The Medium Is the Message: How Do Canadian University Students Want Digital Medication Information?

(1) Background: To facilitate optimal prescription medication benefits and safety, it is important that people are informed about their prescription medications. As we shift towards using the digital medium to communicate medication information, it is important to address the needs and preferences of different user groups so that they are more likely to read and use this information. In this study, we examined what digital medication information (DMI) format Canadian University students want and why. (2) Methods: This study was a qualitative investigation of young (aged 18–35) Canadian University students’ (N = 36) preferences and rationale supporting these preferences with respect to three potential formats for providing DMI: email, a mobile application (app), and online. Reported advantages and disadvantages of each of the three DMI formats were identified and categorized into unique themes. (3) Results: Findings from this study suggest that Canadian University Students most want to receive DMI by email, followed by a mobile app, and finally they were least receptive to online DMI. Participants provided diverse themes of reasons supporting their preferences. (4) Conclusions: Different user groups may have different needs with respect to receiving DMI. The themes from this study suggest that using a formative evaluation framework for assessing different DMI formats may be useful in future research. Email may be the best way to share DMI with younger, generally healthy, Canadian University students who are on few medications. Further research is required to explore whether other mediums for DMI are more appropriate for users with other characteristics (e.g., older and less educated) and contexts (e.g., polypharmacy and complex conditions). Given the flexibility of digital information, DMI could plausibly be provided in multiple formats and could allow users to choose the option they like best and would be most likely to use

eHealth literacy issues, constructs, models, and methods for health information technology design and evaluation

The concept of eHealth literacy is beginning to be recognized as a being of key importance in the design and adoption of effective and efficient health information systems and applications targeted to lay people and patients. Indeed, many systems such as patient portals and personal health records have not been adopted due to a mismatch between the level of eHealth literacy demanded by a system and the level of eHealth literacy possessed by end users. The purpose of this paper is to present an overview of important concepts related to eHealth literacy, as well as how the notion of eHealth literacy can be applied to improve the design and adoption of consumer health information systems. This paper begins with describing the importance of eHealth literacy with respect to design of health applications for the general public paired with examples of consumer health information systems whose limited success and adoption has been attributed to the lack of consideration for eHealth literacy. This is followed by definitions of what eHealth literacy is and how it emerged from the related concept of health literacy. A model for conceptualizing the importance of aligning consumers’ eHealth literacy skills and the demands systems place on their skills is then described. Next, current tools for assessing consumers’ eHealth literacy levels are outlined, followed by an approach to systematically incorporating eHealth literacy in the deriving requirements for new systems is presented. Finally, a discussion of evolving approaches for incorporating eHealth literacy into usability engineering methods is presented

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.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.</p

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

Usability Evaluation Ecological Validity: Is More Always Better?

International audienceBackground: The ecological validity associated with usability testing of health information technologies (HITs) can affect test results and the predictability of real-world performance. It is, therefore, necessary to identify conditions with the greatest effect on validity.Method: We conducted a comparative analysis of two usability testing conditions. We tested a HIT designed for anesthesiologists to detect pain signals and compared two fidelity levels of ecological validity. We measured the difference in the number and type of use errors identified between high and low-fidelity experimental conditions.Results: We identified the same error types in both test conditions, although the number of errors varied as a function of the condition. The difference in total error counts was relatively modest and not consistent across levels of severity.Conclusions: Increasing ecological validity does not invariably increase the ability to detect use errors. Our findings suggest that low-fidelity tests are an efficient way to identify and mitigate usability issues affecting ease of use, effectiveness, and safety. We believe early low-fidelity testing is an efficient but underused way to maximize the value of usability testing

Usability Evaluation Ecological Validity: Is More Always Better?

Background: The ecological validity associated with usability testing of health information technologies (HITs) can affect test results and the predictability of real-world performance. It is, therefore, necessary to identify conditions with the greatest effect on validity. Method: We conducted a comparative analysis of two usability testing conditions. We tested a HIT designed for anesthesiologists to detect pain signals and compared two fidelity levels of ecological validity. We measured the difference in the number and type of use errors identified between high and low-fidelity experimental conditions. Results: We identified the same error types in both test conditions, although the number of errors varied as a function of the condition. The difference in total error counts was relatively modest and not consistent across levels of severity. Conclusions: Increasing ecological validity does not invariably increase the ability to detect use errors. Our findings suggest that low-fidelity tests are an efficient way to identify and mitigate usability issues affecting ease of use, effectiveness, and safety. We believe early low-fidelity testing is an efficient but underused way to maximize the value of usability testing

How to Present Evidence-Based Usability from a Workshop

International audienceMedication alerting system use errors and lack of adoption are often attributed to usability issues. Previous work has used evidence from the literature to reveal usability principles specific to medication alerting systems and identify potential consequences of violating these principles. The current study sought to explore how best to convey these principles to designers and evaluators of these systems to facilitate their work. To this aim, a workshop with 19 participants was used to generate ideas and opinions on how to deliver these topic-specific design principles in a way that would be most helpful for them. Participants generated ideas for how (e.g., a collaborative, continuously updated forum) and what (e.g., illustrations, checklists, evidence sources and strength, consequences of violations) information is most useful to disseminate usability principles for medication alerting systems. Participants, especially designers, expressed desire to use these principles in practice and avoid previously documented mistakes and therefore make design and evaluation of these systems more effective and efficient. Those insights are discussed in terms of feasibility and logistical challenges to developing the proposed documentation). To move this work forward, a more collaborative approach of Human Factors specialists in medical informatics is necessary

Big Data in Healthcare:Defining the Digital Persona through User Contexts from the Micro to the Macro

Summary Objectives: While big data offers enormous potential for improving healthcare delivery, many of the existing claims concerning big data in healthcare are based on anecdotal reports and theoretical vision papers, rather than scientific evidence based on empirical research. Historically, the implementation of health information technology has resulted in unintended consequences at the individual, organizational and social levels, but these unintended consequences of collecting data have remained unaddressed in the literature on big data. The objective of this paper is to provide insights into big data from the perspective of people, social and organizational considerations. Method: We draw upon the concept of persona to define the digital persona as the intersection of data, tasks and context for different user groups. We then describe how the digital persona can serve as a framework to understanding sociotechnical considerations of big data implementation. We then discuss the digital persona in the context of micro, meso and macro user groups across the 3 Vs of big data. Results: We provide insights into the potential benefits and challenges of applying big data approaches to healthcare as well as how to position these approaches to achieve health system objectives such as patient safety or patient-engaged care delivery. We also provide a framework for defining the digital persona at a micro, meso and macro level to help understand the user contexts of big data solutions. Conclusion: While big data provides great potential for improving healthcare delivery, it is essential that we consider the individual, social and organizational contexts of data use when implementing big data solutions.</jats:p