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Editors Note: This article is the third in a periodic series of online articles focusing on emergency management and how its principles can be incorporated into nursing practice.
I remember being told to answer questions on the nursing board exam as if I had an infinite amount of readily available resources. It was called "ivory tower nursing" and was as far away from the reality of daily life as you can get.
In the real world, nurses are often balancing what a patient needs against what would be nice. Bed baths take a back seat to wound care or blood draws. We must plan and prioritize.
Emergency managers often find themselves in a similar situation. We prefer to prevent disasters rather than be forced to respond to them.
Obviously, we can't stop earthquakes and hurricanes, but we can try to prevent accidents and terrorist attacks. So, we seek to determine what threats are out there and then analyze how to neutralize them. The problem is; we can't protect everything.
Take the power grid, for example.
There are thousands of miles of cable crisscrossing the U.S. Multiple companies own and operate multiple power plants providing services across state lines. If we were to attempt to protect the entire system, it would bankrupt the power providers and law enforcement.
How do we decide what gets protected and what doesn't? Risk management!
Probability & Consequence
Risk is defined as a function of probability and consequence. This allows you to analyze things that happen all the time and cause small amounts of damage, to things that happen rarely but cause extreme damage.
For example, power lines fail all the time. Trees fall on them, wind knocks them down, and motorists run into them. Usually, this means a few people lose power for a couple of hours while repair crews fix the problem.
On rare occasions, the power system has a catastrophic failure. A hurricane or earthquake wipes out a large amount of infrastructure. A substation fails and the demand for power outstrips the local supply causing the system to overload and black out. This can put an entire region in the dark for days. Possibly long enough to cause hospital generators to run out of gas.
The first scenario happens regularly. Teams are trained and prepared; responses are swift and usually inexpensive. The second scenario, though unlikely, is extremely costly both in repairs and potentially in human life. Over time, they have similar risk.
Risk Can Never be Zero
A widely used formula is risk equals probability times consequence. It is exceptionally difficult to nail down a numeric value for either variable. You can certainly look back and say a hurricane happens once every 30 years; but, it is only a guess. You can also estimate the damage based on historic amounts or through modeling. But these numbers can often be off.
So, some assign a numeric value to a range of possibilities. For our example, we will assign a 1 for unlikely, a 2 for likely, and a 3 for very likely. For consequence, we'll assign a 1 for a little damage, a 2 for moderate damage, and a 3 for extreme damage.
Our first example happens often and thus rates a 3. However, it does little damage, scoring a 1. Risk would then equal 3 (3 for likelihood times 1 for damage). The second example is unlikely, rating a 1. The damage would be extreme, scoring a 3. The risk would equal 3 (1 for likelihood times 3 for damage). Thus, over time the risk can be similar.
Though oversimplified, this system is how executives in government and the private sector determine how funding is expended to help protect their services. The power company cannot afford to protect every mile of power line. They can afford to trim trees to prevent branches from falling on the cables. They can harden power substations against flooding and high winds. They can plan for a hurricane and train their response teams.
It is impossible to reduce all risk to zero. But it is possible to reduce it.
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