The significance of a skip pattern depends on the question leading to the skip pattern, the questions within that skip pattern, and the variables you intend to analyze. If you fail to check for skip patterns, you may obtain only a proportion of the population, instead of the entire study population.
For example, from the Medical History questionnaire for persons 12-74 years in the Locate Variables module, you should note that some of the sections, such as the blood pressure section, have skip patterns. In the blood pressure section, there are two questions relevant to self-report of hypertension diagnosis:
Note that participants who respond "Yes" to n2ah1059 skipped over the question n2ah1060 and went directly to question n2ah1061. Those answering "No" to n2ah1059 are asked question n2ah1060.
If you would like to estimate the prevalence of diagnosed hypertension (defined as a person ever being told by a doctor that he or she had hypertension) among US adults, you must recode n2ah1059 to include those who answered "Yes" in n2ah1060. Thus, until you recode n2ah1059 (or define a new variable based on it) to include those who answered "Yes" to n2ah1060, these people will be left out of the numerator value. If you fail to do this step, you will not be estimating the total percent of persons with diagnosed hypertension.