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The False Claims Act: Increases in Investigations, Violations, and Penalties
Abstract:
The False Claims Act is a tool used by the government, its contractors, and even employees of healthcare providers to recover overpayments and other improper reimbursements given to physicians for healthcare services provided to Medicare and other federal health program beneficiaries. In recent years, we have seen an increase in the number of False Claims Act cases filed against unsuspecting healthcare providers and practices. These cases have resulted in billions of dollars being paid back to the federal government. Knowing and understanding the requirements of the False Claims Act and implementing best practices and strategies to avoid violating any of these provisions will help practices to ensure that they do not become subject to the massive penalties imposed on violators.
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01:18False Memories
One primary source of false memories is misattribution, where individuals incorrectly associate external information...
01:11Testing a Claim about Mean: Known Population SD
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...
01:24Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
01:19Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
01:21Testing a Claim about Mean: Unknown Population SD
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used;...
01:18Increasing Function