Analysis of Critical Incident Reports Using Natural Language Processing.

A Critical Incident Reporting System (CIRS) collects anecdotal reports from employees, which serve as a vital source of information about incidents that could potentially harm patients. OBJECTIVES: To demonstrate how natural language processing (NLP) methods can help in retrieving valuable information from such incident data. METHODS: We analyzed frequently occurring terms and sentiments as well as topics in data from the Swiss National CIRRNET database from 2006 to 2023 using NLP and BERTopic modelling. RESULTS: We grouped the topics into 10 major themes out of which 6 are related to medication. Overall, they reflect the global trends in adverse events in healthcare (surgical errors, venous thromboembolism, falls). Additionally, we identified errors related to blood testing, COVID-19, handling patients with diabetes and pediatrics. 40-50% of the messages are written in a neutral tone, 30-40% in a negative tone. CONCLUSION: The analysis of CIRS messages using text analysis tools helped in getting insights into common sources of critical incidents in Swiss healthcare institutions. In future work, we want to study more closely the relations, for example between sentiment and topics.

How Participatory Health Informatics Catalyzes One Digital Health.

OBJECTIVE: To identify links between Participatory Health Informatics (PHI) and the One Digital Health framework (ODH) and to show how PHI could be used as a catalyst or contributor to ODH. METHODS: We have analyzed the addressed topics within the ODH framework in previous IMIA Yearbook contributions from our working group during the last 10 years. We have matched main themes with the ODH's framework three perspectives (individual health and wellbeing, population and society, and ecosystem). RESULTS: PHI catalysts ODH individual health and wellbeing perspective by providing a more comprehensive view on human health, attitudes, and relations between human health and animal health. Integration of specific behavior change techniques or gamification strategies in digital solutions are effective to change behaviors which address the P5 paradigm. PHI supports the population and society perspective through the engagement of the various stakeholders in healthcare. At the same time, PHI might increase a risk for health inequities due to technologies inaccessible to all equally and challenges associated with this. PHI is a catalyst for the ecosystem perspective by contributing data into the digital health data ecosystem allowing for analysis of interrelations between the various data which in turn might provide links among all components of the healthcare ecosystem. CONCLUSION: Our results suggest that PHI can and will involve topics relating to ODH. As the ODH concept crystalizes and becomes increasingly influential, its themes will permeate and become embedded in PHI even more. We look forward to these developments and co-evolution of the two frameworks.

Assessing the Potential Risks of Digital Therapeutics (DTX): The DTX Risk Assessment Canvas.

MOTIVATION: Digital therapeutics (DTX), i.e., health interventions that are provided through digital means, are increasingly available for use; in some countries, physicians can even prescribe selected DTX following a reimbursement by health insurances. This results in an increasing need for methodologies to consider and monitor DTX's negative consequences, their risks to patient safety, and possible adverse events. However, it is completely unknown which aspects should be subject to surveillance given the missing experiences with the tools and their negative impacts. OBJECTIVE: Our aim is to develop a tool-the DTX Risk Assessment Canvas-that enables researchers, developers, and practitioners to reflect on the negative consequences of DTX in a participatory process. METHOD: Taking the well-established business model canvas as a starting point, we identified relevant aspects to be considered in a risk assessment of a DTX. The aspects or building blocks of the canvas were constructed in a two-way process: first, we defined the aspects relevant for discussing and reflecting on how a DTX might bring negative consequences and risks for its users by considering ISO/TS 82304-2, the scientific literature, and by reviewing existing DTX and their listed adverse effects. The resulting aspects were grouped into thematic blocks and the canvas was created. Second, six experts in health informatics and mental health provided feedback and tested the understandability of the initial canvas by individually applying it to a DTX of their choice. Based on their feedback, the canvas was modified. RESULTS: The DTX Risk Assessment Canvas is organized into 15 thematic blocks which are in turn grouped into three thematic groups considering the DTX itself, the users of the DTX, and the effects of the DTX. For each thematic block, questions have been formulated to guide the user of the canvas in reflecting on the single aspects. Conclusions: The DTX Risk Assessment Canvas is a tool to reflect the negative consequences and risks of a DTX by discussing different thematic blocks that together constitute a comprehensive interpretation of a DTX regarding possible risks. Applied during the DTX design and development phase, it can help in implementing countermeasures for mitigation or means for their monitoring.

Towards Safe Conversational Agents in Healthcare.

Conversational agents (CA) are becoming very popular to deliver digital health interventions. These dialog-based systems are interacting with patients using natural language which might lead to misunderstandings and misinterpretations. To avoid patient harm, safety of health CA has to be ensured. This paper raises awareness on safety when developing and distributing health CA. For this purpose, we identify and describe facets of safety and make recommendations for ensuring safety in health CA. We distinguish three facets of safety: 1) system safety, 2) patient safety, and 3) perceived safety. System safety comprises data security and privacy which has to be considered when selecting technologies and developing the health CA. Patient safety is related to risk monitoring and risk management, to adverse events and content accuracy. Perceived safety concerns a user's perception of the level of danger and user's level of comfort during the use. The latter can be supported when data security is guaranteed and relevant information on the system and its capabilities are provided.

Social Media, Digital Health Literacy, and Digital Ethics in the Light of Health Equity.

OBJECTIVE: Social media is used in the context of healthcare, for example in interventions for promoting health. Since social media are easily accessible they have potential to promote health equity. This paper studies relevant factors impacting on health equity considered in social media interventions. METHODS: We searched for literature to identify potential relevant factors impacting on health equity considered in social media interventions. We included studies that reported examples of health interventions using social media, focused on health equity, and analyzed health equity factors of social media. We identified Information about health equity factors and targeted groups. RESULTS: We found 17 relevant articles. Factors impacting on health equity reported in the included papers were extracted and grouped into three categories: digital health literacy, digital ethics, and acceptability. CONCLUSIONS: Literature shows that it is likely that digital technologies will increase health inequities associated with increased age, lower level of educational attainment, and lower socio-economic status. To address this challenge development of social media interventions should consider participatory design principles, visualization, and theories of social sciences.

Usability Assessment of Conversational Agents in Healthcare: A Literature Review.

Conversational agents (CA) are chatbot-based systems supporting the interaction with users through text, speech, or other modalities. They are used in an increasing number of medical use cases. Even though usability is considered a prerequisite for the success of mHealth apps using CA, there is still no standard procedure to study usability of health CA. In this paper, we report the results from a systematic literature review aiming at identifying study designs, tools, and metrics used to assess usability in health CA. We searched three bibliographic databases (PubMed, Scopus, IEEE Xplore) for papers reporting on CA in healthcare to extract information on the usability assessment of those CA. From 273 retrieved results, we included 66 papers for full text review. 34 of them reported on usability assessments. A broad range of tools is used (e.g. SUS, UEQ), but also individual questionnaires are exploited. The examined studies use scenario-based setups but assess also real-world usage. Exploratory setups are rarely reported. Due to the differences in the study designs and assessment tools, it is impossible to compare usability among CA. Thus, we recommend to develop a standardised procedure that can be always applied and which can be enriched by assessments needed for evaluating usability of CA-specific features.

Ethical Considerations for Participatory Health through Social Media: Healthcare Workforce and Policy Maker Perspectives.

OBJECTIVES: To identify the different ethical issues that should be considered in participatory health through social media from different stakeholder perspectives (i.e., patients/service users, health professionals, health information technology (If) professionals, and policy makers) in any healthcare context. METHODS: We implemented a two-round survey composed of open ended questions in the first round, aggregated into a list of ethical issues rated for importance by participants in the second round, to generate a ranked list of possible ethical issues in participatory health based on healthcare professionals' and policy makers' opinions on both their own point of view and their beliefs for other stakeholders' perspectives. RESULTS: Twenty-six individuals responded in the first round of the survey. Multiple ethical issues were identified for each perspective. Data privacy, data security, and digital literacy were common themes in all perspectives. Thirty-three individuals completed the second round of the survey. Data privacy and data security were ranked among the three most important ethical issues in all perspectives. Quality assurance was the most important issue from the healthcare professionals' perspective and the second most important issue from the patients' perspective. Data privacy was the most important consideration for patients/service users. Digital literacy was ranked as the fourth most important issue, except for policy makers' perspective. CONCLUSIONS: Different stakeholders' opinions fairly agreed that there are common ethical issues that should be considered across the four groups (patients, healthcare professionals, health IT professionals, policy makers) such as data privacy, security, and quality assurance.

An ethical assessment model for digital disease detection technologies.

Digital epidemiology, also referred to as digital disease detection (DDD), successfully provided methods and strategies for using information technology to support infectious disease monitoring and surveillance or understand attitudes and concerns about infectious diseases. However, Internet-based research and social media usage in epidemiology and healthcare pose new technical, functional and formal challenges. The focus of this paper is on the ethical issues to be considered when integrating digital epidemiology with existing practices. Taking existing ethical guidelines and the results from the EU project M-Eco and SORMAS as starting point, we develop an ethical assessment model aiming at providing support in identifying relevant ethical concerns in future DDD projects. The assessment model has four dimensions: user, application area, data source and methodology. The model supports in becoming aware, identifying and describing the ethical dimensions of DDD technology or use case and in identifying the ethical issues on the technology use from different perspectives. It can be applied in an interdisciplinary meeting to collect different viewpoints on a DDD system even before the implementation starts and aims at triggering discussions and finding solutions for risks that might not be acceptable even in the development phase. From the answers, ethical issues concerning confidence, privacy, data and patient security or justice may be judged and weighted.

eMedication Meets eHealth with the Electronic Medication Management Assistant (eMMA).

BACKGROUND: A patient's healthcare team is often missing a complete overview on the prescribed and dispensed medication. This is due to an inconsistent information flow between the different actors of the healthcare system. Often, only the patient himself knows exactly which drugs he is actually taking. OBJECTIVES: Our objective is to exploit different eHealth technologies available or planned in Switzerland to improve the information flow of the medication data among the stakeholder and to support the patient in managing his medication. METHODS: This work is embedded in the "Hospital of the Future Live" project, involving 16 companies and 6 hospitals in order to develop IT solutions for future optimized health care processes. A comprehensive set of requirements was collected from the different actors and project partners. Further, specifications of the available or planned eHealth infrastructure were reviewed to integrate relevant technologies into a coherent concept. RESULTS: We developed a concept that combines the medication list and an eHealth platform. The resulting electronic medication management assistant (eMMA) designed for the patient provides the current medication plan at any time and supports by providing relevant information through a conversational user interface. CONCLUSION: In Switzerland, we still need a bridging technology to combine the medication information from the electronic patient record with the medication plan's associated QR-Code. The developed app is intended to provide such bridge and demonstrates the usefulness of the eMediplan. It enables the patient to have all data regarding his medication on his personal mobile phone and he can - if necessary - provide the current medication to the health professional.

Making knowledge on healthcare technologies understandable: an ontology for lab-on-a-chip systems.

Technology for supporting diagnosis and treatment is becoming more complex. New developments are coming up and need to be evaluated from various perspectives. Researchers from other disciplines are seldom experts in healthcare technology. The relevant terminology needs to be settled to be able to communicate interdisciplinary. In this paper, we introduce an approach on how to make complex knowledge related to technological developments in healthcare accessible and understandable for experts from other domains. In particular, we consider the field of lab-on-a-chip systems [1]. For this field, we develop an ontology that enables researchers to get insights into the domain and to study the related ethical, sociological, and legal aspects.