document: Ground ambulance services are provided by a wide range of organizations that differ in organizational structure, staffing types, types of transports offered, and revenue sources. Medicare payments for ambulance services are made up of two components: a service-level payment for the type of transport provided and a mileage payment. Providers may be affiliated with an institution (such as a hospital or a fire department) and share resources and operational costs, or they may be independent and freestanding. In addition, providers may be for-profit, nonprofit, or government-based. Providers may rely heavily on volunteers, use both volunteers and paid staff, or use only paid staff. Providers may specialize in nonemergency transports, or offer both nonemergency and emergency (those responding to a 911 call) transports. Also, some providers offer only basic life support (BLS) services, while others offer advanced life support (ALS) services. ALS services require the skills of a medical technician who is more specialized and trained, such as a paramedic, than the technician who can provide BLS services. Revenue sources depend on the resources available in communities and communities’ choices about funding ambulance services. They may include community tax support, charitable donations, in-kind contributions, state and federal grants, subscription programs,payments from Medicare or Medicaid and private health insurance companies (including patient copayments or coinsurance). The mix and amount of revenues available may vary. Communities differ by the level of tax support for specific services, such as ensuring a minimum level of service in remote areas, sophistication of transport vehicles, and the training level of the staff. Medicare pays ambulance providers through a national fee schedule. (See fig. 5 in app. I for an overview of the Medicare ambulance payment formula.) Payments have two components: 1. service-level payment: for the type of transport provided, such as an ALS Level 1 transport;2. mileage payment. The mileage payment is determined by the number of miles traveled with a patient during an ambulance transport and the mileage base rate. Since 2002, CMS has increased the rural mileage rate (which also applies to super-rural transports) by 50 percent for miles 1 through 17. See 67 Fed. Reg. 9100 (Feb. 27, 2002) (adding subpart H to 42 C.F.R. part 414); 42 C.F.R. § 414.610(c)(5)(i)(2011) (this mileage rate increase is not set to expire). Also see fig. 5 in app. I for an overview of the Medicare ambulance payment formula. Improvement, and Modernization Act of 2003, temporarily extended by subsequent acts, and most recently extended through the end of 2012 by the Middle Class Tax Relief and Job Creation Act of 2012. Providers paid under a fee schedule generally have an incentive to keep their costs to deliver services at or below the fee schedule rate. Some providers rely heavily on Medicare revenues, and adequate Medicare margins for these providers may help ensure that beneficiaries have access to ambulance services. In our 2007 report, we found that providers with lower transport volumes generally had higher costs per Because of transport than providers with greater transport volumes.high fixed costs for maintaining readiness—the availability of an ambulance and crew for immediate emergency responses—providers with low volumes, which still need to maintain readiness, tended to have higher costs per transport. Other significant factors that affected cost per transport included level of volunteer staff hours, percentage of Medicare transports that are BLS, percentage of Medicare transports that are super-rural, and level of community tax support. Providers’ costs for providing ground ambulance transports were highly variable in 2010, ranging from a low of $224 per transport to a high of $2,204, with a median cost per transport of $429. The variability of costs per transport reflected differences in certain provider characteristics, such as volume of transports, intensity of Medicare transports, and level of government subsidies received. Providers reported that personnel costs accounted for the largest percentage of their total costs in 2010 and contributed the most to increases in total costs between 2009 and 2010. The median cost per ground ambulance transport for providers in our sample was $429 in 2010, but providers’ costs per transport ranged from a low of $224 to a high of $2,204. Five percent of providers had costs per transport that were less than $253, and 5 percent had costs per transport that were more than $924. Figure 1 shows the distribution of 2010 costs per transport for providers in our sample. Among the population of providers from which our sample was drawn, the estimated median cost per transport ranged from $401 to $475, which represents the 95 percent statistical confidence interval around the median and is the range within which we expect the population median cost per transport to fall in 95 percent of the samples we could have drawn. Super-rural providers had estimated median costs per transport that were significantly higher than urban providers (see table 1). The variability associated with our survey data did not allow us to conclude that rural providers’ estimated median costs per transport were significantly different from super-rural or urban providers. As will be discussed later, when we controlled for other provider characteristics that affected cost per transport using regression analysis, differences in cost per transport by service area were not significant.characteristics other than service area were more important in explaining the variation in cost per transport. The median Medicare margin, including add-on payments, was about positive 2 percent in 2010 for the 153 providers in our sample.removed the add-on payments, we found that payments decreased for the providers in our sample, resulting in a lower median Medicare margin of negative 1 percent for those providers. See table 2. Ambulance transports for all Medicare fee-for-service beneficiaries in the nation increased by 33 percent from 2004 to 2010. All three service areas—urban, rural, and super-rural—experienced growth. Transports per 1,000 beneficiaries in super-rural areas grew the most, by 41 percent, and transports per 1,000 beneficiaries in rural and urban areas increased by 35 percent and 32 percent, respectively. (See table 4.) The increase in ambulance transports from 2004 to 2010 is attributable primarily to an increase in BLS nonemergency transports, which rose by 59 percent from 2004 to 2010. Super-rural areas experienced the largest increase in BLS nonemergency transports (82 percent). The increase in Medicare beneficiaries’ use of ambulance services did not appear to be caused by changes in the demographic characteristics of beneficiaries. For example, factors such as age, race, and sex remained stable from 2004 to 2010 in urban, rural, and super-rural areas. Representatives we spoke with from one ambulance provider organization suggested that some of the increase in ambulance transports was attributable to increased billing for Medicare ambulance services at the local-government level. Some local governments that provided ambulance transports free of charge had been reluctant in the past to bill insurers such as Medicare because patients would then be financially responsible for out-of-pocket insurance costs, such as deductibles and copayments. The increased out-of-pocket costs for patients had the potential to result in less community support of ambulance providers through fewer charitable contributions and fewer volunteers. However, these local governments have begun to bill Medicare as well as other insurers because of increased budgetary pressures. Representatives we spoke with also added that the introduction of the national fee schedule in 2002 may have contributed to increased billing because it allowed providers to better anticipate the amount of revenue they could receive from Medicare. The Department of Health and Human Services (HHS) Office of Inspector General (OIG) has explored increases in ambulance utilization and has cited improper payments as one potential cause. For example, HHS OIG found that nonemergency transports, including BLS nonemergency transports, made up the majority of improper payments for ambulance services, and particularly transports for dialysis services. HHS OIG also found that Medicare’s ambulance transport benefit is highly vulnerable to abuse and found that many ambulance transports paid for by Medicare did not meet Medicare program requirements, including transports that were not medically necessary. We provided a draft of this report to HHS and invited representatives of AAA to review the draft. HHS had no general or technical comments on behalf of CMS. The AAA representatives provided oral comments and generally agreed with our findings; however, AAA had some questions regarding our methodology and conclusions, which we clarified in the report where appropriate and discuss below. In addition, AAA provided technical comments, which we incorporated as appropriate. AAA representatives questioned whether the Medicare margin results were comparable to those of the 2007 report and were concerned that readers would conclude that providers’ Medicare margins have increased over time. We clarified in the report that we do not consider the results reported in 2007 and in the current report to be directly comparable because the samples examined in each report were different and we reported median Medicare margins in the current report whereas in 2007 we reported average Medicare margins. AAA representatives noted that our sample contains providers that have been in business since at least 2003 and that the cost data from this sample may not be representative of all ambulance providers. We agree that the providers in our sample represent mature and well-established organizations—an advantage because this approach avoids start-up organizations with potentially high start-up costs, as described in our scope and methodology. Despite the differences in the samples and the type of measure used for reporting Medicare margins, both of these studies showed wide variation in costs per transport and Medicare margins. AAA representatives had some questions about the results of our regression analysis. For example, the regression results suggest that ambulance providers that receive a greater proportion of government subsidies tend to have higher costs. The representatives theorized that providers with higher costs seek additional government support and did not think this finding was consistent with how their industry operates. As described in the report, the Medicare Payment Advisory Commission found an association between increased resources and increased costs in the hospital industry and theorizes that such hospitals face less pressure to control costs. We found an association in the ambulance industry but determining causality was beyond the scope of our work. AAA representatives also questioned the regression analysis results that indicated that providers’ use of volunteer staff did not significantly contribute to differences in providers’ total costs, because our survey data indicated that personnel costs were, on average, 61 percent of providers’ total costs. The results may be a consequence of the relatively small sample size and, in addition, a small proportion of providers in our sample using volunteer staff (21 percent). Finally, the AAA representatives commented that ground ambulance providers’ current Medicare payments are lower than those we calculated for 2010 because of the expiration of a required temporary increase in Medicare payments for certain geographic areas, the implementation of a policy for reporting fractional mileage, and the introduction of a productivity adjustment relative to the annual inflation adjustment of the fee schedule. In addition, AAA noted that the cost of fuel has increased since 2010. We acknowledge that these factors likely lowered Medicare payments and increased costs for some providers after 2010, the most recent year for which data were available when we began our study. We are sending copies of this report to other congressional committees and the Administrator of CMS. In addition, the report is available at no charge on the GAO website at http://www.gao.gov. If you or your staffs have any questions about this report, please contact me at (202) 512-7114 or cosgrovej@gao.gov. Contact points for our Offices of Congressional Relations and Public Affairs may be found on the last page of the report. GAO staff who made major contributions to this report are listed in appendix II. This appendix describes the data and methods we used to respond to our research objectives. We conducted a survey of ambulance providers to collect data on their costs and other characteristics. We relied on these survey data for much of our analyses and supplemented our survey results with information from other sources, including Medicare claims data, as appropriate. We also analyzed Medicare claims data to determine payments to ambulance providers as well as to determine the number of Medicare ambulance transports. We tested the internal consistency and reliability of the data from our survey and the Medicare claims data and determined that all data sources were adequate for our purposes. We conducted our work from April 2012 through September 2012 in accordance with generally accepted government auditing standards. To collect data on ground ambulance providers’ costs, revenues, transports, and organizational characteristics for calendar year 2010, or for the fiscal year that corresponded to all or the majority of a provider’s calendar year 2010 data, we sent a web-based survey to a random, nationally representative sample of 294 eligible ambulance providers. We obtained data from 154 providers for a response rate of 52 percent, after excluding cost outliers and surveys with unreliable data. We determined that our sample was nationally representative of the approximately 2,900 ambulance providers that billed Medicare in 2003 and 2010, were still operational in 2012, and did not share costs with nonambulance services or air ambulance services. However, the small sample size and the variability of reported costs reduced the precision of our estimates. We drew potentially eligible providers for our survey from an existing sample, originally developed for our 2007 report, of 900 non-hospital- based ground ambulance providers that billed Medicare in 2003. Through Internet searches and phone contacts to ambulance providers, we excluded any providers that (1) were no longer in business; (2) shared costs with nonambulance services, such as those providers affiliated with a fire department; or (3) we were otherwise not able to contact.did for the 2007 report, we excluded ground ambulance providers that also provided air ambulance services. After all exclusions, we had 294 eligible providers for potential survey participation. On the basis of the number of providers that were eligible for our sample and the number of providers that responded to our survey, we calculated sample weights to estimate how many Medicare ambulance providers our sample represented. To develop our survey instrument, we modified the survey instrument used for our 2007 report, which was mailed to ambulance providers, to tailor it to our current objectives and format it for use as a web-based survey. We retained questions about ambulance providers’ costs, revenues, and transports, as well as questions to identify organizational characteristics that might affect ambulance providers’ costs, such as the use of volunteer staff. We added questions related to changes in total cost (increases or decreases) from 2009 to 2010 and the cost components that most contributed to the changes. We also asked providers for their National Provider Identifier (NPI), which providers use to bill Medicare, and their Provider Transaction Access Number (PTAN). These numbers enabled us to identify and analyze Medicare claims for We needed these current identifiers to link the providers we surveyed.the providers in our sample to Medicare claims data because our sample was based on the sampling frame of our 2007 report, and Medicare has implemented a new identification system since then. We sought feedback on our survey instrument from both internal and external sources. It was reviewed by internal survey experts and pretested on seven ambulance providers. We also consulted with the American Ambulance Association (AAA), an industry group that represents ambulance providers. On the basis of the feedback we received, we modified the survey instrument as appropriate. We sent our survey by e-mail to 294 eligible ambulance providers on April 12, 2012. We asked providers to complete the survey within 2 weeks of receipt. We later extended this deadline 2 weeks to give providers more time to complete the survey. Providers were encouraged to contact us by e-mail or a toll-free number so that we could resolve any questions or problems. We sent three reminder e-mails to providers that had not yet completed the survey (6, 14, and 21 days after sending the survey to providers) and made two rounds of reminder telephone calls to encourage participation. AAA and the National Association of Emergency Medical Technicians encouraged providers to participate in the survey. When providers returned surveys that were incomplete, invalid, or resulted in conflicting responses to key items, we conducted follow-up by phone and e-mail. We took steps to ensure that the data reported in the survey were valid and reliable. First, we included in the survey instrument questions intended to validate the reported cost data. For example, we asked providers whether certain cost components (such as personnel costs) were included in the total cost amount submitted, and we asked how confident providers were about the total cost amount submitted. As a result, we excluded from our analyses one provider that was not confident in the total cost amount. Second, we conducted analyses to identify any incomplete data or inconsistencies in responses. If we found such data, we contacted the provider to try to obtain complete or corrected data. We excluded three providers that were not able to provide complete data on total cost or total transports. Third, we used a lognormal distribution to exclude outliers with a cost per transport more than three standard deviations from the mean. We excluded three providers with costs per transport that were outliers. All computer programs we used for our analyses were peer reviewed to verify that they were written correctly and executed properly. On the basis of our efforts to validate the data, including computer testing and corrections, we concluded that the data were sufficiently valid and reliable for our purposes. All sample surveys are subject to sampling error—that is, the extent to which the survey results differ from what would have been obtained from the population instead of the sample. The sample is only one of a number of samples that we might have drawn. As a result, we reported the results of our analyses with their 95 percent confidence intervals. The 95 percent confidence interval refers to the range of values within which we would expect the true population value to fall in 95 percent of the samples we could have drawn. We analyzed 2010 Medicare claims data for the survey nonrespondents and compared this information with similar claims data for providers in our sample. Using Medicare claims data for all survey recipients, we were able to test for potential nonresponse bias for the characteristics contained in the claims data. The nonresponse analysis did not find any statistically measurable bias that would affect our analyses of providers’ costs. We used regression analysis to investigate the relationship between providers’ total cost and provider characteristics that may have affected their costs. We opted for a total cost model using a logarithmic functional form because it is well grounded in microeconomic theory. Although we considered using a similar model of the same functional form with cost per transport as the dependent variable, we determined that the parameter estimates of such a model would be similar to the total cost model. Provider characteristics included in our model were: (1) volume of transports, (2) cost of doing business, (3) mix of Medicare transports, (4) intensity of Medicare transports, (5) service area, (6) use of volunteer staff, (7) receipt of government subsidies, and (8) ownership type. We used those results to produce a graph illustrating the relationship between cost per transport and volume of transports. We also used the results of the regression analysis to estimate the effect on providers’ cost per transport of reducing the value of each of two variables that were significant in the regression. See table 5 for the characteristics included in the model, how each characteristic was measured, and the data source for each characteristic. Our regression analysis modeled total cost at the provider level as a function of the provider characteristics described above. We used ordinary least squares to model the log of total costs for a provider.model was specified in log-log form to conform to standard microeconomic theory regarding cost functions. The two continuous independent variables—transport volume and geographic practice cost index (GPCI)—were entered in log form. The remaining variables were not entered in log form because they were either indicator variables (value of 0 or 1) or percentage variables (values ranging from 0 to 1.00). Three of the explanatory variables in the regression were statistically significant at the 1 percent or better level in explaining the variation in providers’ total costs: total transports, percentage of revenues from The government subsidies, and percentage of Medicare transports that were nonemergency. Table 6 shows the regression results. We used the regression results to predict the log of total cost and then converted it to total cost by taking the antilog. We applied an adjustment to the resulting prediction of total cost to account for the fact that our regression was for log total cost rather than total cost. We then divided total cost by total transports to derive cost per transport. We used this method to produce predictions of cost per transport for the range of 1 to 20,000 transports shown in figure 2 of the report. We also used the regression results to estimate the effect on cost per transport of a reduced percentage of revenues from government subsidies and a reduced percentage of nonemergency transports. In each case, we held the other variables in the regression model at their regression sample mean and calculated cost per transport for the sample two ways: one with the value of the variable of interest set at its sample average and another with it set at a value 25 percent less. We reported the difference between these two values for each variable. To examine the relationship between Medicare payments and providers’ costs, we used Medicare claims data to calculate Medicare payments in 2010 for the providers in our sample, and we calculated Medicare margins—the percentage difference between providers’ Medicare payments per transport and their costs per transport. To examine ambulance transports per 1,000 Medicare beneficiaries, we used Medicare claims data and Centers for Medicare & Medicaid Services (CMS) 2010 Medicare enrollment data. We found CMS’s claims and enrollment data to be sufficiently reliable for the purposes of this report. We calculated 2010 Medicare payments for the providers in our sample using Medicare carrier claims data. We identified relevant ambulance claims for 153 providers by using the NPIs (which providers use to bill Medicare) and PTANs reported by providers on the survey. We excluded any Medicare claims without either service-level or mileage payments and any claims with service-level payments that were more than three standard deviations from the mean of the log distribution for all such claims. We also excluded any claims for transports with multiple patients because the calculations for these payments require additional information not available on Medicare claims. See figure 5 for the payment formulas specified in the Medicare ambulance fee schedule. To calculate service-level payments, we used the type of transport identified on the claim to determine the associated relative value unit, which is a constant multiplier that adjusts the service-level base rate to account for the mix and intensity of the service, and we used the 2010 service-level base rate of $209.65. We used the zip code where the transport originated to determine the adjustment from the geographic practice cost index (GPCI), which is used to account for the different costs of operating ambulance services in different regions of the country. In accordance with CMS’s payment methodology, we adjusted 70 percent of the service-level payment by the GPCI, and we did not adjust the other 30 percent by the GPCI. We also used the zip code where the transport originated to determine the applicable urban, rural, or super-rural add-on payment rate. To calculate mileage payments, we used the number of miles reported on the claim and the 2010 mileage base rate of $6.74. We used the zip code where the transport originated to determine the applicability of the permanent mileage increase for miles 1 through 17 for rural and super-rural transports and to determine the applicable urban, rural, or super-rural add-on payment rate. The total fee schedule payment for each transport is the sum of the service-level and mileage payments. We calculated payments with and without the applicable add-on payment rates, and we assumed that providers charged the maximum allowed amount under the ambulance fee schedule.that our payment calculations were comparable to actual payments made based on the claims, we compared the payments we calculated with add- ons to the payment amounts on the claims for a random sample of 6,000 urban, rural, and super-rural claims, and we found the difference in the amounts to be less than 1 percent. All payments are expressed in 2010 dollars. To ensure For the providers in our sample, we reported the median of providers’ Medicare payment per transport by predominant service area (urban, rural, or super-rural) and for all providers. Medicare payment per transport, we divided the sum of the provider’s Medicare payments by the sum of its Medicare transports. To calculate each provider’s Medicare margin, we used the provider’s cost per transport, as calculated from the survey responses, and its Medicare payment per transport, described in the previous section. We subtracted the provider’s cost per transport from its Medicare payment per transport, and we divided this amount by the provider’s Medicare payment per transport. For the providers in our sample, we reported the median Medicare margin and the distribution of providers’ Medicare margins by predominant service area (urban, rural, or super-rural) and for all providers. As we did in the 2007 report, we classified providers as super-rural if 60 percent or more of their Medicare transports in 2010 originated in a super-rural zip code. We classified providers as rural if they did not meet the super-rural definition and 60 percent or more of their Medicare transports in 2010 originated in rural or super-rural zip codes. We classified providers as urban if they did not meet the rural or super-rural classifications. Since some providers furnish transports in more than one area, there is likely to be some measurement error in identifying the full effect of service area on costs. excluded claims with service-level payments outside of three standard deviations from the mean of the log distribution for all such claims for each of these years. We counted Medicare beneficiaries as the number of months beneficiaries were enrolled in Medicare Part A or B in 2010 divided by 12. We then divided the number of transports by the number of enrolled Medicare beneficiaries and multiplied the quotient by 1,000. We also examined the change in transports per 1,000 Medicare beneficiaries from 2004 to 2010. Medicare claims data, which are used by the Medicare program as a record of payments made to health care providers, are closely monitored by both CMS and Medicare Administrative Contractors—contractors that process, review, and pay claims for Medicare Part B–covered services, including ambulance services. The data are subject to various internal controls, including checks and edits performed by the contractors before claims are submitted to CMS for payment approval. Although we did not review these internal controls, we assessed the reliability of Medicare claims data by reviewing related CMS documentation, interviewing agency officials about the data, and comparing payments in a sample of claims to expected payments based on Medicare’s published ambulance fee schedule. We determined that the Medicare claims data were sufficiently reliable for the purposes of this report. In addition, we assessed the reliability of CMS’s enrollment data by reviewing related CMS documentation and comparing the enrollment data to published sources. We determined that Medicare enrollment data were sufficiently reliable for the purposes of this report. In addition to the contact named above, Christine Brudevold, Assistant Director; Ramsey Asaly; Carl S. Barden; Stella Chiang; Carolyn Fitzgerald; Leslie V. Gordon; Corissa Kiyan; Rich Lipinski; Elizabeth T. Morrison; Aubrey Naffis; and Eric Wedum made key contributions to this report. Ambulance Providers: Costs and Expected Medicare Margins Vary Greatly. GAO-07-383. Washington, D.C.: May 23, 2007. Ambulance Services: Medicare Payments Can Be Better Targeted to Trips in Less Densely Populated Areas. GAO-03-986. Washington, D.C.: September 19, 2003.
summary: Since 2004, Congress has authorized supplemental temporary payments, called "add-on" payments, to augment Medicare fee schedule payments to ambulance providers. The add-on payments increased payments for transports in urban, rural, and super-rural (the least densely populated) areas by $175 million in calendar year 2011, according to the Medicare Payment Advisory Commission. In 2007, GAO reported a decline in transports by beneficiaries in super-rural areas and recommended that the Centers for Medicare & Medicaid Services (CMS) monitor beneficiary use of ambulance transports to ensure access to services, particularly in super-rural areas. The Middle Class Tax Relief and Job Creation Act of 2012 required GAO to update the 2007 report. GAO examined, for 2010 (the most recent year complete data were available when GAO began the study), (1) ground ambulance provider costs for transports, (2) the relationship between Medicare payments and provider costs, and (3) beneficiary use of ground ambulance transports. To do this work, GAO sent a survey to a sample of eligible providers based on the 2007 report sample asking for provider costs and characteristics. The sample is representative of all ground ambulance providers that billed Medicare in 2003 and 2010, were operational in 2012, and did not share costs with nonambulance services or air ambulance services. GAO also performed a regression analysis to examine factors that affect costs, analyzed Medicare claims and enrollment data, and interviewed representatives of ambulance provider organizations. CMS reviewed a draft of this report and had no comments. Ground ambulance providers' costs per transport for 2010 varied widely. The median cost per transport for the providers in GAO's sample was $429, ranging from $224 to $2,204 per transport. Provider characteristics that affected cost per transport were volume of transports (including both Medicare and non-Medicare transports), intensity of transports (the proportion of Medicare transports that were nonemergency), and the extent to which providers received government subsidies. Higher volume of transports, higher proportions of nonemergency transports, and lower government subsidies were associated with lower costs per transport. Providers reported that personnel cost was the largest cost component in their 2010 total costs and the biggest contributor to increases in their total costs from 2009 to 2010. The median Medicare margin, including add-on payments, was about +2 percent in 2010 (meaning that providers' Medicare payments per transport exceeded their overall costs per transport) for the providers in GAO's sample, but Medicare margins varied widely for those providers. When GAO removed the add-on payments, payments decreased for the providers in the sample, resulting in a lower median Medicare margin of -1 percent. Due to the wide variability of Medicare margins for providers in the sample, GAO cannot determine whether the median provider among the providers in the population that the sample represents had a negative or positive margin. The median Medicare margin with add-on payments ranged from about -2 percent to +9 percent, while the median Medicare margin without add-on payments ranged from about -8 percent to +5 percent. Ground ambulance transports for all Medicare fee-for-service beneficiaries grew 33 percent from 2004 to 2010. Transports by beneficiaries nationwide grew the most in super-rural areas (41 percent) relative to urban and rural areas. The increase overall is attributable primarily to an increase of 59 percent over this period in basic life support (BLS) nonemergency transports, which include noninvasive interventions, such as administering oxygen. In comparing this growth by service area, BLS nonemergency transports in super-rural areas grew the most--by 82 percent. Representatives from an ambulance provider organization suggested the increase in transports may be from increased billing by local governments. Some local governments that used to provide Medicare transports free of charge may bill Medicare now because of increased budgetary pressures. The Department of Health and Human Services Office of Inspector General has cited improper payments--which can be the result of billing mistakes--as one potential cause for increases in Medicare ambulance utilization and has stated that the Medicare ambulance transport benefit is highly vulnerable to abuse, with some payments for transports not meeting program requirements.