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the integrated medical model - optimizing in-flight space medical systems to reduce crew health risk and mission impactsThe Integrated Medical Model (IMM) is a decision support tool used by medical system planners and designers as they prepare for exploration planning activities of the Constellation program (CxP). IMM provides an evidence-based approach to help optimize the allocation of in-flight medical resources for a specified level of risk within spacecraft operational constraints. Eighty medical conditions and associated resources are represented in IMM. Nine conditions are due to Space Adaptation Syndrome. The IMM helps answer fundamental medical mission planning questions such as What medical conditions can be expected? What type and quantity of medical resources are most likely to be used?", and "What is the probability of crew death or evacuation due to medical events?" For a specified mission and crew profile, the IMM effectively characterizes the sequence of events that could potentially occur should a medical condition happen. The mathematical relationships among mission and crew attributes, medical conditions and incidence data, in-flight medical resources, potential clinical and crew health end states are established to generate end state probabilities. A Monte Carlo computational method is used to determine the probable outcomes and requires up to 25,000 mission trials to reach convergence. For each mission trial, the pharmaceuticals and supplies required to diagnose and treat prevalent medical conditions are tracked and decremented. The uncertainty of patient response to treatment is bounded via a best-case, worst-case, untreated case algorithm. A Crew Health Index (CHI) metric, developed to account for functional impairment due to a medical condition, provides a quantified measure of risk and enables risk comparisons across mission scenarios. The use of historical in-flight medical data, terrestrial surrogate data as appropriate, and space medicine subject matter expertise has enabled the development of a probabilistic, stochastic decision support tool capable of optimizing in-flight medical systems based on crew and mission parameters. This presentation will illustrate how to apply quantitative risk assessment methods to optimize the mass and volume of space-based medical systems for a space flight mission given the level of crew health and mission risk.
Document ID
20080043911
Document Type
Conference Paper
Authors
Kerstman, Eric
(Texas Univ. Galveston, TX, United States)
Walton, Marlei
(Wyle Integrated Science and Engineering Group Houston, TX, United States)
Minard, Charles
(Wyle Integrated Science and Engineering Group Houston, TX, United States)
Saile, Lynn
(Wyle Integrated Science and Engineering Group Houston, TX, United States)
Myers, Jerry
(NASA Glenn Research Center Cleveland, OH, United States)
Butler, Doug
(Wyle Integrated Science and Engineering Group Houston, TX, United States)
Lyengar, Sriram
(Texas Univ. Health Science Center Houston, TX, United States)
Fitts, Mary
(NASA Johnson Space Center Houston, TX, United States)
Johnson-Throop, Kathy
(NASA Johnson Space Center Houston, TX, United States)
Date Acquired
August 24, 2013
Publication Date
January 1, 2009
Subject Category
Aerospace Medicine
Meeting Information
80th Annual Scientific Meeting of the Aerospace Medical Association(Los Angeles, CA)
Distribution Limits
Public
Copyright
Other