| dc.description.abstract | Long communication latencies in exploration spaceflight will make current real-time support paradigms for urgent medical events infeasible. Further, as mission duration increases for exploration, so too will the probability of adverse low- and high-criticality medical events. The need for in-situ resolution to medical problems will require crewmembers to perform rapid and precise decision-making to both diagnose issues and formulate treatment plans. We posit that integrating automation into the care paradigm can address the challenges to medical care in long-duration spaceflight posed by resource gaps (e.g., training, access to expertise, and tools). However, it is not clear what aspects of the exploration care paradigm are most well-suited for the integration of automation. Using the lens of Point-of-Care Ultrasound (POCUS) (a viable diagnostic tool for exploration medicine due to its portable, low mass/volume, speedy, versatile nature), this work proposes a new framework, the automation to translate patient care from the hospital to the austere and spaceflight environments and explores how automation may enable that transition. We investigated the role of human-automation teams for emergency care in spaceflight through the Automation Framework for Exploration Medicine (AFEM), a process using naturalistic methods with a two-pronged approach: 1) characterizing a candidate task for automation and 2) characterizing the work domain(s) encompassing that task within the human-automation system. To overcome the challenge of characterizing a dynamic system surrounding a task that does not exist in its intended—inaccessible—usecase (i.e., POCUS on Mars), we leveraged existing analogous domains to guide the development of human-automation systems. We conducted in-situ observations in a hospital Emergency Department to understand how clinicians process contextual information in an urgent medical setting to provide care using ultrasound technology. We also engaged specialists in semi-structured interviews (based upon human-machine teaming systems engineering methodologies) to identify key procedural information components for automation. Lastly, we developed a Toolkit–grounded in cognitive systems engineering methodologies–that provides a novel framework for identifying domain-and task-specific constraints from analogous environments. A supporting Roadmap provides guidance for experimenters interested in further development of automated and autonomous systems. From this work, we conclude that specific aspects of the care environment which influence the result of a task or process (“Mediating Factors”) from candidate work domains call 3for distinct, targeted guidance for automation support and are valuable in providing system developers with tunable automation level and implementation guidelines within and/or between those work domains. Further, our findings elucidated highest-priority system design requirements for non-expert POCUS end-users regarding transparency, augmenting cognition, and coordination to support generating a common mental model. Finally, the Toolkit and Roadmap scaffold guide system development in integrating automation into this novel ecosystem. This scaffold is well-positioned to be leveraged by other system designers who do not have easy, reasonable, or sufficient access to a unique domain for which they are developing systems. AFEMsupports large-scale efforts in preparing for future human exploration missions not only on the level of augmenting exploration medical capabilities, but also on the higher level of developing the structure by which automation and autonomy is integrated into human exploration missions in non-medical domains. Evidence-based design practice is directly translatable to automation assistance for medical providers in resource-limited environments, as well as to any situation where a person’s sensory processing, perception, decision-making, or response selection could be aided with automation to accomplish a task. | |
