilient Smart Healthcare design. Unfortunately, in our days at a global basis, there is rather a little concern for accessibility options. Most of city Information Technology services do not consider accessibility options or when they make it they have a very narrow perspective. Smart applications that add accessibility options over archival documents or set up mechanisms to automate accessibility options for any generated document is a key development. For example, consider an application that adds voice descriptions in documents for blind people or enables speech navigation to menus of resilient Smart Healthcare services.

• Collaborative construction of resilient Smart Healthcare Wikis and Blogs: The development of Open Collaborative Wikis for different topics in the context of resilient Smart Healthcare design cultivates further the community culture and builds connections between citizens. The provision of a Wiki and Blog ecosystem within a resilient Smart Healthcare area adds significant credits to knowledge management and shared vision of citizens. An application in which Open Wikis technologies can be exploited for the construction of content archives can be a good approach for this category. In addition, the use of such a central wiki hub can be the basis for opinion and social mining. Open Blogs and Wikis should be critical information flows for more advanced analytics and insights related to City Life, perceptions about quality of life, opinions and ideas for prosperity and response to critical social