Question

I am reposting the question because I am looking for how each correlation and causation applies in healthcare operations management.

Please provide an example of correlation and an example of causation as it relates to healthcare operations management and then explain how these concepts are important in identifying and prioritizing operational improvement opportunities.

Answer 1

****Please please please LIKE THIS ANSWER, so that I can get a small benefit, Please****

Correlations explain the size and direction of a relationship between two or more variables. Causation proves that one event is the result of the happening of another event, also known as cause and effect. A high coefficient determination does not necessarily mean that a relationship exists between variables, therefore correlation is not causation.

An example of this is a study in a hospital trying to determine the underlying factor of dissatisfied patients. This study may reveal that people who are complaining most are the ones coming in to the ER, so it can be tempting to conclude that the healthcare staff in the ER need better training in customer service and they are causing upset patients. However, it could also be the case that patients coming into the ER are already very upset and out of their element because of recently getting very hurt or having a loved one hurt. Therefore we can say there is a correlation between people coming in to the ER feeling dissatisfied and rude/non empathetic staff, but we do not know for sure if it's the staff are the ones causing the customers to be unhappy.

These concepts are often important in identifying and prioritizing operational improvement opportunities. It is easier to find evidence of a correlation of two things than it is to find evidence that one actually causes the other. A correlation does not mean causation and although a relationship may be shared between the two, it doesn't necessarily mean that one causes the other. When identifying and prioritizing improvement opportunities, the correct correlation or causation needs to be identified so that the results can change for the better.