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.

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.

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.

Reinventing virtual care: Bridging the healthcare system and citizen silos to create an integrated future.

The pandemic has accelerated the move to virtual care. This has included remote monitoring and implementation of technologies that allow for patient care at home and assisted living for ageing in place. Technologies are available to help consumers to maintain their health and wellness. However, challenges associated with implementing virtual care remain. In this article, we describe some of these challenges, along with the need to develop new models for promoting effective and sustainable virtual care. This includes the need for integration of institutional efforts (eg, government and hospital) with emerging access to commercially available home technologies supplied to patients and citizens. The authors argue that consideration of a personal digital ecosystem and its relation to institutional digital health ecosystems is critical. The authors suggest virtual care be considered in the combined context of the person and healthcare system. Implications for future research directions for virtual care are discussed.

Facing disruption: Learning from the healthcare supply chain responses in British Columbia during the COVID-19 pandemic.

The healthcare supply chain crisis surrounding Personal Protective Equipment (PPE) during the onset of the COVID-19 pandemic presented unique and complex challenges in achieving the primary aim of supply chain management, that is, delivering the right amount of the right supplies to the right people at the right time. This article describes the key findings from a case study on PPE supply chain responses to the COVID-19 pandemic in British Columbia (BC). It highlights a set of constructive response mechanisms to potential crises along healthcare supply chain. Effective and trusted leadership, a unity of purpose, integrated and robust digital infrastructure and capabilities, consistent learning, resilience building, and environmental sensing for reliable intelligence were found to be essential for preparing, for containing, and mitigating the crisis as it evolved across various phases of crisis management.

Improving the Usability and Safety of Digital Health Systems: The Role of Predictive Human-Computer Interaction Modeling.

In this paper, we describe techniques for predictive modeling of human-computer interaction (HCI) and discuss how they could be used in the development and evaluation of user interfaces for digital health systems such as electronic health record systems. Predictive HCI modeling has the potential to improve the generalizability of usability evaluations of digital health interventions beyond specific contexts, especially when integrated with models of distributed cognition and higher-level sociotechnical frameworks. Evidence generated from building and testing HCI models of the user interface (UI) components for different types of digital health interventions could be valuable for informing evidence-based UI design guidelines to support the development of safer and more effective UIs for digital health interventions.

Best practices for EHR implementation: A BC First Nations community's experience.

First Nations and other health leaders are looking to Electronic Health Records (EHRs) to improve the quality of health information, efficiency of health services, and health outcomes for Indigenous people in Canada. This study used qualitative and quantitative methods to identify the success factors in an EHR implementation at a First Nations health centre in British Columbia, Canada. The Best Practices EHR Implementation Framework (EHRIF) was used to analyze the success factor data and found that all of the success factors from the planning and implementation phases in the framework were important. Provincial and federal government commitment and collaboration with key stakeholders including a local physician champion were also critically important for the electronic medical record implementation to proceed. This study suggests the EHRIF can be used to promote successful EHR implementations in Aboriginal communities and can contribute to building health informatics expertise and capacity in First Nations communities.

Employing a user-centered cognitive walkthrough to evaluate a mHealth diabetes self-management application: A case study and beginning method validation.

INTRODUCTION: Self-management of chronic diseases using mobile health (mHealth) systems and applications is becoming common. Current evaluation methods such as formal usability testing can be very costly and time-consuming; others may be more efficient but lack a user focus. We propose an enhanced cognitive walkthrough (CW) method, the user-centered CW (UC-CW), to address identified deficiencies in the original technique and perform a beginning validation with think aloud protocol (TA) to assess its effectiveness, efficiency and user acceptance in a case study with diabetes patient users on a mHealth self-management application. MATERIALS AND METHODS: A total of 12 diabetes patients at University of Utah Health, USA, were divided into UC-CW and think aloud (TA) groups. The UC-CW method included: making the user the main evaluator for detecting usability problems, having a dual domain facilitator, and using three other improved processes: validated task development, higher level tasks and a streamlined evaluation process. Users interacted with the same mHealth application for both methods. Post-evaluation assessments included the NASA RTLX instrument and a set of brief interview questions. RESULTS: Participants had similar demographic characteristics. A total of 26 usability problems were identified with the UC-CW and 20 with TA. Both methods produced similar ratings: severity across all views (UC-CW = 2.7 and TA = 2.6), numbers of problems in the same views (Main View [UC-CW = 11, TA = 10], Carbohydrate Entry View [UC-CW = 4, TA = 3] and List View [UC-CW = 3, TA = 3]) with similar heuristic violations (Match Between the System and Real World [UC-CW = 19, TA = 16], Consistency and Standards [UC-CW = 17, TA = 15], and Recognition Rather than Recall [UC-CW = 13, TA = 10]). Both methods converged on eight usability problems, but the UC-CW group detected five critical issues while the TA group identified two. The UC-CW group identified needed personalized features for patients' disease needs not identified with TA. UC-CW was more efficient on average time per identified usability problem and on the total evaluation process with patients. NASA RTLX scores indicated that participants experienced the UC-CW half as cognitively demanding. Common themes from interviews indicated the UC-CW as enjoyable and easy to perform while TA was considered somewhat awkward and more cognitively challenging. CONCLUSIONS: UC-CW was effective for finding severe, recurring usability problems and it highlighted the need for personalized user features. The method was also efficient and had high user acceptance. These results indicate UC-CW's utility and user acceptance in evaluating a mHealth self-management application. It provides an additional usability evaluation technique for researchers.

The Importance of Health Information on the Internet: How It Saved My Life and How it Can Save Yours.

The internet holds the potential promise of improved patient outcomes, especially when one is faced with a critical or life-threatening disease or condition. Appropriate and timely access to health information can support informed negotiation of optimal treatments, optimal management, and expedited recovery, and to an improved outcome for a patient. However, there are many human and technical barriers that may prevent the application of the best possible information for both patient and provider alike, making the patient journey complex and potentially dangerous. In this viewpoint paper, the author (who is also a JMIR editor) reflects on a personal patient journey, where use of the internet facilitated a means of reaching a good patient outcome in the face of a variety of informational and organizational limitations and gaps. This journey illustrates the importance of human-related factors affecting access to health information. The application of a range of internet information resources at critical points can result in a positive patient outcome, as this case illustrates. This paper reflects on how the experience highlights several information needs and concerns. It also highlights the need for improved access to appropriate health information along the patient journey that can support patient and provider joint decision-making. This access to information can make the difference between positive clinical outcomes and death, illustrating how health information on the internet can be both critical and life saving.

Clinical simulation: A method for development and evaluation of clinical information systems.

Use of clinical simulation in the design and evaluation of eHealth systems and applications has increased during the last decade. This paper describes a methodological approach for using clinical simulations in the design and evaluation of clinical information systems. The method is based on experiences from more than 20 clinical simulation studies conducted at the ITX-lab in the Capital Region of Denmark during the last 5 years. A ten-step approach to conducting simulations is presented in this paper. To illustrate the approach, a clinical simulation study concerning implementation of Digital Clinical Practice Guidelines in a prototype planning and coordination module is presented. In the case study potential benefits were assessed in a full-scale simulation test including 18 health care professionals. The results showed that health care professionals can benefit from such a module. Unintended consequences concerning terminology and changes in the division of responsibility amongst healthcare professionals were also identified, and questions were raised concerning future workflow across sector borders. Furthermore unexpected new possible benefits concerning improved communication, content of information in discharge letters and quality management emerged during the testing. In addition new potential groups of users were identified. The case study is used to demonstrate the potential of using the clinical simulation approach described in the paper.

Usability study of clinical exome analysis software: top lessons learned and recommendations.

OBJECTIVES: New DNA sequencing technologies have revolutionized the search for genetic disruptions. Targeted sequencing of all protein coding regions of the genome, called exome analysis, is actively used in research-oriented genetics clinics, with the transition to exomes as a standard procedure underway. This transition is challenging; identification of potentially causal mutation(s) amongst ∼10(6) variants requires specialized computation in combination with expert assessment. This study analyzes the usability of user interfaces for clinical exome analysis software. There are two study objectives: (1) To ascertain the key features of successful user interfaces for clinical exome analysis software based on the perspective of expert clinical geneticists, (2) To assess user-system interactions in order to reveal strengths and weaknesses of existing software, inform future design, and accelerate the clinical uptake of exome analysis. METHODS: Surveys, interviews, and cognitive task analysis were performed for the assessment of two next-generation exome sequence analysis software packages. The subjects included ten clinical geneticists who interacted with the software packages using the "think aloud" method. Subjects' interactions with the software were recorded in their clinical office within an urban research and teaching hospital. All major user interface events (from the user interactions with the packages) were time-stamped and annotated with coding categories to identify usability issues in order to characterize desired features and deficiencies in the user experience. RESULTS: We detected 193 usability issues, the majority of which concern interface layout and navigation, and the resolution of reports. Our study highlights gaps in specific software features typical within exome analysis. The clinicians perform best when the flow of the system is structured into well-defined yet customizable layers for incorporation within the clinical workflow. The results highlight opportunities to dramatically accelerate clinician analysis and interpretation of patient genomic data. CONCLUSION: We present the first application of usability methods to evaluate software interfaces in the context of exome analysis. Our results highlight how the study of user responses can lead to identification of usability issues and challenges and reveal software reengineering opportunities for improving clinical next-generation sequencing analysis. While the evaluation focused on two distinctive software tools, the results are general and should inform active and future software development for genome analysis software. As large-scale genome analysis becomes increasingly common in healthcare, it is critical that efficient and effective software interfaces are provided to accelerate clinical adoption of the technology. Implications for improved design of such applications are discussed.

Diagnostic imaging ordering practices: physician perspectives and implications for decision support.

This study explored how referring physicians order diagnostic imaging (DI) services, and possible methods to reduce inappropriate ordering. Telephone interviews were conducted with non-radiologist physicians (general practitioners and specialists). Interview data were analyzed using grounded theory. Both appropriate and inappropriate DI ordering practices emerged as the overarching themes. Specifically, the majority of participants described their top methods of obtaining information support as (1) contacting another physician or (2) consulting the literature. Additionally, participants discussed contributing factors and solutions to inappropriate DI ordering, including clinical decision support systems. These results were used to inform the design of a DI decision support system prototype. This study explored ways to reduce inappropriate DI ordering and identified socio-technical factors that need to be considered when developing ways to mitigate this phenomenon. Promoting more appropriate ordering can improve patient safety and the responsible use of limited diagnostic imaging resources.

Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review.

BACKGROUND: Artificial intelligence (AI) use cases in health care are on the rise, with the potential to improve operational efficiency and care outcomes. However, the translation of AI into practical, everyday use has been limited, as its effectiveness relies on successful implementation and adoption by clinicians, patients, and other health care stakeholders. OBJECTIVE: As adoption is a key factor in the successful proliferation of an innovation, this scoping review aimed at presenting an overview of the barriers to and facilitators of AI adoption in health care. METHODS: A scoping review was conducted using the guidance provided by the Joanna Briggs Institute and the framework proposed by Arksey and O'Malley. MEDLINE, IEEE Xplore, and ScienceDirect databases were searched to identify publications in English that reported on the barriers to or facilitators of AI adoption in health care. This review focused on articles published between January 2011 and December 2023. The review did not have any limitations regarding the health care setting (hospital or community) or the population (patients, clinicians, physicians, or health care administrators). A thematic analysis was conducted on the selected articles to map factors associated with the barriers to and facilitators of AI adoption in health care. RESULTS: A total of 2514 articles were identified in the initial search. After title and abstract reviews, 50 (1.99%) articles were included in the final analysis. These articles were reviewed for the barriers to and facilitators of AI adoption in health care. Most articles were empirical studies, literature reviews, reports, and thought articles. Approximately 18 categories of barriers and facilitators were identified. These were organized sequentially to provide considerations for AI development, implementation, and the overall structure needed to facilitate adoption. CONCLUSIONS: The literature review revealed that trust is a significant catalyst of adoption, and it was found to be impacted by several barriers identified in this review. A governance structure can be a key facilitator, among others, in ensuring all the elements identified as barriers are addressed appropriately. The findings demonstrate that the implementation of AI in health care is still, in many ways, dependent on the establishment of regulatory and legal frameworks. Further research into a combination of governance and implementation frameworks, models, or theories to enhance trust that would specifically enable adoption is needed to provide the necessary guidance to those translating AI research into practice. Future research could also be expanded to include attempts at understanding patients' perspectives on complex, high-risk AI use cases and how the use of AI applications affects clinical practice and patient care, including sociotechnical considerations, as more algorithms are implemented in actual clinical environments.

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.

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.

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.

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.