ALBERT

Description: Future exploration missions will be the first time humanity travels beyond Low Earth Orbit (LEO) since the Apollo program, taking us to cis-lunar space, interplanetary space, and Mars. These long-duration missions will cover vast distances, severely constraining opportunities for emergency evacuation to Earth and cargo resupply opportunities. Communication delays and blackouts between the crew and Mission Control will eliminate reliable, real-time telemedicine consultations. As a result, compared to current LEO operations onboard the International Space Station, exploration mission medical care requires an integrated medical system that provides additional in-situ capabilities and a significant increase in crew autonomy. The Medical System Concept of Operations for Mars Exploration Missions illustrates how a future NASA Mars program could ensure appropriate medical care for the crew of this highly autonomous mission. This Concept of Operations document, when complete, will document all mission phases through a series of mission use case scenarios that illustrate required medical capabilities, enabling the NASA Human Research Program (HRP) Exploration Medical Capability (ExMC) Element to plan, design, and prototype an integrated medical system to support human exploration to Mars.

Description: Introduction: The emphasis of this research is on the Human Research Program (HRP) Exploration Medical Capability's (ExMC) "Risk of Unacceptable Health and Mission Outcomes Due to Limitations of In-Flight Medical Capabilities." Specifically, this project aims to contribute to the closure of gap ExMC 2.02: We do not know how the inclusion of a physician crew medical officer quantitatively impacts clinical outcomes during exploration missions. The experiments are specifically designed to address clinical outcome differences between physician and non-physician cohorts in both near-term and longer-term (mission impacting) outcomes. Methods: Medical simulations will systematically compare success of individual diagnostic and therapeutic procedure simulations performed by physician and non-physician crew medical officer (CMO) analogs using clearly defined short-term (individual procedure) outcome metrics. In the subsequent step of the project, the procedure simulation outcomes will be used as input to a modified version of the NASA Integrated Medical Model (IMM) to analyze the effect of the outcome (degree of success) of individual procedures (including successful, imperfectly performed, and failed procedures) on overall long-term clinical outcomes and the consequent mission impacts. The procedures to be simulated are endotracheal intubation, fundoscopic examination, kidney/urinary ultrasound, ultrasound-guided intravenous catheter insertion, and a differential diagnosis exercise. Multiple assessment techniques will be used, centered on medical procedure simulation studies occurring at 3, 6, and 12 months after initial training (as depicted in the following flow diagram of the experiment design). Discussion: Analysis of procedure outcomes in the physician and non-physician groups and their subsets (tested at different elapsed times post training) will allow the team to 1) define differences between physician and non-physician CMOs in terms of both procedure performance (pre-IMM analysis) and overall mitigation of the mission medical impact (IMM analysis); 2) refine the procedure outcome and clinical outcome metrics themselves; 3) refine or develop innovative medical training products and solutions to maximize CMO performance; and 4) validate the methods and products of this experiment for operational use in the planning, execution, and quality assurance of the CMO training process The team has finalized training protocols and developed a software training/testing tool in collaboration with Butler Graphics (Detroit, MI). In addition to the "hands on" medical procedure modules, the software includes a differential diagnosis exercise (limited clinical decision support tool) to evaluate the diagnostic skills of participants. Human subject testing will occur over the next year.

Description: Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.

Description: NASA medical care standards establish requirements for providing health and medical programs for crewmembers during all phases of a mission. These requirements are intended to prevent or mitigate negative health consequences of long-duration spaceflight, thereby optimizing crew health and performance over the course of the mission. Current standards are documented in the two volumes of the NASA-STD-3001 Space Flight Human-System Standard document, established by the Office of the Chief Health and Medical Officer. Its purpose is to provide uniform technical standards for the design, selection, and application of medical hardware, software, processes, procedures, practices, and methods for human-rated systems. NASA-STD-3001 Vol. 1 identifies five levels of care for human spaceflight. These levels of care are accompanied by several components that illustrate the type of medical care expected for each. The Exploration Medical Capability (ExMC) of the Human Research Program has expanded the context of these provided levels of care and components. This supplemental information includes definitions for each component of care and example actions that describe the type of capabilities that coincide with the definition. This interpretation is necessary in order to fully and systematically define the capabilities required for each level of care in order to define the medical requirements and plan for infrastructure needed for medical systems of future exploration missions, such as one to Mars.

Description: The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project.

Description: Future exploration missions will be the first time humanity travels beyond Low Earth Orbit (LEO) since the Apollo program, taking us to cis-lunar space, interplanetary space, and Mars. These long-duration missions will cover vast distances, severely constraining opportunities for emergency evacuation to Earth and cargo resupply opportunities. Communication delays and blackouts between the crew and Mission Control will eliminate reliable, real-time telemedicine consultations. As a result, compared to current LEO operations onboard the International Space Station, exploration mission medical care requires an integrated medical system that provides additional in-situ capabilities and a significant increase in crew autonomy. The Medical System Concept of Operations for Mars Exploration Missions illustrates how a future NASA Mars program could ensure appropriate medical care for the crew of this highly autonomous mission. This Concept of Operations document, when complete, will document all mission phases through a series of mission use case scenarios that illustrate required medical capabilities, enabling the NASA Human Research Program (HRP) Exploration Medical Capability (ExMC) Element to plan, design, and prototype an integrated medical system to support human exploration to Mars.

Description: To validate and further improve the Integrated Medical Model (IMM), medical event data were obtained from 32 ISS and 122 STS person-missions. Using the crew characteristics from these observed missions, IMM v4.0 was used to forecast medical events and medical resource utilization. The IMM medical condition incidence values were compared to the actual observed medical event incidence values, and the IMM forecasted medical resource utilization was compared to actual observed medical resource utilization. Qualitative comparisons of these parameters were conducted for both the ISS and STS programs. The results of these analyses will provide validation of IMM v4.0 and reveal areas of the model requiring adjustments to improve the overall accuracy of IMM outputs. This validation effort should result in enhanced credibility of the IMM and improved confidence in the use of IMM as a decision support tool for human space flight.

Description: Lifetime Surveillance of Astronaut Health (LSAH) provided observed medical event data on 33 ISS and 111 STS person-missions for use in further improving and validating the Integrated Medical Model (IMM). Using only the crew characteristics from these observed missions, the newest development version, IMM v4.0, will simulate these missions to predict medical events and outcomes. Comparing IMM predictions to the actual observed medical event counts will provide external validation and identify areas of possible improvement. In an effort to improve the power of detecting differences in this validation study, the total over each program ISS and STS will serve as the main quantitative comparison objective, specifically the following parameters: total medical events (TME), probability of loss of crew life (LOCL), and probability of evacuation (EVAC). Scatter plots of observed versus median predicted TMEs (with error bars reflecting the simulation intervals) will graphically display comparisons while linear regression will serve as the statistical test of agreement. Two scatter plots will be analyzed 1) where each point reflects a mission and 2) where each point reflects a condition-specific total number of occurrences. The coefficient of determination (R2) resulting from a linear regression with no intercept bias (intercept fixed at zero) will serve as an overall metric of agreement between IMM and the real world system (RWS). In an effort to identify as many possible discrepancies as possible for further inspection, the -level for all statistical tests comparing IMM predictions to observed data will be set to 0.1. This less stringent criterion, along with the multiple testing being conducted, should detect all perceived differences including many false positive signals resulting from random variation. The results of these analyses will reveal areas of the model requiring adjustment to improve overall IMM output, which will thereby provide better decision support for mission critical applications.