Background

Ground ambulance services are provided by a wide range of organizations  that differ in their organizational structure, types of services offered,  staffing, and revenue sources. Local conditions—including whether  providers are affiliated with other organizations; whether their service  areas are predominately urban, rural, or super-rural; and the amount of  community-dedicated revenues—contribute to this diversity.
In addition, communities have few, if any, tools to help them decide the  optimal organizational structure, staffing, or amount of funding for  ambulance services, given local conditions. Although there have been  efforts to establish national performance or quality standards, there is  limited information about how to best evaluate the costs of providing  ambulance services in a community. In recent years, industry associations  and federal agencies have worked to develop a data system and  mechanisms for measuring the performance of emergency medical  services (EMS); however, these tools cannot yet be applied to measure  performance and evaluate the efficiency of ambulance services. The lack  of data and performance standards makes it difficult to assess whether  any given provider is delivering quality care or whether services are being  provided efficiently.
Organizational structures differ in that some ambulance providers are  affiliated with another institution, such as a hospital or fire department,  and in that providers may or may not offer other types of services, such as  hospital services, fire suppression, rescue, or wheelchair transportation.  Providers affiliated with another institution or that offer other types of  services may share resources and operational costs, such as building  space, administrative support, or personnel, with these other entities and  services. About two-fifths of the ambulance industry shared operational  costs with other institutions or services in 2004. Nine percent of the  ambulance industry was affiliated with a hospital, while 37 percent was  affiliated with a fire department and 21 percent was affiliated with another  government agency. Other communities (33 percent of the ambulance  industry in 2004) were served by freestanding, for-profit or not-for-profit  provider organizations.
The types of services offered and the staff employed also vary among  providers. Some providers perform only emergency transports, in  response to a 911 or equivalent call, while other providers offer  nonemergency transports, which are typically transfers from one facility to  another and may be scheduled in advance. In 2004, 45 percent of the  ambulance industry performed only emergency transports; 55 percent  performed emergency and nonemergency transports. Some providers  perform only basic life support (BLS) transports because their staff are  not certified to perform more intensive medical assessments and  interventions, such as advanced life support (ALS) and other more  complex services. In 2004, 9 percent of the ambulance industry specialized  in only ALS and more complex Medicare transports, such as those  requiring one or more ALS services or respiratory care; 14 percent  performed only BLS Medicare transports; and 86 percent provided a mix  of BLS, ALS, and more complex Medicare transports. Fire departments  are more likely to be specialized in ALS and more complex services.  According to the fire departments that responded to our survey,   70 percent of their Medicare transports, on average, required ALS or more  complex services; for other providers ALS and more complex transport  services constituted only 49 percent of their Medicare transports.
Ambulance providers use of a variety of staff to deliver services to their  communities. First, providers and communities determine what  proportion of their staff will be emergency medical technicians (EMT)  trained to perform BLS services, and what proportion will be EMT- intermediates or paramedics, who have training to perform more intensive  ALS interventions. In 2004, 77 percent of providers that completed our  survey reported having at least one staff member trained as a paramedic,  nurse, or physician, but the remaining 23 percent of respondent providers  relied on staff with less training than a paramedic. Other staffing choices  include whether to employ career-oriented paid staff, rely on volunteers,  or use a mix of paid and volunteer staff. Some providers choose to employ  cross-trained staff. In 2004, two-fifths of the ambulance industry relied  substantially on volunteer staff. In addition, providers and communities  make different choices about whether to maintain backup vehicles and  staff or to rely to a greater extent on nearby providers for backup  assistance.
Providers’ service areas can be urban, rural, super-rural, or a mix of areas.  During 2004, CMS defined urban transports as those that originate within  metropolitan statistical areas (MSA) and New England county  metropolitan areas (NECMA), rural transports as those that originate in  rural counties that are outside of MSAs and NECMAs, and super-rural  transports as those that originate in the bottom 25 percent of rural areas as  defined by population density. About half of the ambulance providers  served predominately urban areas, and the other half served  predominately rural and super-rural areas. However, three-fourths of all  Medicare transports originated in urban areas. Therefore, rural and super- rural providers performed fewer transports on average than urban  providers. In addition, rural and super-rural transports were longer than  urban transports, on average, requiring more time and resources per  transport. In 2004, urban Medicare transports averaged 7 miles, while rural  Medicare transports averaged 13 miles and Medicare transports from  super-rural areas averaged 20 miles.
Providers have several potential revenue sources depending on their  communities and their choices about funding ambulance services.
Revenue sources can include community tax support (such as revenue  from local governments); charitable donations; state and federal grants;  subscription programs; and reimbursements from Medicare or Medicaid  patients, and private health insurance companies. Not all providers receive  revenues from all sources, and the mix and amount of revenues available  may vary. For example, 48 percent of the ambulance industry indicated  that a state or local government approves the fees they may choose to  charge. In communities that limit ambulance providers’ fees, providers  may bill Medicare (and other payers) less than the allowed amount and  therefore do not receive the maximum Medicare payment allowed for their  services. In 2004, Medicare payments for ambulance transports accounted  for 31 percent of the providers’ revenues, on average, while Medicare  beneficiaries accounted for about 40 percent of their transports during  that same year. However, the percentage of Medicare revenues among  providers ranged from less than 1 percent to 80 percent. Furthermore,  different communities provide different levels of tax support to address  specific issues, such as ensuring a minimum level of service in remote  areas or being equipped with more sophisticated transport vehicles or  having more highly trained staff.

		Medicare Ambulance National Fee Schedule

The ambulance national fee schedule was part of a series of payment  reforms to make Medicare a more equitable and prudent purchaser of  health care services. Phased in from April 2002 through December 2005,  the national fee schedule standardized payment rates and reduced wide  variations in payments for the same service.
Medicare ambulance payments under the fee schedule have two  components: a base-rate payment and a mileage payment. The base-rate  component of ambulance payments under the fee schedule consists of the  relative value unit (RVU), the conversion factor (CF), and a geographic  adjustment factor. Ambulance RVUs account for the relative resources  needed to provide services during an ambulance transport. The  ambulance CF converts the RVU into a payment expressed in dollars and  is set by CMS annually. Ambulance base-rate payments are also adjusted  by a geographic practice cost index (GPCI), which is intended to account  for regional differences in the cost of providing ambulance services. The  mileage component consists of the number of miles traveled during an  ambulance transport multiplied by the applicable mileage rate. (See fig. 1  for an example of the payment formula.)
The ambulance national fee schedule was phased in from April 2002  through December 2005 by blending new fee schedule payments with  historical payments. During this transition, the national fee schedule  portion constituted a greater share of the total blended ambulance  payment each year until January 2006, when the historical payment  portion of the blend was discontinued. For example, in the latter part of  2002, total ambulance payments were a blend of 20 percent under the  national fee schedule and 80 percent under the historical payment system.  In 2004, the blend was 60 percent national fee schedule and 40 percent  historical payment system. (See fig. 2 for further details on the blending of  historic payments and national fee schedule payments.)

		MMA Temporary Payment Provisions

The MMA introduced several temporary ambulance payment provisions  that were implemented in 2004, the last of which expires at the end of  2009. CMS estimates that these payment adjustments will add $840 million  to Medicare ambulance services over the 5 years they are in effect. The  MMA provisions increased payment rates for urban and rural transports  and for transports 51 miles or greater. The MMA also provided a  significant base rate increase for transports originating in super-rural areas  and provided for a new regional fee schedule based on the nine census  divisions.
The regional fee schedule was designed to ease the transition from the  historical payment system to the national fee schedule. The introduction  of the regional fee schedule overlapped with the phase-in of the national  fee schedule. The regional fee schedule gave temporarily higher  ambulance payments than what would generally be paid under the  national fee schedule to ambulance providers in census divisions that had  historically higher payments. If the regional base-rate payment was  determined to be greater than the national base-rate payment for a  particular region, then the region received the more advantageous blend of  the regional fee schedule base-rate payment and the national fee schedule  base-rate payment. For example, in the second half of 2004 under the  regional fee schedule, affected regions received a blend of 80 percent of  their regional fee schedule base-rate payment and 20 percent of the  national fee schedule base payment rate. This base-rate payment was then  further blended with historical payments as a part of the gradual phase-in  of the ambulance national fee schedule. The regional fee schedule  component of the base rate blend was reduced each year from 2005  through 2007, and expires at the end of 2009. (See fig. 2 for further details  on the blending of historical, national fee schedule, and regional fee  schedule payments.)
In addition to providing for a regional fee schedule, the MMA temporarily  required higher payment rates for super-rural transports. As a result, base  rate payments for transports originating in super-rural areas increased  about 23 percent. The MMA also provided for a 25 percent increase in the  mileage rate for every ambulance mile traveled exceeding 50. Finally, the  MMA required an increase in payment rates for mileage and transports  originating in urban and rural areas by 1 percent and 2 percent,  respectively. (See table 1 for MMA temporary payment provisions and  their expiration dates.)

		Medicare Margins and Costs

A provider’s Medicare margin under a fee schedule generally depends on  whether the provider’s costs of delivering a service are below its Medicare  payments for the service. Under the ambulance national fee schedule,  providers with costs per transport less than the Medicare payment for that  transport are able to retain the difference between the fee schedule  payment and their costs per transport. Likewise, providers with costs per  transport above the national fee schedule payment will lose the difference  between the Medicare payment and their costs per transport. Therefore,  ambulance providers that can control their costs per transport may have  an advantage over those that cannot control their costs per transport.
A 2003 GAO study found that transport costs are likely to be higher in less  densely populated rural areas because rural providers furnish fewer  transports and because fewer transports were linked to higher costs per  transport. As a result, we recommended that CMS adjust payments for  transports in rural counties with particularly low population density to  help ensure Medicare beneficiaries’ access to ambulance services in those  areas. Subsequently, the MMA increased payments for super-rural  transports from July 1, 2004, through December 31, 2009. The report also  found that the majority of ambulance providers’ costs were related to  readiness—the availability of ambulance and crew for immediate  emergency response—and were fixed costs. Fixed costs, such as staff on  call, vehicles, building space, and administration, generally do not increase  as the number of transports increases. Fuel costs and supplies are not  fixed costs because they increase with the number of transports.

	Costs per Transport Were Highly Variable, Reflecting Differences in Certain Provider Characteristics

Costs of ground ambulance transports were highly variable across  providers without shared costs; an average ambulance transport ranged  from a low of $99 to a high of $1,218 during 2004, the year for which we  gathered data. The variability of costs per transport reflected differences  in certain characteristics—volume and mix of transports; service areas  (urban, rural, and super-rural); productivity, which we defined as  transports per staffed hour; and amount of local tax support. As  expected, low volume, a greater percentage of ALS and more complex  transports, and more transports from super-rural areas were key  characteristics that helped explain why some providers without shared  costs had higher costs per transport. Two other provider characteristics— productivity and amount of local tax support—were also associated with  higher costs per transport for providers without shared costs. Other  provider and local area characteristics—such as type of provider, region,  building rent, and price of fuel—did not significantly affect average costs  per transport among providers without shared costs.

		Providers’ Reported Costs per Transport Were Highly Variable

Providers’ average costs for a ground ambulance transport varied from   $99 to $1,218—a range of more than $1,100—across providers without  shared costs in 2004. Figure 3 shows the wide variation in the reported  costs per transport among providers without shared costs. Five percent of  providers without shared costs had average costs per transport that were  less than $152, while 5 percent of providers had average costs per  transport more than $913. From our sample of providers without shared  costs, we estimated the average cost per transport at $415, with a 95  percent confidence interval—the range within which we expect the  population average cost per transport to fall 95 percent of the time—of  $381 to $450. This means that the actual average cost per transport across  ambulance providers in the United States without shared costs was from  $381 to $450 in 2004.
When we categorized providers without shared costs by service area and  compared the average costs per transport across the groups, average cost  per transport among super-rural providers was statistically significantly  different from that of urban providers, but rural providers’ average cost  per transport was not statistically significantly different from that of urban  providers. The average cost per transport for super-rural providers  without shared costs was $538, statistically significantly different from  the $370 average cost per transport for urban providers without shared  costs. The 95 percent confidence interval for average costs per transport  among super-rural providers without shared costs ranged from $448 to  $628 and among urban providers without shared costs ranged from $326 to  $414. The average cost per transport among rural providers without shared  costs was $409 within a confidence interval spanning $354 to $465, an  interval that overlapped with the average costs per transport estimates for  both urban and super-rural providers without shared costs.

		Certain Provider Characteristics Contributed to Differences in Costs per Transport

The variability of costs per transport among providers without shared  costs reflected differences in certain provider characteristics. The  provider characteristics that contributed to significant differences in costs  per transport were volume, mix of transports, service area, productivity,  and amount of local tax support. (See table 2 and app. I for a full  description of our methods.)
Providers without shared costs that had lower transport volumes generally  had higher average costs than providers without shared costs with higher  transport volumes. Our analysis affirms the finding of our prior work, that  volume of transports was the main characteristic affecting providers’ costs  per transport. Because most ambulance costs are fixed, and therefore do  not increase significantly when a provider completes more transports, it is  expected that as the number of transports provided increases, associated  costs per transport will be lower. In 2004, the volume of transports  completed by a provider without shared costs ranged from 21 to more  than 50,000. Estimated average cost per transport is reduced, from $464  for providers without shared costs completing 2,000 or fewer transports a  year to $327 for those completing from 3,001 to 4,000 transports. Although  estimated average cost per transport is slightly higher for 4,001 to 5,000  transports, rising to $330, and again above 6,000 transports, rising to $330,  every other volume category of provider without shared costs had lower  estimated average costs per transport than the lowest volume group of  2,000 transports or less.
Also, as expected, we observed that average costs per transport were  higher for providers without shared costs that also had a greater  percentage of ALS and more complex transports (compared with BLS  transports) and those with a greater percentage of super-rural transports  (compared with urban transports)—two characteristics incorporated into  the national fee schedule to account for the additional costliness  associated with more intensive services and isolated service areas. ALS  and more complex transports completed by providers without shared  costs ranged from 0 to 100 percent of transports provided. We estimated  that providers without shared costs specializing in ALS and more complex  transport services had average costs of $476, which was 32 percent higher  than providers without shared costs specializing in BLS transport services.  We estimated that the average cost of a super-rural transport was $545,  while the average cost of an urban transport was $358. Rural transports  were not significantly higher cost than urban transports.
Two other provider characteristics—productivity and amount of local tax  support—were also associated with higher average costs per transport.  Costs were higher when providers without shared costs had lower  productivity or a lower ratio of transports per staffed hour. The average  level of productivity for providers without shared costs was 0.12, or about  one transport per 8 staffed hours, and had an estimated average cost per  transport of $437. The second highest level of productivity for these  providers was 0.64, or more than five transports per 8 staffed hours, and  had an estimated average cost per transport of $386. The impact of  productivity on average costs may be explained by the fixed costs incurred  in maintaining readiness—having an ambulance and crew available to  respond to emergency calls. Although providers may have discretion about  staffing and the ability to make backup arrangements to substitute for  additional staff, not all providers can increase productivity by increasing  the number of transports they provide or reducing the number of staffed  ambulance hours. For example, providers that operate in small or isolated  communities with one ambulance on call may serve only their own  community’s needs and may not be able to expand their service area or  increase their volume of ambulance transports.
Average costs were also higher for providers without shared costs that  derived a larger percentage of their total revenues from local tax support.  Among providers without shared costs, those with the largest percentage  of revenues from local tax support (81 percent of revenues) had estimated  average costs that were $240, or 61 percent, above those with no local tax  support. Again, this effect was independent of volume and mix of  transports, service area, cost of labor, use of volunteers, productivity, and  other provider and local area characteristics. The relationship between  greater local tax support and higher average costs may be explained as the  income effect: if an organization has more money, it is able to and likely to  spend more. Moreover, if costs increase without resulting in additional  transports, the average cost per transport will increase.
Characteristics that did not significantly contribute to the variability of  average costs per transport among providers without shared costs  included type of provider; a provider’s region, as measured by the nine  census divisions that defined the regional fee schedule; building rent; and  the price of fuel.

	Average Payments under the National Fee Schedule Will Be Greater Than Average Historical Payments, but Providers’ Expected Medicare Margins Will Vary Greatly

Average ambulance national fee schedule payments in 2010 are estimated  to be 3 percent higher overall than payments in 2001, after adjusting for  inflation and assuming that providers bill the maximum amounts allowed.  However, the Medicare margins of providers without shared costs— whether they make a profit or a loss on Medicare transports—will vary  under the national fee schedule. We cannot assess whether providers  without shared costs will break even, lose, or profit on average under the  ambulance national fee schedule in 2010 after all of the MMA temporary  payment provisions have expired, because the 95 percent confidence  interval surrounding the average Medicare margin spans from negative   14 percent to positive 2 percent. However, across all providers without  shared costs, we estimate that 39 to 56 percent will have average Medicare  payments above their average costs per transport under the ambulance  national fee schedule even after all of the MMA provisions expire.

		Average Payments under the National Fee Schedule Will Be Greater Than Average Historical Payments and Will Be Redistributed from Urban Transports to Rural and Super-Rural Transports

Compared with average historical payments in 2001, average payments  under the national fee schedule in 2010 will be 3 percent higher, after  adjusting for inflation and assuming providers will bill the maximum  amount allowed under the national fee schedule. According to our  analysis, urban transports will experience a decrease in payments, on  average, while rural and super-rural transports will receive an increase  that is greater than the overall increase. Average payments for rural and  super-rural transports will increase 20 percent and 15 percent,  respectively, while average payments for urban transports will decline   3 percent compared with average payments prior to the fee schedule. (See  table 3.)

		Expected Medicare Margins Will Vary Greatly

After all of the MMA temporary payment provisions expire, expected  Medicare margins under the national fee schedule will vary greatly among  providers without shared costs. When we compared expected payments  under the national fee schedule in 2010 with providers’ costs per transport,  the resulting Medicare margins ranged from negative 194 percent for one  provider to positive 76 percent for another provider. This wide difference  is related to the great variability in reported costs among providers  without shared costs.
Among providers without shared costs, we estimated that the average  Medicare margin, or the average percentage difference between these  providers’ Medicare payments and their costs, will be about negative   6 percent with a 95 percent confidence interval from negative 14 percent  to positive 2 percent. (See table 4.) This span in the confidence interval  means we cannot assess whether providers without shared costs would  break even, lose, or profit, on average, under the national fee schedule in  2010 after all of the MMA temporary payment provisions have expired.
Similarly, we estimated that the average Medicare margin for urban, rural,  and super-rural providers without shared costs will be negative under the  national fee schedule, but each estimate will fall within a broader  confidence interval range that includes positive Medicare margins. The  estimated Medicare margin for an urban provider without shared costs  will be negative 18 percent to positive 6 percent, while the estimated  Medicare margin for a rural provider without shared costs will be negative  13 percent to positive 12 percent. We estimated that a super-rural provider  without shared costs will have an estimated Medicare margin from  negative 35 percent to positive 2 percent, making it more likely that the  average Medicare margin for any given super-rural provider without  shared costs would be negative rather than positive. However, given the  confidence intervals surrounding the estimated average margin for each  subset of providers without shared costs and the lack of statistical  difference between them, we cannot conclude with certainty that any  subset of providers would have significantly better or worse financial  experience under Medicare’s national fee schedule than another. Rather,  we can conclude only that Medicare margins are likely to vary even among  urban, rural, and super-rural providers without shared costs.
When we assessed the likely experiences of all providers without shared  costs under the national fee schedule after all of the MMA temporary  payment provisions expire, we estimated that 39 to 56 percent of them will  have positive Medicare margins. Among urban and rural providers, 39 to  65 percent and 34 to 64 percent, respectively, will have positive Medicare  margins, according to our estimations. Among super-rural providers,  however, we estimate that 18 to 51 percent will have positive Medicare  margins, while 49 to 82 percent would have zero or negative Medicare  margins. (See fig. 4.) The breadth of these confidence intervals reflects the  variability of providers’ costs in 2004 and expected financial experience  under the national fee schedule after MMA temporary payment provisions  expire.

	MMA Provisions Resulted in Greater Average Payments for Higher-Cost Super- Rural Transports and Adjusted Payments Regionally Where No Significant Cost Differences Were Observed

The MMA temporary payment provisions, which were implemented by  CMS in the second half of 2004, resulted in raised ambulance average  payments overall, particularly for super-rural transports, which we found  typically more costly to provide. Payment adjustments under the MMA’s  regional fee schedule were not justified on the basis of regional cost  differences, as we did not find significant differences in average cost per  transport across regions.

		Payment Increases Were Targeted to Higher-Cost Super-Rural Transports

When we compared ambulance payments in the first half of 2004, prior to  the implementation of the MMA provisions, with ambulance payments in  the second half of 2004, after the temporary payment provisions were  implemented and had their maximum effect, we found that payments, on  average, increased by 5 percent overall. Super-rural transports received  more substantial payment increases than urban or rural transports. (See  table 5.) After MMA temporary payment provisions were implemented,  average payments for urban and rural transports increased by 5 and   3 percent, respectively, while average payments for super-rural transports  rose by 12 percent, compared with average payments before the MMA  provisions were implemented. Increased payments for super-rural  transports under the MMA were in keeping with our finding that super- rural transports were more costly than urban transports, independent of  other characteristics that affected ambulance costs.

		Regional Payment Adjustments Required by the MMA Were Not Justified on the Basis of Regional Cost Differences

Regional payment adjustments under the MMA were not warranted on the  basis of regional cost differences. The MMA required a regional fee  schedule, which resulted in ambulance payments for similar services that  differed based on the region where they were provided. When comparing  average regional payments before the implementation of MMA provisions  to payments after implementation of the MMA, when the regional fee  schedule had its greatest effect, we found that average payments increased  substantially for some regions but not others. (See table 6.) However, we  found no significant differences in costs by region, after controlling for  differences in volume and mix of transports, cost of labor, service area,  and other characteristics that may have affected costs. The regional fee  schedule is due to expire on December 31, 2009.

	Medicare Beneficiaries’ Use of Ambulance Transports Increased from 2001 to 2004, Except in Super-Rural Areas

Nationally, the use of ambulance transports by Medicare beneficiaries  increased by 16 percent, from 2001, the year before the transition to the  national fee schedule began, to 2004, the year we studied. (See table 7.)  Medicare beneficiaries’ use of ambulance transports in urban areas  experienced the greatest growth, 19 percent, while rural areas experienced  a modest increase of 6 percent. However, Medicare transports per 1,000  beneficiaries in super-rural areas decreased by 8 percent. The decrease in  Medicare beneficiaries’ use of ambulance transports in super-rural areas  was driven mostly by a decline in the volume of transports rather than any  significant change in the number of beneficiaries or the demographic  characteristics of beneficiaries residing in super-rural areas. For example,  factors such as age, race, and gender remained stable in the super-rural  Medicare population. Meanwhile, Medicare beneficiaries’ use of  ambulance transports increased in all regions from 2001 to 2004, including  one region that had a decrease in average payments under the MMA  compared with before the implementation of MMA payment provisions.

	Conclusions

The diversity of the ambulance industry is reflected in its range of  organizations, services offered, staffing, revenue sources, and costs per  transport. We found that certain ambulance provider characteristics, such  as volume, mix of transports, service area, productivity, and amount of  local tax support, affected the cost per transport of providers without  shared costs. For some providers and communities, these characteristics  may be self-determined and may reflect those communities’ preferences  for readiness, quality standards, and ambulance services offered. For  example, some communities may prefer to fund the greater costs of  operating at a higher level of readiness or being equipped with more  sophisticated transport vehicles and more highly trained staff. Other  providers and communities have little or no control over the  characteristics that affect providers’ cost per transport. These  communities, particularly more rural areas with low population density,  may be constrained by local conditions, including their financial  resources. Therefore, local conditions and community preferences may  explain some of the predicted variability in the financial experience of  providers without shared costs under the Medicare national fee schedule.
We are unable to discern whether providers without shared costs would  be compensated appropriately under the national fee schedule for two  reasons. First, when providers experience the national fee schedule  payments in 2010 after all of the MMA temporary payment provisions  expire, they may make changes to control or reduce their costs. The cost  data we collected were from 2004 and may not reflect any changes  providers may make to control or reduce their costs in response to the  national fee schedule. Second, we did not assess if Medicare beneficiaries  are receiving quality care that is delivered efficiently. There are no  national performance standards to use as benchmarks for determining  quality and efficiency of services or for assessing whether providers could  increase productivity by increasing the number of transports they provide  or by reducing the number of staffed ambulance hours. However, current  efforts to develop a national data system and indicators for EMS systems  may, in the future, yield useful tools for measuring efficiency and quality of  ambulance services under the Medicare program.
Based on our survey of ambulance costs, we were able to estimate that  some providers without shared costs would have positive Medicare  margins under the national fee schedule after the MMA provisions expire,  while others would have negative Medicare margins. Among super-rural  providers, we estimated that 18 to 51 percent would have positive  Medicare margins. However, 49 to 82 percent would have zero or negative  Medicare margins. Ideally, Medicare payments should be adequate to  ensure beneficiary access to services while using the program’s resources  judiciously. The decline in use of super-rural ground ambulance transports  from 2001 to 2004, a time when payments for super-rural transports were  increased, suggests that Medicare payment levels may not be linked to the  decreased utilization of transports in super-rural areas. However declining  utilization coupled with potentially negative Medicare margins in super- rural areas, which could be exacerbated when the MMA provisions expire,  raise questions as to whether Medicare payments will be adequate to  support beneficiary access in super-rural areas.

	Recommendation for Executive Action

In light of the variability in ambulance providers’ Medicare margins and  the potential for negative margins to have an impact on beneficiary access,  we recommend that the Administrator of CMS monitor utilization of  ambulance transports to ensure that Medicare payments are adequate to  provide for beneficiary access to ambulance services, particularly in  super-rural areas.

	Agency and External Comments and Our Evaluation

We provided a draft of this report to CMS and to five associations that  represent the ambulance industry: the American Ambulance Association,  the National Association of State EMS Officials, the National Ambulance  Coalition, the National Volunteer Fire Council, and the International  Association of Fire Chiefs. CMS’s written comments are reprinted in  appendix II.
CMS stated that, for the most part, the report reinforces its findings. CMS  also stated that it agreed with our recommendation that the agency  monitor utilization of ambulance transports to ensure that Medicare  payments are adequate to provide for beneficiary access to ambulance  services, particularly in super-rural areas. CMS noted that it would  continue to monitor ambulance rates and would make adjustments should  the original assumptions made during the development of the ambulance  fee schedule need to be changed. In addition, CMS also highlighted its  implementation of a refinement in the definition of rural areas that should  enable rural areas within urban areas to receive the benefit of higher rural  payments under the ambulance fee schedule.
CMS noted that we should have discussed in our conclusions the  implications of omitting “shared services” providers from our analysis, as  these providers tend to have higher costs. As we discussed in the report,  ambulance providers that could not separately report the costs of the  ambulance portion of their business were excluded because their cost  data were determined to be unreliable. Consequently, we have no basis or  information to suggest that providers with shared services have higher or  lower costs than other providers.
Ambulance industry associations generally agreed with our findings.  However, the associations raised various concerns regarding our  calculations and assumptions. Two associations questioned the inclusion  in our analysis of ambulance providers that used unpaid staff and  suggested that it might have been more appropriate to focus on providers  who bear the full cost of providing ambulance services. As we note in the  report, use of unpaid staff by ambulance providers is widespread with an  estimated two-fifths of the industry relying substantially on volunteers in  2004. Thus, in order for our analysis to be representative of ambulance  providers, we included those that used volunteer staff. We recognize that  use of volunteer staff affects ambulance providers’ costs and included the  percentage of volunteer hours as a control variable in our cost model.
Two associations were concerned that we did not allow for the effect of  Medicare bad debt in our analysis and may have therefore overestimated  payments. We acknowledge that bad debt will affect the percentage of  costs recoverable for providing ambulance services. However, we  explicitly state that our payment estimates assume providers are paid the  full Medicare payment amounts. It was beyond the scope of our study to  estimate the effect of Medicare bad debt on ambulance payments or to  determine the extent to which payments should be adjusted to reflect bad  debt.
Two associations expressed concern that our analysis showed a 3 percent  increase in payments to ambulance providers with the transition from the  historical payment system to the fully implemented national fee schedule  and thought payments should have been relatively level. We note that our  analysis incorporated increases in mileage rates over time that likely  accounted for some of this increase. In addition, when simulating  payments under the national fee schedule, we assumed that providers  would bill Medicare for all services they were entitled to bill. However, as  we noted in the report, nearly half of the industry indicated that a state or  local government approves the fees they may charge, and some providers  are required to bill Medicare less than the allowed amount and therefore  do not receive the maximum Medicare payment allowed under the fee  schedule. This discrepancy between the state or local allowed amount and  the actual Medicare payment could also account for some of the 3 percent  increase.
CMS and the associations also provided technical comments and  clarifications, which we incorporated as appropriate.
We are sending copies of this report to other interested congressional  committees and the Administrator of CMS. We will also provide copies to  others upon request. The report will also be available at no charge on the  GAO Web site at http://www.gao.gov.
If you or your staff have any questions, please contact me at (202) 512-7119  or kingk@gao.gov. Contact points for our Offices of Congressional  Relations and Public Affairs may be found on the last page of this report.  GAO staff who made major contributions to this report are listed in  appendix III.

Appendix I: Data and Methods

This appendix describes, in detail, the data and methods we used to  respond to our research objectives and evaluate ambulance providers’  costs per transport and Medicare payments under the national ambulance  fee schedule. We conducted a survey of ambulance costs to collect cost  data. We relied on these survey data for much of our analyses of costs and  supplemented our survey results with information from other sources,  including Medicare claims data, as appropriate. We also analyzed Medicare  claims data to determine the effect of the national fee schedule and the  Medicare Prescription Drug, Improvement and Modernization Act of 2003  (MMA) temporary payment provisions on payments, as well as to describe  changes in beneficiaries’ use of ambulance transports over time. We tested  the internal consistency and reliability of the data from our survey and  other non-Medicare data sources and determined that all data sources  were adequate for our purposes. We conducted our work from July 2004  through April 2007 in accordance with generally accepted government  auditing standards.

	National Survey of Ground Ambulance Providers’ Costs

To collect data on ground ambulance providers’ costs, revenues,  transports, and organizational characteristics for their most recently  completed fiscal year, we mailed a survey to a nationally representative  sample of 500 eligible ambulance service providers that billed Medicare in  2003. We used a two-stage sampling process to select a stratified, random  sample of providers. In the first stage, we selected a preliminary sample of  hospital and nonhospital-based providers for screening. In the second  stage, we conducted telephone screening interviews to confirm eligibility  for the study and, for nonhospital-based providers, to identify provider  type. We obtained 321 completed surveys for a response rate of 64 percent.  We excluded two cost outliers. We also excluded from our analysis  providers that reported sharing ambulance costs with other institutions or  other nonambulance services, including, but not limited to, all fire  departments, after preliminary analysis revealed problems with the  reliability of their reported costs. The resulting sample size was 215  providers. The results from our analysis are nationally representative of all  Medicare ambulance providers that can distinguish their costs for  providing ambulance services from the costs of other services they  provide. However, the small sample size and the variability of reported  costs reduce the precision of our estimates.

		Survey Instrument Development

To develop our survey instrument, we reviewed other survey instruments  and analyses of ambulance cost data, consulted with experts in survey  methods and the ambulance industry, and tested our survey instrument.  We reviewed cost data collected in 1999 by Project HOPE Center for  Health Affairs, which was a nonprofit health policy research organization,  during a survey effort sponsored by the American Ambulance Association.  We also reviewed other surveys of emergency medical services, as well as  industry and association guidelines about emergency medical and  ambulance services. In addition to surveying ambulance providers on their  costs and revenues, we included questions to identify organizational and  local area characteristics that might affect ambulance costs, such as the  number of emergency transports and number of volunteer hours.
Industry experts and a survey specialist reviewed and commented on the  draft survey instrument. We conducted a pilot test of the survey with 104  ambulance service providers as well. We redesigned and refined the  instrument based on the experience of the pilot test. Then, to further  refine the wording of our survey questions, we asked four types of  ambulance service organizations and a former volunteer fire chief to  pretest the instrument and point out any issues they noted. These pretests  were conducted mostly by telephone—one pretest was in person.

		Sample Design

We developed separate lists for all hospital-based and nonhospital-based  providers from information maintained by the Centers for Medicare &  Medicaid Services (CMS), the agency that oversees the Medicare program.  Next, we used a two-stage sampling process to select a stratified, random  sample of providers. In the first stage, we sorted each list by census  division and predominant service area (urban, rural, or super-rural), began  sampling the list at a random starting point, and chose providers at regular  intervals from their respective lists. This method of sampling implicitly  included representation across census divisions and service areas. In the  second stage, telephone screening interviews were conducted with each  sampled provider to confirm eligibility for the study and, for nonhospital- based providers, to identify their type—volunteer, fire department,  government, or freestanding. Once a provider’s type was established,  providers were stratified by type and randomly selected to ensure  somewhat equal representation among all provider types. We developed  initial sample rates for each type of provider and adjusted the rates  midway through the screening process. Each provider representative was  told at the close of the telephone screening call whether the provider had  been selected to participate in our survey. Finally, a survey instrument was  mailed to the selected providers.
To identify nonhospital-based ambulance providers that billed Medicare,  we contacted Medicare carriers for a list of ambulance providers and  matched this list to 2003 carrier claims for ambulance services by provider  identification numbers. Our nonhospital-based sample frame included  12,082 unique provider identification numbers. We later learned that a  number of provider identification numbers in the nonhospital-based  sample frame were duplicate entries for ambulance providers that had  more than one Medicare provider identification number for the same  location. We analyzed the extent of duplication in the sample frame and  reduced the estimated population size to 7,968. Although our sample frame  included a substantial number of duplicate entries, there were only 28  duplicates among our first-stage sample of 900 nonhospital-based  providers. The sample weights were adjusted to account for the duplicate  entries in the sample frame.
To identify the total number of hospital-based ambulance providers that  billed Medicare, we matched Medicare’s Provider of Service file with  Medicare Part A inpatient and outpatient claims for ambulance services.  We excluded skilled nursing facilities for a total of 828 hospital-based  ambulance service providers. We then selected a first-stage sample of 150  hospital-based ambulance providers.
To make our survey sample representative of all Medicare ambulance  providers, the population from which the sample was drawn, we  computed a sample weight for each respondent provider. The computation  of the sample weight took into account the type of provider, sample rate,  and the response rate for the type of provider—hospital, volunteer, fire  department, government, or freestanding.

		Survey Administration

We contracted with CODA Inc., an independent survey research firm, to  perform the telephone screening and administer the mailed survey  instrument. The contractor screened the 900 nonhospital-based and 150  hospital-based providers we selected for our first-stage sample, and mailed  the survey instrument to 500 eligible organizations, randomly sampled by  provider type. In order to properly select our sample with even  representation across all types of providers nationally, we designed our  sampling strata using data collected from our pilot test.
CODA Inc., administered the mailed surveys and conducted all follow-up  and data coding in coordination with us. Our survey period began in April  2005 and ran through September 2005. The survey instruments were  mailed using Federal Express and 2-day Priority Mail. Telephone contact  was initiated 3 business days after the instrument was mailed to ascertain  when the respondent could return the completed instrument. Prompting  and follow-up requests for data were conducted by phone and occurred  whenever providers’ returned instruments were incomplete, vague, or  included conflicting responses to key items. In some cases, follow-up  requests involved multiple contacts, faxing survey instruments, and  spending an hour or more on the phone with the respondent. On average,  more than 4 phone calls were made for each respondent with as many as  20 calls made to one respondent.
All requests for data were conducted by CODA Inc. staff following strict  protocols that we developed. Respondents were encouraged to contact  CODA Inc. and GAO via toll-free numbers, so that any questions or  problems could be resolved. All survey data were double-key entered into  an electronic file, and computer programs were checked for keying  discrepancies and data inconsistencies. In all, we received 321 completed  surveys; this represents a response rate of 64 percent.

		Survey Data Validity and Reliability

In addition to the survey administration procedures described above, we  took several measures to ensure that the data reported on the survey were  valid and reliable. First, the survey instrument included items intended to  validate the reported cost data. We also used strict protocols during  follow-up to validate the reported cost data. For example, if respondents  could not provide cost breakdowns by the categories listed in our survey  instrument, a separate phone protocol was used to verify the reported cost  data.
Second, we tested the data for internal consistency and excluded cases  when necessary. Computer analyses were performed to identify and,  where possible, correct any inconsistencies in responses or other errors.  We also excluded 2 providers that appeared to be cost outliers. These  providers had costs per transport that were at least three standard  deviations above the mean of the standard statistical distribution (the  lognormal), and no other variables explained their extraordinary costs.  Through our analyses, we determined that the costs reported by providers  that shared costs with other institutions or offered other services appeared  to be unreliable. We found the costs reported by these “shared costs”  providers to be highly variable, which may reflect inconsistent methods  for separating staff time and other resources across different services.  Therefore, we excluded these providers—including but not limited to all  fire departments—from our analysis. The resulting sample size was 215  providers, representing a population of more than 5,200 providers without  shared costs.
Third, we compared information reported on the survey to information on  Medicare claims submitted by respondents, such as the number of  Medicare transports and percentage of emergency Medicare transports. All  computer syntax was peer reviewed and verified by separate programmers  to ensure that the syntax was written and executed correctly.
We used providers’ total costs and total transports reported on the survey  to compute providers’ average costs per transport. This cost information  and other information about revenues and provider characteristics were  used to model ambulance costs per transport. Although these survey data  were self-reported and had not been audited, based on efforts to validate  the data, computer testing, and corrections and comparisons with  Medicare data, we have concluded that they were sufficiently valid and  reliable for our purposes.

		Interpretation of Confidence Intervals and Analysis of Nonrespondents

All sample surveys are subject to sampling error—that is, the extent to  which the survey results differ from what would have been obtained if we  had collected responses from every ambulance provider in the country.  Because we used a sample, it is only one of a large number of samples that  we might have drawn. As each sample could have provided different  estimates, we express our confidence in the precision of our particular  sample’s results as a 95 percent confidence interval. This is the interval  that would contain the actual value for all providers for 95 percent of the  samples we could have drawn. As a result, we are 95 percent confident  that the reported confidence intervals based on the mailed survey include  the true values for all providers. For this reason, all costs per transport  and provider margins are reported with their confidence intervals.
We also analyzed 2004 Medicare claims data for survey nonrespondents  and compared this information with similar claims information for  providers without shared costs in our sample. Nonrespondents served  predominantly urban areas rather than rural or super-rural areas. On  average, nonrespondents completed about half the number of Medicare  transports in 2004 compared with providers without shared costs.  Nonrespondents also had a higher percentage of basic life support (BLS)  transports, as opposed to advanced life support (ALS) and more complex  transports, and about the same percentage of nonemergency transports  compared with providers without shared costs.
It is unclear whether nonrespondents had higher or lower costs, on  average, than providers without shared costs. In our regression analysis of  the cost information for providers without shared costs, we found that  those with fewer transports per year generally had higher costs per  transport than those with more transports. Providers without shared costs  that served predominately urban areas had lower costs compared with  providers serving super-rural areas. We also found that providers with  higher percentages of BLS transports had lower costs compared to  providers with no BLS transports. Although nonrespondents’  characteristics differed from those of providers without shared costs,  these differences were associated with both higher and lower costs among  providers without shared costs. Therefore, we have no basis for  concluding that nonresponse has biased our cost estimates in any  particular direction.

	Modeling Ambulance Costs per Transport

We analyzed the relationship between providers’ average costs of  ambulance transports and the provider and local area characteristics that  may have affected their average costs. We used regression analysis to  examine the effect of these characteristics on providers’ costs per  transport. We then used the results from this regression analysis to predict  the average costs per transport across all providers without shared costs,  based on five key provider characteristics: (1) total transports per year,   (2) percentage of BLS Medicare transports, (3) percentage of Medicare  transports in rural and super-rural areas, (4) number of ambulance  transports per staffed hour, and (5) amount of revenue derived from local  tax support.
To perform these analyses, we identified measures and data sources for  each of the provider and local area characteristics that we identified as  potentially contributing to differences in costs per transport. A summary  of these characteristics, measures we used to assess their potential  relationship to costs per transport, and data sources used is presented in  table 8.

		Average Cost Regression Analysis—Methods and Results

Our regression analysis modeled the average cost of a transport at the  provider level as a function of the provider and local area characteristics  described above. We modeled the lognormal distribution of average cost  per transport for a provider, which was calculated as the log of total costs  divided by the total number of transports for that provider. We estimated  the model using least squares and applied the appropriate sample  weights. We used the statistical program SUDAAN® in SAS to estimate  this model, which takes account of the sample stratification and weighting  to obtain appropriate parameter estimates and standard errors. We tested  for and found no specification problems in the model resulting from  heteroscedasticity, misspecification, or evidence of a particular  observation having undue influence.
Tables 9 and 10 show the regression results for estimating the  determinants of cost per transport. We ran two sets of average cost  regressions. The first regression results, in table 9, do not include two  provider characteristics, (1) transports per staffed ambulance hour and   (2) community tax support as a percentage of total ambulance provider  revenue, because data on these variables were not available for a number  of providers in our sample. Including these variables as explanatory  independent variables reduces the number of observations in the  regression from 205 to 157. Nevertheless, we wanted to measure the  impact of these policy variables, in addition to maintaining a larger sample  size, in order to have a more precise estimate of the impact of the other  explanatory variables. Therefore, we ran the same regression model with  and without these two explanatory variables.
We estimated the average cost per transport associated with a range of  values for each of five provider characteristics by using our regression  result parameter estimates and fixed values for five provider  characteristics. For each of the five provider characteristics, we assumed  that all providers in the sample had the same value for one provider  characteristic and used the national average value for all other  characteristics. The five provider characteristics of interest were (1) total  transports per year, (2) percentage of BLS Medicare transports,   (3) percentage of Medicare transports in rural and super-rural areas,   (4) number of transports per staffed ambulance hour, and (5) amount of  revenue derived from local tax support. We estimated the cost per  transport associated with two or more values for each of five provider  characteristics. Our estimates are presented in table 2 of this report.
In order to create the estimated costs per transport for one value of a  provider characteristic, we performed the following steps. First, we  modified the data set we used in the regression model by assigning one  fixed value for one provider characteristic, such as the percentage of  super-rural Medicare transports, for all observations in the data set. For  this characteristic, we fixed the percentage of Medicare super-rural  transports to 100 percent and the percentage of Medicare rural transports  to 0 percent for all observations in the data set. Second, we used our  regression result parameter estimates for all the other characteristics in  the regression model and calculated an estimated average cost per  transport for each provider. Third, we computed the mean of these  estimated costs per transport. We report this hypothetical value as the  estimated average cost per transport associated with the fixed value of the  provider characteristic of interest. In the example above, we computed  our estimated average cost per transport of a super-rural Medicare  transport assuming that every provider in the sample provided only super- rural Medicare transports and their other characteristics—volume and mix  of transports, productivity, and amount of local tax support—were the  national average.

	Estimating Average Medicare Ambulance Payments and Use of Transports with Claims Data

To assess the effect of the ambulance national fee schedule on Medicare  payments, we used Medicare claims data to compute average payments in  2001, before the implementation of the fee schedule, and in 2004, 2 years  after the phase-in of the national fee schedule had begun. For all analyses  of Medicare payments, we expressed payments in 2004 dollars. We also  used Medicare claims data and payment formulas as specified in federal  regulations to simulate average payments under the national fee schedule  in 2010, after all the MMA provisions are due to expire on December 31,  2009, but computed these payments in 2004 dollars, the year that best  reflects the cost data collected in our survey. We used the simulated  payments to compute providers’ Medicare margins, a comparison that  assumes that providers’ cost structures under the fee schedule would be  the same as they were in 2004. We also assessed the effect of the MMA  temporary payment provisions on payments in 2004 using Medicare claims  data by examining the change in payments from the first half of the year,  before the MMA changes were implemented, with the second half of the  year, when MMA payment provisions had their maximum effect.
To estimate average Medicare ambulance payments in 2001 and 2004, we  used Medicare Part A and Part B claims data from Medicare’s National  Claims History files. We constructed summary data sets with the number  of ambulance transports, miles, and their Medicare payments, total and  by level of service, at the zip code level for 2001 and 2004 to compare  payments over time. These data sets were classified by three geographic  levels: national; census divisions; and urban, rural, and super-rural areas.
Census divisions were categorized according to the U.S. Census Bureau’s  guidelines. (See table 11 for a listing of census divisions.) CMS designates  urban, rural, and super-rural areas according to population density.

		Medicare Payment Calculations and Simulation

We chose to examine payments in three distinct time periods: 2001, the  first half of 2004, and the second half of 2004. The year before the national  fee schedule was implemented was 2001. The first half of 2004 represented  a period after the implementation of the national fee schedule but before  the introduction of MMA temporary payment changes. It also coincided  with the year for which we have cost data. The second half of 2004  represented a period after the introduction of MMA provisions when the  regional fee schedule had its greatest effect.
In general, average Medicare payments were estimated as the sum of the  average base rate payment—that is, the amount paid for the level of  service—and the average mileage payment. Base rate payments and  mileage payments for each period were computed separately. Average  Medicare payments were calculated nationally; by census division; and by  urban, rural, and super-rural areas. All payments are expressed in 2004  dollars.
For the first half of 2004, the average base rate payment was calculated by  dividing total base rate payments by the total number of transports  provided in the first half of 2004. For 2001 and the second half of 2004, the  average service-level base payment rate was calculated by dividing total  base rate payments for each level of service by the total number of  transports provided at each level of service. Then we computed a  weighted average base rate payment for 2001 and for the second half of  2004 by applying the percentage of transports for each level of service  (also known as the mix of services) for the first half of 2004 to the service- level base payment rates in 2001 and the second half of 2004, respectively.  The 2001 payments were adjusted to 2004 dollars by multiplying weighted  average base rate payment by the ratio of the 2004 Consumer Price Index  for All Urban Consumers (CPI-U) over the 2001 CPI-U.
For simulated 2010 base rate payments, we multiplied the 2004 conversion  factor (CF) and applicable relative value unit (RVU) for each level of  service to compute the service level payments. Then, we computed a  weighted average base rate payment by applying the service mix from the  first half of 2004 to the 2004 service-level payments. The weighted average  base-rate payment was adjusted for regional differences in the cost of  providing ambulance services by the GPCI. In accordance with CMS’s  payment methodology, only 70 percent of the average base rate payment  was adjusted by the GPCI.
Average mileage payments were calculated by multiplying the average  miles per transport in each geographic level from the first half of 2004 by  mileage rates in the other periods. (See tables 12 and 13.) For example,  when estimating average 2001 mileage payments for urban transports, the  2001 mileage rate applicable to urban areas was used, but the average  mile per transport in urban areas for the first half of 2004 was applied. For  simulated payments in 2010, mileage rates from the first half of 2004 were  applied. For average national and census division mileage payments,  weighted mileage rates were applied reflecting the applicable percentage  of urban and rural miles in the first half of 2004. Because the average mile  per transport for super-rural areas was above 17, simulated payments for  super-rural areas were computed using the two rural mileage rates—$8.48  for miles 1 through 17 and $5.65 for miles 18 through 50.

		Analysis of Medicare Margins

We used simulated Medicare payments and costs per transport to compute  Medicare margins under the national fee schedule after MMA temporary  payment provisions are due to expire, to determine how much providers  stood to lose or gain. To do this, we merged the survey results with  providers’ Medicare payment information from 2004. For each provider,  we computed the mix of services and the average miles per transport for  January 2004 through June 2004. This information was used to simulate  each provider’s average Medicare payment under the national fee schedule  in 2010 after all MMA temporary payment provisions are set to expire on  December 31, 2009. We subtracted the provider’s 2004 cost per transport  from the simulated average Medicare payment under the national fee  schedule, and then divided by the simulated average payment to compute  the provider’s Medicare margin.

		Estimating Use of Ambulance Transports by Medicare Beneficiaries

To estimate transports per 1,000 Medicare beneficiaries, we supplemented  our Medicare claims data with CMS enrollment data from 2001 and 2004,  which contained information regarding Medicare beneficiaries. The  numbers of Medicare beneficiaries in 2001 and 2004 were measured as the  number of months beneficiaries were covered by Medicare in each year  divided by 12. A ratio of the number of transports over the number of  Medicare beneficiaries was estimated in each year and multiplied by 1,000.

		Medicare Claims Data Reliability

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 carriers—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 carriers before claims are submitted to  CMS for payment approval. Although we did not review these internal  controls, we found the data to be sufficiently reliable for the purposes of  this report. We also assessed the reliability of CMS’s enrollment data. We  found these data to be sufficiently reliable for the purposes of this report.

Appendix II: Comments from the Centers for Medicare & Medicaid Services

Appendix III: GAO Contact and Staff Acknowledgments

	Acknowledgments

In addition to the contact named above, Christine Brudevold, Assistant  Director; Jennie F. Apter; Carl S. Barden; Stella Chiang; Kevin J. Dietz;  James M. Fields; Leslie V. Gordon; Michael Kendix; and Jessica Cobert  Smith made key contributions to this report.

Related GAO Products

Ambulance Services: Medicare Payments Can Be Better Targeted to  Trips in Less Densely Populated Rural Areas. GAO-03-986. Washington,  D.C.: September 19, 2003.
Ambulance Services: Changes Needed to Improve Medicare Payment  Policies and Coverage Decisions. GAO-02-244T. Washington, D.C.:  November 15, 2001.
Emergency Medical Services: Reported Needs Are Wide-Ranging, With A  Growing Focus on Lack of Data. GAO-02-28. Washington, D.C.:   October 12, 2001.
Rural Ambulances: Medicare Fee Schedule Payments Could Be Better  Targeted. GAO/HEHS-00-115. Washington, D.C.: July 17, 2000.

Summary:
Why GAO Did This Study

In 2002, Medicare implemented a national fee schedule designed to standardize payments for ambulance services. The Medicare Prescription Drug, Improvement and Modernization Act of 2003 (MMA) required GAO to study ambulance service costs. GAO examined providers' costs of ground ambulance transports in 2004 and factors that contributed to cost differences; average Medicare ambulance payments expected under the national fee schedule in 2010 and how those payments will relate to providers' costs per transport; and changes that occurred in Medicare beneficiaries' use of ambulance transports from 2001 to 2004. GAO estimated costs of ambulance transports based on a nationally representative survey of 215 ambulance providers that did not share costs with nonambulance services. Providers that shared costs with other institutions or services and could not report their costs for ambulance services separately, such as fire departments, were excluded because their reported costs appeared unreliable. GAO used its survey, Medicare claims, and other data for its analyses.

What GAO Found

Costs of ground ambulance services were highly variable across providers that did not share costs with nonambulance services in 2004, reflecting differences in certain provider and community characteristics. Costs per transport among these providers varied from $99 per transport to $1,218. Providers without shared costs that had higher costs per transport typically had fewer transports per year, a greater percentage of transports in which more than a basic medical intervention occurred, more transports in super-rural areas (rural counties with lowest population density), lower productivity--measured as number of transports furnished per staffed hour, and a greater percentage of revenues from local tax support. Average payments under the national fee schedule in 2010 are expected to be higher than historical payments, but providers' Medicare margins will vary greatly. GAO could not assess whether, on average, providers without shared costs would break even, lose, or profit under the national fee schedule, because the average Medicare margin for providers without shared costs was estimated to fall from negative 14 percent to positive 2 percent. However, GAO estimated that approximately 39 to 56 percent of providers without shared costs would have average Medicare payments above their average cost per transport under the national fee schedule in 2010. From 2001 to 2004, utilization of ambulance transports per beneficiary increased 16 percent overall. However, use declined by 8 percent in super-rural areas. Declining utilization coupled with potentially negative Medicare margins in super-rural areas, which could be exacerbated when the MMA temporary payment provisions expire, raise questions as to whether Medicare payments will be adequate to support beneficiary access in super-rural areas.