Factors Affecting Sample Size in Health Care Claims Processing

B.

Attribute sampling is a statistical sampling technique used in auditing to estimate the proportion of a population that has a certain characteristic or attribute, such as errors. In attribute sampling, the sample size is determined based on the desired level of precision and confidence in the results.

The sample size required for attribute sampling depends on several factors, including population size, expected error rate, acceptable risk level, and tolerable error rate.

The correct answer to the question is option D, "Tolerable error rate increase." When the tolerable error rate increases, the sample size required to achieve the desired level of precision and confidence decreases.

The tolerable error rate is the maximum error rate that the auditor is willing to accept without concluding that the control or process is not effective. If the tolerable error rate increases, the auditor is willing to accept a higher error rate in the sample, which means that a smaller sample size is required to achieve the desired level of precision and confidence.

On the other hand, an increase in population size (option A) would increase the sample size required, as a larger population means a larger sample is needed to represent it accurately. Similarly, an increase in the expected error rate (option B) would increase the sample size required, as a higher expected error rate means a larger sample is needed to achieve the desired level of precision and confidence.

Finally, a decrease in the acceptable risk level (option C) would also increase the sample size required. The acceptable risk level is the maximum risk that the auditor is willing to take of concluding that the control or process is effective when it is not. If the acceptable risk level decreases, the auditor is willing to take less risk, which means that a larger sample size is required to achieve the desired level of precision and confidence.