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  • 1
    Publication Date: 2019-07-12
    Description: The Exploration Medical Capability (ExMC) element is one of six elements under NASA's Human Research Program (HRP). The goal of the ExMC element is to address the risk of the "inability to adequately recognize or treat an ill or injured crewmember." This poster highlights the evidence-based approach that the ExMC element has taken to address this goal, and the ExMC element's current areas of interest.
    Keywords: Aerospace Medicine
    Type: JSC-CN-24832
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  • 2
    Publication Date: 2019-07-13
    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.
    Keywords: Aerospace Medicine
    Type: GRC-E-DAA-TN29847 , 2016 NASA Human Research Program Investigators'' Workshop (HRP IWS 2016); 8-11 Feb. 2016; Galveston, TX; United States
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  • 3
    Publication Date: 2019-07-13
    Description: The Human Research Program funded the development of the integrated medical model (IMM) to quantify the medical component of overall mission risk. The IMM uses Monte Carlo methodology to integrate space flight and ground medical data to assess the probability of mission medical outcomes and resource utilization. To determine the credibility of IMM output the IMM project team completed two validation studies that compare IMM output to observed medical events from a selection of Shuttle Transportation System (STS) and International Space Station (ISS) missions.
    Keywords: Life Sciences (General); Aerospace Medicine
    Type: GRC-E-DAA-TN51425 , 2018 NASA Human Research Program Investigators'' Workshop; 22-25 Jan. 2018; Galveston , TX; United States
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  • 4
    Publication Date: 2019-07-13
    Description: The IMMs ability to assess mission outcome risk levels relative to available resources provides a unique capability to provide guidance on optimal operational medical kit and vehicle resources. Post-processing optimization allows IMM to optimize essential resources to improve a specific model outcome such as maximization of the Crew Health Index (CHI), or minimization of the probability of evacuation (EVAC) or the loss of crew life (LOCL). Mass and or volume constrain the optimized resource set. The IMMs probabilistic simulation uses input data on one hundred medical conditions to simulate medical events that may occur in spaceflight, the resources required to treat those events, and the resulting impact to the mission based on specific crew and mission characteristics. Because IMM version 4.0 provides for partial treatment for medical events, IMM Optimization 4.0 scores resources at the individual resource unit increment level as opposed to the full condition-specific treatment set level, as done in version 3.0. This allows the inclusion of as many resources as possible in the event that an entire set of resources called out for treatment cannot satisfy the constraints. IMM Optimization version 4.0 adds capabilities that increase efficiency by creating multiple resource sets based on differing constraints and priorities, CHI, EVAC, or LOCL. It also provides sets of resources that improve mission-related IMM v4.0 outputs with improved performance compared to the prior optimization. The new optimization represents much improved fidelity that will improve the utility of the IMM 4.0 for decision support.
    Keywords: Aerospace Medicine; Statistics and Probability; Computer Programming and Software
    Type: GRC-E-DAA-TN29567 , 2016 NASA Human Research Program Investigators'' Workshop (HRP IWS 2016); 8-11 Feb. 2016; Galveston, TX; United States
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  • 5
    Publication Date: 2019-07-13
    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.
    Keywords: Aerospace Medicine
    Type: GRC-E-DAA-TN29568 , 2016 NASA Human Research Program Investigators'' Workshop (HRP IWS 2016); 8-11 Feb. 2016; Galveston, TX; United States
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  • 6
    Publication Date: 2019-07-13
    Description: No abstract available
    Keywords: Electronics and Electrical Engineering; Aerospace Medicine
    Type: JSC-CN-35404 , Human Research Program Investigators'' Workshop (HRP IWS 2016); 8-11 Feb. 2016; Galveston, TX; United States
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  • 7
    Publication Date: 2019-07-13
    Description: The Integrated Medical Model is a probabilistic simulation model that uses input data on 100 medical conditions to simulate expected medical events, the resources required to treat, and the resulting impact to the mission for specific crew and mission characteristics. The newest development version of IMM, IMM v4.0, adds capabilities that remove some of the conservative assumptions that underlie the current operational version, IMM v3. While IMM v3 provides the framework to simulate whether a medical event occurred, IMMv4 also simulates when the event occurred during a mission timeline. This allows for more accurate estimation of mission time lost and resource utilization. In addition to the mission timeline, IMMv4.0 features two enhancements that address IMM v3 assumptions regarding medical event treatment. Medical events in IMMv3 are assigned the untreated outcome if any resource required to treat the event was unavailable. IMMv4 allows for partially treated outcomes that are proportional to the amount of required resources available, thus removing the dichotomous treatment assumption. An additional capability IMMv4 is to use an alternative medical resource when the primary resource assigned to the condition is depleted, more accurately reflecting the real-world system. The additional capabilities defining IMM v4.0the mission timeline, partial treatment, and alternate drug result in more realistic predicted mission outcomes. The primary model outcomes of IMM v4.0 for the ISS6 mission, including mission time lost, probability of evacuation, and probability of loss of crew life, are be compared to those produced by the current operational version of IMM to showcase enhanced prediction capabilities.
    Keywords: Computer Programming and Software; Statistics and Probability; Aerospace Medicine
    Type: GRC-E-DAA-TN20329 , NASA Human Research Program Investigators'' Workshop: Integrated Pathways to Mars; 13-15 Jan. 2015; Galveston, TX; United States|Space Radiation Investigators'' Workshop and Behavioral Health and Performance Working Group; 12-15 Jan. 2015; Galveston, TX; United States
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  • 8
    Publication Date: 2019-07-13
    Description: ObjectiveDevelop an evidence-based, probabilistic risk forecasting model that can help guide mission planning, requirements development, and align science with engineering technology development.
    Keywords: Aerospace Medicine
    Type: JSC-17762 , Human Research Program Investigator''s Workshop; 2 - 4 Feb. 2009; Texas; United States
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  • 9
    Publication Date: 2019-07-13
    Description: The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions occurred and decrements the pharmaceuticals and supplies required to diagnose and treat these medical conditions. If supplies are depleted, then the medical condition goes untreated, and crew and mission risk increase. The IMM currently models approximately 30 medical conditions. By the end of FY2008, the IMM will be modeling over 100 medical conditions, approximately 60 of which have been recorded to have occurred during short and long space missions.
    Keywords: Aerospace Medicine
    Type: Human Research Program Investigators'' Workshop; 4-6 Feb. 2008; League City, TX; United States
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  • 10
    Publication Date: 2019-07-13
    Description: No abstract available
    Keywords: Man/System Technology and Life Support; Computer Programming and Software
    Type: JSC-CN-35403 , Human Research Program Investigators'' Workshop (HRP IWS 2016); 8-11 Feb. 2016; Galveston, TX; United States
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