Medicare: Information on Medicare-Dependent Hospitals

The MDH program was enacted in 1989, providing a financial benefit to some small, rural hospitals with high shares of Medicare patients. The original MDH program was established through statute for 3 years, and Congress has extended it on several occasions. The Bipartisan Budget Act of 2018 included a provision to extend the MDH program through 2022, as well as a provision for GAO to review the MDH program.

This report describes, among other things, the changes that occurred in the number of MDHs and selected metrics over time. GAO analyzed data submitted to CMS by hospitals from fiscal years 2011 through 2017—the most recent year for which consistent data were available at the time of GAO's analysis—among other CMS data. GAO also reviewed CMS regulations and other agency documents.

The Department of Health and Human Services provided technical comments on a draft of this report, which GAO incorporated as appropriate.

The Centers for Medicare & Medicaid Services (CMS) operates the Medicare-dependent Hospital (MDH) program, which assists hospitals that have 60 percent or more of inpatient days or discharges from Medicare patients, 100 or fewer beds, and that are generally located in a rural area. MDHs receive an additional payment if their historic costs in one of three base years adjusted for inflation, among other things, are higher than what the hospital would have otherwise received under the inpatient prospective payment system (IPPS). In contrast, if the IPPS amount was higher than historic costs, the MDH would receive no additional payment. In fiscal year 2018, CMS paid approximately $119 million in additional payments to MDHs.

From fiscal years 2011 through 2017, the number of MDHs declined by around 28 percent. (See figure.) In addition, the number of MDHs that received an additional payment declined by around 15 percent.

Over this period of time, MDHs also experienced a 13 percent decrease in the share of their Medicare revenue that came from inpatient services. In addition, there was a decline in the share of total MDH revenue that was attributed to Medicare patients, and a decline in Medicare profit margins by about 6 percentage points.

In the 1980s, the Centers for Medicare & Medicaid Services (CMS)  transitioned from paying hospitals based on their reported costs to  implementing Medicare’s inpatient prospective payment system (IPPS),  which pays hospitals a set amount based on a beneficiary’s diagnosis. In  mandating this transition, Congress’s intent was to control Medicare costs  by giving hospitals financial incentives to deliver services more efficiently  and reduce unnecessary use of inpatient services by paying hospitals a  predetermined amount. However, for some small rural hospitals, the  Medicare payments they received under the IPPS were not sufficient to  cover their reported costs for services provided to Medicare beneficiaries,  resulting in increased financial distress for these hospitals. In response,  Congress created rural payment designations that, among other things,  can provide hospitals with additional payments on top of what CMS pays  through the IPPS. There are currently five Medicare rural payment  designations.

One such designation—the Medicare-dependent hospital (MDH)  program—was created in 1989 as a temporary program providing a  financial benefit for eligible hospitals—in general, small, rural hospitals  with large shares of Medicare patients. Congress has extended the  program on several occasions, most recently through 2022. To be  eligible for the MDH program, hospitals must have at least 60 percent of  inpatient days or discharges involving Medicare patients, have 100 or  fewer beds, and be located in a rural area, though hospitals can also be  eligible if they are located in a state without any rural areas and meet  other specified criteria. Some, though not all, MDHs receive additional  payment above what they are paid under the IPPS. CMS determines the  amount of these additional MDH payments using each hospital’s historical  cost data. In fiscal year 2018, CMS estimated that the MDH program paid  approximately $119 million in additional payments to MDHs.

The Bipartisan Budget Act of 2018 included a provision for us to review  MDH program criteria. This report describes  1.  how the MDH designation differs from the other rural hospital  2.  the extent to which the number of MDHs and other select MDH  metrics have changed over time.

To describe how the MDH designation differs from the other rural hospital  designations, we reviewed CMS documentation, such as CMS  regulations that specify how payments are to be made under the  designations and which hospitals are eligible to receive them. We also  identified the number of rural hospitals that have each designation. To  identify the universe of rural hospitals, we used the CMS IPPS Impact  File. We then used the Provider Specific File (PSF) to identify the  number of hospitals that had each of the five rural payment designations  and, where possible, calculated the median amounts of additional  payment received under each designation using Medicare Cost Reports  (MCR) in fiscal year 2017—the most recent year for which consistent data  were available at the time of our analysis. We also interviewed relevant  CMS officials and representatives from a non-generalizable set of  stakeholder groups, such as groups that represent hospitals, health care  providers, and beneficiaries. Additionally, we interviewed researchers in  the field of rural health policy.

To describe changes in the number and selected metrics of MDHs from  fiscal year 2011 through 2017, we calculated the number of MDHs and  the distribution of additional payments for MDHs in each year using CMS  IPPS Impact Files, PSF, and MCR data. Using these data sources, we  then calculated three standard industry financial and operational metrics  for MDHs as compared to all rural hospitals and all hospitals in  aggregate. The first metric is the median proportion of total Medicare  payments—referred to as revenue—the hospitals received from providing  inpatient and outpatient care to Medicare beneficiaries. The second  metric is hospitals’ profit margins—a profitability measure calculated as  the amount of revenue the hospital received minus reported costs,  divided by the amount of revenue received. We calculated profit margins  specific to Medicare revenue and costs (Medicare profit margins) but also  for revenue and costs beyond Medicare (total facility profit margins),  including payments for treating non-Medicare (including privately insured)  patients. We calculated Medicare and total facility profit margins at the  hospital level using hospital-reported costs and revenues from the MCRs, and reported the median margins for each hospital group. Third, we  calculated hospitals’ degree of Medicare dependence using three  separate definitions, or measures, of dependence: (1) the amount of  revenue the hospital received from Medicare as a share of all the revenue  the hospital received for inpatient and outpatient services (total care  revenue), (2) the share of inpatient days of care the hospital provides that  are attributed to Medicare beneficiaries, and (3) the share of inpatient  discharges that are attributed to Medicare beneficiaries. We separately  analyzed data for MDHs that were eligible for the MDH program based on  data from the 1980s. We identified these MDHs using data from Medicare  Administrative Contractors—third party entities that administer Medicare  program payments.

We also used regression models to estimate the relationship between  MDH program criteria and the three definitions of Medicare dependence  using data from the MCR, PSF, and CMS IPPS Impact Files. We also  separately estimated the relationship between total facility profit margin  (without additional MDH payment) and MDH program criteria. Each model  held certain hospital and market factors constant, including hospital  ownership status, distance to the nearest 100-bed hospital, and  percentage of population 65 and older. We assessed the reliability of  each of the data sets we used for these analyses by interviewing CMS  officials, reviewing related documentation, and performing data checks.  On the basis of these steps, we concluded that the data were sufficiently  reliable for the purposes of our reporting objectives. For more information  on our methodology for the data analysis, see appendix I.

We conducted this performance audit from March 2019 to February 2020  in accordance with generally accepted government auditing standards.  Those standards require that we plan and perform the audit to obtain  sufficient, appropriate evidence to provide a reasonable basis for our  findings and conclusions based on our audit objectives. We believe that  the evidence obtained provides a reasonable basis for our findings and  conclusions based on our audit objectives.

Background Payment for Hospital Services under Medicare

Under traditional Medicare, hospitals are paid for the inpatient and  outpatient services they provide under two distinct payment systems.

Inpatient stays, including services incurred after being admitted to the  hospital, are paid under the IPPS. Under this system, Medicare pays  hospitals a flat fee per beneficiary stay, set in advance, with different  amounts generally based on the beneficiary’s condition. Payment  rates are also influenced by hospital-specific factors such as the  relative hourly wage in the area where the hospital is located, and  whether the hospital qualifies for other case- or hospital-specific  additional payments.

Outpatient services, including services obtained through the  emergency department or other services incurred without being  admitted to the hospital, are paid under the outpatient prospective  payment system. Under this system, Medicare pays hospitals a flat  fee per service, set in advance, with different amounts for each type of  service. As with the IPPS, payment rates are adjusted for geographic  factors.

Congress has established payment adjustments for certain hospitals  under the IPPS by changing the qualifying criteria for IPPS payment  categories, creating and extending exceptions to IPPS rules, or  exempting certain types of hospitals from the IPPS. These adjustments  may help ensure beneficiary access to care or to help hospitals recruit  and retain physicians and other medical professionals.

Created through the Omnibus Budget Reconciliation Act of 1989, the  MDH designation is an example of how Congress can enhance payments  to certain hospitals. To qualify as an MDH, a hospital must demonstrate  that it is:

Medicare-dependent, defined as having at least 60 percent of their  inpatient days or discharges attributable to Medicare beneficiaries;  small, defined as having 100 or fewer beds; and  rural, defined as being located in a rural area, though hospitals can  also be eligible if they are located in a state without any rural areas.

CMS regulations provide that hospitals can meet the requirement of  demonstrating a 60 percent Medicare share of days or discharges using  two of the three most recently settled cost reports, or using cost reports from 1987 or 1988. We refer to hospitals that meet this criterion using  1987 or 1988 cost report data as “legacy MDHs.”

MDH Designation Payment Criteria and Payment Methodology

Some, but not all, MDHs are eligible to receive additional payment each  year if they meet the payment criterion. Specifically, MDHs are assigned  a payment rate—known as the hospital-specific rate (HSR)—based on  their historic reported inpatient operating costs, trended forward to adjust  for inflation and other factors, from one of three years (1982, 1987, or  2002). If the payment based on the HSR is higher than what the MDH  would have otherwise received under IPPS, the MDH receives an  additional payment. In this case, the MDH additional payment is  calculated as 75 percent of the difference between the HSR and the IPPS  amount. If the IPPS amount were higher than the HSR, the MDH would  receive no additional payment. (See fig. 1.)

Hospitals with an MDH designation are also eligible to receive other  benefits. For example, MDHs are eligible for a separate additional  payment if the hospital experiences at least a 5 percent decline in  inpatient volume due to circumstances beyond its control. The MDH  program does not provide for additional payments for outpatient services.

The MDH Program Differs from Other Medicare Rural Hospital Payment Designations in Terms of Eligibility Criteria, Financial Benefit, Legislative Permanence, and Relative Size

In addition to the MDH designation, four other rural hospital designations  exist: (1) critical access hospitals (CAH), (2) sole community hospitals  (SCH), (3) low-volume adjustment hospitals (LVA), and (4) rural referral  centers (RRC). Our review of CMS documentation shows that the MDH  payment designation differs from the other rural payment designations in  terms of eligibility criteria, financial benefit, extent of legislative  permanence, and size—that is, the number of hospitals receiving the  designation. (For detailed information on the five rural payment  designations, see app. II.)

Eligibility Criteria. The MDH designation differs from the other  designations in terms of eligibility criteria. As noted earlier, MDHs must  have at least 60 percent of their inpatient days or discharges attributed to  Medicare patients, must be small and, with few exceptions, rural. In  contrast, both the SCH and CAH designations require hospitals to be  remote rural hospitals (i.e., located a specified distance from the nearest  hospital). Similarly, LVAs are generally required to be more than 15  miles from the nearest hospital. Rural hospital designations also differ in  terms of eligibility criteria related to bed size. CAH-designated hospitals  are required to have 25 inpatient beds or fewer, while MDHs must have  100 beds or fewer. RRCs must have at least 275 beds or meet other  criteria, such as serving a high proportion of remote patients, among  other things.

Financial Benefit. The MDH designation has a relatively small financial  benefit compared to most of the other rural hospital designations, and the  benefit only applies to costs associated with inpatient services. MDHs  generally can only receive 75 percent of the difference between payment  based on their HSR and the payment they would have otherwise received  based on the IPPS rate as an additional payment added to their IPPS rate  payment. In contrast, the SCH and CAH designations have both  inpatient and outpatient payment benefits. Hospitals with an SCH  designation can receive an additional payment added to their IPPS rate  payment equal to 100 percent of the difference between payment based  on the HSR and what the hospital would otherwise receive as payment  based on the IPPS rate, as well as a 7.1 percent addition to their  outpatient payments. The CAH designation results in the highest  financial benefit by generally providing 101 percent of the hospital’s  reported costs in the current year for both inpatient and outpatient  Medicare services. LVAs generally can receive up to 25 percent in  additional payments, and while RRCs receive no direct financial benefit,  they are exempt from certain requirements related to geographic  reclassification (as are SCHs).

Legislative Permanence. Unlike all but one other rural payment  designation, the MDH program is a temporary program and must be  extended periodically by Congress in order to continue. Historically, the  extension by Congress has sometimes occurred after the program has  expired and as a result there were temporary lapses in payments to MDH  designated hospitals. The Bipartisan Budget Act of 2018 included a  provision to extend the MDH program through fiscal year 2022. The only  other designation that must be extended is the LVA designation. In 2010,  the Patient Protection and Affordable Care Act temporarily expanded the  LVA designation eligibility criteria to include hospitals with a higher  volume of discharges and located closer to other hospitals than in  previous years. These expanded eligibility criteria have been amended  and extended through fiscal year 2022. If Congress does not extend the  expanded eligibility criteria beyond fiscal year 2022, the LVA designation  will return to the narrower eligibility criteria that were in place prior to the  Patient Protection and Affordable Care Act.

Relative size and overlap. Of the 2,204 rural hospitals in fiscal year  2017, a relatively small share of these hospitals were MDHs. (See fig.  2.) In total, 138 hospitals, or 6.3 percent of those rural hospitals with at  least one designation, were MDHs. In contrast, CAHs comprised the  largest proportion of rural hospitals with a designation. In fiscal year 2017,  1,246 rural hospitals—or 56.5 percent of those rural hospitals with at least  one designation—were CAHs. Of the five designations, three—CAHs,  MDHs, and SCHs—are exclusive to each other, meaning a hospital can  only have one of the three designations at any time. Hospitals designated  as MDHs and SCHs may also be designated as LVAs, RRCs, or both.  Approximately 75 percent of MDHs and 81 percent of SCHs had at least  one concurrent designation in fiscal year 2017; in contrast, none of the  CAHs received a secondary designation because CAHs are not eligible to  receive other designations. Those MDHs with a concurrent designation  consisted of 88 that had an LVA designation, 14 that had an RRC  designation, and 2 that had both an LVA and RRC designation. (For  detailed information on the 5 rural payment designations including LVA  and RRC eligibility and financial benefit, see app. II.)

The Number of MDHs Declined over Time, As Did the Inpatient Share of Medicare Revenue and Profit Margins

From fiscal years 2011 through 2017, the number of MDHs declined, as  well as the number of MDHs that received an additional payment under  the program. In addition, during this period MDHs varied on other  operational and financial metrics, including the share of Medicare revenue  coming from inpatient care, various measures of Medicare dependence,  and profit margins.

From Fiscal Years 2011 through 2017, the Number of MDHs Declined by 28 Percent, and the Number of MDHs Receiving Additional Payments Decreased by 15 Percent

Our analysis of CMS data shows that the number of MDHs declined from  193 to 138—a 28 percent decrease over the 7-year period from fiscal  year 2011 through fiscal year 2017. (See fig. 3.) This decline can be due  to a number of factors, including hospital closures, mergers, or changes  in designation. For example, we previously reported that 16 MDHs closed  between 2013 and 2017. Moreover, our review of Medicare  Administrative Contractor documentation found that some MDHs became  ineligible for the program due to no longer meeting eligibility criteria. In  addition, the number of MDHs that received an additional annual payment  also declined, from 92 MDHs in fiscal year 2011 to 78 MDHs in fiscal year  2017—a 15 percent decrease.

Among MDHs that received an additional payment, the amount received  and the share of the hospital’s total revenue this payment represented  varied widely across the years, though the average amount generally  increased over time. (See table 1.) For example, in fiscal year 2017, one  hospital received around $1,000 in additional payment while another  received almost $10.5 million. While the trend was not uniform among all  MDHs, the median additional payment increased from about $695,000 in  fiscal year 2011 to about $812,000 in fiscal year 2017.

Our analysis of CMS data also shows that the average additional  payment MDHs received ranged from less than 0.1 percent up to 8.7  percent of total facility revenue, with a fairly consistent average of 1.2 to  1.6 percent. (See table 2.) This underscores that the additional payment  under the MDH program can be small relative to the overall revenue that  the hospital receives.

MDHs Varied over Time on Select Operational and Financial Metrics

Our analysis of CMS data also shows that from fiscal years 2011 through  2017, MDHs varied on selected operational and financial metrics: the mix  of Medicare revenue that came from inpatient versus outpatient care,  various measures of Medicare dependence, and profit margins.

On average, MDHs experienced a decline in the share of Medicare  revenue that came from inpatient services. (See fig. 4.) In fiscal year  2011, around 66 percent of MDH Medicare revenue came from inpatient  services compared to 58 percent in fiscal year 2017—a 13 percent  decrease. This trend was slightly greater than that for all rural hospitals  (an 11 percent decrease) and all hospitals (a 10 percent decrease).

The trends across three measures of Medicare dependence varied for  MDHs over time. Looking at the Medicare share of total revenue for  MDHs, we found this share decreased when comparing fiscal years 2011  and 2017, from 25 to 22 percent. (See fig. 5.)

In contrast, in terms of the number of inpatient days and discharges  attributable to Medicare beneficiaries, we found these measures both  increased slightly over time. Specifically, the median share of MDH  inpatient days attributable to Medicare beneficiaries increased, although  by less than a percentage point, and the median Medicare share of  inpatient discharges increased by about 2 percentage points, when  comparing fiscal years 2011 and 2017. (See figures 6 and 7.)

To obtain additional context on the relationship between MDH eligibility  criteria and the various measures of Medicare dependence, we ran  regression models to identify the extent to which hospitals’ bed size and  rural status were associated with the Medicare share of days, discharges,  and total care revenue for all hospitals from fiscal years 2011 through  2017. We found that rural hospitals with fewer beds were associated with  higher Medicare shares of inpatient days and discharges, holding all other  factors constant.  This indicates that by targeting smaller, rural hospitals  in its eligibility criteria, the MDH program is targeting hospitals that are  Medicare-dependent defined in terms of inpatient volume. At the same  time, rural hospitals with fewer beds generally received a smaller share of  their total care revenue from Medicare compared with other hospitals.  This suggests that hospitals associated with high Medicare inpatient  volume may not have relatively high shares of total care revenue coming  from Medicare. For more technical detail on our regression analyses and  findings, see appendix III.

Our analysis of self-reported data from hospitals shows that Medicare  profit margins and total facility profit margins declined for MDHs from  fiscal year 2011 through 2017. (See table 3.) The degree to which  Medicare margins declined for MDHs during this time period (6  percentage points) was greater than the degree to which they declined for  rural hospitals (4 percentage points) and all hospitals (3 percentage  points). The self-reported data show that unlike rural and all hospitals,  MDHs were not profitable in 2017—meaning that the revenue they  received from Medicare and other payers was less than their reported  costs for providing services. Specifically, the total facility profit margin  turned from positive to negative and dropped almost two percentage  points between fiscal years 2011 and 2017.

We also ran regression models to examine the relationship between all  hospitals’ total profit margins and the various measures of Medicare  dependence. We found that hospitals with a higher Medicare share of  total-care revenue had lower total facility margins on average, holding all  other factors constant; in contrast, there was no significant relationship  between total facility margins and the inpatient volume-based measures  of Medicare dependence.  This indicates that a higher volume of  inpatient services was not associated with lower profitability.

We provided a draft of this report to the Department of Health and Human  Services for comment. The Department of Health and Human Services  provided technical comments, which we incorporated as appropriate.

We are sending copies of this report to the Secretary of the Department  of Health and Human Services. In addition, this 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 farbj@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 key contributions to this report are  listed in appendix IV.

This appendix explains the quantitative scope and methodology used to  examine how the Medicare-dependent hospital (MDH) designation differs  from the other Medicare rural hospital designations. This appendix also  explains the scope and methodology used to describe changes in the  number and selected metrics of MDHs and other hospital types, including  those used for a regression analysis to provide information on the  relationship between MDH program criteria and Medicare dependence.

Differences between MDH and Other Designations

To describe how the MDH designation differs from other rural hospital  designations, we used CMS data—specifically, the Provider Specific File  (PSF)—to identify the number of MDHs, critical access hospitals (CAH),  sole community hospitals (SCH), rural low-volume adjustment hospitals  (LVA), and rural referral centers (RRC) in fiscal year 2017. We then  identified all rural hospitals without a designation in 2017 using the 2018  CMS Inpatient Prospective Payment System (IPPS) Impact File because  those data are prepared in the middle of the year preceding the fiscal  year. We define rural hospitals using the CMS MDH programmatic  definition; that is, those hospitals that are not located in metropolitan  statistical areas, as well as those hospitals that reclassified as rural for  CMS payment purposes. We next identified the number of hospitals with  each designation and the value of additional payments received under the  rural designations that each hospital had in that year using data provided  by each hospital through their Medicare Cost Report (MCR).  The MCR  is submitted to CMS by hospitals each fiscal year and contains  information such as facility characteristics, utilization data, and costs to  provide services to Medicare beneficiaries and all patients. Because  CAHs are paid based on cost under a different payment system than the  other hospitals, we did not have complete data to estimate what those  hospitals would have been paid under the inpatient prospective payment  system and thus could not identify the additional payments received by  CAHs. In addition, RRCs only receive indirect payment benefits, and thus  we could not calculate a comparable additional payment for that group of  hospitals. For all analyses, we excluded hospitals within the Indian Health  Service, as well as hospitals in Maryland and those outside of the  remaining 49 states and the District of Columbia. We also excluded  hospitals with reporting periods greater than 14 months or less than 10  months and those that reported zero or negative Medicare revenue.

To describe changes in the number and select metrics of MDHs and other  hospital types, we examined MCR data for fiscal years 2011 through  2017. To first identify the universe of MDHs, rural hospitals, and all acute  care inpatient prospective payment system (IPPS) hospitals, we used the  PSF and MCR for fiscal years 2011 through 2017, as well as CMS Impact  Files for fiscal years 2012 through 2018. Then, we used the MCR to  calculate the number of MDHs that received the MDH payment  adjustment and the distribution of additional payments among MDHs in  each year. Using those same data sources, we then calculated several  metrics and examined trends for MDHs as compared to all rural hospitals  and all hospitals overall. The first metric is the median proportion of total  Medicare payments—referred to as revenue—each hospital group  received from providing inpatient and outpatient care to Medicare  beneficiaries. The second metric is hospitals’ median profit margins—a  profitability measure calculated as the amount of revenue the hospital  received minus reported costs, divided by the amount of revenue  received. We calculated profit margins specific to Medicare revenue and  costs (Medicare profit margins) but also for revenue and costs beyond  Medicare (total facility profit margins), including payments for treating  non-Medicare (including privately insured) patients. We calculated  Medicare and total facility profit margins at the hospital level using  hospital-reported costs and revenues from the MCRs, and reported the median margins for each hospital group. The Medicare margin reflects  only payments and costs received for inpatient and outpatient services  (about 90 percent of total Medicare revenue, according to CMS officials)  and excludes payments and costs for other hospital-based services, such  as those for skilled nursing and home health care. Third, we calculated  hospitals’ degree of Medicare dependence using three separate  definitions, or measures, of dependence: (1) the amount of revenue the  hospital received from Medicare as a share of all the revenue the hospital  received for inpatient and outpatient services (total care revenue), (2) the  share of inpatient days of care the hospital provides that are attributed to  Medicare beneficiaries, and (3) the share of inpatient discharges that are  attributed to Medicare beneficiaries. We also calculated these metrics  separately for those MDHs that were eligible for the program based on  data from the 1980s—legacy MDHs. To do so, we used data provided by  Medicare Administrative Contractors—third-party entities that administer  Medicare program payments and determine MDH eligibility.

To provide additional context on the relationship between MDH eligibility  criteria and the various definitions of Medicare dependence, we  developed an econometric model to analyze the association between bed  size, rural status, and the three measures of Medicare dependence. We  conducted the regression analysis using data from the CMS IPPS Impact  Files and MCRs from fiscal years 2011 through 2017. We used the  following measures as dependent variables: (1) the amount of revenue  the hospital received from Medicare as a share of all the revenue the  hospital received for inpatient and outpatient services (total care  revenue), (2) the share of inpatient days of care the hospital provides that  are attributed to Medicare beneficiaries, and (3) the share of inpatient  discharges that are attributed to Medicare beneficiaries.

𝑌𝑌𝑖𝑖𝑖𝑖=log (𝑅𝑅𝑖𝑖𝑖𝑖) .

Where 𝑅𝑅𝑖𝑖𝑖𝑖 represents the Medicare share of revenue, inpatient days or  discharges, and the i and t subscripts represent the hospital and year,  respectively. This formulation has the advantage of restricting the models’  predicted values to be positive and also allows for a relatively  straightforward interpretation of the parameter estimates.

We included hospital capacity or size as measured by the number of  hospital beds. The number of beds is itself one of the criteria for MDH  eligibility, and we were interested in whether hospitals of smaller sizes  have more or less Medicare dependency.

We included an indicator variable flagging whether the hospital is in a  rural location. Rural location is one of the criteria for MDH program  eligibility, and so this was a key variable in our model.

We included the ownership category of the hospital, such as whether  a hospital is for-profit or not for-profit, or whether it is a public or  private institution. This organizational category may determine  institutional characteristics, which affects the likelihood that the  hospital serves either more or fewer Medicare beneficiaries.

We included the degree of proximity to other hospitals of substantive  size; specifically, the distance from the closest hospital with at least  100 beds. In addition to our rural indicator variable, this controlled for  whether more remote hospitals are more likely to be more dependent  on Medicare.

We included whether the state in which the hospital is located has  expanded Medicaid to provide coverage to low-income, non-elderly  adults, because it is possible that an increased number of Medicaid- eligible patients may affect the number of Medicare patients using  hospital services. This variable may be associated with less Medicare  dependence if Medicaid becomes a relatively larger payer source, or it  may be associated with more Medicare dependence if Medicaid  eligibility brings Medicare-eligible people into the health care system.

We included the percent of population in the hospital’s county over  age 65, because areas with larger numbers of people over age 65  may be more likely to have a higher proportion of Medicare  beneficiaries using health care services.

We included the percent growth in county population, which allowed  us to control for areas with declining populations that may be more  likely to contain Medicare-dependent hospitals.

Our model included time fixed effects (a dummy variable for each year  in the analysis). The time fixed effects controlled for factors affecting  hospitals nationally in as given year—in particular, those factors for  which data were unavailable.

We included a set of state fixed effects (a dummy variable for each of  the states in the analysis) to control for effects that are common to a  specific area, but for which data may have been unavailable.

We estimated specifications that included interactions between our  bed size categories and rural location. This allowed us to determine  whether bed size had the same impact on Medicare dependence for  hospitals in rural locations compared with those in urban locations.

ln (𝑅𝑅𝑖𝑖𝑖𝑖)=�𝑓𝑓𝑖𝑖𝐹𝐹𝑖𝑖 +𝑋𝑋𝑖𝑖𝑖𝑖𝛽𝛽+𝐶𝐶𝑠𝑠𝑖𝑖𝛾𝛾+𝜀𝜀𝑖𝑖𝑖𝑖,𝑡𝑡=1,…,𝑇𝑇; 𝑖𝑖=1,…,𝐻𝐻.

The dependent variable is the logarithm of our measure of Medicare

𝑋𝑋𝑖𝑖𝑖𝑖 is a 1 x k vector of hospital characteristics and possible 𝛽𝛽 is a k x 1 vector of parameters associated with the hospital interactions of these characteristics, where i denotes the ith hospital ∑ ∑

𝐶𝐶𝑠𝑠𝑖𝑖 is a 1 x m vector of time-varying county-level variables hospital and their associated (lower case) parameters. 𝛾𝛾 is an m x 1 vector of parameters associated with the state-level characteristics such as the percent of the population over 65 and the  dependence, 𝑅𝑅𝑖𝑖𝑖𝑖.  and t denotes the year. 𝑋𝑋𝑖𝑖𝑖𝑖 contains key explanatory variables such as  characteristics, 𝑋𝑋𝑖𝑖𝑖𝑖. ownership type, the number of beds, rural or urban location, whether  𝑇𝑇𝑖𝑖=2a hospital receives MDH program monies and other characteristics.  represents the set of time (year) dummy variables (upper  𝑆𝑆𝑠𝑠=2 represents the set of state dummy variables (upper case) case) and their associated (lower case) parameters.  characteristics such as the percent of the population over 65 and the  county population growth rate.  characteristics, 𝐶𝐶𝑐𝑐𝑖𝑖.

Our model includes an interaction effect between the rural dummy  variable and each of the characteristics except the geographic fixed  effects.  𝜀𝜀𝑖𝑖𝑖𝑖 is a well-behaved Gaussian random error term that may have a  heteroskedastic and/or clustered structure.

We used Stata® to estimate the regression model, using fixed effects  at the state-level to account for unobserved heterogeneity and  clustering at the county-level.

Specification of the Bed Size Categories and Geographic Fixed Effects

Our focus was on the main criteria for MDH eligibility—namely hospital  size as measured by number of beds and rural versus no-rural hospital  location. We divided the hospitals into five bed number categories:

Over 300 beds to 400 beds  This categorization strikes a balance between having too many  categories, which would reduce the statistical power of our analysis, and  having too few categories, which would fail to identify any non-linear  pattern in the statistical relationship. These categories also contain the  100 bed criterion as one of the cut-off points.

Our analysis controls for location and possible heterogeneity by using  geographic fixed effects but we also want to identify the impact of rural  location. Selecting too detailed a level of geographic fixed effect such as  county or zip code would limit our ability to identify the rural effect so we  used states. We recognized that state fixed effects may not identify more  localized effects; this is a limitation of our model.

Total Facility Profit Margins and Measures of Medicare Dependence

We also modeled the effects of hospital characteristics on total facility  profit margins; that is, the difference between revenue and costs as a  percent of revenue. For MDHs in our analysis, we excluded any MDH  additional payment from the margin calculation in order to isolate and  remove the program impact on financial status.

We used the same explanatory factors in our econometric model of  hospital margins as in our models of Medicare dependence but we  supplement these factors with our three measures of Medicare  dependence—a separate model for each measure. This allowed us to  assess how our different measures of Medicare dependence are  associated with financial well-being.

We assessed the reliability of the relevant fields in each of the data sets  we used for these analyses by interviewing CMS officials, reviewing  related documentation, and performing data checks. On the basis of  these steps, we concluded that the data were sufficiently reliable for the  purposes of our reporting objective.

Appendix II: Medicare Rural Hospital Payment Designation Eligibility and Payment

We identified five Medicare rural hospital payment designations and  categorized them into two categories: (1) primary payment designations  and (2) secondary payment designations. Primary designations include  critical access hospitals (CAH), sole community hospitals (SCH), and  Medicare-dependent Hospitals (MDH). Each designation has distinct  eligibility requirements and payment methodologies.

This appendix describes the full results for our modeling of Medicare  dollars as a percentage of total revenue, the percent of inpatient days, the  percent of inpatient discharges, and total hospital profit margins.

Results for Modeling Medicare Revenue as a Share of Total Revenue

We tested for the hypothesis that key groups of parameters were  significantly different between urban and rural locations.

We performed a k-parameter post-estimation Wald linear restriction  where 𝛽𝛽𝑘𝑘𝑢𝑢 and 𝛽𝛽𝑘𝑘𝑟𝑟 are matrices of the estimated urban and rural  parameters, respectively, for each of the k categories (bed-size,  ownership type, etc.). We rejected the null hypothesis of parameter  equality for bed-size, ownership types, Medicaid expansion, and year  dummies at the 5 percent level. The miles distance parameters  rejected the hypothesis at marginally above the 5 percent level.

Rural hospitals generally were associated with larger Medicare shares  of revenue than urban hospitals. In every bed-size category, the  parameters for rural hospitals were significantly greater than for urban  hospitals. In addition, controlling for urban-rural location, with the  exception of the largest hospital category (over 400 beds) hospitals  with fewer beds had a smaller Medicare share of revenue, as shown  in figure 8.

Hospitals in counties with higher percentages of people over age 65  were significantly associated with greater Medicare dependence.

Results for Modeling Medicare as a Share of Total Inpatient Days

Our Wald tests rejected the null that parameters rural and urban were  equal in the bed-number categories and in the ownership categories.

As with the Medicare share of total revenue, our model for Medicare  share of inpatient days showed, controlling for bed numbers, that rural  hospitals generally had significantly greater Medicare dependence  than urban hospitals. In most bed-size categories, the parameters for  rural hospitals were greater than for urban hospitals.

The pattern for bed size was different for Medicare dependence  measured in revenue in that for rural hospitals, dependence fell as  bed numbers rose, but, for urban hospitals, we observed a hump- shape distribution with the middle bed-number categories having  higher dependence than the smallest and largest categories, as  shown in figure 9.

Hospitals located in counties with higher percentages of people over  age 65 had higher dependence.

Results for Modeling Medicare as a Share of Total Inpatient Discharges

Our model for the Medicare share of inpatient discharges showed that,  controlling for bed numbers, rural hospitals generally had greater  Medicare dependence than urban hospitals.

In most bed-size categories, the parameters for rural hospitals were  significantly greater than for urban hospitals. Our Wald tests rejected  the null hypothesis that parameters for rural and urban were equal in  the bed-size categories, Medicaid expansion variables, and in the  ownership categories.

The pattern for bed numbers was also different to Medicare  dependence measured in revenue. The urban hospitals had a hump- shape distribution with the middle bed-number categories having  higher dependence than the smallest and largest categories, whereas  the rural showed largest effects at the smallest and the larger  intermediate categories, as shown in figure 10.

Results for Modeling Hospital Profit Margins

The Medicare share of total revenue was significantly associated with  smaller total facility profit margins and was the only statistically significant  measure of Medicare dependence in the margin models. In general,  hospitals with small numbers of beds—fewer than 100—were associated  with smaller hospital margins relative to our reference category of large  urban hospitals. However, there was no significant difference in any of the  bed-number categories between urban and rural hospitals.

Appendix IV: GAO Contact and Staff Acknowledgments

Jessica Farb, (202) 512-7114 or farbj@gao.gov  In addition to the contact named above, Gregory Giusto (Assistant  Director), Kate Nast Jones (Analyst-in-Charge), Britt Carlson, Rachel  Gringlas, Michael Kendix, Vikki Porter, Caitlin Scoville, Jennifer Rudisill,  and Jeffrey Tamburello made key contributions to this report.

Medicare pays hospitals set amounts based on the diagnoses of the Medicare patients they serve. Small, rural hospitals that meet certain eligibility criteria can qualify for additional payments.

If those hospitals serve a high proportion of Medicare patients, they can apply for the additional payments under the Medicare-dependent hospital program. We found that between 2011 and 2017:

The number of Medicare-dependent hospitals decreased by about 28% because, for example, they became ineligible for the program, merged with other hospitals, or closed.

The typical Medicare-dependent hospital saw profits decrease by almost 2 percentage points.


Federal Contracting: Information on Agencies' Use of the Lowest Price Technically Acceptable Process

When awarding a contract competitively, agencies can evaluate proposals using a best value, LPTA process that assesses which firm offered the lowest priced technically acceptable proposal. Section 813 of the NDAA for Fiscal Year 2017, as amended, included limitations on DOD's use of the LPTA process and required DOD to revise its acquisition regulation to reflect new criteria for use of the LPTA process. Section 880 of the NDAA for Fiscal Year 2019 required the FAR to be updated with similar requirements for civilian agencies.

Sections 813 and 880 also included provisions for GAO to report on the number of instances where the LPTA process was used for contracts exceeding $5 million. This report describes (1) the status of regulatory changes governing the use of the LPTA process; and (2) the extent to which DOD and selected civilian agencies used the LPTA process to competitively award contracts and orders valued over $5 million in fiscal year 2018.

GAO interviewed DOD and civilian agency officials involved in revising the DFARS and the FAR. GAO used data from the Federal Procurement Data System-Next Generation to select the top four DOD components and the top five civilian agencies based on the total number of contracts and orders valued at $5 million or more and competitively awarded in fiscal year 2018. Using this data, GAO developed generalizable samples to estimate these components' and agencies' use of the LPTA process in fiscal year 2018.

Defense and civilian agencies are in the process of revising acquisition regulations to include criteria and limitations for using the lowest price technically acceptable (LPTA) process, as established under the National Defense Authorization Acts (NDAA) for Fiscal Years 2017 and 2019. While the Acts required revised regulations to be in place within 120 days of enactment, officials involved in revising the regulations stated that this process typically takes at least a year. The Department of Defense (DOD) issued a proposed Defense Federal Acquisition Regulation Supplement (DFARS) rule in December 2018 and expects the rule to be finalized by the end of fiscal year 2019. Officials responsible for revising the Federal Acquisition Regulation (FAR) have drafted a proposed FAR rule. The proposed FAR rule is scheduled to be published in the Federal Register in September 2019. See the figure below for the time frames and actions taken to update the DFARS and the FAR.

Based on the results of GAO's generalizable samples, DOD used the LPTA process more frequently than selected civilian agencies in fiscal year 2018 for competitive contracts and orders valued at $5 million or more (see table).

In fiscal year 2018, federal agencies obligated more than $550 billion to  acquire products and services such as military aircraft, information  technology software, and maintenance services. Of this amount, about  $350 billion—or 63 percent—was obligated under competitively awarded  contracts. When awarding a contract competitively, agencies have a  number of source selection processes they can use to evaluate firms’  proposals. One process is a best value, lowest price technically  acceptable (LPTA) process. In the LPTA process, an agency awards the  contract to the firm presenting the lowest evaluated price that is  technically acceptable, and no trade-offs are permitted. Alternatively, an  agency can use a best value trade-off process, in which it can vary the  relative importance of cost or price to other factors such as a firm’s  technical capability or past performance. In these cases, the agency may  award a contract to a firm offering other than the lowest priced proposal if  it determines that this is in the best interest of the government.

Section 813 of the National Defense Authorization Act (NDAA) for Fiscal  Year 2017, as amended, required the Department of Defense (DOD) to  revise the Defense Federal Acquisition Regulation Supplement (DFARS)  to allow the use of the LPTA process only when eight criteria are met.  For example, one criterion is that defense contracting officials must  determine that little or no value would be gained from a proposal  exceeding the solicitation’s minimum technical requirements.  Subsequently, Section 880 of the NDAA for Fiscal Year 2019 required the  Federal Acquisition Regulation (FAR) to be revised to allow civilian  agency use of the LPTA process only when six similar criteria are met.  For the purposes of this report, we refer to Section 813 of the NDAA for  Fiscal Year 2017, as amended, as “the defense provisions” and Section  880 of the NDAA for Fiscal Year 2019 as “the civilian provisions.” Both  provisions also placed limitations on the use of the LPTA process in  procurements for certain categories of products and services, such as  personal protective equipment and information technology services, by  requiring agencies to avoid use of the LPTA process in these  procurements to the maximum extent practicable. The specific criteria  and limitations stemming from these defense and civilian provisions for  using the LPTA process are discussed in the background section of this  report.

Section 813 of the NDAA, as amended, also included a provision that we  report on the number of instances where DOD used the LPTA process for  contracts exceeding $5 million, as well as provide an explanation of how  acquisition officials considered the new criteria in making a determination  to use the LPTA process. We have previously issued two reports in  response to this provision. Subsequently, Section 880 of the NDAA for  fiscal year 2019 included a provision that we report on the number of  instances where civilian agencies used the LPTA process for contracts  exceeding $5 million, as well as provide an explanation of how acquisition  officials considered the six criteria in making a determination to use the  LPTA process. This report, which addresses both provisions, describes  (1) the status of regulatory changes required by the defense and civilian  provisions for using the LPTA process; and (2) the extent to which DOD  and selected civilian agencies used the LPTA process to competitively  award contracts and orders valued at $5 million or more in fiscal year  2018, and what they bought using this process.

To address both objectives and select the DOD components and civilian  agencies included in our scope, we used data from the Federal  Procurement Data System-Next Generation (FPDS-NG) to identify the  DOD components and civilian agencies that awarded the highest number  of contracts and orders in fiscal year 2018 that were reported as  competitively awarded and valued at $5 million or more.

For DOD, we focused our review on the top four DOD components— Army, Navy, Air Force, and Defense Logistics Agency (DLA)—which  accounted for about 5,400—or about 88 percent—of all DOD  contracts and orders valued at $5 million or more that were reported  as competitively awarded in fiscal year 2018.

For civilian agencies, we focused our review on the top five  agencies—the Departments of Veterans Affairs (VA), Health and  Human Services (HHS), Homeland Security (DHS), and Agriculture  (USDA) and the General Services Administration (GSA)—which  accounted for about 3,000—or about 66 percent—of all civilian  agency contracts and orders valued at $5 million or more that were  reported as competitively awarded in fiscal year 2018.

To describe the status of regulatory changes required by the defense and  civilian provisions for using the LPTA process, we obtained information on  agency officials’ efforts to amend the DFARS and the FAR. We also  interviewed officials from DOD and the Office of Federal Procurement  Policy. We analyzed agency guidance and interviewed acquisition and  contracting policy officials at DOD and each of the selected civilian  agencies to determine whether the agencies had existing guidance that  already addressed the defense and civilian provisions, in whole or in part,  and the extent to which they were developing such guidance.

According to officials, DOD and the selected civilian agencies do not  maintain centralized data on whether the LPTA process is used to award  contracts and orders. Consequently, to describe the extent to which the  DOD components and the civilian agencies within our scope used the  LPTA process in fiscal year 2018, we used data from FPDS-NG to select  two generalizable samples of competitively awarded contracts and orders  valued at $5 million or more. For each contract and order in our sample,  we requested that the selected agencies identify whether the LPTA  process was used. We independently verified agency responses by  reviewing the solicitations for each of the contracts and orders within our  two samples. From these samples, we also summarized the products and  services that were purchased using the LPTA process.

We determined that all the data we used were sufficiently reliable for the  purposes of our reporting objectives. For example, we verified FPDS-NG  data on estimated value and competition using agency-provided  documentation for the contracts and orders we reviewed. Appendix I  contains a detailed description of our scope and methodology.

We conducted this performance audit from February 2019 to September  2019 in accordance with generally accepted government auditing  standards. Those standards require that we plan and perform the audit to  obtain sufficient, appropriate evidence to provide a reasonable basis for  our findings and conclusions based on our audit objectives. We believe  that the evidence obtained provides a reasonable basis for our findings  and conclusions based on our audit objectives.

FAR Part 15 describes negotiated contracting, which includes the use of  several competitive source selection processes.  The processes are  associated with the best value continuum, which includes the LPTA  process on one end and the trade-off process on the other (see figure 1).

Federal agencies may elect to use the LPTA process where the  requirement is clearly defined and the risk of unsuccessful contract  performance is minimal. In such cases, agencies can determine that cost  or price should play a dominant role in the source selection. When using  the LPTA process, the agency specifies the evaluation factors that  establish the requirements of acceptability in the solicitation. Firms submit  their proposals and the agency determines which of the proposals meet  those requirements. No trade-offs between cost or price and non-cost  factors (for example, technical capabilities or past performance) are  permitted. Non-cost factors are rated on an acceptable or unacceptable  basis. The award is made based on the lowest priced, technically  acceptable proposal submitted to the government.

In contrast, agencies may elect to use the trade-off process in  acquisitions where the requirement is less definitive, more development  work is required, or the acquisition has a greater performance risk. In  these instances, non-cost factors may play a dominant role in the source  selection process. Trade-offs between price and non-cost factors allow  agencies to accept other than the lowest priced proposal. The FAR  requires the solicitation to state whether all evaluation factors other than  cost or price, when combined, are significantly more important than,  approximately equal to, or significantly less important than cost or price.

Contracting officials have broad discretion in the selection of the  evaluation criteria that will be used in an acquisition. When one is  required, a written acquisition plan generally should include a description  of the acquisition’s source selection process and the relationship of the  evaluation factors to the acquisition objectives. The FAR does not  explicitly require contracting officials to document the reasons why the  specific source selection process was chosen.

The defense and civilian provisions required the DFARS and FAR,  respectively, be revised to require that the LPTA process only be used if  certain criteria are met, as described in table 1.

The defense and civilian provisions also required that the use of the LPTA  process be avoided, to the maximum extent practicable, in procurements  that are predominantly for the products and services identified in table 2.

The process for revising the FAR and DFARS is governed by statute,  which generally requires agencies to issue a proposed rule in the Federal  Register. Agencies are also required to provide at least a 30-day public  comment period following publication of the proposed rule. Figure 2  illustrates the basic process that is generally used to revise the FAR and  the DFARS.

Recent Reports on DOD’s Use of the LPTA Process

We have issued two reports in response to the defense provisions  requiring us to review DOD’s use of the LPTA process. In November  2017, we found that the Army, Navy, and Air Force used the LPTA  process for information technology and other services in 9 out of 133  instances when awarding contracts valued at $10 million or more in the  first half of fiscal year 2017. Contracting officials stated that the LPTA  process was used in these instances, in part, because the requirements  were well-defined, noncomplex, or recurring. We also found that  contracting officials’ use of the LPTA process was generally consistent  with the criteria listed in the defense provisions.

In November 2018, we estimated that about 26 percent of DOD’s  contracts and orders valued at $5 million or more in fiscal year 2017 were  competitively awarded using the LPTA process. We found that DOD  used the LPTA process to buy equipment, fuel, information technology  services, and construction services, among other things. We also found  that contracting officials used the LPTA process for reasons consistent  with the criteria in the defense provisions. Specifically, contracting officials  associated with the 14 contracts and orders we selected used the LPTA  process, in part, because they determined there was no trade-off  available or determined that DOD would not derive any benefit from  paying a premium for offers that exceeded the minimum capabilities.  Finally, we found that some contracting officials were confused about how  to apply two of the criteria included in the defense provisions. Specifically,  contracting officials were confused regarding how to assess life cycle  costs associated with their procurements (shown as criterion 6 in table 1)  or whether the products and services they were acquiring would be  considered expendable in nature (criterion 8). Absent clarification on how  to consider these two criteria, we found there was potential for increased  risk that DOD contracting officials would not consistently apply the criteria  of the defense provisions. Accordingly, we recommended that DOD  address how contracting officials should apply these two criteria when  using the LPTA process. DOD concurred with our recommendations, and  plans to address them by issuing guidance concurrent with publication of  the final rule at the end of fiscal year 2019.

Status of Revisions to Regulations Addressing Use of the LPTA Process

Defense and Civilian Agencies’ Revisions to the DFARS and the FAR

In December 2018, DOD issued a proposed DFARS rule for public  comment to address the defense provisions for using the LPTA process.  The December 2018 proposed rule reflected the criteria and limitations for  using the LPTA process set forth in the defense provisions, and provided  further clarification that these provisions were applicable to both contracts  and orders. The public comment period ended on February 4, 2019,  during which time the Defense Acquisition Regulations Council received  15 comments. In commenting on the proposed rule, industry  representatives generally indicated their support for the proposed rule. On  June 19, 2019, the Council agreed to move forward with the process for  issuing a final rule revising the DFARS. Defense Pricing and Contracting  officials stated that DOD expects to finalize the rule by the end of fiscal  year 2019.

The time required to develop and finalize the revisions to the DFARS has  been longer than provided for under the NDAA for fiscal year 2017, which  required the DFARS be revised within 120 days after enactment, which  would have been in April 2017. In July 2019, we found that it can take a  year or longer to issue a final DFARS rule. For this DFARS case, a  Defense Pricing and Contracting official cited several reasons why the  revisions have been delayed, including the need to address LPTA-related  provisions in two separate NDAAs and the need to resolve a backlog of  DFARS changes.

In addition to ongoing efforts to update DFARS regulations, DOD officials  plan to update the DFARS Procedures, Guidance and Information to  provide defense contracting officers with supplemental guidance on  applying the new criteria for using the LPTA process. A Defense Pricing  and Contracting official stated that this update would be finalized by the  end of fiscal year 2019 to coincide with the issuance of the final DFARS  rule.

The FAR Council has also initiated efforts to incorporate the civilian  provisions for using the LPTA process into the FAR. The NDAA for Fiscal Year 2019 required that the FAR be revised to incorporate the  civilian provisions within 120 days after enactment, which would have  been in December 2018. Officials from the Office of Federal Procurement  Policy told us, however, that it generally takes much longer than 120 days  to revise the FAR. According to an analysis provided by DOD, it takes  483 days on average to issue a FAR rule. The FAR case to implement  the civilian LPTA provisions was initiated in August 2018—the same  month the NDAA for Fiscal Year 2019 was enacted. Office of Federal  Procurement Policy officials stated that a proposed FAR rule is scheduled  to be published in the Federal Register in September 2019. The public  comment period for the proposed rule is scheduled to end in November  2019.

Figure 3 shows when the defense and civilian provisions were enacted,  when the rules were required to be implemented, and some of the efforts  associated with revising both the DFARS and the FAR.

Of the six agencies we reviewed, we found that DOD and DHS had  existing source selection guidance that already reflected some of the  criteria for using the LPTA process identified in the defense and civilian  provisions. The other four civilian agencies did not have source selection  guidance specific to using the LPTA process. Table 3 shows the status of  selected agencies’ existing guidance related to the LPTA process.

DOD’s March 2016 Source Selection Procedures generally includes  five of the eight criteria for using the LPTA process. A Defense Pricing  and Contracting official stated that this guidance could be updated  after the DFARS rule is implemented and the Procedures, Guidance,  and Information resource is updated.

The DHS September 2013 Source Selection Guide generally includes  the first four of the six criteria for using the LPTA process. DHS  officials stated that they plan to update their guidance after the FAR is  amended to reflect the criteria and limitations for using LPTA.

Acquisition policy officials from VA, GSA, USDA, and HHS stated that  they do not have agency-specific guidance for using the LPTA  process beyond what is currently provided for under the FAR. These  officials stated that they were waiting for regulations to be finalized  before determining if there is a need to develop any new guidance.

DOD Used the LPTA Process More Frequently Than Selected Civilian Agencies in Fiscal Year 2018

Based on the results of our generalizable samples, we estimate that the  selected DOD components used the LPTA process for about 25 percent  of competitive contracts and orders valued at $5 million or more in fiscal  year 2018, compared to about 7 percent of such contracts and orders at  selected civilian agencies, as shown in Table 4.

Our findings regarding how often DOD uses the LPTA process are  consistent with what we found in our prior work. In November 2018, for  example, we reported that Army, Navy, Air Force, and DLA awarded  about 26 percent of contracts and orders using the LPTA process in fiscal  year 2017. In November 2017, we reported that officials told us the  LPTA process was used in instances where the requirements were well- defined, noncomplex, or recurring.

This is the first year we were required to evaluate civilian agencies’ use of  the LPTA process. Civilian agency officials we interviewed provided  various perspectives on the extent to which their agency used the LPTA  process.

HHS officials told us that their acquisitions are generally complex, so  the LPTA process is not often deemed the appropriate mechanism for  determining best value.

USDA officials told us that they have few acquisitions valued at more  than $5 million, and that those acquisitions are likely to have more  complex requirements. In such cases, the officials told us, technical  and performance considerations generally would be more important  than price factors. In analyzing FPDS-NG data, we found that 1  percent of USDA’s fiscal year 2018 contracts and orders were valued  at more than $5 million.

GSA officials told us their agency often procures services where it is  beneficial for industry to propose solutions to a stated need, rather  than GSA dictating the solution, such as professional services or  information technology systems for a secure network solution. In  these cases, officials said they would not have the technical  specifications that an LPTA process would require.

Officials from DHS and VA stated that they do not centrally track the  source selection method used and they do not have sufficient  information to say why their agencies use LPTA less frequently than  other source selection methods.

Within the sample of contracts we reviewed, we found DOD and the five  selected civilian agencies bought a variety of products and services using  the LPTA process in fiscal year 2018 (see table 5).

We found that four of these DOD contracts and orders and one civilian  agency order were for services that could be considered within the  categories for which the defense and civilian provisions place limitations  on, but do not prohibit, use of the LPTA process. In November 2018, we  found that DOD contracting officers generally justified the use of the  LPTA process for products and services in these categories. As  described earlier in this report, the DFARS and FAR are in the process of  being revised and do not currently address the limitations on the use of  LPTA for these products and services.

We provided a draft of this report to OFPP, DOD, VA, HHS, GSA, DHS,  and USDA for review and comment. OFPP, DOD, GSA, DHS and HHS  provided technical comments, which we incorporated as appropriate. VA  and USDA told us that they had no comments on the draft report.

We are sending copies of this report to the appropriate congressional  committees, the Director of the Office of Management and Budget, the  Secretary of Defense, the Administrator of General Services, the  Secretary of Veterans Affairs, the Secretary of Homeland Security, the  Secretary of Agriculture, and the Secretary of Health and Human  Services. In addition, the report is available at no charge on the GAO  website at http://www.gao.gov.

If you or your staff have any questions about this report, please contact  me at (202) 512-4841 or dinapolit@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 key contributions to this  report are listed in appendix II.

Appendix I: Objectives, Scope, and Methodology

Section 813 of the National Defense Authorization Act (NDAA) for Fiscal  Year 2017, as amended, included a provision that we report on the  number of instances where Department of Defense (DOD) used the  lowest price technically acceptable (LPTA) process for contracts  exceeding $5 million, as well as provide an explanation of how acquisition  officials considered the new criteria in making a determination to use the  LPTA process. We have previously issued two reports in response to this  provision. Subsequently, Section 880 of the NDAA for Fiscal Year 2019  included a provision that we report on the number of instances where  civilian agencies used the LPTA process for contracts exceeding $5  million, as well as provide an explanation of how acquisition officials  considered the six criteria in making a determination to use the LPTA  process. This report, which addresses both provisions, describes (1) the  status of regulatory changes required by the defense and civilian  provisions for using the LPTA process and (2) the extent to which DOD  and selected civilian agencies used the LPTA process to competitively  award contracts and orders valued at $5 million or more in fiscal year  2018, and what they bought using this process.

To address both objectives and select the DOD components and civilian  agencies included in our scope, we used data from the Federal  Procurement Data System-Next Generation (FPDS-NG) to identify the  population of DOD and civilian agency contracts and orders that were  reported as competitively awarded and valued at $5 million or more in  fiscal year 2018. For DOD, we focused our review on the top four DOD  components—Army, Navy, Air Force, and Defense Logistics Agency  (DLA)—because they accounted for about 5,400—or about 88 percent— of all DOD contracts and orders valued at $5 million or more that were  reported as competitively awarded in fiscal year 2018. Similarly, we  focused our analysis on the top five civilian agencies—the Departments  of Veterans Affairs (VA), Health and Human Services (HHS), Homeland  Security (DHS), and Agriculture (USDA) and the General Services  Administration (GSA)—which accounted for about 3,000—or about 66  percent—of all civilian agency contracts and orders valued at $5 million or  more that were reported as competitively awarded in fiscal year 2018.

To describe the status of regulatory changes governing the use of the  LPTA process, we obtained information on agency officials’ efforts to  amend the Defense Federal Acquisition Regulation Supplement (DFARS)  and the Federal Acquisition Regulation (FAR). To do this, we met with  DOD and Office of Federal Procurement Policy officials responsible for  overseeing the regulatory changes. We also reviewed DOD’s December  2018 proposed rule to revise the DFARS and the 15 public comments  DOD received on the proposed rule. Because revisions to the FAR and  DFARS have not been finalized, regulations do not yet require or provide  guidance to acquisition officials on how to consider the new criteria.  Therefore, we also analyzed agency guidance and interviewed acquisition  and contracting policy officials at DOD and each of the selected civilian  agencies to determine whether agencies had existing guidance that  addressed the defense and civilian provisions, in whole or in part.  Specifically, we reviewed agency-specific source selection guidance from  DOD, DHS, and VA. GSA, USDA, and HHS do not have source selection  guidance that specifically addresses the LPTA process.

According to officials, DOD and the selected civilian agencies do not  maintain centralized data on whether the LPTA process is used to award  contracts and orders. Consequently, to describe the extent to which DOD  and civilian agencies used the LPTA process in competitively awarded  contracts and orders valued at $5 million or more in fiscal year 2018, we  used FPDS-NG to select two generalizable random samples of contracts  and orders to estimate the use of LPTA by the DOD components and the  civilian agencies within our scope. This resulted in samples of 102  contracts and orders for the four selected DOD components and 100 for  the five selected civilian agencies.

We removed five contracts and orders from our DOD sample: two  contracts and one order because they were incorrectly reported by the  agency in FPDS-NG as having been competitively awarded, and two  contracts because they were classified. We removed three contracts and  orders from our civilian agency sample: two orders because they were  incorrectly reported by the agency in FPDS-NG as having been  competitively awarded, and one contract because it was incorrectly  reported as having an estimated value of more than $5 million.

After removing these contracts and orders, our generalizable sample  consisted of 97 DOD contracts and orders and 97 civilian agency  contracts and orders. For each contract and order in our sample, we  requested that the selected agencies identify whether the LPTA process  was used. We independently verified agency responses by reviewing the  solicitations for each of the contracts and orders within our two samples.  We also verified relevant FPDS-NG data on estimated value and  competition using agency-provided documentation for the contracts and  orders we reviewed. Based on this, we determined these data were  sufficiently reliable for us to estimate the percentage of contracts and  orders valued at $5 million or more that the four components within DOD  and the five selected civilian agencies competitively awarded in fiscal  year 2018 using the LPTA process.

We also used FPDS-NG product and service codes to identify whether  the LPTA contracts and orders in our sample could be considered to be  within one of the categories that the defense and civilian provisions direct  agencies to avoid use of the LPTA process to the maximum extent  practicable. The regulatory changes required by the defense and civilian  provisions are not yet in place, and the defense and civilian provisions do  not explicitly prohibit use of the LPTA process to acquire these categories  of products and services. Therefore, we did not evaluate the reasons why  an agency may have used the LPTA process in these instances. The  findings based on our review of the product and services codes for the  LPTA contracts and orders in our sample are not generalizable.

Appendix II: GAO Contact and Staff Acknowledgments

In addition to the contact named above, Justin Jaynes (Assistant  Director), Heather B. Miller (Analyst-in-Charge), Sarah Cantatore,  Matthew T. Crosby, Lorraine Ettaro, Lori Fields, Stephanie Gustafson,  Julia Kennon, Sarah Martin, Alyssa Weir, and Khristi Wilkins made key  contributions to this report.

Federal agencies may award a competitive contract using a “lowest price technically acceptable” process, picking the least expensive offer that meets requirements. However, this process may not be the best choice if requirements are complex, such as for IT services.

DOD used the process more than civilian agencies. Civilian officials told us their acquisitions of $5 million or more are generally too complex for this process.

Congress required agencies to update the rules on using the process: DOD in 2017, and civilian agencies in 2019. They were required to do so in 120 days, but agency officials told us updates usually take a year or more.