Final answer:
A negative likelihood ratio of less than 0.1 indicates that a negative test is good at 'ruling out' a disease. This measurement is used in clinical decision-making to interpret diagnostic test results in the context of epidemiology and public health.
Step-by-step explanation:
A negative likelihood ratio (LR-) of less than 0.1 suggests that a negative test result is good at ruling out a disease or disorder. When a test has a low negative likelihood ratio, it means that a negative result on that test is a strong indicator that the patient does not have the condition being tested for. This is an important concept in epidemiology and public health for interpreting diagnostic test results.
The use of likelihood ratios is crucial in clinical decision-making as it helps healthcare providers determine whether a patient likely has or does not have a particular medical condition based on their test results. In other words, a very low LR- (<0.1) substantially decreases the probability of the disease being present, which is critical information for guiding further diagnostic or therapeutic decisions.