THE CHALLENGES OF DIGITAL HEALTH APPROACHES FOR THE 2020-2030 EUROPEAN HEALTH PROFESSIONALS. THE QUALITY OF RESEARCH AND BEST PRACTICE.

PERSONALIZED GENOMICS SERVICES IN PATIENT CARE

The challenge that we are facing for?Health Care Workforce in the Digital Age requires the explicit definition of few concepts. Most or all concepts must be shared and agreed before discussing of any clinical revolution from digital health approaches. This theme, encompassing predictive, preventive and personalized medicine, is mostly relevant for our need of innovation and of participatory medicine: for this reason the topic is again discussed in the current article.

????????Digital literacy is rapidly increasing worldwide, also among the health human resources galaxy. It refers to an individual's ability to find, evaluate, and compose clear information through writing and other mediums on various digital platforms. Digital literacy is evaluated by an individual's grammar, composition, typing skills and ability to produce writings, images, audio and designs using technology. While digital literacy initially focused on digital skills and stand-alone computers, the advent of the Internet and use of social media, has caused that most of its focus to shift to mobile devices. Moreover, self-instructional learning and market-driven information are overwhelming, and web-literacy, i.e. the skills of reading, writing and participating on the web, contributing to both content and activity is becoming an all-embracing feature of the digital revolution.

???????????????Digital health literacy uses the same operational definition, but in the context of technology. Technology solutions have the potential to both promote health literacy or be a barrier. To be effective, health technology solutions should go beyond building literacy and numeracy skills to functional and critical skills, such as navigating the healthcare system, communication with healthcare providers, and shared decision making. According to P. Dunn et al. (2019) digital health literacy, demands particular skills complementary to general and health literacy both in health professionals and in general population.

Also in medicine, digital competences should be appropriately increased and warranted, avoiding unrealistic and over-ambitious goals but with the aim of training appropriately future-proof health care workforce. In general, the term "future-proof" refers to the ability of something to continue to be of value into the distant future— with some guarantee that the item does not become obsolete. The concept of future-proofing is the process of anticipating the future and developing methods of minimizing the effects of shocks and stresses of future events, tasks and development.?

???????????Health workforce includes medical doctors, nurses but also health professionals that support the health services, such as hospital managers, ambulance drivers etc. No skilled health worker might be able to deliver services effectively without adequate facilities, equipment and consumables such as basic or advanced devices and a reliable supply of medicines and technologies, backed by adequate funding, strong health plans and evidence-based policies. It is not a simple task the choice of the knowledge and skills that health care workers reasonably need to maximise the benefits of digital technologies, already in use or forthcoming.

???????????Accordingly, health system budgets need to balance several vital demands – human resources, physical capital and consumables along with the novel lines of continuous and vocational education within a meaningful strategy.

???????????The goal of reaching an universal health care coverage requires knowledgeable, skilled and motivated health workforce.?WHO estimates a projected shortfall of 18 million health workers by 2030, mostly in low- and lower-middle income countries. However, Countries at all levels of socioeconomic development face, to varying degrees, difficulties in the education, employment, deployment, retention, and performance of their workforce.

Digital revolution refers mainly to the shift from mechanical and analogue electronic technology to digital electronics which began anywhere 60-70 years ago with the adoption and proliferation of digital computers and digital record. Digital computing and communication technology are paving the road of the mass production and widespread use of digital logic and devices. Greater interconnectedness, easier communication among individuals, groups and population?allowed that comprehensive information may be more freely delivered everywhere and to everybody with limited political or authoritarian constraints. Nonetheless, information overload, invasions of “internet predators”, the strategies based on faked news and disinformation, several forms of social isolation, and last but not least, media saturation on specific topic must be faced as the most ominous facets of this process. Overall, digital technologies have significantly increased productivity and performance of industry, organizations and, in general, businesses. Menaces to privacy are many, including mass surveillance, which is of great concern for civil and human rights issues. Reliability of data is an urgent issue in many field because information could easily be replicated, but not easily verified, with consequent cascade effects with economic, social and political implications.

Artificial intelligence (AI) development is the first of the goals of the digital revolution. It refers to the capability of a machine to imitate human intelligence, reacting, working and even ideating like human or non-human living beings.

Machine learning (ML) refers to computer systems using algorithms and statistical models for tasks without using explicit instructions, relying on patterns and inference instead.

Deep learning is one arm?of machine learning methodology which can be supervised, semi-supervised or unsupervised. Its architectures are based on deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks. All, and others, have been applied to fields including computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they are claimed increasingly of results comparable to and in some cases superior to those reached by human experts.

Digital health refers to?digital technologies, which already widely use deep learning, exerting direct or indirect impact on?health, healthcare, living, and society. Digital health focuses to increase the efficiency of healthcare delivery and organization, eventually making medicine more personalized and precise.

????????????The questions chosen by Health First Europe are very pertinent to the current debate and put unmet needs of the population, along the unmet needs of health professionals, namely medical doctors, at the center of this process of development, addressing to changes and challenges related to the digital revolution in health systems:

1.????????What structural changes in health care settings can support health workers in leading the digital revolution?

2.????????What skills do health care workers need to maximize the benefits of digital technologies?

3.????????How EU policies can support health care workers in scaling up innovation?

?There are few adjunctive questions, taking into account that relationship among several factors and stakeholders are complex. and among them:

?4.????????Is it demonstrated, or likely, that digital health changes may improve health care quality and effectiveness, sustainability and affordability also in limited resources subsets?

5.????????Do digital health changes may be in conflict with marketing information strategies in the wider audiences?

6.????????Is this process aligned with the increasing request of more “humanities” in medicine and the approaches addressing to the global ecosystem health?

?Digital Scribe and electronic clinical records. One particularly relevant topic in rapid advancement regards the development of “digital scribe”. According to E. Coiera et al (2019), nothing appears to cause more frustration for many clinicians than the electronic health record (EHR). Current generation electronic health records suffer a number of problems that make them inefficient and associated with poor clinical satisfaction. Digital scribes or intelligent documentation support systems, take advantage of advances in speech recognition, natural language processing and artificial intelligence, to automate the clinical documentation task currently conducted by humans. Whilst in their infancy, digital scribes are likely to evolve through three broad stages. Human led systems task clinicians with creating documentation, but provide tools to make the task simpler and more effective, for example with dictation support, semantic checking and templates. Mixed-initiative systems are delegated part of the documentation task, converting the conversations in a clinical encounter into summaries suitable for the electronic record. Computer-led systems are delegated full control of documentation and only request human interaction when exceptions are encountered. Intelligent clinical environments permit such augmented clinical encounters to occur in a fully digitised space where the environment becomes the computer. Data from clinical instruments can be automatically transmitted, interpreted using AI and entered directly into the record. Digital scribes raise many issues for clinical practice, including new patient safety risks. Automation bias may see clinicians automatically accept scribe documents without checking. The electronic record also shifts from a human created summary of events to potentially a full audio, video and sensor record of the clinical encounter. Digital scribes promisingly offer a gateway into the clinical workflow for more advanced support for diagnostic, prognostic and therapeutic tasks.

????????????DIGITAL KNOWLEDGE AND SKILLS should integrate and overlap practical skills and clinical reasoning and actions. They must not counteract any of them in the na?ve or ambitious aims and claims of being advancements or substitutes of the actual contact, not only relationship, between patients and health professionals. This is a relevant concern of patients and medical doctors.

???????????The wider use of digital technologies is contributing to the efficiency of healthcare delivery also in limited resources subsets. Actually, affordable and reliable information and communication are a valuable help for addressing the medical problems and challenges faced by people in health and disease, in public health and in the base of primary care, i.e. family and community medicine.

???????????Hardware and software solutions and services, including telemedicine, web-based analysis, email, mobile phones and applications, text messages, wearable devices, and clinic or remote monitoring sensors concur to the development of interconnected health systems.

???????????The use of computational technologies, smart devices, computational analysis techniques, and communication media to aid healthcare professionals and their clients manage illnesses and health risks, as well as promote health and wellbeing are facets of this multi-disciplinary scenario. The involvement and commitment of different stakeholders, including clinicians, researchers and scientists, engineers, industry and policy makers addressing public health, health economics and data management choices are the vital components of this process. Also gender and racial inequalities, including domestic violence, are topics under active development by digital health strategies.

EUROPEAN HEALTH CARE NEEDS ALSO A GREATER SUSTAINABLE CONTRIBUTION BY PRECISION MEDICINE TOOLS.

Precision Medicine, almost a synonymous of personalized medicine, is an approach in active development for disease treatment and prevention. It takes into account individual variability in genes, environment, and lifestyle for each person to predict more accurately which diagnostic workup, treatment and prevention strategies will be more suitable for a disease, a complain and for which groups of people. Its basis are also clinical medicine, including health psychology, physical examination and epidemiology, which are activities suitable of measure and inclusion in numeric data-bases. Bioinformatics and computational biology are key preliminary components of precision medicine and, comprehensively, of digital health. Medical best practice and improvement of any aspect of health care?is the goal of digital revolution in health systems,? but the counterpart is a possible useless and effects of pervasive non-clinical expertise.

Bioinformatics is an hybrid science that links biological data with techniques for information storage, distribution, and analysis to support multiple areas of scientific research, including biomedicine. It is fed by high-throughput data-generating experiments, including genomic sequence determinations and measurements of gene expression patterns. Database projects curate and annotate the data and then distribute them via the World Wide Web. Mining these data leads to scientific discoveries and to the identification of new clinical applications. It has since several years also practical applications, well established in genetics and rare disease, and even more in oncology.

Computational Biology, with wide areas of overlap with bioinformatics, is the science of using biological data to develop algorithms or models to understand biological systems and also their relationships with health and disease.

?????????The BioSProject is an ErasmusPlus action focused to widening expertise and knowledge in Bioinformatics and Computational biology, by a forthcoming e-learning/mooc course. This will be a valuable open access contribution for improving quality of skills and performances of European Health Professionals and Medical Doctors, enhancing interest and active participation of health professionals to innovative experience and practice.

TARGET.

No health system change?change is realistically planned and developed without dual educational interventions addressed to undergraduate and post-graduate students of medical schools and to already active health professional. All will benefit of well targeted continuous medical education actions. In this sense, careful on-site analysis of actual skills and of unmet needs of health workers are the preliminary steps. Accordingly, the achievement of basic digital and web-based social media competences is only a first step. Knowledge in Bioinformatics is a basic mathematical template for?medical reasoning.

???????????Actually, the different profiles of health professionals correspond to different needs and lines of access to big-data banks and tools: genetics, oncology, infectious disease, cardiovascular disease, behavioral and lifestyle approaches, robotic surgery are different field which must be addressed appropriately and also by attractive dissemination campaigns.

WHICH IS THE ROLE OF A GOOD QUALITY RESEARCH

Research, also medical research, is a risky task. If we knew what it was we were doing, it would not be called research, would it? As Albert Einstein said.

There is no definite consensus on how to judge the quality of Research) projects, which makes them difficult to plan and evaluate. A frequent refrain that one hears proposed concerns the request for a high quality of research, in general and in the scientific-medical-biological field, also including the aspects and tools of bioinformatics and artificial intelligence - machine learning and more -.

From the beginning, what is research? A basic definition describes research as a creative and systematic work undertaken to increase the stock of knowledge. It involves the unbiased collection, organization and analysis of information to increase understanding of a topic or issue. A research project may be an expansion on past work in the field. To test the validity of instruments, procedures, or experiments, research may replicate elements of prior projects or the project as a whole.

This is only a beginning, because, for instance, academic research involves more than just choosing a topic, collecting and analyzing data, and leveraging academic writing tools: it also implies a judgment on its recognizable quality.

Good research is anchored on a sound research question: developing a research question is the most important step in doing a research project: the research question influences the rest of the steps a researcher thereafter takes: the formulation of a research question is often easier said than done. The overall quality and success of a research study are largely determined by the research methodology it uses: choosing an appropriate research methodology helps ensure that researchers can collect relevant data and use the right data analysis methods. While good research leads to the discovery of new knowledge, it also means studying previous research on the topic. By studying scholarly articles and other works related to your subject of interest, you get an idea of what has already been studied and how your study fits into existing research.

One of the most important qualities of a good research study is that it deals with empirical data. Moreover, criteria of good research include often being representative. i.e., that has a sample with the ability to represent a larger group. One of the distinguishing characteristics of good or excellent research is that the entire process is guided by logic. Using logic, for instance, can help researchers determine what kind of data they need for answering their research question.

Replicability, reproducibility, and transparency are some of the most important characteristics of research, i.e., for replicability it is needed that other researchers should be able to test the study’s findings.?Research is reproducible if researchers achieve consistent results using the same data and analysis methods. The reproducibility and replicability of a research study and its findings can confirm the study’s overall validity and credibility. For research to be replicable or reproducible, it must also be transparent or available to other researchers.

A good quality of research refers to a robust external validity, i.e., that its results or findings can be applied to the real world. If the research findings can be generalized to other situations or applied to a broader context, the study has high external validity.

A quite simple approach can be itemized by the basic grid below, we sometimes still use for assessing some aspects of the quality of a research project:

1)?????The idea: there is a sound research question and how much is it an "idea"?

2) How much significant are implications and traceability of what is wished to do during the research and how it is expected to led to the research conclusions: is there a logical pathway in the research design?

3)?????Which is the Reasonableness, i.e., rationale for choices made during the research process? There is a definite establishment of a repeatable process for design practice or explanation of the use of design practice norms, and/or of general design research norms.

Quoting Aristotle: Quality is not an act, it is a habit.

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The Author: Guglielmo Trovato, MD, Professor of Internal Medicine at the School of Medicine, the University of Catania, Italy, is the EMA Director for MEDIA, e-learning and Telemedicine.

Acknowledgements. This article is the preliminary draft of the contribution to the meeting “A Health Care Workforce for the Digital Age” held the 5th??November 2019 in the European Parliament (Brussels, room ASP 5G 305) from 12:00 to 14:00.

APPENDIX

MODULE 3 - Additional readings and training material. -

COMMERCIAL PERSONALIZED GENOMICS SERVICES IN PATIENT CARE

?????????SNPs and their role in health and disease

????????Disease risk related statistics and their interpretation

????????Overview of reports from services such as 23andMe, deCODE, Gene by Gene

????????Translating example reports to non-disease phenotypes with selected example traits, e.g. bitter taste perception

????????Translating example reports to disease risks with selected example diseases, e.g. asthma

????????Translating example reports to drug response traits with relevant examples, e.g. Warfarin sensitivity

?This is the comment to the articles included by EMA in the portfolio of training material for the Health Professionals enrolled in the BioS Course in Computational Biology and bioinformatics.

You are now achieving from the BioS program knowledge and skills according to the topics of the four modules of the course.

This contribution is aimed to provide not something similar to a parallel course, but an overview of the perspective and of the development of interest for bioinformatics in the last years, from perspective and research of Medical Doctors and EMA. Accordingly, you find this itinerary stepped by the actual lectures or researches performed and published.

This is only a companion, not mandatory but, in our view, useful for some or most of you.

?Key teaching and learning plans and itineraries are, obviously, those addressed by the Lecturers of each module.

?We list below few articles, which are itemized by their main contents and concepts, and referenced choosing exclusively full free open access texts easily reachable in the web and downloadable in the most usual ways.

If accessed through the vpn of a European Teaching Institution, as most trainees will probably be able to do, for instance in their condition of medical under- or post-graduate students or through Eduroam, other articles, not listed here, can be read and downloaded as well.

?1.?????Our material contributed to this module begins with “the hardcore of Horizon 2020 - EPMA position paper”. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3985551/

Committed Medical Associations, being at the forefront of the global efforts, promote integrative and innovative concepts among health care stakeholders, governmental institutions, educators, funding bodies, patient organizations and in the public domain.

?Reviews with some topics integrative with those dealt in this module, published in top-ranked Journals are:

2.?????An evolution from genetic counselling to genomic counselling, which is particularly relevant for the perspectives which are opened in a plain way.?https://www.sciencedirect.com/science/article/pii/S1769721219302514?via%3Dihub ;

?3.?????A framework for identification of on- and off-target transcriptional responses to drug treatment, combining promoter expression profiling after drug treatment with gene perturbation of the primary drug target. https://www.nature.com/articles/s41598-019-54180-4.pdf

?4.?????Bioinformatic: Big Data Versus the Big C – where Big C stands for Cancer – is a clear, brief and easy to follow overview.

https://www.nature.com/articles/509S66a.pdf ;

?5.?????Génétique et séquence d’ADN de nouvelle génération en cardiologie?

https://www.cardiologie-pratique.com/journal/article/0028119-genetique-sequence-dadn-nouvelle-generation-en-cardiologie-pediatrique ;

?6.?????Identifier les maladies rares grace à l’intelligence artificielle https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6575632/pdf/pnas.201815601.pdf ;

?7.?????Multiomic patterns in body fluids is a special article, contributed by EMA “MULTIOMIC PATTERNS IN BODY FLUIDS: TECHNOLOGICAL CHALLENGE WITH A GREAT POTENTIAL TO IMPLEMENT THE ADVANCED PARADIGM OF 3P MEDICINE. https://onlinelibrary.wiley.com/doi/pdf/10.1002/mas.21612

?Moreover, two articles with a plain presentation of very relevant and challenging themes in oncology are included – in Italian, the first delivered by the greatest pofessional medical journal in Italy with more than 300.000 subscribers and readers, the second by Scientific American:

?8.?????Il cancro, dal modello istologico a quello mutazionale https://www.quotidianosanita.it/stampa_articolo.php?articolo_id=72642 ;

?9.?????La prima mappa del cancro su scala genomica, con l'aiuto di CRISPR.?https://www.lescienze.it/news/2019/04/12/news/crispr_mappa_cancro_scala_genomica-4367563/

?Disclaimer. The article is also an educational tool of BioS Project, an Erasmus Plus action https://bios-project.eu/site/??addressed to a Multilanguage e-learning course in Bioinformatics and computational biology, disseminated also through https://twitter.com/BiosProject1?lang=en??and https://www.facebook.com/383190028923085/posts/550894582152628?sfns=mo?The Project is in active development with multiple Partners, including EMA https://emanet.org/ . The European Commission support for the production of this publication does not constitute an endorsement of the contents which reflect the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.