Ebook: Digital Professionalism in Health and Care: Developing the Workforce, Building the Future

The European Federation for Medical Informatics (EFMI) 2022 Special Topic Conference (STC) was held in Cardiff, Wales, on September 7–8, 2022. The Scientific Programme Committee (SPC) was co-chaired by Dr Philip Scott, Programme Director at the University of Wales Trinity Saint David and Chair of BCS Health & Care, and Professor John Mantas, Director of the Health Informatics Laboratory, National and Kapodistrian University of Athens, Greece.

The theme of STC 2022 was “Digital Professionalism in Health and Care: Developing the Workforce, Building the Future”. This theme emphasized the vital need for professional education, training and continuing development of the health and care informatics workforce. This includes health and care practitioners who work in informatics and informatics practitioners who work in health and care.

Seminal reports such as the Topol Review have stressed the importance of equipping health and care staff with the skills and knowledge that they need to make effective use of digital technology. Equally, multiple failures of digital projects in health and care demonstrate that simply relocating IT generalists into this specialist field is not a guaranteed formula for success. Much learning is of course transferable from other industries, but the unique complexities of the data, information standards, knowledge, working environment and the typically under-resourced legacy infrastructures of health and care create challenges that demand suitable education and training. Such an informed perspective helps to counter the commonplace commercial and political exaggeration of what technology can offer, and enables focus on realising benefits that can actually be achieved by the usually more limited reality.

These proceedings present full papers and short communications covering a broad range of topics and methods in informatics education and training, as well as a smaller selection from the broader subdomains of biomedical informatics. The proceedings are published online with open access and indexed in the major bibliographic databases such as Medline and Scopus to ensure visibility to the wider scientific community.

We would like to thank all members of the SPC for their hard work and commitment to manage the submissions and the programme: Dr Parisis Gallos, Dr Arriel Benis, Professor Kaija Saranto, Dr Ivana Ognjanović, Professor Andrew Ware and Professor Ian Wells. We also thank all of our authors for submitting their work, our peer reviewers who volunteered their time and expertise to ensure the quality of the programme, and Professor Wendy Dearing, University of Wales Trinity Saint David, for leading the work of the local organizing committee, which handled all the practical arrangements for the conference.

Dr Philip Scott and Professor John Mantas

SPC Co-chairs

The relationship between poor EHR training and subsequent poor usability is increasingly being recognized. We utilized objective EHR audit log data to personalize EHR training with the goal of improving EHR usability and to identify changes in physician perceptions pre- and post-intervention. We found that time in the system and Pajama time decreased post-coaching intervention. Different physician perceptions were reported pre- and post-coaching. Overall, personalized EHR coaching improved the usability and perceptions of physicians.

Digital medicines management is a high priority in Norwegian e-health strategies. A key challenge is the existence of multiple electronic information sources and systems, which require multi-professional cooperation. Lack of communication, understanding and collaboration between pharmacies, hospitals and community caregivers is also a challenge. Communities of practices (CoPs) have been used to establish arenas for discussing issues challenging the workflow to reach a common agreement on successful work practices for electronic medicines management. The purpose of this paper is to explore: How can we establish communities of practice (CoPs) to gather new knowledge on the facilitators and challenges for electronic medicines management practices in Norway? The results show engagement in establishing the CoPs and a willingness for joint enterprise. The establishment of the CoPs was performed simply based on established forms of collaboration. For CoPs to be effective, established alliances need to be expanded and renewed to form new group dynamics and thus a basis for new knowledge about electronic medicines management.

NHS knowledge and library specialists have been shown to save the time of busy healthcare professionals through the range of services they provide. To ensure continued effectiveness it is vital that appropriate learning and development opportunities are provided to maintain and enhance the knowledge and skills of this highly specialist staff group. This paper outlines recent progress in developing accredited continuing professional development opportunities for NHS knowledge and library specialists with a focus on the development of digital and data skills.

The aim of this paper is to present the use of Medical Informatics Multilingual Ontology (MIMO) to index digital health resources that are (and will be) included in SaNuRN (project to teach digital health). MIMO currently contains 1,379 concepts and is integrated into HeTOP, which is a cross-lingual multiterminogy server. Existing teaching resources have been reindexed with MIMO concepts and integrated into a dedicated website. A total of 345 resources have been indexed with MIMO concepts and are freely available at https://doccismef.chu-rouen.fr/dc/#env=sanurn. The development of a multilingual MIMO for enhancing the quality and the efficiency of international projects is challenging. A specific semantic search engine has been deployed to give access to digital health teaching resources.

The Digital Health Leadership Programme is commissioned by Health Education England and part of the wider NHS Digital Academy. The Programme is a consortium of Imperial College London’s Institute of Global Health Innovation, The University of Edinburgh’s Usher Institute and Harvard Medical School. In 2021, Health Data Research UK joined Imperial and Edinburgh to deliver phase 2. The aim is to develop a new generation of digital health leaders to drive transformation of the NHS through digitisation. Participants gain the skills and knowledge to create change so that patient care and organisational operations can benefit from the many improvements and innovations modern technology has to offer.

Mobile health applications can help to disseminate educational health interventions and be widely used. However, mobile health applications not carefully developed will likely not be adopted by the intended users. This paper describes the methodology used to develop a mobile health application for teaching critical thinking about health to youth attending youth friendly centres in Rwanda. The app includes the adapted content of a children’s “health choices book”. We adapted the book into audio podcasts to fit the context of young adults. The application was developed following a framework for developing mobile health applications. The framework follows three theories: health belief model, the theory of planned behavior and technology acceptance model. We developed an Android based application which can be freely accessed in the Play store. The content in the app explains the need for critical thinking, the 10 audio podcasts, the support, and chat window where users share their experience of using the app. The app will be piloted in two youth centers in Rwanda.

In medicine, many international exchange opportunities exist, yet often only towards the end of the course of study. Opportunities for students to gain high-level international research experience early during the studies are rare. A good student-mentor relationship during a research stay abroad is a key factor for scientific success. The aims of this paper are to report on an international exchange and education program that has funded more than 700 students and has been carefully developed and advanced over more than 40 years, its mentor-to-mentor concept and potential success factors for building and maintain such programs. A summary of the history, the concept and the experiences of students is provided, along with a discussion of evaluation results and success factors. The Biomedical Education Program (BMEP) team has – within the last seven years of leadership by the authors – selected and funded 83 German students from different biomedical studies who went abroad for research projects. Preliminary evaluation results show a high degree of satisfaction with the program and its mentor-to-mentor concept, which we deem to be the key to success. Further factors include continued funding, determination, self-organization and assertiveness, an excellent alumni network and a meticulous selection process for both, students and hosts. Further, more detailed evaluation of survey results has to follow. Our results may support the build-up of similar exchange programs.

The digital transformation of the UK’s healthcare system necessitates the development of digital capabilities across the workforce. This ranges from basic digital literacy through to advanced skills with data and analytic methods. We present two projects that apply co-design to work with end-users and other stakeholders to produce a digital healthcare technologies capability framework aimed at the wider NHS workforce and a post graduate Clinical Data Science course aimed at bridging the gap between clinicians and the data-centric professions (e.g. analysts, data scientists, informaticians) to aid in digital transformation projects.

The digital healthcare workforce is usually composed of two major types of professionals: the healthcare workers, who are the users of eHealth, and the health informatics developers, who are usually computer scientists, biomedical engineers, or other technical experts. Health informatics educators have the responsibility to develop the appropriate skills for both, acting within their specific curricula. Here we present the experience of the Italian Society of Biomedical Informatics (SIBIM) and show that, whereas the technical curricula are widely covered with a large range of topics, the eHealth education in medical curricula is often limited to simple bioengineering and informatics skills, thus suggesting that eHealth associations and organizations at the national level should focus their efforts towards increasing the level of eHealth contents in medical schools.

Health data science is an emerging discipline that bridges computer science, statistics and health domain knowledge. This consists of taking advantage of the large volume of data, often complex, to extract information to improve decision-making. We have created a Master’s degree in Health Data Science to meet the growing need for data scientists in companies and institutions. The training offers, over two years, courses covering computer science, mathematics and statistics, health and biology. With more than 60 professors and lecturers, a total of 835 hours of classes (not including the mandatory 5 months of internship per year), this curriculum has enrolled a total of 53 students today. The feedback from the students and alumni allowed us identifying new needs in terms of training, which may help us to adapt the program for the coming academic years. In particular, we will offer an additional module covering data management, from the edition of the clinical report form to the implementation of a data warehouse with an ETL process. Git and application lifecycle management will be included in programming courses or multidisciplinary projects.

Progress in methods for biomedical research, such as multi-omics analyses and in data-driven healthcare, such as new procedures in diagnostic imaging lead, along with the rising availability of additional data sources, to a growing demand for experts in biomedical data analysis. Addressing this need in academic education and the challenge of interdisciplinary teamwork in the biomedical domain, the authors have designed and implemented a new Master’s program for biomedical data science that accepts students with different educational backgrounds, medical doctors, veterinarians and students with a Bachelor’s degree in life sciences, and incorporates blended learning. This paper aims to present the didactic concept of the program, report on feedback from the students and first evaluation results, and discuss the benefits and drawbacks of this approach. Our results show that the program is well-accepted by the students, who stress the benefits of working in interprofessional teams, the option for part-time study along with their jobs with flexible learning opportunities, and of good and intensive interaction offers with their peers and teachers. Readjustments are necessary to improve tutoring support and alignment of content among distinct modules and to decrease workload peaks. While our evaluation results are still preliminary, we are convinced that our approach of mostly online offers, yet with a strong focus on teamwork, practical exercises guided by experts and communication skills, may serve to educate students to be well-prepared for their future tasks and operations in biomedical data science, in research, clinical care and industry.

For the success of digital applications, especially AI applications, it is essential that both developers and medical professionals are enabled to understand each other’s perspective. For this reason, a new concept for an interdisciplinary complex practical course was developed for the master’s program in computer science at a German university, based on online learning nuggets and a hackathon on site. The core of the concept is a real-world medical application task: extracting ECG patient data from a smartwatch to support primary care physicians in making decisions regarding an action. The concept was developed based on the so-called constructive alignment concept. An initial application of the concept showed that it was rated as very positive in terms of learning experience and working atmosphere.

For Medical Informatics graduates, there is no compatibility between the training knowledge and skills at universities and the job requirements. This study aimed to determine the skills and competencies requirements for medical informatics graduates and possible job positions in an emerging discipline. This qualitative study was conducted using a questionnaire developed by the researchers. Nine independent medical informatics professionals assessed the initial draft of this tool to determine its face and content validity, and reliability. The questionnaire was distributed among 80 medical informaticians with a doctorate or a master’s degree. In this study, items with an average of 4 and higher were confirmed; out of the 78 items, 66 were approved. The highest number of unapproved items was related to managerial knowledge and skills. Research knowledge, training skills, individual skills, technical capacities, specific skills in the health industry, and managerial skills are the main areas that graduates must learn. This survey can help develop a curriculum and job descriptions for medical informatics.

Data quality is essential for utilizing real world data (RWD) in scientific context. Based on drug prescriptions in a hospital information system (HIS), algorithms performed a mapping of unstructured drug data to ATC codes. Visualization of the resulting distribution of structured to unstructured data based on ATC codes was created and used to explore a defined limitation of the current drug prescription highlighting the example of proton pump inhibitors. As a second step, a generalization of this approach was inductively created. As result we were able to identify 4 crucial steps for a feedback loop framework: The first step being the actual use of the HIS by clinician for drug prescription, second the processing of the entered unstructured and structured data and performing automatic analyses and visualization of the resulting distributions. The third step included an interdisciplinary expert evaluation of the data distribution followed by the fourth step, consisting of feedback to the stakeholders and generating actions as teaching or re-modelling of the system incorporating the actual learning process. The presented approach represents a continuously learning system based on RWD, although it is limited by analyzing the distribution of mapped unstructured text to ATC codes and therefore does not allow to analyze free text not mapped to ATC codes (false negatives). Future work will focus on the evaluation of this approach to analyze the impact on prescription data quality and the potential improvement on patient safety in general.

The Wales Institute of Digital Information has developed a flexible model of education, CPD, research and innovation for the Welsh health and care sectors, in the digital arena. The co-produced model had produced significant benefits for both health employers and the Universities involved in the partnership. The model is continuing to develop collaborative educational provision from level 2 to level 8 and is concentrating on expanding its digital research and innovation offering to the health and care sector in a similar co-developed collaborative way.

The data collected in the clinical registries or by data reuse require some modifications in order to suit the research needs. Several common operations are frequently applied to select relevant patients across the cohort, combine data from multiple sources, add new variables if needed and create unique tables depending on the research purpose. We carried out a qualitative survey by conducting semi-structured interviews with 7 experts in data reuse and proposed a standard workflow for health data management. We implemented a R tutorial based on a synthetic data set using Jupyter Notebook for a better understanding of the data management workflow.

Augmented Reality (AR) is already used as the primary visualization and user interaction tool in several scientific and business areas. At the same time new AR technologies and frameworks considerably facilitate both the development of innovative applications and also their wide adoption in different domains of everyday life. In the area of healthcare AR solutions make use of mobile or wearable devices and glasses to support, among others, education and healthcare professionals training. The aim of this paper is to present a prototype mHealth app for education, which uses AR and computer vision technologies for pharmaceutical substances recognition on drug packaging. The conceptual design of the system includes three main components which are responsible for a) Text recognition, b) Drug identification and c) AR operations for interactivity. The prototype application is available in Android or iOS platforms and has been evaluated in real-world scenarios. Camera and screen of the mobile phones fulfill the text recognition and AR operations, which eliminates the need for special equipment, while PubChem and 3D Model databases provide assets required for the drug identification and AR visualizations. The results highlight the value of AR for educational purposes, especially when combined with advanced image recognition technologies to build interactive AR encyclopedias.

Computable knowledge artefact development is challenging and often culminates in the development of unique single usage solutions. Libraries of computable knowledge artefacts have the possibility to enhance the Learning Health System in order to improve the benefits of innovation and the decision making of clinicians. This paper aims to discuss the process of creating the use cases and the tutorial material that would enable students to both understand how the interaction between the dataset and the outcome occurs as well as how HL7 Clinical Quality Language can be used to create artefacts of re-usable code.

Issues of non-use of available health information technology (HIT) have been referred to as the ‘last mile problem’ impeding harnessing the full potential of HIT. We reflect upon which competencies are needed to address the last mile problem by ensuring a context-sensitive implementation. We argue that there is a need for context-sensitive digital integrators, who can navigate the realm where technological systems meet practice. This entails a situated, socio-technical, context-sensitive approach and competencies which are not easily addressed through formal training but require lifelong situated learning, as the field evolves continuously. Our ambition is to highlight the complexities of implementation and integration into local practice. This paper emphasizes the role of digital integrators in the hope of fostering further discussions on how to acknowledge and nourish these competencies in order to address and go beyond the last mile problem.

The health and social care sector has experienced an optimistic turn in the last decade. There has been substantial growth in recent years due to the COVID-19 pandemic that forced the entire sector to identify digital methods of delivering a better level of care than before the pandemic. This paper used the Theory to Change (ToC) approach to demonstrate how the digital skills development of the health and care workforce can be achieved in specific contexts. The paper offers background on digital technologies used in healthcare and outlines the steps and methods used in developing a ToC map. The impact of the proposed ToC approach provides a measurable and predictable way to onboard the health and social care workforce into digital technologies, providing a more digitally skilled and literate workforce.

The Electronic Health Record has failed to meet its intended purpose. We propose a new approach focusing on the use of data for health and health care. The first step is to create a repository of all patient data with data storage independent of data use. All use functionality is external to data storage. We propose the development of a common data model in which data elements have a rich set of attributes including actionable knowledge. Finally, functionality is provided through a series of application program interfaces (API). New APIs will address directly new methods for using data to increase the effectiveness of data application to improve management of the health and care of a patient. Together these components will open a pathway to finally accomplish the goals of a better future health system.

One possible cause of overprescribing (or insufficient deprescribing) is the failure to explicitly address the individual’s life expectancy (LE). For example, if a LE estimate shows the person has six months to live, this should influence the prescribing of a medication that offers benefits only over a much longer LE. Predicting exactly the number of years a person will live is impossible, but probabilistic forecasting is possible and arguably essential, both for the selection of the optimal intervention and for meeting the ‘reasonable patient’ standard of information about the harms and benefits of alternative options. One side-effect of the COVID-19 pandemic has been to bring mortality into greater prominence, hopefully facilitating its discussion in the clinic as part of the ‘new normal’. This paper outlines the case for introducing LE into prescribing decisions as a way of making more individualised decisions and potentially reducing overprescribing. It concentrates on how the clinical task of arriving at individualised estimates of LE might be tackled, especially in the case of the growing number of older patients with heterogeneous sociodemographic characteristics who are experiencing multiple long term conditions of varying severity and are frequently subject to ‘polypharmacy’.

A large number of Electronic Medical Records (EMR) are currently available with a variety of features and architectures. Existing studies and frameworks presented some solutions to overcome the problem of specification and application of clinical guidelines toward the automation of their use at the point of care. However, they could not yet support thoroughly the dynamic use of medical knowledge in EMRs according to the clinical contexts and provide local application of international recommendations. This study presents the development of the Clinical Knowledge Platform (CKP): a collaborative interoperable environment to create, use, and share sets of information elements that we entitled Clinical Use Contexts (CUCs). A CUC could include medical forms, patient dashboards, and order sets that are usable in various EMRs. For this purpose, we have identified and developed three basic requirements: an interoperable, inter-mapped dictionary of concepts leaning on standard terminologies, the possibility to define relevant clinical contexts, and an interface for collaborative content production via communities of professionals. Community members work together to create and/or modify, CUCs based on different clinical contexts. These CUCs will then be uploaded to be used in clinical applications in various EMRs. With this method, each CUC is, on the one hand, specific to a clinical context and on the other hand, could be adapted to the local practice conditions and constraints. Once a CUC has been developed, it could be shared with other potential users that can consume it directly or modify it according to their needs.