Developing a Tailored Website for Promoting Awareness about Obstructive Sleep Apnea (OSA) Among Blacks in Community-Based Settings

Blacks are at greater risk for lower sleep quality and higher risk for obstructive sleep apnea (OSA) than other racial groups. In this study, we summarize the development of a tailored website including visuals, key messages, and video narratives, to promote awareness about sleep apnea among community-dwelling blacks. We utilized mixed methods, including in-depth interviews, usability-testing procedures, and brief surveys (n = 9, 55% female, 100% black, average age 38.5 years). Themes from the qualitative analysis illuminated varied knowledge regarding OSA symptoms and prevalent self-reported experience with sleep disturbance and OSA symptoms (e.g., snoring). On a scale from 1 (not at all) to 5 (very high), participants provided favorable ratings of website usefulness (mean = 4.9), user friendliness (mean = 4.9) and attractiveness (mean = 4.3). Our findings suggest although tailored health communication has potential for serving as a tool for advancing health equity, usability-testing of health materials is critical to ensure that culturally and linguistically tailored messages are acceptable and actionable in the intended population

Using Clinical Data Visualizations in Electronic Health Record User Interfaces to Enhance Medical Student Diagnostic Reasoning: Randomized Experiment

BackgroundIn medicine, the clinical decision-making process can be described using the dual-process theory consisting of the fast, intuitive “System 1,” commonly seen in seasoned physicians, and the slow, deliberative “System 2,” associated with medical students. System-1—type diagnostic reasoning is thought to be less cognitively burdensome, thereby reducing physician error. To date, limited literature exists on inducing System-1–type diagnosis in medical students through cognitive heuristics, particularly while using modern electronic health record (EHR) interfaces. ObjectiveIn this experimental pilot study, we aimed to (1) attempt to induce System-1—type diagnostic reasoning in inexperienced medical students through the acquisition of cognitive user interface heuristics and (2) understand the impact of clinical patient data visualizations on students' cognitive load and medical education. MethodsThe participants were third- and fourth-year medical students recruited from the University of Pittsburgh School of Medicine who had completed 1+ clinical rotations. The students were presented 8 patient cases on a novel EHR, featuring a prominent data visualization designed to foster at-a-glance rapid case assessment, and asked to diagnose the patient. Half of the participants were shown 4 of the 8 cases repeatedly, up to 4 times with 30 seconds per case (Group A), and the other half of the participants were shown cases twice with 2 minutes per case (Group B). All participants were then asked to provide full diagnoses of all 8 cases. Finally, the participants were asked to evaluate and elaborate on their experience with the system; content analysis was subsequently performed on these user experience interviews. ResultsA total of 15 students participated. The participants in Group A scored slightly higher on average than those in Group B, with a mean percentage correct of 76% (95% CI 0.68-0.84) versus 69% (95% CI 0.58-0.80), and spent on average 50% less time per question than Group B diagnosing patients (13.98 seconds vs 19.13 seconds, P=.03, respectively). When comparing the novel EHR design to previously used EHRs, 73% (n=11) of participants rated the new version on par or higher (3+/5). Ease of use and intuitiveness of this new system rated similarly high (mean score 3.73/5 and 4.2/5, respectively). In qualitative thematic analysis of poststudy interviews, most participants (n=11, 73%) spoke to “pattern-recognition” cognitive heuristic strategies consistent with System 1 decision-making. ConclusionsThese results support the possibility of inducing type-1 diagnostics in learners and the potential for data visualization and user design heuristics to reduce cognitive burden in clinical settings. Clinical data presentation in the diagnostic reasoning process is ripe for innovation, and further research is needed to explore the benefit of using such visualizations in medical education

Defining Telehealth for Research, Implementation, and Equity

When the COVID-19 pandemic spurred a disruption in health care delivery, the role of telehealth shifted from an option to a near necessity to maintain access when in-person care was deemed too risky. Each state and many organizations developed temporary telehealth policies for the COVID-19 emergency, each policy with its own definitions, coverage, government cases, and regulations. As pandemic-era policies are now being replaced with more permanent guidelines, we are presented with an opportunity to reevaluate how telehealth is integrated into routine health care delivery. We believe that the timing and nature of the sequential steps for redefining telehealth are critical and that it is important to develop a clear and agreed-on definition of telehealth and its components at this time. We further suggest a necessary preliminary step is to support clear communication and interoperability throughout the development of this definition. Precise and standardized definitions could create an unambiguous environment for clinical care for both patients and providers while enabling researchers to have more precise control over their investigations of telehealth. A consensus when defining telehealth and its derivatives at this critical stage could create a consistent expectation of care for all patients and those who set the standards of care, as it has for other clinical scenarios with clear guidelines

Enhancing Safety During a Pandemic Using Virtual Care Remote Monitoring Technologies and UML Modeling

OBJECTIVES: This paper describes a methodology for gathering requirements and early design of remote monitoring technology (RMT) for enhancing patient safety during pandemics using virtual care technologies. As pandemics such as COrona VIrus Disease (COVID-19) progress there is an increasing need for effective virtual care and RMT to support patient care while they are at home. METHODS: The authors describe their work in conducting literature reviews by searching PubMed.gov and the grey literature for articles, and government websites with guidelines describing the signs and symptoms of COVID-19, as well as the progression of the disease. The reviews focused on identifying gaps where RMT could be applied in novel ways and formed the basis for the subsequent modelling of use cases for applying RMT described in this paper. RESULTS: The work was conducted in the context of a new Home of the Future laboratory which has been set up at the University of Victoria. The literature review led to the development of a number of object-oriented models for deploying RMT. This modeling is being used for a number of purposes, including for education of students in health infomatics as well as testing of new use cases for RMT with industrial collaborators and projects within the smart home of the future laboratory. CONCLUSIONS: Object-oriented modeling, based on analysis of gaps in the literature, was found to be a useful approach for describing, communicating and teaching about potential new uses of RMT. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit.