Medical device design in context: a model of user–device interaction and consequences

The practice of evaluating interaction with devices is embedded in disciplines such as human-computer interaction and cognitive ergonomics, including concepts such as affordances, error analysis, skill, rule and knowledge based behaviour and decision making biases. This paper considers the way in which the approach that has been routinely applied to displays and control design within the control and transport domains can be transferred to the context of medical devices. The importance of considering the context in which medical devices are used and implemented is presented, and the need for a systems approach to medical device design is emphasised. Five case studies from medical device control and display design are presented as an aide to developing an understanding of the relationship between device design and resultant behaviours. On the basis of these case studies, four types of mediating factors (catalysts, enablers, facilitators and enhancers) are proposed and a model to describe the link between device design, user, context and consequences is presented

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use