Human Error Information
Human reliability is related to the field of human factors engineering and ergonomics, and refers to the reliability of humans in fields such as manufacturing, transportation, the military, or medicine. Human performance can be affected by many factors such as age, state of mind, physical health, attitude, emotions, propensity for certain common mistakes, errors and cognitive biases, etc.
Human reliability is very important due to the contributions of humans to the resilience of systems and to possible adverse consequences of human errors or oversights, especially when the human is a crucial part of the large socio-technical systems as is common today. User-centered design and error-tolerant design are just two of many terms used to describe efforts to make technology better suited to operation by humans.
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Human reliability analysis techniques
A variety of methods exist for human reliability analysis (HRA).[1][2] Two general classes of methods are those based on probabilistic risk assessment (PRA) and those based on a cognitive theory of control.
PRA-based techniques
One method for analyzing human reliability is a straightforward extension of probabilistic risk assessment (PRA): in the same way that equipment can fail in a plant, so can a human operator commit errors. In both cases, an analysis (functional decomposition for equipment and task analysis for humans) would articulate a level of detail for which failure or error probabilities can be assigned. This basic idea is behind the Technique for Human Error Rate Prediction (THERP).[3] THERP is intended to generate human error probabilities that would be incorporated into a PRA. The Accident Sequence Evaluation Program (ASEP) human reliability procedure is a simplified form of THERP; an associated computational tool is Simplified Human Error Analysis Code (SHEAN).[4] More recently, the US Nuclear Regulatory Commission has published the Standardized Plant Analysis Risk (SPAR) human reliability analysis method also because of human error.[5][6]
Cognitive control based techniques
Erik Hollnagel has developed this line of thought in his work on the Contextual Control Model (COCOM) [7] and the Cognitive Reliability and Error Analysis Method (CREAM).[8] COCOM models human performance as a set of control modes—strategic (based on long-term planning), tactical (based on procedures), opportunistic (based on present context), and scrambled (random) - and proposes a model of how transitions between these control modes occur. This model of control mode transition consists of a number of factors, including the human operator's estimate of the outcome of the action (success or failure), the time remaining to accomplish the action (adequate or inadequate), and the number of simultaneous goals of the human operator at that time. CREAM is a human reliability analysis method that is based on COCOM.
Related techniques
Related techniques in safety engineering and reliability engineering include failure mode and effects analysis, hazop, fault tree, and SAPHIRE: Systems Analysis Programs for Hands-on Integrated Reliability Evaluations.
Human error
Human error has been cited as a cause or contributing factor in disasters and accidents in industries as diverse as nuclear power (e.g., Three Mile Island accident), aviation (see pilot error), space exploration (e.g., Space Shuttle Challenger Disaster), and medicine (see medical error). It is also important to stress that "human error" mechanisms are the same as "human performance" mechanisms; performance later categorized as 'error' is done so in hindsight:[9][10] therefore actions later termed "human error" are actually part of the ordinary spectrum of human behaviour. The study of absent-mindedness in everyday life provides ample documentation and categorization of such aspects of behavior. While human error is firmly entrenched in the classical approaches to accident investigation and risk assessment, it has no role in newer approaches such as resilience engineering.[11]
Categories of human error
There are many ways to categorize human error.[12][13]
- exogenous versus endogenous (i.e., originating outside versus inside the individual)[14]
- situation assessment versus response planning[15] and related distinctions in
- errors in problem detection (also see signal detection theory)
- errors in problem diagnosis (also see problem solving)
- errors in action planning and execution[16] (for example: slips or errors of execution versus mistakes or errors of intention[17][18])
- By level of analysis; for example, perceptual (e.g., optical illusions) versus cognitive versus communication versus organizational.
The cognitive study of human error is a very active research field, including work related to limits of memory and attention and also to decision making strategies such as the availability heuristic and other cognitive biases. Such heuristics and biases are strategies that are useful and often correct, but can lead to systematic patterns of error.
Misunderstandings as a topic in human communication have been studied in conversation analysis, such as the examination of violations of the cooperative principle and Gricean maxims.
Organizational studies of error or dysfunction have included studies of safety culture. One technique for organizational analysis is the Management Oversight Risk Tree (MORT).[19][20]
Human Factors Analysis and Classification System (HFACS)
Main article: Human Factors Analysis and Classification System- See Human Factors Analysis and Classification System in Main article: National Fire Fighter Near-Miss Reporting System
The Human Factors Analysis and Classification System (HFACS) was developed initially as a framework to understand "human error" as a cause of aviation accidents.[21][22] It is based on James Reason's Swiss cheese model of human error in complex systems. HFACS distinguishes between the "active failures" of unsafe acts, and "latent failures" of preconditions for unsafe acts, unsafe supervision, and organizational influences. These categories were developed empirically on the basis of many aviation accident reports.
"Unsafe acts" are performed by the human operator "on the front line" (e.g., the pilot, the air traffic controller, the driver). Unsafe acts can be either errors (in perception, decision making or skill-based performance) or violations (routine or exceptional). The errors here are similar to the above discussion. Violations are the deliberate disregard for rules and procedures. As the name implies, routine violations are those that occur habitually and are usually tolerated by the organization or authority. Exceptional violations are unusual and often extreme. For example, driving 60 mph in a 55-mph zone speed limit is a routine violation, but driving 130 mph in the same zone is exceptional.
There are two types of preconditions for unsafe acts: those that relate to the human operator's internal state and those that relate to the human operator's practices or ways of working. Adverse internal states include those related to physiology (e.g., illness) and mental state (e.g., mentally fatigued, distracted). A third aspect of 'internal state' is really a mismatch between the operator's ability and the task demands; for example, the operator may be unable to make visual judgments or react quickly enough to support the task at hand. Poor operator practices are another type of precondition for unsafe acts. These include poor crew resource management (issues such as leadership and communication) and poor personal readiness practices (e.g., violating the crew rest requirements in aviation).
Four types of unsafe supervision are: inadequate supervision; planned inappropriate operations; failure to correct a known problem; and supervisory violations.
Organizational influences include those related to resources management (e.g., inadequate human or financial resources), organizational climate (structures, policies, and culture), and organizational processes (such as procedures, schedules, oversight).
Controversies
Some researchers have argued that the dichotomy of human actions as "correct" or "incorrect" is a harmful oversimplification of a complex phenomena.[23][24] A focus on the variability of human performance and how human operators (and organizations) can manage that variability may be a more fruitful approach. Newer approaches such as resilience engineering mentioned above, highlights the positive roles that humans can play in complex systems. In resilience engineering, successes (things that go right) and failures (things that go wrong) are seen as having the same basis, namely human performance variability. A specific account of that is the efficiency–thoroughness trade-off (ETTO) principle,[25] which can be found on all levels of human activity, in individual as well as collective.
See also
- Absolute probability judgement
- Latent human error
- Human error assessment and reduction technique (HEART), a technique used in the field of human reliability
- Influence diagrams approach
Footnotes
- ^ Kirwan and Ainsworth, 1992
- ^ Kirwan, 1994
- ^ Swain & Guttman, 1983
- ^ Wilson, 1993)
- ^ SPAR-H
- ^ Gertman et al., 2005
- ^ (Hollnagel, 1993)
- ^ (Hollnagel, 1998)
- ^ Reason, 1991
- ^ Woods, 1990
- ^ Hollnagel, E., Woods, D. D. & Leveson, N. G. (2006). Resilience engineering: Concepts and precepts. Aldershot, UK: Ashgate
- ^ Jones, 1999
- ^ Wallace and Ross, 2006
- ^ Senders and Moray, 1991
- ^ Roth et al., 1994
- ^ Sage, 1992
- ^ Norman, 1988
- ^ Reason, 1991
- ^ (Kirwan and Ainsworth, 1992;
- ^ search for MORT on the FAA Human Factors Workbench
- ^ Shappell and Wiegmann, 2000
- ^ Wiegmann and Shappell, 2003
- ^ Hollnagel, E. (1983). Human error. (Position Paper for NATO Conference on Human Error, August 1983, Bellagio, Italy)
- ^ Hollnagel, E. and Amalberti, R. (2001). The Emperor’s New Clothes, or whatever happened to “human error”? Invited keynote presentation at 4th International Workshop on Human Error, Safety and System Development.. Linköping, June 11–12, 2001.
- ^ Hollnagel, E. (2009). The ETTO Principle - Efficiency-Thoroughness Trade-Off. Why things that go right sometimes go wrong. Ashgate
References
- Gertman, D. L. and Blackman, H. S. (2001). Human reliability and safety analysis data handbook. Wiley.
- Gertman, D., Blackman, H., Marble, J., Byers, J. and Smith, C. (2005). The SPAR-H human reliability analysis method. NUREG/CR-6883. Idaho National Laboratory, prepared for U. S. Nuclear Regulatory Commission. [1]
- Hollnagel, E. (1993). Human reliability analysis: Context and control. Academic Press.
- Hollnagel, E. (1998). Cognitive reliability and error analysis method: CREAM. Elsevier.
- Hollnagel, E. and Amalberti, R. (2001). The Emperor’s New Clothes, or whatever happened to “human error”? Invited keynote presentation at 4th International Workshop on Human Error, Safety and System Development.. Linköping, June 11–12, 2001.
- Hollnagel, E., Woods, D. D., and Leveson, N. (Eds.) (2006). Resilience engineering: Concepts and precepts. Ashgate.
- Jones, P. M. (1999). Human error and its amelioration. In Handbook of Systems Engineering and Management (A. P. Sage and W. B. Rouse, eds.), 687-702. Wiley.
- Kirwan, B. (1994). A Guide to Practical Human Reliability Assessment. Taylor & Francis.
- Kirwan, B. and Ainsworth, L. (Eds.) (1992). A guide to task analysis. Taylor & Francis.
- Norman, D. (1988). The psychology of everyday things. Basic Books.
- Reason, J. (1990). Human error. Cambridge University Press.
- Roth, E. et al. (1994). An empirical investigation of operator performance in cognitive demanding simulated emergencies. NUREG/CR-6208, Westinghouse Science and Technology Center. Report prepared for Nuclear Regulatory Commission.
- Sage, A. P. (1992). Systems engineering. Wiley.
- Senders, J. and Moray, N. (1991). Human error: Cause, prediction, and reduction. Lawrence Erlbaum Associates.
- Shappell, S. & Wiegmann, D. (2000). The human factors analysis and classification system - HFACS. DOT/FAA/AM-00/7, Office of Aviation Medicine, Federal Aviation Administration, Department of Transportation.. [2]
- Swain, A. D., & Guttman, H. E. (1983). Handbook of human reliability analysis with emphasis on nuclear power plant applications.. NUREG/CR-1278 (Washington D.C.).
- Wallace, B. and Ross, A. (2006). Beyond human error. CRC Press.
- Wiegmann, D. & Shappell, S. (2003). A human error approach to aviation accident analysis: The human factors analysis and classification system.. Ashgate.
- Wilson, J.R. (1993). SHEAN (Simplified Human Error Analysis code) and automated THERP. United States Department of Energy Technical Report Number WINCO--11908. [3]
- Woods, D. D. (1990). Modeling and predicting human error. In J. Elkind, S. Card, J. Hochberg, and B. Huey (Eds.), Human performance models for computer-aided engineering (248-274). Academic Press.
Further reading
- Autrey, T.D. (2007). . Practicing Perfection Institute Mistake-Proofing Six Sigma: How to Minimize Project Scope and Reduce Human Error.
- Davies, J.B., Ross, A., Wallace, B. and Wright, L. (2003). Safety Management: a Qualitative Systems Approach. Taylor and Francis.
- Dekker, S.W.A., (2005). Ten Questions About Human Error: a new view of human factors and systems safety]. Lawrence Erlbaum Associates.
- Dekker, S.W.A., (2006). The Field Guide to Understanding Human Error. Ashgate.
- Dekker, S.W.A., (2007). Just Culture: Balancing Safety and Accountability. Ashgate.
- Dismukes, R. K., Berman, B. A., and Loukopoulos, L. D. (2007). The limits of expertise: Rethinking pilot error and the causes of airline accidents. Ashgate.
- Forester, J., Kolaczkowski, A., Lois, E., and Kelly, D. (2006). Evaluation of human reliability analysis methods against good practices. NUREG-1842 Final Report. U. S. Nuclear Regulatory Commission. [4]
- Goodstein, L. P., Andersen, H. B., and Olsen, S. E. (Eds.) (1988). Tasks, errors, and mental models. Taylor and Francis.
- Grabowski, M. and Roberts, K. H. (1996). Human and organizational error in large scale systems, IEEE Transactions on Systems, Man, and Cybernetics, Volume 26, No. 1, January 1996, 2-16.
- Greenbaum, J. and Kyng, M. (Eds.) (1991). Design at work: Cooperative design of computer systems. Lawrence Erlbaum Associates.
- Harrison, M. (2004). Human error analysis and reliability assessment. Workshop on Human Computer Interaction and Dependability, 46th IFIP Working Group 10.4 Meeting, Siena, Italy, July 3–7, 2004. [5]
- Hollnagel, E. (1991). The phenotype of erroneous actions: Implications for HCI design. In G. W. R. Weir and J. L. Alty (Eds.), Human-computer interaction and complex systems. Academic Press.
- Hutchins, E. (1995). Cognition in the wild. MIT Press.
- Kahneman, D., Slovic, P. and Tversky, A. (Eds.) (1982). Judgment under uncertainty: Heuristics and biases. Cambridge University Press.
- Leveson, N. (1995). Safeware: System safety and computers. Addison-Wesley.
- Morgan, G. (1986). Images of organization. Sage.
- Mura, S. S. (1983). Licensing violations: Legitimate violations of Grice's conversational principle. In R. Craig and K. Tracy (Eds.), Conversational coherence: Form, structure, and strategy (101-115). Sage.
- Perrow, C. (1984). Normal accidents: Living with high-risk technologies. Basic Books.
- Rasmussen, J. (1983). Skills, rules, and knowledge: Signals, signs, and symbols and other distinctions in human performance models. IEEE Transactions on Systems, Man, and Cybernetics, SMC-13, 257-267.
- Rasmussen, J. (1986). Information processing and human-machine interaction: An approach to cognitive engineering. Wiley.
- Silverman, B. (1992). Critiquing human error: A knowledge-based human-computer collaboration approach. Academic Press.
- Swets, J. (1996). Signal detection theory and ROC analysis in psychology and diagnostics: Collected papers. Lawrence Erlbaum Associates.
- Tversky, A. and Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124-1131.
- Vaughan, D. (1996). The Challenger launch decision: Risky technology, culture, and deviance at NASA. University of Chicago Press.
- Woods, D. D., Johannesen, L., Cook, R., and Sarter, N. (1994). Behind human error: Cognitive systems, computers, and hindsight. CSERIAC SOAR Report 94-01. Crew Systems Ergonomics Information Analysis Center, Wright-Patterson Air Force Base, Ohio.
- CCPS, Guidelines for Preventing Human Error. This book explains about qualitative and quantitative methodology for predicting human error. Qualitative methodology called SPEAR: Systems for Predicting Human Error and Recovery, and quantitative methodology also includes THERP, etc.
External links
Standards and guidance documents
Tools
Research labs
- Erik Hollnagel at the Crisis and Risk Research Centre at MINES ParisTech
- Human Reliability Analysis at the US Sandia National Laboratories
- Center for Human Reliability Studies at the US Oak Ridge National Laboratory
- Flight Cognition Laboratory at NASA Ames Research Center
- David Woods at the Cognitive Systems Engineering Laboratory at The Ohio State University
- Sidney Dekker's Leonardo da Vinci Laboratory for Complexity and Systems Thinking, Lund University, Sweden
Media coverage
- “Human Reliability. We break down just like machines“ Industrial Engineer - November 2004, 36(11): 66
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