SafetyDog

Beyond Reason…to Resiliency

In High Reliability Orgs, human error, Human Factors, Normal Accident Theory on November 13, 2010 at 5:06 pm

An earlier post presented James Reason’s Swiss cheese model of failure in complex organizations. This model and the concept of latent failures are linear models of failure in that the failure is the result of one breakdown then another then another which all combined contribute to a failure by someone or something at the sharp end of a process.
More recent theories expand on this linear model and describe complex systems as interactive in that complex interactions, processes and relationships all interact in a non-linear fashion to produce failure. Examples of these are Normal Accident theory (NAT) and the theory of High Reliability Organizations (HRO). NAT holds that once a system becomes complex enough accidents are inevitable. There will come a point when humans lose control of a situation and failure results; such as in the case of Three Mile Island. In High Reliability Theory, organizations attempt to prevent the inevitable accident by monitoring the environment (St Pierre, et al., 2008). HRO look at their near misses to find holes in their systems; they look for complex causes of error, reduce variability and increase redundancy in the hopes of preventing failures (Woods, et al., 2010). While these efforts are worthwhile, this still has not reduced failures in organizations to an acceptable level. Sometimes double checks fail and standardization and policies increase complexity.

One of the new ways of thinking about safety is known as Resilience Engineering.
In this concept failures are not viewed as a breakdown in normal processes but as a breakdown in the adaptations used to cope with complexity (Woods, et al., 2010). Success is defined as “the ability of groups to anticipate the changing shape of risk before damage occurs. Failure is the temporary or permanent loss of that ability” (Woods, 2010, p. 83).
Woods, et al. (2010) use the case of the shuttle Columbia to describe the concept in resilience engineering of goal tradeoffs. Goal tradeoffs involve focusing on one goal while gradually neglecting others. Woods, et al. (2010) describe a common example of this is focusing on an acute issue like production and efficiency over a chronic issue like safety. If an organization focuses too much on production pressure, ignoring early warning signs of safety it is acting with too much risk. In resilience engineering a ramping up of production would be associated with additional focus on the side effects production pressures might have on risk (Woods, et al., 2010).
Properties of resilient systems include: buffering capacity, flexibility margin and tolerance (Woods, et al., 2010). Too much efficiency can prevent resiliency and adaptability (Haskins, 2010). Resilient organizations do not view the absence of failure as a sign that hazards are not present. Resilient organizations look for fragmented problem solving and attempt to cross-check rationales by having various team members involved in decision making.
Tucker and Spear (2006) describe resiliency issues in hospital nursing. They studied two issues of complexity in nursing: managing changing patient conditions and managing faulty systems. In their study they identified some adaptive techniques that nurses use to prevent failure as partitioning, interweaving and reprioritization (Tucker & Spear, 2006). Partitioning is defined as postponing a task until something arrived like a supply, a medication or additional help (Tucker & Spear, 2006). Interweaving describes the necessity of providing care to patients in a cyclical fashion where a nurse or other clinician has to repeatedly switch among patients rather than complete tasks in a linear manner (Tucker & Spear, 2006). In one of their observations, a nurse had to switch amongst her 5 patients 74 times in an 8 hour shift. Reprioritization is described as the constant problem solving required as new information about patients became evident, tasks were added or subtracted, admissions or discharges were addressed, or a patient’s condition changed (Tucker & Spear, 2006). Interruptions were cited as a 4th issue related to resiliency.

Given these challenges how do we prevent nurses and other clinicians from temporarily or permanently “losing the ability of to anticipate the changing shape of risk before damage occurs?”

Lots to think about…more on Resiliency engineering to come…

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