National Trial Overview: Towards Accessible and Patient-Centered Healthcare.

This protocol paper explores the initiative to build and implement a National Trial Overview to make clinical trials more accessible to patients and health professionals in Denmark. The paper address how a user-centered evaluation of the platform will be conducted and how the National Trial Overview can contribute to enhancing diversity, equity, and inclusion of patients and health professionals, and make access to clinical trials more patient-centered.

Citizens Access to Health Information in National Portals in the Nordic Countries.

National eHealth portals for citizens are available in the five Nordic countries. This study describes and compares the Nordic citizen portals and identifies variations in content access and functionality. The findings suggest that availability of information and services depend on the organisation of the health system, the connection to national health information exchange platforms and incentives for providing data and services.

Citizens' Access to Online Health Information - An International Survey of IMIA Member Countries.

Citizens' access to their online health information is pivotal. Therefore, this study examines citizens' access to their online health information across countries and healthcare settings. The study is based on a survey design targeting the 98 IMIA representatives of the national societies. Results indicate that Test results and Medications are the two types of online information that citizens in most cases have access to. Ten countries provide citizens access to all the different types of information included in the study. That relatively few countries provide citizens access to all the included types of online health information underscores the importance of continuous emphasis on accessibility and research within this field.

One Health: Insights from Organizational & Social, Technology Assessment and Human Factors Perspectives.

OBJECTIVES: To offer diverse but complementary perspectives on how biomedical and health informatics can be informed by and help to achieve the vision of One Health. METHODS: Overview of key considerations and critical discussion of common themes, barriers and opportunities, based on collaborative review by International Medical Informatics Association (IMIA) working group members active in related fields. RESULTS: Health and care systems are complex sociotechnical systems that need explicit design and implementation strategies to align with the goals of One Health. The evidence-based health informatics paradigm and associated frameworks for evaluation of digital health technologies need to broaden their scope to take full account of the One Health approach. Informatics has specific contributions to make to One Health, for example by improved user experience reducing energy consumption and effective app design enhancing medication adherence. CONCLUSIONS: One Health is inherently intertwined with ergonomic, sociotechnical and evaluation perspectives in biomedical and health informatics. Health is a planetary issue that requires interdisciplinary collaborative action. The theories and principles of biomedical and health informatics offer many opportunities to transform digital health technology to better serve the One Health agenda.

Equity in digital healthcare - the case of Denmark.

As digital healthcare services are expanding in use and purpose in a Danish context so are the functionalities embedded in these, constituting citizens' access to healthcare services and personal health data. In Denmark, the impact of inequalities in digital healthcare remains largely unexplored, making it crucial to pay close attention to this aspect as the digital transformation of the sector progresses. According to the Danish Health Act (2019), the Danish healthcare system is required to ensure easy and equal access to healthcare, high-quality treatment, coherent patient pathways, freedom of choice, easy access to information, transparency, and short waiting times for every citizen. These are focal law-based requirements influenced by the digitalisation of healthcare. Hence, based on insights from a highly digitalised country, in this case, Denmark, this paper aims to initiate a discussion on inequities in digital healthcare, address current challenges, and consider future directions by elaborating on conceptual, ethical, evidence-informed, and methodological issues linked to inequities in digital healthcare. Specifically, this paper discusses why inequities in digital healthcare in a Danish context need increased attention, how health equity is embedded in Danish legislation and how it can be approached from an ethical perspective. The central focus revolves around the essential principles of empowerment, emancipation, and equity, which are being highlighted to emphasise that the digitalisation of healthcare should actively work towards preventing and avoiding the perpetuation of healthcare inequalities. The paper concludes by discussing future directions for ensuring a more sustainable, robust, and equitable digital healthcare system.

Keyphrase Identification Using Minimal Labeled Data with Hierarchical Context and Transfer Learning.

Interoperable clinical decision support system (CDSS) rules provide a pathway to interoperability, a well-recognized challenge in health information technology. Building an ontology facilitates creating interoperable CDSS rules, which can be achieved by identifying the keyphrases (KP) from the existing literature. However, KP identification for data labeling requires human expertise, consensus, and contextual understanding. This paper aims to present a semi-supervised KP identification framework using minimal labeled data based on hierarchical attention over the documents and domain adaptation. Our method outperforms the prior neural architectures by learning through synthetic labels for initial training, document-level contextual learning, language modeling, and fine-tuning with limited gold standard label data. To the best of our knowledge, this is the first functional framework for the CDSS sub-domain to identify KPs, which is trained on limited labeled data. It contributes to the general natural language processing (NLP) architectures in areas such as clinical NLP, where manual data labeling is challenging, and light-weighted deep learning models play a role in real-time KP identification as a complementary approach to human experts' effort.

Differential Perceptions of What Constitutes a Medical Error Associated with Electronic Medical Records.

Perceptions of errors associated with healthcare information technology (HIT) often depend on the context and position of the viewer. HIT vendors posit very different causes of errors than clinicians, implementation teams, or IT staff. Even within the same hospital, members of departments and services often implicate other departments. Organizations may attribute errors to external care partners that refer patients, such as nursing homes or outside clinics. Also, the various clinical roles within an organization (e.g., physicians, nurses, pharmacists) can conceptualize errors and their root causes differently. Overarching all these perceptual factors, the definitions, mechanisms, and incidence of HIT-related errors are remarkably conflictual. There is neither a universal standard for defining or counting these errors. This paper attempts to enumerate and clarify the issues related to differential perceptions of medical errors associated with HIT. It then suggests solutions.

Decentralized Clinical Trials: Potentials for Equity in Digital Health.

The COVID-19 pandemic has rapidly increased the possibilities for conducting Decentralized Clinical Trials (DCT). This paper addresses the potential for conducting DCT in Denmark and discusses how this potential can improve equity in digital healthcare. From stakeholder interviews, we learned that DCT has the potential to be implemented, as DCT guidelines are in place in Denmark. DCT can potentially improve equal access and inclusion of diverse populations, home administration of medication, retention and compliance, and monitoring of patients and side effects. While DCT has potential in a Danish context, the challenges regarding DCT need to be considered carefully, particularly concerning equity in digital health.

The Inverse Data Law: Market Imperatives, Data, and Quality in AI Supported Care.

Over the last decade, the explosion of "Big Data" and its fusion with AI has led many to believe that the development and integration of AI systems in healthcare will usher in a transformative revolution that democratises access to high quality healthcare and collectively improve patient outcomes. However, the nature of market forces in the evolving data economy, has started to show evidence that the opposite is more likely to be true. This paper argues that there is a poorly understood "Inverse Data Law" that will exacerbate the widening health divide between affluent and marginalised communities because: (1) data used to train AI systems favour individuals that are already engaged with healthcare, who have the lowest burden of disease, but the highest purchasing power; and (2) data used to drive market decisions around investment in AI health technology favours tools that increase the commodification of healthcare through over-testing, over-diagnosis, and the acute and episodic management of disease, over tools that support the patient to prevent disease. This dangerous combination is more likely to cripple efforts towards preventative medicine, as data collection and utilisation tends to be inversely proportional to the needs of the patients served - the inverse data law. The paper concludes by introducing important methodological considerations in the design and evaluation of AI systems to promote systems improvement for marginalised users.

Perceptions of Learning Activities in Electronic Health Record Transition.

Learning activities are at the front-line of first impressions. In this paper, the education and training program for a large electronic health record transition project is presented. Management, and staff were interviewed before, during, and after implementation on their perception, reception, and benefit of various learning activities. Daily clinical work and obligations complicate adherence to learning programs, and the clinical professions differ in their approach to mandatory activities. Local learning activities empower staff, and planners should consider embedding room for adjustment of learning program during implementation.

Ontologies Applied in Clinical Decision Support System Rules: Systematic Review.

BACKGROUND: Clinical decision support systems (CDSSs) are important for the quality and safety of health care delivery. Although CDSS rules guide CDSS behavior, they are not routinely shared and reused. OBJECTIVE: Ontologies have the potential to promote the reuse of CDSS rules. Therefore, we systematically screened the literature to elaborate on the current status of ontologies applied in CDSS rules, such as rule management, which uses captured CDSS rule usage data and user feedback data to tailor CDSS services to be more accurate, and maintenance, which updates CDSS rules. Through this systematic literature review, we aim to identify the frontiers of ontologies used in CDSS rules. METHODS: The literature search was focused on the intersection of ontologies; clinical decision support; and rules in PubMed, the Association for Computing Machinery (ACM) Digital Library, and the Nursing & Allied Health Database. Grounded theory and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines were followed. One author initiated the screening and literature review, while 2 authors validated the processes and results independently. The inclusion and exclusion criteria were developed and refined iteratively. RESULTS: CDSSs were primarily used to manage chronic conditions, alerts for medication prescriptions, reminders for immunizations and preventive services, diagnoses, and treatment recommendations among 81 included publications. The CDSS rules were presented in Semantic Web Rule Language, Jess, or Jena formats. Despite the fact that ontologies have been used to provide medical knowledge, CDSS rules, and terminologies, they have not been used in CDSS rule management or to facilitate the reuse of CDSS rules. CONCLUSIONS: Ontologies have been used to organize and represent medical knowledge, controlled vocabularies, and the content of CDSS rules. So far, there has been little reuse of CDSS rules. More work is needed to improve the reusability and interoperability of CDSS rules. This review identified and described the ontologies that, despite their limitations, enable Semantic Web technologies and their applications in CDSS rules.

The Last Mile Problem and Beyond in HIT - The Role of Context-Sensitive Digital Integrators.

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.

Hidden in Plain Sight: Overlooked Results and Other Errors in Evaluating Online Laboratory Results.

People are increasingly accessing their own laboratory (lab) results online. However, Canadians may be expected to use different systems to access their results, depending upon where they are tested (e.g., community lab vs. hospital), and these results may be displayed differently. This study examined the extent to which participants without medical expertise (N = 25) made errors identifying lab results (i.e., missing or mis-identifying abnormal results) in a mock report. Six participants overlooked each of the flagged values, 20 participants missed an abnormal result that was not flagged, and 2 participants mis-identified a normal value as out of range. We describe potential causes of these errors and the implications for the design of consumer-facing lab results.

AI Diagnostic Technologies and the Gap in Colorectal Cancer Screening Participation.

AI augmented clinical diagnostic tools are the latest research focus in colorectal cancer (CRC) detection. While the opportunity presented by AI-enhanced CRC diagnosis is sound, this paper highlights how its effectiveness with respect to reducing CRC-related mortality and enhancing patient outcomes may be limited by the fact that patient participation remains extremely low globally. This paper builds a foundation to consider how human factors tend to contribute to low participation rates and suggests that a more nuanced socio-technical approach to the development, implementation and evaluation of AI systems that is sensitive to the psycho-social and cultural dimension of CRC may lead to tools that increase screening uptake.

A Systematic Approach to Configuring MetaMap for Optimal Performance.

BACKGROUND: MetaMap is a valuable tool for processing biomedical texts to identify concepts. Although MetaMap is highly configurative, configuration decisions are not straightforward. OBJECTIVE: To develop a systematic, data-driven methodology for configuring MetaMap for optimal performance. METHODS: MetaMap, the word2vec model, and the phrase model were used to build a pipeline. For unsupervised training, the phrase and word2vec models used abstracts related to clinical decision support as input. During testing, MetaMap was configured with the default option, one behavior option, and two behavior options. For each configuration, cosine and soft cosine similarity scores between identified entities and gold-standard terms were computed for 40 annotated abstracts (422 sentences). The similarity scores were used to calculate and compare the overall percentages of exact matches, similar matches, and missing gold-standard terms among the abstracts for each configuration. The results were manually spot-checked. The precision, recall, and F-measure (ß =1) were calculated. RESULTS: The percentages of exact matches and missing gold-standard terms were 0.6-0.79 and 0.09-0.3 for one behavior option, and 0.56-0.8 and 0.09-0.3 for two behavior options, respectively. The percentages of exact matches and missing terms for soft cosine similarity scores exceeded those for cosine similarity scores. The average precision, recall, and F-measure were 0.59, 0.82, and 0.68 for exact matches, and 1.00, 0.53, and 0.69 for missing terms, respectively. CONCLUSION: We demonstrated a systematic approach that provides objective and accurate evidence guiding MetaMap configurations for optimizing performance. Combining objective evidence and the current practice of using principles, experience, and intuitions outperforms a single strategy in MetaMap configurations. Our methodology, reference codes, measurements, results, and workflow are valuable references for optimizing and configuring MetaMap.

The Importance of Contextual Understanding in Solving the Last Mile Problem.

The COVID-19 pandemic has disrupted many global industries and shifted the digital health landscape by stimulating and accelerating the delivery of digital care. It has emphasized the need for a system level informatics implementation that supports the healthcare management of populations at a macro level while also providing the necessary support for front line care delivery at a micro level. From data dashboard to Telemedicine, this crisis has necessitated the need for health informatics transformation that can bridge time and space to provide timely care. However, heath transformation cannot solely rely on Health Information Technology (HIT) for progress, but rather success must be an outcome of system design focus on the contextual complexity of the health system where HIT is used. This conference highlights the important roles context plays for health informatics in global pandemics and aims to answer critical questions in four main areas: 1) health information management in the covid-19 context, 2) implementation of new practices and technologies in healthcare, 3) sociotechnical analysis of task performance and workload in healthcare, and 4) innovations in design and evaluation methods of health technologies. We deem this as a call to action to understand the importance of context while solving the last mile problem in delivering the informatics solutions that are needed to support our public health response.

User Perception of Automated Dose Dispensed Medicine in Home Care: A Scoping Review.

(1) Background: Automated dose dispensing (ADD) systems are today used around the world. The ADD robots are placed in patients' homes to increase medication safety as well as medication adherence; however, little is known about how ADD robots affect the patient's day-to-day lives, receiving the daily doses of medicine from a machine rather than from a human healthcare professional. The aim of this study is to review the available literature on users' perceptions of having an ADD robot and collect evidence on how they perceive having less human contact after implementing this technology in their homes. (2) Methods: References were searched for in Embase and PubMed. Literature investigating ADD robots in primary healthcare was included in this study and literature in a hospital setting was excluded. After screening processes, eleven publications were included in this review. (3) Results: The literature reported high medication adherence when using ADD robots and general satisfaction in terms of user experiences with the acceptability and functionality of ADD. (4) Conclusion: The review is the first focusing on user experience and perceptions regarding ADD robots. General satisfaction was shown towards ADD robots as an intervention, but the review indicates that research is missing on healthcare professionals and patient perceptions on how ADD affects their routines, both in relation to work and daily life.

Advances in E-Health.

E-health offers new ways to access health information, to deliver health and social care and to perform self-management [...].

A Simple Assessment of Information Security Awareness in Hospital Staff Across Five Danish Regions.

Information Security Awareness among employees in healthcare has become an essential part in safeguarding health information systems against cyber-attacks and data breaches. We present three simple security awareness questions that can be included in larger surveys gauging other aspects of information systems. The questions have been tested in a national Danish survey to evaluate correlations among medical profession, computer proficiency, experience, and place of employment. We find that dissatisfaction with system usability is strongly linked with reduced information security awareness, and that clinical professions have different responses to security concerns.