Earth Independent Medical Operations
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Dana R Levin↗
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Root Cause Analysis of Data Refinement Process – Medical Conditions Capability Resource Tables
- Objective - Background - Capability Resource Tables (CRT) - Root Cause Analysis(RCA) - Error types - RCA - Fishbone; 5 whys - Lessons Learned
Arian Anderson↗
Space Exploration Medical Evacuation Risk Assessments: A Qualitative Investigation
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Austin Almand↗
Enabling Human Space Exploration Missions Through Progressively Earth Independent Medical Operations (EIMO)
Goal: Current Space Medicine operations depend on terrestrial support to manage medical events. As astronauts travel to destinations such as the Moon, Mars, and beyond, distance will substantially limit this support and require increasing medical autonomy from the crew. This paper defines Earth Independent Medical Operations (EIMO) and identifies key elements of a conceptual EIMO system. Methods: The NASA Human Research Program Exploration Medical Capability Element held a 2-day conference at Johnson Space Center in Houston, TX with NASA experts representing all aspects of Space Medicine. Results: EIMO will be a process enabling progressively resilient deep space exploration systems and crews to reduce risk and increase mission success. Terrestrial assets will continue to provide pre-mission screening, planning, health maintenance, and prevention, while onboard medical care will increasingly be the purview of the crew. Conclusions: This paper defines and describes the key components of EIMO.
ExMC↗
IMPACTing Exploration Spaceflight Risk Prediction and Medical System Design
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Benjamin Easter↗
An Evidence-Based, Systematic, and Repeatable Method to Determine Candidate Clinical Capabilities and Resources for Exploration Missions
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Crew Medical Officer (CMO)↗
A Pilot Project for Quantifying the Effect of Medical Provider Knowledge, Skills, and Abilities on Outcomes for Spaceflight Using a Probabilistic Risk Assessment Tool
In order to enable the future of long-duration deep space exploration we must confront the uncertainty in medical risk. Limitations of communication, resupply, and evacuation in deep space will require a high degree of crew autonomy and accurate risk assessment will be critical to ensure adequate crew training and medical system design. To address this, NASA’s Human Research Program Exploration Medical Capability Element has developed the Informing Mission Planning via Analysis of Complex Tradespaces Tool (IMPACT). IMPACT is a suite of tools that can provide evidence-based, data-driven trade space assessments between available medical resources in the mass- and volume-constrained environment of a deep space exploration vehicle. In the current model, medical conditions either can or cannot be treated based on the availability of medical system resources and equipment. However, medical outcomes often depend just as much on the knowledge, skills, and abilities (KSA) of the provider operating the system. This paper presents a method for modeling and quantifying the effect of medical officer KSA on medically relevant mission risk outcomes during spaceflight.
capabilities↗
A Qualitative Investigation of Space Exploration Medical Evacuation Risks
Exploration beyond low Earth orbit requires innovative solutions to support the crew medically, especially as the opportunity for timely evacuation to Earth diminishes. This includes assessing the risks and benefits that a complicated medical evacuation (MEDEVAC) poses to the injured crewmember and crew and to accomplishing the mission. This qualitative study identifies common MEDEVAC risk assessment principles used in spaceflight and other extreme environments to better inform future risk assessment tools and exploration mission concepts.
cislunar↗
Improving Quantification of Medical Evacuation Risk for Human Spaceflight in the IMPACT Model
Traditionally, mission planners have used a heuristic and qualitative approach to design medical systems based on prior experience however this approach may result in high variability and implicit bias to design and could put missions and crewmembers at risk. The Informing Mission Planning through Analysis of Complex Tradespaces (IMPACT) tool is a probabilistic risk assessment tool designed by NASA to model medical risk in long duration missions outside of low earth orbit (LEO). This tool can quantify risk metrics such as risk of crewmember death, loss of crew task time, and the need for medical evacuation to better inform and augment the more traditional approach to medical system design. The risk metric of Return to Definitive Care (RTDC) represents the likelihood of requiring medical evacuation and has been difficult to quantify in a reliable and standardized manner. Initial development of the RTDC metric was constrained due to the complexity of a medical evacuation decision and the lack of prior spaceflight data and this presentation will discuss the review and improvement process used to increase model accuracy and fidelity.
Prashant Parmar↗
Overlapping Conditions in IMPACT
Introduction The IMPACT 1.0 model assumes independence of 119 different medical conditions. That is, it is assumed that one medical event maps to a single medical condition. However, it is often the case that a single medical event may lead to several different concurrent conditions (e.g., a single accident resulting in multiple fractures, chest/abdominal trauma, and sepsis). There is a significant overlap between many of the conditions in ICL 1.0. For example, depression and anxiety are two separate conditions but often co-exist. This overlap may lead to an overestimation in the incidence calculation. In future iterations of the model, we plan to address progression of medical conditions. Methods There are two possible methods to approach progression of a medical condition. The first is to take any medical condition in ICL, calculate its incidence and determine its outcomes no matter what sequelae occur. For example, calculate the incidence of prostatitis and determine its metrics (e.g., loss of crew life, risk of medical evacuation or task time affected) no matter what the sequelae might be (sepsis, hydronephrosis, renal failure, etc.). The second approach is to take any medical condition in the ICL and calculate the outcomes based on transitions to any other condition. For example, calculate the incidence of nephrolithiasis and determine the incidence of each possible transition (e.g., hydronephrosis, renal failure, UTI, pyelonephritis, sepsis) and then determine its metrics. With perfectly informative evidence, the answers should be the same using either method. The question is which approach best reduces the opportunity for overlapping. Results The team identified 31 conditions that were the most likely to transition to a secondary condition such as sepsis and respiratory failure. It was felt that the first approach, as described above, would be the easiest to implement and would have the greatest reduction in overlapping conditions. The identified conditions were primarily infectious conditions, like UTI and pneumonia (which could lead to both respiratory failure and sepsis), toxic inhalations, cardiac arrest, seizures, and trauma. Once these conditions were identified, the conditions were divided between the four clinicians on the team to identify those that were not consistent with the others in way they were approached. There were 13 conditions that were found to be problematic. Some condition definitions needed to be changed to eliminate references to transitions or to update them in cases where the definitions were out of date. Some conditions required new evidence to correct the loss of crew life, and one condition was felt to have so much overlap that it was recommended for elimination. A second effort required modification of the sepsis incidence calculation to prevent double counting of the conditions, such as prostatitis, that could progress to sepsis. Conclusion The team made significant progress in clarifying the method for dealing with transitions from one medical condition to another. In addition, errors were found and corrected in definitions, incidence, and loss of crew life as well as a condition in which reference was made to a CLiFF that was no longer included. These modifications will provide greater fidelity in the IMPACT model and reduce overlap.
Arian Anderson↗
Eddy-Mediated Turbulent Mixing of Oxygen in the Equatorial Pacific
In the tropical Pacific, weak ventilation and intense microbial respiration at depth give rise to a low dissolved oxygen (O 2 ) environment that is thought to be ventilated primarily by the equatorial current system (ECS). The role of mesoscale eddies and vertical mixing as potential pathways of O 2 supply in this region, however, remains poorly known due to sparse observations and coarse model resolution. Using an eddy resolving simulation of ocean circulation and biogeochemistry, we assess the contribution of these processes to the O 2 budget balance and find that vertical mixing of O 2 , which is modulated by the surface wind speed and the vertical shear of the eddying currents, contributes substantially to the replenishment of O 2 in the upper equatorial Pacific thermocline, complementing the advective supply of O 2 by the ECS and meridional circulation at depth. These transport processes vary seasonally in conjunction with the wind: mixing of O 2 into the upper thermocline is strongest during boreal summer and fall when the vertical shear and eddy kinetic energy are intensified. The relationship between eddy activity and the downward mixing of O 2 arises from the modulation of equatorial turbulence by Tropical Instability Waves via their impacts on the vertical shear. This interaction of processes across scales sustains a local pathway of O 2 delivery into the equatorial Pacific interior and highlights the need for adequate observations and models of turbulent mixing and mesoscale processes for understanding and predicting the fate of the tropical Pacific O 2 content in a warmer and more stratified ocean.
Eddy-Mediated↗
Progressively Enabling Earth Independent Medical Operations (EIMO)
This panel presents the findings from a series of Technical Interchange Meetings (TIMs) hosted by the Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program. The topics for the TIMs were derived from a 2-day conference of senior leaders and subject matters experts that collectively outlined a multi-faceted strategy designed to optimize crew health and performance through an increasingly autonomous medical approach. The first abstract in this panel outlines the scope of issues related to data collection, usage, transmission and computing capacity to facilitate EIMO. The second presentation provides an overview of the challenges in developing curricula and advanced training tools to baseline knowledge, skills and abilities (KSA), verify clinical competency and assure retention during prolonged durations inherent in exploration-class missions. An overview of the complicated medical supply and resource chain necessary to facilitate EIMO is provided in the third presentation of this panel. The final presentation in this EIMO panel surveys the breadth and depth of demands on cognitive load expected to be experienced by crew on an exploration mission and proposes strategies to mitigate the prospect of cognitive overload through methods to shift task load from the crew to multi-modal artificial intelligence based medical support systems. Taken together, these presentations summarize the challenges to be expected and potential solution spaces to be explored and developed to progressively enable increasing autonomous medical operations to support crewed missions beyond low earth orbit. Through EIMO focused pre-mission planning, integrated data architecture design, innovative training development and AI-assisted task load management, the gradual transition of medical care and decision making from terrestrial to space-based assets enabling support of astronaut health and performance and reducing overall mission risk is achievable.
Jay Lemery↗
Progressively Enabling Earth Independent Medical Operations (EIMO)
This panel presents the findings from a series of Technical Interchange Meetings (TIMs) hosted by the Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program. The topics for the TIMs were derived from a 2-day conference of senior leaders and subject matters experts that collectively outlined a multi-faceted strategy designed to optimize crew health and performance through an increasingly autonomous medical approach. The first abstract in this panel outlines the scope of issues related to data collection, usage, transmission and computing capacity to facilitate EIMO. The second presentation provides an overview of the challenges in developing curricula and advanced training tools to baseline knowledge, skills and abilities (KSA), verify clinical competency and assure retention during prolonged durations inherent in exploration-class missions. An overview of the complicated medical supply and resource chain necessary to facilitate EIMO is provided in the third presentation of this panel. The final presentation in this EIMO panel surveys the breadth and depth of demands on cognitive load expected to be experienced by crew on an exploration mission and proposes strategies to mitigate the prospect of cognitive overload through methods to shift task load from the crew to multi-modal artificial intelligence based medical support systems. Taken together, these presentations summarize the challenges to be expected and potential solution spaces to be explored and developed to progressively enable increasing autonomous medical operations to support crewed missions beyond low earth orbit. Through EIMO focused pre-mission planning, integrated data architecture design, innovative training development and AI-assisted task load management, the gradual transition of medical care and decision making from terrestrial to space-based assets enabling support of astronaut health and performance and reducing overall mission risk is achievable.
John Lemery↗
Supply and Resource Management to Progressively Enable EIMO
BACKGROUND: Current medical operations in Low Earth Orbit (LEO) allow for real-time audio-video communication with a flight surgeon at mission control, resupply, and medical evacuation to earth on the order of hours. As mission profiles change from LEO to the Moon, Mars, and beyond, medical risk as a contribution to overall mission risk is anticipated to rise substantially. Concurrently, due to the distance, the medical systems on board vehicles proposed for these mission types are expected to have reduced mass and volume allocation. Together, astronaut crews will be at a higher risk of major medical events, be required to perform a broader set of tasks, and have substantially reduced resources and support to do so. Earth Independent Medical Operations (EIMO) aims to identify and fill the gaps present in this progressively changing paradigm. OVERVIEW: Medical supplies, resources, and skills are central to spaceflight medical systems. Vehicles used for non-LEO missions are anticipated to be smaller and thus the medical system will also need to have reduced mass, volume, and power. Medical resources are another form of consumable and may need resupply or pre-deployment to meet crew needs. One particular concern is the degradation of medications which become less efficacious and potentially toxic with time, particularly given environmental conditions such as temperature, humidity, oxygen, and radiation which have not yet been fully studied. Supply and resource management in LEO is dependent on resupply, however the supply chain of transporting equipment does not yet have a clear infrastructure for missions beyond LEO. DISCUSSION: EIMO is intended to systemically identify and fill these gaps with forward-looking solutions. In mission monitoring of resources with technology like RFID, improving medical resource longevity, targeted resupply and careful pre-mission planning will be central to facilitate crew health and performance. One approach to optimizing resources is the Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool, which uses probabilistic risk assessment (PRA) to quantitatively predict medical risk and identify resources and skills that mitigate this risk. This evidence based, quantitative analysis prediction tool and several other approaches to meeting the challenge of supply and resource management are discussed.
Arian Anderson↗
Task Load Management in Earth Independent Medical Operations
BACKGROUND: Medical care in spaceflight carries a high task load and can easily overwhelm a small crew. Present day operations in low Earth orbit (LEO) offload most medical tasks to ground teams in mission control. This team includes dozens of flight surgeons, specialists, and engineers and supports the on-orbit crew in monitoring environmental systems, tracking medications, guiding procedures, providing expert advice, and many other tasks. However, the physical limitations of the speed of light and technical limitations of bandwidth, channel capacity, and signal processing mean that missions beyond LEO cannot rely on this level of telemedical support. The further we travel from Earth the more these tasks will fall on the shoulders of the crew and the greater the risk of task saturation to the wellbeing of the crew and the success of the mission. Exploration class space crews will need progressively more robust systems for managing task load as they progress further out in space. OVERVIEW: Medical task management systems will need to assist with two broad categories of tasks; cognitively intensive tasks and procedure execution tasks. In both cases the goal is for the systems to operate in the background with minimal human-in-the-loop intervention. To accomplish this such systems will need to be designed with careful consideration for human factors and human systems integration to maximize efficiency, minimize alarm fatigue, and avoid inadvertently increasing task loads. Finally, the key domains of space medicine tasking can be used to map present day and near future technologies to the areas where they are best suited to support and identify gaps which can be targeted for research and development. DISCUSSION: Task load is a major challenge for Earth Independent Medical Operations to overcome. It will require careful coordination between experts in a variety of fields paying attention to human factors and human systems integration as well as technical and medical expertise. If done well medical task management systems can handle many of the tasks currently run by humans in mission control and enable human crews to maintain terrestrial standards of care in the extraterrestrial environment.
Dana Levin↗
Crew Medical Training to Progressively Enable EIMO
Background. Onboard medical capabilities have greatly expanded over the history of the US space program. Newly identified space-related medical conditions, technological advances, and longer mission durations have led to an increasing need for on-demand medical expertise. Lengthy communications delays, lack of resupply and evacuation opportunities on exploration-class missions place an ever-increasing burden on the crew to provide medical care. Having adequate knowledge, skills, and abilities (KSA) available is an essential component of successful Earth Independent Medical Operations (EIMO). Without appropriate crew training and KSA, cutting-edge medical equipment has little value. Presumably, the crew will include a qualified physician; however, if the physician is incapacitated, a non-physician crew medical officer (CMO) will be needed. While more crew time is needed for medical training, there will be concomitant increases in preflight training demands for vehicle system management, operations, science, and contingencies. In truly independent operations, onboard resources such as just-in-time training, mixed reality, decision support tools, and AI-enabled chatbot “consultants” will be needed to augment KSA. Overview. Because of crew time constraints, topical priorities must be determined for preflight training. Curricula should be developed that emphasize management of conditions with relatively high incidence and morbidity/mortality. Defining the required KSA levels to treat each condition is essential, but all crewmembers should have basic lifesaving skills. Procedural and diagnostic training on live patients and simulators should be prioritized over classroom lectures. Crews must be trained with onboard equipment, resources, mixed reality, and AI-based decision support tools. Mission simulations should include medical problems with/without ground support and with appropriate communication delays. Certification guidelines for each level of KSA must be established. Skills rapidly decay for non-physician CMO’s; both pre-flight and in-flight refresher training will be needed. During spaceflight just-in-time training, simulations, and onboard CME with crew physician can help retain skills. Discussion. Medical technology, simulation design, mixed reality, and AI are advancing at a dizzying rate. Recognizing the severe constraints on crew time, it is critical that astronaut training is highly efficient and adapted to keep pace with new innovations both pre-flight and during exploration missions. These challenges will be discussed during this panel session.
Jay Lemery↗
Datascope to Enable Earth Independent Medical Operations (EIMO)
BACKGROUND: NASA has amassed sixty years of knowledge and experience relevant to maintenance of crew health and performance in low earth orbit. The Apollo Program introduced the importance of ensuring progressively autonomous operational capability. Earth Independent Medical Operations (EIMO) will require a gradual shift in the balance of medical responsibility, management, and authority from terrestrial to space-based assets. Terrestrial assets will continue to be essential for pre-mission screening and planning in addition to maintenance of crew health and performance. However, new capabilities are needed to enable EIMO and the amount of data required to support these systems, and mitigate the impacts of data transmission delays and reduced bandwidth coupled with lack of cloud-like resources and on-board computing capacity that is currently unclear or operationally insufficient. OVERVIEW: The overall goal of EIMO is to develop artificial intelligence (AI)-based solutions to analyze crew health and performance data utilizing a clinical decision support system (CDSS) to provide crew medical officers (CMO) with the equivalent of real-time, on-board medical consults. The EIMO ecosystem is envisioned as a “system of systems” where embedded reference databases and real-time data streams from multiple input vectors continuously and seamlessly assess crew health and performance. EIMO will be designed to make recommendations to the CMO using multi-modal AI-based natural language processing and machine learning methods with interoperability to push/pull data within and between multiple vehicle and habitat architectures. DISCUSSION: Data flows and storage/retrieval capacity are severely constrained during space missions and the challenges will become even greater during exploration missions. Just as each past program from Mercury to the International Space Station (ISS) required rethinking the interaction between ground-based controllers and space-based crew, so too will future missions to the Moon and Mars. While the NASA High-Performance Spaceflight Computing Processor project aims to increase computational capacity by 100 times over current spaceflight computers, the projected deliverable still lags considerably behind what will be needed to enable an AI-driven CDSS. Restrictions in processing speed and data storage capacity, coupled with transmission bottlenecks and delays, necessitate definition and optimization of an integrated data architecture to enable a progressively autonomous medical capability.
Medical operations↗
Medical Risk Estimates and Clinical Capability needs for a Long Duration Artemis Mission
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Arian Anderson↗