Question

What is the difference between correlation and causation? Offer an example of each as it relates to healthcare operations management. Then explain how these concepts are important in identifying and prioritizing operational improvement opportunities.

Answer 1

Correlation is a statistical measure (expressed as a number) that describes the size and direction of a relationship between two or more variables. A correlation between variables, however, does not automatically mean that the change in one variable is the cause of the change in the values of the other variable.

Causation indicates that one event is the result of the occurrence of the other event; i.e. there is a causal relationship between the two events. This is also referred to as cause and effect. difference between the two types of relationships are easy to identify — an action or occurrence can cause another (e.g. smoking causes an increase in the risk of developing lung cancer), or it can correlate with another (e.g. smoking is correlated with alcoholism, but it does not cause alcoholism). In practice, however, it remains difficult to clearly establish cause and effect, compared with establishing correlation

Correlations are often mistaken for causation because common sense seems to dictate that one caused the other. After all, bad smells and disease are both unpleasant, and always seem to appear at the same time and in the same places. But you can have a foul odor without a disease. Diseases can strike even in places where standing water isn’t present—like hospitals where the surgeons aren’t washing their hands.

To prove causation, you need to find a direct relationship between variables. You need to show that one relies on the other, not just that the two appear to move in concert.

correlation can help you predict what will happen. But finding the ’cause’ of something means you can change it.”

Unlike correlations, causal relationships don’t happen by accident. Once you lay out the variables, you can control and change them to meet your needs.

Once you find a correlation, you can prove causation by running experiments where you control the other variables and measure the difference.