Visioning future emergency healthcare collaboration: Perspectives from large and small medical centers

Abstract

New video technologies are emerging to facilitate collaboration in emergency healthcare. One such technology is 3D telepresence technology for medical consultation (3DMC) that may provide richer visual information to support collaboration between medical professionals to, ideally, enhance patient care in real time. Today only an early prototype of 3DMC exists. To better understand 3DMC's potential for adoption and use in emergency healthcare before large amounts of development resources are invested we conducted a visioning study. That is, we shared our vision of 3DMC with emergency room physicians, nurses, administrators, and information technology (IT) professionals working at large and small medical centers, and asked them to share their perspectives regarding 3DMC's potential benefits and disadvantages in emergency healthcare and its compatibility and/or lack thereof with their and their organization's current ways of working. We found that social and technical challenges can be identified regarding new innovations even before working prototypes are available. The compatibility of 3DMC with current ways of working was conceptualized by participants in terms of processes, relationships, and resources. Both common and unique perceptions regarding 3DMC emerged, illustrating the need for 3DMC, and other collaboration technologies, to support interwoven situational awareness across different technological frames.

Grappling with the future: The messiness of pilot implementation in information systems design

“…Visioning study A method for better understanding the potential of new technologies through discussions stimulated by, for example, concept-level videos and for identifying social and technical challenges even before prototypes are available 6 Scenarios A method for creating technologies by first making descriptions of people using the technology, thereby emphasizing use and inquiries into the use context and postponing commitment to specific technological designs 7…”

Turnaround Time Prediction for a Medical Laboratory Using Artificial Neural Networks

“…The iteration is also named as "epoch" in ANN terminology, an epoch can be defined as a single pass through the entire training set within ANN model where backpropagation errors are calculated, and nodes' weights are updated [17]. The weight update calculation within each connection is given in the equations (6) and 7where Wij(k-1) is the change in Wij in the previous (k-1) th iteration, W'ij is the new value for the k th iteration, Errj denotes the error in node j, Oi is output from node i and λ denotes the learning rate of the ANN where (0 < λ < 1).…”

Designing Simulation-Based Training for Prehospital Emergency Care: Participation from a Participant Perspective

“…In prehospital work settings, a number of challenges are added, e.g., concrete factors such as time constraints, weather, portability requirements and communication infrastructure, but also to formal guidelines such as work protocols; security and safety aspects; different organizational and thus funding structures; and, the need for "hard evidence" in terms of improved patient outcomes [e.g. 4,5]. This calls for multidisciplinary, holistic design and development approaches that take domain knowledge from multiple perspectives into account.…”