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* Consequence Assessment* Given exposure to the hazardous event/agent, what is the likelihood of harm under a pre-defined endpoint? Endpoint examples: Death Illness Worry OAI *A.K.A. “Dose-Response Assessment” (see next slide) * Consequence Assessment Quantity of contamination (“non-sterility”) i.e., in “bacteria counts per vial” Proportion of exposed persons who become ill 100% 50% 0% ED50 * Qualitative Consequence Assessment High Medium Low Relative Effect/Impact Quantitative relationships known in few cases Low Medium High (Exposure or Dose Metric) * Risk Estimation Bring together the information about the hazard, the extent of exposure to the hazard, the consequences of exposures, and then estimate the risk. Includes a critical analysis of uncertainty in both the data and risk assessment models. * Uncertainties in Risk Assessment Knowledge Variability Data Parameters Model Temporal Spatial Inter-individual * Conceptual Models for RM in PQ Initiative * The PQ Risk Management Problem Diverse PQ failure (hazards) are identified. Wide-ranging risk (= chance that exposure to the hazard will result in harm [adverse outcome]). Wide-ranging consequences (death to worry). Quantitative risk analysis hazard-by-hazard too vast an undertaking. Ranking of risks for re-linking worst PQ risks with worst health risks, etc. How can we objectively rank “apples and oranges” among the “potatoes and beans?” * From the Beginning… Is risk analysis for each hazard– independently—feasible? * Bulb Fails No electricity Power Plant Fails Power Line Fails Glass Broken Filament Broken Connector Corroded Vacuum Leak Tree Breaks Line Wind Breaks Line Impurities Vibrations Fault Trees for each process? * Faults Magnified N-fold for a Simple Manufacturing Process * Decision Analyses for Each Hazard Multiplies Complexity! e.g., * Solution? A Multifactor Approach to PQ Risk Management Multifactor methods already exist. Some tools (software) already developed. Appropriately
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