A sample gathered of high dollar CPT®/HCPCS codes is referred to as what type of sampling?

The correct answer is proportional sampling, as this method involves selecting a sample that reflects the proportions of particular categories within a larger population. In the context of high dollar CPT®/HCPCS codes, proportional sampling means that the sample will include instances of these codes in proportion to their occurrence in the overall data set. This technique helps ensure that the analysis accurately represents the distribution of high dollar codes, facilitating a more comprehensive understanding of billing patterns and potential compliance issues.

Stratified sampling, on the other hand, refers to dividing the population into subgroups (strata) and sampling from each stratum. While related, it emphasizes the pre-selection of specific groups rather than ensuring representation according to existing proportions. Cluster sampling involves dividing the population into clusters and then randomly selecting entire clusters, which may not yield the same proportional representation. Random sampling, while it can yield a representative sample, does not specifically focus on ensuring that high dollar codes are adequately represented in the proportions they appear in the overall population. Proportional sampling, therefore, is the most accurate choice for reflecting the distribution of high dollar codes within the broader dataset.