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By Guglielmo M. Trovato MD, the European Medical Association (EMA)

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, and 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.

future proof digital knowledge and skills.

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.

The main components of digital revolution.

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:

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:

Relationship among several factors and stakeholders are complex.

 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 naïve 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.


Medical practice and any aspect of health care is the goal of digital revolution in health systems, but the counterpart is the possible and useless effects of excessive non-clinical expertise.

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.

Knowledge in Bioinformatics is a basic mathematical template for medical reasoning.


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.

G. Trovato EMA

Guglielmo Trovato 

EMA– European Medical Association


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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.

Acknowledgments and disclaimer. This article is the preliminary draft of the contribution to the forthcoming meeting “A Health Care Workforce for the Digital Age” to be held the 5th  November 2019 in the European Parliament (Brussels, room ASP 5G 305) from 12:00 to 14:00. The article is also an educational tool of BioS Project, an Erasmus Plus action  addressed to a Multilanguage e-learning course in Bioinformatics and computational biology, disseminated also through  and The Project is in active development with multiple Partners, including EMA . 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.