HCI-modelling for improving the clinical usability of digital health technologies.

INTRODUCTION: Digital Health Technologies (DHTs) have been shown to have variable usability as measured by efficiency, effectiveness and user satisfaction despite large-scale government projects to regulate and standardise user interface (UI) design. We hypothesised that Human-Computer Interaction (HCI) modelling could improve the methodology for DHT design and regulation, and support the creation of future evidence-based UI standards and guidelines for DHTs. METHODOLOGY: Using a Design Science Research (DSR) framework, we developed novel UI components that adhered to existing standards and guidelines (combining the NHS Common User Interface (CUI) standard and the NHS Design System). We firstly evaluated the Patient Banner UI component for compliance with the two guidelines and then used HCI-modelling to evaluate the "Add New Patient" workflow to measure time to task completion and cognitive load. RESULTS: Combining the two guidelines to produce new UI elements is technically feasible for the Patient Banner and the Patient Name Input components. There are some inconsistencies between the NHS Design System and the NHS CUI when implementing the Patient Banner. HCI-modelling successfully quantified challenges adhering to the NHS CUI and the NHS Design system for the "Add New Patient" workflow. DISCUSSION: We successfully developed new design artefacts combing two major design guidelines for DHTs. By quantifying usability issues using HCI-modelling, we have demonstrated the feasibility of a methodology that combines HCI-modelling into a human-centred design (HCD) process could enable the development of standardised UI elements for DHTs that is more scientifically robust than HCD alone. CONCLUSION: Combining HCI-modelling and Human-Centred Design could improve scientific progress towards developing safer and more user-friendly DHTs.

A Comprehensive Framework for Hospital@Home Care Models.

Hospital@home is a healthcare approach, where patients receive active treatment from health professionals in their own home for conditions that would normally necessitate a hospital stay. OBJECTIVE: To develop a framework of relevant features for describing hospital@home care models. METHODS: The framework was developed based on a literature review and thematic analysis. We considered 42 papers describing hospital@home care approaches. Extracted features were grouped and aggregated in a framework. RESULTS: The framework consists of nine dimensions: Persons involved, target patient population, service delivery, intended outcome, first point of contact, technology involved, quality, and data collection. The framework provides a comprehensive list of required roles, technologies and service types. CONCLUSION: The framework can act as a guide for researchers to develop new technologies or interventions to improve hospital@home, particularly in areas such as tele-health, wearable technology, and patient self-management tools. Healthcare providers can use the framework as a guide or blueprint for building or expanding upon their hospital@home services.

Empathetic and Emotive Design Heuristics: Preliminary Results of Their Application to Evaluating Survey User Interfaces.

Empathetic and emotive design is becoming increasingly important in the digital age. In this research we describe the results of a combined cognitive walkthrough and heuristic evaluation using newly developed, empirically derived empathy or emotive design heuristics. We applied the heuristics to the evaluation of four commonly used survey platforms. Our preliminary findings revealed that the heuristics performed effectively in scoring survey platforms on their level of empathy. Survey platforms that are highly empathetic were scored highest.

Empathetic and Emotive Design: A Scoping Review.

With the advent of the digital health era, there has emerged a new emphasis on collecting health information from patients and their families using technology platforms that are both empathetic and emotive in their design to meet the needs and situations of individuals, who are experiencing a health event or crisis. Digital empathy has emerged as an aspect of interactions between individuals and healthcare organizations especially in times of crises as more empathetic and emotive digital health platforms hold greater capacity to engage the user while collecting valuable health information that could be used to respond to the individuals' needs. In this paper we report on the results of a scoping review used to derive an initial set of evidence-based empathetic or emotive design heuristics.

Empathetic and Emotive Design Heuristics.

The design of user interfaces and systems that promote positive emotional interaction and reaction from end users is becoming a critical area in the design of applications and systems for use by the general population. In this paper we describe our work in the creation of a set of empathetic design heuristics that were developed from examination of the literature in this area within the context of healthcare user interface design. The heuristics and their potential application are explored.

Canada's Digital Health Workforce: The Role of Innovation, Research and Policy.

The rapid growth of digital health and use of technology has led to an increased demand for qualified professionals in the areas of health informatics (HI) and health information management (HIM). This is reflected by the growth in the number of educational programs and graduates in these areas. However, to develop a culture of digital health innovation in Canada, the role of research needs to be critically examined. In this paper we discuss some of these issues around the relation between research and innovation, and the development of an innovation culture in health informatics, health information management and digital health in Canada. Recommendations for facilitating this development in terms of funding, granting and policy are also explored.

Canadian employers' perspectives on a new framework for health informatics competencies.

Competencies are the knowledge, skills, and abilities needed to operate and perform successfully in the workplace. Due to the evolving nature of health informatics, it is important continuously examine and refine competencies in this field. In this study, we administered a questionnaire to Canadian employers (N = 29) of health informatics cooperative education (co-op) students to garner their feedback on competencies within a New Health Informatics Professional Competencies Framework. Overall, the findings supported this new framework. An average of ratings within each of the four competency categories revealed that participants perceived Management Science to be the most important, followed by Information & Computer Science, then Health Science and finally Data Science. Further, at least 20 (69 %) respondents rated nine of the 12 competencies as important. Of the 12 competencies, Biological and Clinical Science was rated the lowest. Findings from this study can potentially be used to inform curricula, career progression, and hiring practices in health informatics. Future work includes refining the questionnaire to assess the competencies more comprehensively and potentially exploring the importance of more transferable skills or general competencies (e.g., communication, problem-solving). Additionally, we want to survey a broader sample of health informatics professionals and integrate recent national and international work on health informatics competencies. Future work is also recommended towards the development of a maturity model for competencies of more experienced health informatics professionals.

Patient Journey Map: Metal Hypersensitivity.

In this study, we highlight patients' experiences with metal hypersensitivity (MH) after receiving implantable medical devices (IMDs). We aim to identify gaps in clinical care and improve outcomes for individuals who have or may be sensitive to metals. Secondary data analysis from a previous interpretative phenomenological qualitative study was utilized. Using patient journey maps, we explored the experiences of 8 individuals from outpatient settings who received IMD and have first-hand experience with MH. We documented their journey from MH symptom recognition to diagnosis and subsequent IMD management. The results reveal that the time frames from device implantation to the treatment of MH varied from 17 to 228 months. The longest phase on the patient journey maps was the symptom recognition phase, which refers to the time between symptom emergence and MH diagnosis. Participants also required extensive healthcare utilization following their initial surgery. These findings emphasize that MH should be considered in differential diagnoses for patients with IMD. Early screening and detection of MH can enhance patient safety, alleviate distress, and reduce unnecessary healthcare utilization.

Modelling Information Needs and Sources in a COVID-19 Designated Hospital.

COVID-19 remains an important focus of study in the field of public health informatics. COVID-19 designated hospitals have played an important role in the management of patients affected by the disease. In this paper we describe our modelling of the needs and sources of information for infectious disease practitioners and hospital administrators used to manage a COVID-19 outbreak. Infectious disease practitioner and hospital administrator stakeholders were interviewed to learn about their information needs and where they obtained their information. Stakeholder interview data were transcribed and coded to extract use case information. The findings indicate that participants used many and varied sources of information in the management of COVID-19. The use of multiple, differing sources of data led to considerable effort. In modelling participants' activities, we identified potential subsystems that could be used as a basis for developing an information system specific to the public health needs of hospitals providing care to COVID-19 patients.

Digital health as an enabler for hospital@home: A rising trend or just a vision?

Background: Hospital@home is a model of healthcare, where healthcare professionals actively treat patients in their homes for conditions that may otherwise require hospitalization. Similar models of care have been implemented in jurisdictions around the world over the past few years. However, there are new developments in health informatics including digital health and participatory health informatics that may have an impact on hospital@home approaches. Objectives: This study aims to identify the current state of implementation of emerging concepts into the hospital@home research and models of care; to identify strengths and weaknesses, opportunities, and threats associated with the models of care; and to suggest a research agenda. Methods: We employed two research methodologies, namely, a literature review and a SWOT (strengths, weaknesses, opportunities, and threats) analysis. The literature from the last 10 years was collected from PubMed using the search string "hospital at home" OR "care at home" OR "patient at home." Relevant information was extracted from the included articles. Results: Title and abstract review were conducted on 1,371 articles. The full-text review was conducted on 82 articles. Data were extracted from 42 articles that met our review criteria. Most of the studies originated from the United States and Spain. Several medical conditions were considered. The use of digital tools and technologies was rarely reported. In particular, innovative approaches such as wearables or sensor technologies were rarely used. The current landscape of hospital@home models of care simply delivers hospital care in the patient's home. Tools or approaches from taking a participatory health informatics design approach involving a range of stakeholders (such as patients and their caregivers) were not reported in the literature reviewed. In addition, emerging technologies supporting mobile health applications, wearable technologies, and remote monitoring were rarely discussed. Conclusion: There are multiple benefits and opportunities associated with hospital@home implementations. There are also threats and weaknesses associated with the use of this model of care. Some weaknesses could be addressed by using digital health and wearable technologies to support patient monitoring and treatment at home. Employing a participatory health informatics approach to design and implementation could help to ensure the acceptance of such care models.

Human factors in healthcare IT: Management considerations and trends.

A range of human factors issues are recognized as critical to the success of projects involving Health Information Technology (HIT). Problems related to the usability of HIT have come to the fore, with continued reports of systems that are non-intuitive and difficult to use and that may even pose safety risks. In this article, we consider a number of approaches from usability engineering and human factors that can be applied to improve the chances of system success and adoption. A range of methods focused around human factors can be employed throughout the system development cycle of HIT. The purpose of this article is to discuss human factors approaches that can be used to improve the likelihood of successful system adoption and also provide input into the selection and procurement process of HIT. The article concludes with recommendations regarding how understanding of human factors can be integrated into healthcare organizational decision making.

Updating professional competencies in health informatics: A scoping review and consultation with subject matter experts.

INTRODUCTION: The discipline of health informatics emerged to address the need for uniquely skilled professionals to design, develop, implement, and evaluate health information technology. Core competencies are an essential pre-requisite for establishing a professional discipline such as health informatics. In 2012, Digital Health Canada released a framework (DHC Framework) for Canadian health informatics competencies. Multiple perspectives on health informatics competencies have evolved to reflect global and unique country contexts. In this paper, we will describe a two-phase study in which we ultimately developed a new framework for health informatics competencies. METHODS: In Phase 1, we conducted a scoping review of to identify health informatics competencies from research articles and grey literature from professional associations. Of 1038 articles identified in the search, ultimately 38 met our inclusion criteria and were subject to in-depth analysis. We summarized our findings from this phase into a preliminary framework of health informatics competencies and then in Phase 2, we shared these findings with subject matter experts (SMEs; N = 5) to garner their feedback. The SMEs were all instructors in health informatics in Canada and held various roles (director, professor, advisor, and co-operative education coordinator). We used their insights into the current and forecasted Canadian health informatics landscape to iteratively develop a new framework until we achieved consensus amongst the subject matter experts. RESULTS: In Phase 1, all competencies of the DHC Framework were supported by the literature. However, we also identified two emergent competencies: Human Factors and Data Science. In Phase 2, consultations with SMEs guided the introduction of one new competency category and seven new competencies. One competency was renamed and two were removed from the DHC Framework. Additionally, we added new terms that encompass the framework and labelled the core of the framework Health Informatics Professionalism. DISCUSSION: We found that the DHC Framework did not capture all necessary competencies required by health informatics professionals. Based on the literature and consultations with SMEs, we extended the DHC Framework to better reflect the current Canadian context and propose a new Health Informatics Core Competencies Framework. The new framework can be used to inform Canadian health informatics programs to ensure graduates are equipped for careers in health informatics. Future work includes validating the new framework with Canadian health informatics employers to assess whether this new framework adequately reflects their needs, and more detail may be required to define specific skills necessary in each competency.

Health technology, quality and safety in a learning health system.

Health technology quality and safety is an important issue for health informatics (i.e. digital health) professionals. Health technologies have been used to (1) collect data that can be analyzed to improve the quality and safety of healthcare activities and (2) re-engineer and/or automate error-prone processes. Health technologies are also able to introduce new types of errors (i.e. technology-induced errors) and have been implicated in propagating errors across digital health ecosystems. To develop a learning health system, health technologies need to be considered in terms of how they can improve the quality and safety of health activities traditionally carried out by humans (patients and health professionals) and also how the technology's quality and safety can be improved. This article outlines how this can be done by integrating evidence from health informatics research into practice using a learning health systems approach.

Recommendations of the International Medical Informatics Association (IMIA) on Education in Biomedical and Health Informatics: Second Revision.

BACKGROUND: The purpose of educational recommendations is to assist in establishing courses and programs in a discipline, to further develop existing educational activities in the various nations, and to support international initiatives for collaboration and sharing of courseware. The International Medical Informatics Association (IMIA) has published two versions of its international recommendations in biomedical and health informatics (BMHI) education, initially in 2000 and revised in 2010. Given the recent changes to the science, technology, the needs of the healthcare systems, and the workforce of BMHI, a revision of the recommendations is necessary. OBJECTIVE: The aim of these updated recommendations is to support educators in developing BMHI curricula at different education levels, to identify essential skills and competencies for certification of healthcare professionals and those working in the field of BMHI, to provide a tool for evaluators of academic BMHI programs to compare and accredit the quality of delivered programs, and to motivate universities, organizations, and health authorities to recognize the need for establishing and further developing BMHI educational programs. METHOD: An IMIA taskforce, established in 2017, updated the recommendations. The taskforce included representatives from all IMIA regions, with several having been involved in the development of the previous version. Workshops were held at different IMIA conferences, and an international Delphi study was performed to collect expert input on new and revised competencies. RESULTS: Recommendations are provided for courses/course tracks in BMHI as part of educational programs in biomedical and health sciences, health information management, and informatics/computer science, as well as for dedicated programs in BMHI (leading to bachelor's, master's, or doctoral degree). The educational needs are described for the roles of BMHI user, BMHI generalist, and BMHI specialist across six domain areas - BMHI core principles; health sciences and services; computer, data and information sciences; social and behavioral sciences; management science; and BMHI specialization. Furthermore, recommendations are provided for dedicated educational programs in BMHI at the level of bachelor's, master's, and doctoral degrees. These are the mainstream academic programs in BMHI. In addition, recommendations for continuing education, certification, and accreditation procedures are provided. CONCLUSION: The IMIA recommendations reflect societal changes related to globalization, digitalization, and digital transformation in general and in healthcare specifically, and center on educational needs for the healthcare workforce, computer scientists, and decision makers to acquire BMHI knowledge and skills at various levels. To support education in BMHI, IMIA offers accreditation of quality BMHI education programs. It supports information exchange on programs and courses in BMHI through its Working Group on Health and Medical Informatics Education.

What Can We Learn from Quality Requirements in ISO/TS 82304-2 for Evaluating Conversational Agents in Healthcare?

Evaluating conversational agents (CA) that are supposed to be applied in healthcare and ensuring their quality is essential to avoid patient harm. However, most researchers only study usability and use the CA in clinical trials before conducting such careful evaluation. In previous work, consensus on metrics for evaluating healthcare CA have been found. However, the metrics are still too generic to form an evaluation framework. In this work, we try to link the ISO technical specification ISO/TS 82304-2 Quality Requirements for Health and Wellness Apps to the set of metrics to come a step closer towards an evaluation framework. We identify three links between ISO requirements and the set of metrics, namely accessibility, usability, and security. Although the technical specification rather lists aspects to be considered during development instead of concrete metrics for studying the quality, we can link to some aspects that are also of interest for health CA evaluation. For example, measuring the readability for ensuring accessibility or implementing the Web Content Accessibility Guidelines are two aspects of relevance for health CA.

The Utilization of Health Informatics Interventions in the COVID-19 Pandemic: A Scoping Review.

On March 11, 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the highly infectious virus that causes coronavirus disease (COVID-19), was characterized by the World Health Organization (WHO) as a global pandemic [1,2]. Due to its highly contagious nature, COVID-19 has catalyzed the introduction of non-pharmaceutical interventions such as social distancing and quarantine measures [6]. Thus, the pandemic has shifted society to become reliant on healthcare technologies. The objective of this scoping review is to establish what health informatics interventions have been applied, validated and tested globally during the COVID-19 pandemic. The findings demonstrated a range of 12 types of health informatics interventions with various global applications and use. As evidenced by the intervention heterogeneity, the necessity to adopt a global cohesive strategy to improve human safety through the utilization of smart, efficient, and communicable technologies is vital.

Integrating Human Patterns of Qualitative Coding with Machine Learning: A Pilot Study Involving Technology-Induced Error Incident Reports.

The objective of this research was to develop a reproducible method of integrating human patterns of qualitative coding with machine learning. The application of qualitative codes from the technology-induced error and safety literatures to the analysis of incident reports was done successfully, helping to identify the factors that lead to an error as well as the errors themselves. The method described in this paper may provide additional insights into understanding technology-induced errors.

Do Health Technology Safety Issues Vary by Vendor?

There is a need to determine the relative similarity and differences in safety issues across specific types of software and medical devices in order to develop standardized solutions that can be used across these technologies. Over the past several years, health informatics researchers have identified differing types of technology-induced errors or safety issues. This work has led to a literature that has been effective in identifying varying technology-induced errors. Less effort has been made in attempting to understand if there are common types of safety issues and outcomes across vendors for specific types of technology such as electronic health records (EHRs). Our findings demonstrate that some safety issues are common across the same type of software. The findings suggest there is a need to develop standardized approaches to managing technology-induced errors.

Complexity and Health Technology Safety.

In many ways health technology safety has improved significantly over the past few decades. Yet, we still have examples of incidents where safety of health technology systems of care have led to possible and actual safety incidents. In this paper we examine the complexity of errors in an increasingly complex and digitized system of care. Although safety incidents are decreasing over time due to improvements in the tools used to support care, they still occur. Simple safety incidents prevailed in the 2005. Today, incident reports suggest complexity has emerged as an important issue that needs to be addressed in order to make further healthcare industry safety gains.

Business Intelligence Dashboards for Patient Safety and Quality: A Narrative Literature Review.

Business Intelligence (BI) dashboards are interactive data visualization displays identifying key patient quality and safety trends and metrics. Yet, it remains unclear whether dashboards are impacting clinical care for desired organizational outcomes. In this paper we summarize the positive and negative impacts of dashboards on safety and quality from the literature and those insights are used to develop a dashboard checklist tool. The research involved 3 phases. In Phase 1 a narrative literature review used "Dashboards AND ("Patient Safety" OR "Quality")" as primary search terms. In Phase 2, A SWOT (strengths, weaknesses, opportunities, threats) analysis was conducted based on the findings from the previous phase. Strengths and opportunities included focusing on metrics, clear goals, routine data review processes, transparency, quality improvement interventions and centralized monitoring. Weaknesses and threats included usability issues, cultural barriers, wrong metrics, tunnel vision and siloed development. Phase 3 involves translating the SWOT analysis to a checklist for evidence informed dashboard development and deployment.