Presentation
HE5 - Characterizing Information Needs for Point-of-Care Ultrasound in Hospital vs. Austere Environment Medicine Through Practitioner Interviews: Implications for Automation Support Integration and Spaceflight Medical Utilization
DescriptionHumans have sustained a continuous presence in low-Earth orbit for over 20 years on the International Space Station (ISS). Throughout this time, the inhospitable, extreme environment of outer space has included a myriad of health challenges for its human explorers. Medical event management on the ISS is currently supported by ground Mission Control Center and flight surgeons, who provide detailed feedback and guidance in real time as crewmembers perform complicated procedures. In the event of a critical medical event that exceeds the crew’s abilities or resources, an emergency evacuation can transport the injured crewmember back to Earth in a matter of hours. As missions extend human presence to the Moon then Mars, unanticipated medical events will endanger crew health when one single loop of communication could take 40 minutes while the crew is months away from Earth with no possibility of emergency evacuation back to ground. Therefore, the current ISS paradigm that relies on ground control guidance for medical monitoring and procedures will not be sufficient. Further, as mission duration increases for exploration, so too does the probability that adverse low- and high-criticality medical events will occur. Longer and more complex surface extra vehicular activities (EVAs) (e.g., exploration and habitat construction/maintenance) create a significant risk of traumatic injury (Robertson et al., 2020). Potential medical events include abdominal injury and chest injury/pneumothorax (collapsed lung) (Robertson et al., 2020). While extended communication delays are manageable for standard preventative care, input from the ground will be infeasible during these types of urgent medical situations. This paradigm will require crewmembers to perform rapid and precise decision-making to both diagnose issues and formulate treatment plans.
On Earth, there are care environments that share some characteristics with the spaceflight setting; the Emergency Department in a hospital must treat critical care trauma patients with rapid response times. However, the well-equipped infrastructure of resources that hospitals typically have at their disposal (e.g., diverse teams of specialized experts and high mass/volume resources allocated to diagnostic equipment and treatment tools) is not feasible with exploration medical care where personnel, mass, and volume are incredibly limited. Conversely, wilderness medicine (the practice of resource-limited medicine under austere conditions) on Earth faces many similar challenges, but care is administered by experts with decades of training for this environment. We do not expect the same level of expertise in every crewmember on future missions. We posit that the challenges of having non-experts performing expert-level medical tasks in a wilderness/spaceflight environment can be addressed by automating parts of the decision-making process; however, to do so, we must characterize the differences between the wilderness medicine and hospital settings to begin bridging this work to the surface exploration paradigm.
The work outlined in this paper discusses the results of identifying the information streams that are most pertinent to medical decision-making via interviews with specialists from both the hospital and in wilderness medicine regarding a procedure relevant to both care settings and exploration spaceflight: point-of-care ultrasound (POCUS) for traumatic injury. Synthesizing information needs directly from users accustomed to the hospital setting and contrasting those needs with the information sources available in a wilderness setting is instrumental to characterize how we can augment decision-making via automation in trauma POCUS.
We engaged specialists with POCUS expertise in semi-structured interviews that were designed based upon human-machine teaming systems engineering and cognitive systems engineering methodologies (McDermott et al., 2018). Interviewees were recruited with varying levels of POCUS expertise, ranging from first-year residents whose US knowledge was still being developed, attending level physicians, physicians who were also ultrasound educators, and wilderness medicine/space medicine experts in order to identify where informational needs differ based on a user’s level of expertise. Interviews were structured to focus on extracting clinical perspectives on predictability, observability, anomaly detection, attention/information presentation, self-monitoring, improvisation, and job smarts during the POCUS task to better understand the potential role of automation. Qualitative thematic analysis consisted of coding (descriptive labels attached to data) using a software tool (ATLAS.ti, 2023) to find, categorize, and extract these human-automation teaming elements.
The resulting data from these interviews will be incorporated into a greater body of naturalistic approaches—the direct study of decision-making in complex and natural environments—as a tool to capture operational norms and contextual needs to characterize the role of automation in emergency care. The direct application of this characterization is to enable the adoption of automation as a tool in simulating the well-equipped infrastructure available in a hospital setting to supplement decision-making in an exploration environment that has severe limitations in terms of equipment and caregiver resources.
On Earth, there are care environments that share some characteristics with the spaceflight setting; the Emergency Department in a hospital must treat critical care trauma patients with rapid response times. However, the well-equipped infrastructure of resources that hospitals typically have at their disposal (e.g., diverse teams of specialized experts and high mass/volume resources allocated to diagnostic equipment and treatment tools) is not feasible with exploration medical care where personnel, mass, and volume are incredibly limited. Conversely, wilderness medicine (the practice of resource-limited medicine under austere conditions) on Earth faces many similar challenges, but care is administered by experts with decades of training for this environment. We do not expect the same level of expertise in every crewmember on future missions. We posit that the challenges of having non-experts performing expert-level medical tasks in a wilderness/spaceflight environment can be addressed by automating parts of the decision-making process; however, to do so, we must characterize the differences between the wilderness medicine and hospital settings to begin bridging this work to the surface exploration paradigm.
The work outlined in this paper discusses the results of identifying the information streams that are most pertinent to medical decision-making via interviews with specialists from both the hospital and in wilderness medicine regarding a procedure relevant to both care settings and exploration spaceflight: point-of-care ultrasound (POCUS) for traumatic injury. Synthesizing information needs directly from users accustomed to the hospital setting and contrasting those needs with the information sources available in a wilderness setting is instrumental to characterize how we can augment decision-making via automation in trauma POCUS.
We engaged specialists with POCUS expertise in semi-structured interviews that were designed based upon human-machine teaming systems engineering and cognitive systems engineering methodologies (McDermott et al., 2018). Interviewees were recruited with varying levels of POCUS expertise, ranging from first-year residents whose US knowledge was still being developed, attending level physicians, physicians who were also ultrasound educators, and wilderness medicine/space medicine experts in order to identify where informational needs differ based on a user’s level of expertise. Interviews were structured to focus on extracting clinical perspectives on predictability, observability, anomaly detection, attention/information presentation, self-monitoring, improvisation, and job smarts during the POCUS task to better understand the potential role of automation. Qualitative thematic analysis consisted of coding (descriptive labels attached to data) using a software tool (ATLAS.ti, 2023) to find, categorize, and extract these human-automation teaming elements.
The resulting data from these interviews will be incorporated into a greater body of naturalistic approaches—the direct study of decision-making in complex and natural environments—as a tool to capture operational norms and contextual needs to characterize the role of automation in emergency care. The direct application of this characterization is to enable the adoption of automation as a tool in simulating the well-equipped infrastructure available in a hospital setting to supplement decision-making in an exploration environment that has severe limitations in terms of equipment and caregiver resources.
Event Type
Poster Presentation
TimeTuesday, March 264:45pm - 6:15pm CDT
LocationSalon C
Digital Health
Simulation and Education
Hospital Environments
Medical and Drug Delivery Devices
Patient Safety Research and Initiatives