Summary: In Chapter 3, I link patient demographic information and ambulance, outpatient, and inpatient claims to look for the inconsistency of having a claim for an ambulance transport with seemingly no real patient - a 'ghost'. I find 1.9% of emergency transports have this inconsistency. I estimate the distribution of ghost ride rates by suppliers and separately, by counties, using an expectation-maximization algorithm. I find the ghost rides are not evenly distributed across counties or suppliers. Although it is not possible to conclusively distinguish billing anomalies due to fraud from data entry errors and similar explanations, this type of analysis may provide useful starting points for further investigation of Medicare fraud.