Medicare Fee-For-Service: Modernizing Cost-sharing Design Would Involve Trade-offs, the Results of Which Would Depend on Time Horizon

To address concerns with the current Medicare FFS cost-sharing design, various groups have proposed modernizing the design to make it simpler and include features found in private plans. These proposals have generally included a single deductible, modified cost-sharing requirements (e.g., a uniform coinsurance), and the addition of a cap on beneficiaries' annual cost-sharing responsibilities.

GAO was asked to review how modernized cost-sharing designs would affect beneficiaries' costs over multiple years. This report describes implications of the current cost-sharing design; options for modernizing; and how modernized cost-sharing designs could directly and indirectly affect beneficiaries' costs.

GAO reviewed studies related to modernizing Medicare's cost-sharing design and interviewed authors of those studies and other experts. GAO also used summarized Medicare claims data from 2007 to 2014 (the most recent data available) to develop four illustrative modernized designs, each including a single deductible, uniform coinsurance, and an annual cap while maintaining Medicare program spending similar to the current design. For each design, GAO calculated how beneficiaries' annual cost-sharing responsibilities compared with the current design over a 1-, 4-, and 8-year time horizon.

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

GAO and others have raised concerns about the design of Medicare fee-for-service (FFS) cost-sharing—the portion of costs beneficiaries are responsible for when they receive care. The current cost-sharing design has been largely unchanged since Medicare's enactment in 1965, can be confusing for beneficiaries, and can contribute to overuse of services. Additionally, the design leaves some beneficiaries exposed to catastrophic costs that can exceed tens of thousands of dollars annually. The complexity of the design and lack of an annual cap on cost-sharing responsibilities also increases demand for supplemental insurance, which can cost beneficiaries thousands annually and further contribute to overuse of services.

Modernizing Medicare FFS's cost-sharing design to include features found in private plans could help address these concerns, but would involve design trade-offs. For example, adding an annual cap on cost-sharing responsibilities while maintaining Medicare's aggregate share of costs similar to the current design would involve a trade-off between the level of the cap and other cost-sharing requirements.

In analyzing four illustrative FFS cost-sharing designs, GAO found that the direct effect of modernizing the design on beneficiaries' cost-sharing responsibilities—that is, the effect when holding utilization and enrollment constant—would depend on the specific revisions and the time horizon examined. For example, GAO found that

During year 1, cost-sharing designs that feature relatively low deductibles (costs a beneficiary is responsible for before Medicare starts to pay) and relatively high caps would result in a median annual beneficiary cost-sharing responsibility close to or below that of the current design. In contrast, designs with relatively low caps—and therefore greater beneficiary protection from catastrophic costs—would result in a median annual cost-sharing responsibility above that of the current design.

By the end of 8 years, there would still be differences in the median annual beneficiary cost-sharing responsibility across different designs, but they would become less pronounced.

Modernizing the Medicare FFS cost-sharing design would also affect beneficiaries' costs indirectly through altered incentives. The studies GAO reviewed and experts GAO interviewed identified several types of behavioral responses that would influence the net effect of a modernized design on beneficiaries' out-of-pocket costs, including changes in beneficiaries' demand for and insurers' supply of supplemental insurance; changes in beneficiaries' use of services; changes in Medicare beneficiaries' enrollment in FFS versus Medicare's private plan alternative; and interactions among these and other behavioral responses, including effects on the price of supplemental insurance.

GAO and others have long noted concerns about the design of Medicare  fee-for-service (FFS) cost-sharing—the portion of costs for covered  services that beneficiaries are responsible for when they receive care.  Generally, health care insurers set three types of cost-sharing  parameters: (1) deductibles—costs a beneficiary is responsible for before  the health insurance plan will start to pay any costs; (2) coinsurance or  copayments (per-service payments) once the deductible is met; and (3)  caps—limits on the maximum cost-sharing amount a beneficiary can be  responsible for during a year for covered services. Medicare FFS’s cost- sharing is complicated and not well designed to discourage unnecessary  use of services. For example, Medicare FFS’s cost-sharing design  includes two separate deductibles: a relatively high deductible for hospital  services, which are usually not discretionary and are less likely to be  influenced by cost-sharing requirements, and a relatively low deductible  for outpatient services, which are more often discretionary and likely to be  influenced by cost-sharing requirements. In addition, Medicare FFS lacks  an annual cap, which can leave beneficiaries vulnerable to catastrophic  costs.

To address these concerns, various groups have proposed revising  Medicare FFS’s cost-sharing design, which has been largely unchanged  from when Medicare was enacted in 1965. Specifically, groups have  proposed that Medicare FFS’s cost-sharing design be simplified and  include features found in private plans (including in Medicare Advantage  (MA), the private plan alternative to Medicare FFS), which have evolved  over time to promote prudent use of health care services and protect  beneficiaries from catastrophic care costs. Although the specifics of each  proposal to revise Medicare FFS’s cost-sharing design have varied, the  proposals have generally shared three features. First, they have  proposed establishing a single deductible to replace the current separate  deductibles for hospital and outpatient services. Second, they have  proposed modifying the per-service payments, with some proposals  suggesting moving to a uniform coinsurance that would be the same for  all services and others suggesting variable copayments tied to the clinical  value of the service. Third, they have proposed adding an annual cap.

Modernizing Medicare’s cost-sharing design would have both direct and  indirect effects on beneficiaries’ costs. The direct effect would be how the  revised design would change beneficiaries’ cost-sharing responsibilities  for a given set of services. The indirect effect would be that the altered  incentives under a revised design would trigger behavioral responses,  such as changes in beneficiaries’ utilization of health care services,  enrollment in supplemental insurance to help cover their Medicare cost- sharing responsibilities, or enrollment in Medicare FFS or MA. The  indirect and direct effects together would determine how a modernized  design would affect beneficiaries’ total out-of-pocket costs for covered  services (the amount of cost-sharing paid directly by the beneficiary plus  the premiums (monthly fees) that beneficiaries pay for their Medicare  coverage and other supplemental insurance they may have).

Some studies have examined how modernizing Medicare’s cost-sharing  design would affect beneficiaries financially; however, they have primarily  focused on first-year effects and may have understated the advantages to  beneficiaries of adding an annual cost-sharing cap. Over longer time  horizons, the percentage of beneficiaries who would benefit from a  catastrophic coverage cap in at least 1 year increases. However, as the  time horizon lengthens it becomes more difficult to predict beneficiaries’  behavioral responses and their interactions with any degree of  confidence. Analyzing the direct effect of a modernized cost-sharing  design—the effect on beneficiaries’ cost-sharing responsibilities, holding  utilization and enrollment constant—over multiple years provides a  baseline for understanding how the effect would vary depending on the  parameters of the revised design and the time horizon examined. In turn,  discussing behavioral responses that might be triggered by this direct  effect provides a fuller picture of how a modernized cost-sharing design  might affect beneficiaries’ total out-of-pocket costs.

You requested that we examine the potential annual and multiyear effects  on beneficiaries’ costs if the Medicare FFS cost-sharing design were  modernized to include a single deductible, uniform coinsurance above the  deductible, and an annual cap. This report describes  1.  implications of the current Medicare FFS cost-sharing design and  options for modernizing while maintaining Medicare’s and  beneficiaries’ aggregate share of costs;  2.  how modernized cost-sharing designs could directly affect  beneficiaries’ cost-sharing responsibilities; and  3.  how modernized cost-sharing designs could indirectly affect  beneficiaries’ out-of-pocket costs.

To identify implications of the current cost-sharing design and options for  modernizing, we reviewed relevant studies and analyzed summary  Medicare claims data. In particular, we reviewed studies exploring  implications of the current design and potential options for modernizing,  as well as studies and documentation on cost-sharing design in private  plans, including those in MA. We also analyzed claims data from 2014  (the most recent year of data available at the time we began our study) to  describe beneficiaries’ cost-sharing responsibilities under the current  design. We also used claims data to develop four illustrative options for  modernized cost-sharing designs, each of which included a single  deductible, uniform coinsurance, and an annual cap, while maintaining  Medicare’s aggregate share of costs similar to the current design when  holding health care utilization and beneficiary enrollment constant. To do  so, we first identified the approximately 28 million Medicare FFS  beneficiaries who were continuously enrolled in Medicare FFS from  January 2007 through December 2014 or their death. We then  calculated each beneficiary’s annual cost-sharing responsibilities under  the current design and what they would have been under a revised  design, holding utilization and enrollment constant. To identify the specific  parameters for each illustrative design, we started with one of the four  caps applicable to MA plans in 2014 and a uniform coinsurance of 20  percent (the same level as the coinsurance for most Part B services  under the current design). We then tested different possible levels of the  deductible until we found a level that maintained Medicare program  spending and the split of costs between Medicare and beneficiaries  similar to the current design.

To illustrate how modernized cost-sharing designs could directly affect  beneficiaries’ cost-sharing responsibilities, we used the same cohort of 28  million beneficiaries. First, we calculated the distribution of these  beneficiaries’ 1-year, 4-year, and 8-year annual cost-sharing  responsibilities—including the median and maximum responsibility— under the current cost-sharing design and each of the four illustrative  designs, and compared these distributions. Second, we calculated the  percentage of beneficiaries who would have experienced a change in  their annual cost-sharing responsibilities in specified ranges—including at  least $100 lower or at least $100 higher than their responsibilities under  the current design—and the average change among these groups. We  also calculated how these changes were related to whether a beneficiary  reached the cap at least once. To assess the accuracy of the summary  Medicare claims data, we reviewed related documentation; interviewed  Centers for Medicare & Medicaid Services (CMS) officials knowledgeable  about the data; conducted checks for missing, duplicative, or erroneous  data; and compared our results with published data. Based on these  activities, we determined that the data we used were sufficiently reliable  for the purposes of our reporting objectives.

To identify how modernized cost-sharing designs could indirectly affect  beneficiaries’ out-of-pocket costs, we reviewed relevant studies and  interviewed experts. The experts we interviewed included staff from  CMS’s Office of the Actuary; organizations that conducted studies on  modernizing the Medicare FFS cost-sharing design (the Congressional  Budget Office, Kaiser Family Foundation, and Medicare Payment  Advisory Commission (MedPAC)); and other entities with insight on some  of the potential effects of modernizing the Medicare FFS cost-sharing  design (the American Academy of Actuaries and National Association of  Insurance Commissioners).

We conducted this performance audit from March 2016 to January 2018  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.

In 2016, Medicare spent about $380 billion on health care services for  beneficiaries enrolled in Medicare FFS, which consists of two separate  parts: Medicare Part A, which primarily covers hospital services, and  Medicare Part B, which primarily covers outpatient services. The majority  of the 38 million Medicare FFS beneficiaries were enrolled in both Part A  and Part B, although about 5 million were enrolled in Part A only and 0.3  million were enrolled in Part B only.

The general design of Medicare FFS cost-sharing has been largely  unchanged since Medicare’s enactment in 1965. It includes separate  deductibles for Part A and Part B services, a variety of per-service  copayments and coinsurance after the deductibles are met, and no cap  on beneficiaries’ cost-sharing responsibilities (see table 1).

Supplemental Insurance among Medicare FFS Beneficiaries

The current cost-sharing design leaves beneficiaries exposed to  potentially catastrophic cost-sharing, and in part because of that, in 2015,  81 percent of Medicare FFS beneficiaries obtained supplemental  insurance that covered some or all of their Medicare cost-sharing  responsibilities, often in exchange for an additional premium (see table 2).  For example, in 2015, 31 percent of Medicare FFS beneficiaries  purchased a private Medigap plan, the most common types of which fully  insulated them from Medicare cost-sharing responsibilities in exchange  for an average annual premium of $2,400. Another 20 percent of  Medicare FFS beneficiaries enrolled in Medicaid, which generally covered  most of their Medicare cost-sharing responsibilities; however, these low- income beneficiaries generally only paid a limited or no premium for this  supplemental coverage.

Medicare FFS Cost- sharing Can Be Confusing and Lead to Overuse of Services; Modernizing Could Address Concerns, but Would Involve Trade-offs

The current Medicare FFS cost-sharing design can be confusing,  contribute to beneficiaries’ overuse of services, and leave beneficiaries  exposed to catastrophic costs. Modernizing the design could address  these concerns, but would involve trade-offs. For example, as shown in  four illustrative designs that we evaluated, maintaining Medicare’s share  of costs would involve a trade-off between the level of the cap and the  deductible (or other cost-sharing).

Medicare FFS Cost- sharing Design Can Be Confusing, Contribute to Beneficiaries’ Overuse of Services, and Leave Them Exposed to Catastrophic Costs

As noted by Medicare advocacy groups and others, the current Medicare  FFS cost-sharing design, which includes multiple deductibles, can be  confusing for beneficiaries. In 2014, 16 percent of Medicare FFS  beneficiaries were responsible for at least one Part A deductible for an  episode of inpatient care as well as the annual Part B deductible.  (Medicare FFS beneficiaries may be subject to more than one Part A  deductible during the year, as the Part A deductible applies to each  admission to an inpatient hospital or skilled nursing facility that occurs  more than 60 consecutive days after the prior admission.) The  Congressional Budget Office has cited the separate deductibles as one  way in which Medicare FFS cost-sharing is more complicated than private  plans. In 2016, according to a survey conducted by the Kaiser Family  Foundation, only 1 percent of workers with employer-sponsored  insurance had a separate deductible for inpatient services. Moreover,  inpatient services tend to be nondiscretionary, and one or more  deductibles for those services can create a financial burden for  beneficiaries, while having minimal effect on their use of inpatient  services.

The cost-sharing design also affects beneficiaries’ utilization of services.  For example, as noted by the bipartisan Simpson-Bowles Fiscal  Commission, the lack of a coherent cost-sharing system is a significant  contributor to overuse and misuse of care. This is particularly true for  services such as home health and clinical laboratory services, which  currently have no cost-sharing under Medicare FFS and thus do not  provide beneficiaries an incentive to decline care of negligible value.  Because of these concerns, MedPAC recommended adding a cost- sharing requirement for home health services that were not preceded by  hospitalization or post-acute care, noting that the current lack of cost- sharing has likely contributed to the significant rise in utilization for these  services, which suggests some overuse.

At the same time, the lack of an annual cost-sharing cap prevents  Medicare FFS from fulfilling a key purpose of health insurance: protecting  beneficiaries from catastrophic medical expenses. While most  beneficiaries had cost-sharing responsibilities under $2,000 in 2014, 1  percent—over 300,000 beneficiaries—had responsibilities over $15,000,  including several hundred beneficiaries with responsibilities between  $100,000 and $3 million. (See fig. 1.) Given the risk of catastrophic  medical expenses, a focus group of current and future Medicare  beneficiaries convened by MedPAC indicated that an annual cap is the  cost-sharing design feature they were most interested in seeing added to  the Medicare benefit. Annual caps are a common design feature of  private plans, as most are required to have an annual cap, including  those participating in MA.  Specifically, since 2011, CMS has required  most MA plans to have an annual cap of $6,700 or less and grants them  additional flexibility in their cost-sharing design if they voluntarily set their  cap at or below $3,400. The mandatory and voluntary caps for certain MA plans that provide both in- and out-of-network coverage are the same  ($6,700 and $3,400) for in-network services, and 1.5 times higher  ($10,000 and $5,100) for combined in- and out-of-network services.

In addition to these implications of the cost-sharing design itself, the  American Academy of Actuaries and others have noted that the  complexity and the possibility of unlimited responsibilities increases  demand for supplemental insurance, which can lead to added costs for  beneficiaries and the Medicare program. It is uncommon for beneficiaries  enrolled in private health insurance to have supplemental coverage. By  insulating beneficiaries from some or all cost-sharing responsibilities (and  not just catastrophic costs), supplemental insurance further reduces the  incentives for beneficiaries to evaluate the need for discretionary care. In  part because of these reduced incentives, we previously estimated that  both beneficiaries’ average total out-of-pocket costs and average  Medicare program spending were higher for Medicare FFS beneficiaries  with Medigap than those with FFS only.

Modernizing Medicare FFS Cost-sharing Could Address Concerns, but Would Involve Design Trade-offs

Modernizing Medicare FFS cost-sharing could address these concerns,  but would involve design trade-offs. Specifically, as proposed by various  groups, revising Medicare’s cost-sharing design to include a single  deductible, modified cost-sharing requirements, and an annual cost- sharing cap could address concerns with the current cost-sharing design.  However, there are multiple options for revising within this broad  framework, including two key design trade-offs that would affect the  extent to which a modernized structure would address concerns about the  current design (and possibly also raise new concerns).

One trade-off centers on how to modify the existing complicated set of  cost-sharing requirements for different services. While the reform  proposals have generally suggested moving to a single deductible, they  have varied in how to modify the subsequent per-service payments.  Some proposals have emphasized the value of simplicity and suggested  replacing the complex set of per-service payments above the deductible  with a uniform coinsurance. A uniform coinsurance would simplify the  cost-sharing design, provide beneficiaries insight into the total cost of  each service, and introduce cost-sharing for certain potentially  discretionary services, such as home health services. However, as noted  by the Medicare Payment Advisory Commission and Congressional  Budget Office, uniform coinsurance also has drawbacks, such as a fixed  percentage of an unknown bill being harder for beneficiaries to  understand and predict than copayments. Other proposals have  emphasized the need to set cost-sharing based on the value of services,  and have suggested moving Medicare toward a value-based insurance  design in which per-service cost-sharing would vary based on the clinical  value of the service to an individual beneficiary. While a value-based  design would specifically target cost-sharing to promote prudent use of  health care services, implementing it is challenging in practice and would  be more complicated for beneficiaries to understand and for CMS to  administer, though CMS is testing the feasibility of value-based insurance  design in MA.

A second design trade-off centers on how to set the level of the  deductible and the annual cap. As shown in the four illustrative cost- sharing designs we evaluated, the lower the cap, the higher the  deductible (or other cost-sharing requirements) would need to be to  maintain Medicare’s and beneficiaries’ aggregate share of costs similar to  that of the current design. For example, holding utilization and  enrollment constant, we found that even without any deductible, a uniform  coinsurance of 18 percent (a level below the existing 20 percent  coinsurance for most Part B services) would be sufficient to add a cap  near $10,000 (the mandatory cap for certain MA plans that allow  beneficiaries to see any provider). In contrast, it would take a deductible  near $1,225 (a level similar to the existing Part A deductible for each  inpatient episode) and a uniform coinsurance of 20 percent to establish a  cap of $3,400 (the voluntary cap for most MA plans). (See table 3.)

Different levels of the deductible and cap would address certain concerns  of the current design raised by GAO and others but also could create new  ones. For example, as our analysis of four illustrative cost-sharing  designs shows, designs with relatively high caps would provide some  additional protection from catastrophic costs while maintaining a  deductible and coinsurance near or below the current levels for Part B  services. However, per an analysis conducted by Kaiser Family  Foundation and the Urban Institute, half of Medicare beneficiaries in 2016  were living on less than $26,200 in income; thus, caps of $6,700 or  higher may still leave some beneficiaries vulnerable to costs that are  catastrophic for them and may not significantly decrease the associated  demand for supplemental insurance. In contrast, designs with relatively  low caps would provide greater protection from catastrophic costs.  However, as noted by the Congressional Budget Office, beneficiaries who  reached the cap would have less incentive to use services prudently. In  addition, the higher deductible needed to offset a lower cap while  maintaining Medicare’s share of costs could present a financial barrier for  some beneficiaries to obtain necessary care.

Direct Effect of Modernizing Medicare FFS Cost- sharing Design Would Depend on Specific Revisions and Time Horizon

The direct effect of modernizing the Medicare FFS cost-sharing design  (i.e., the effect when holding utilization and enrollment constant) on  beneficiaries’ cost-sharing responsibilities would depend on the specific  revisions and the time horizon examined. As we noted above,  modernizing the FFS cost-sharing design while maintaining Medicare’s  aggregate share of costs similar to the current design requires a trade-off  between the level of the deductible and cap. At the beneficiary level, this  design trade-off affects beneficiaries’ annual cost-sharing and the degree  to which beneficiaries would be protected from catastrophic costs. One  way of viewing how the design trade-off affects beneficiaries is to  compare across different designs the median annual cost-sharing  responsibility with the level of the cap (see fig. 2). In examining the direct  effect of the four illustrative modernized designs we analyzed, we found  the following:

During year 1, cost-sharing designs that feature relatively low  deductibles and relatively high caps would result in a median annual  beneficiary cost-sharing responsibility close to or below that of the  current design. In contrast, designs with relatively low caps—and  therefore greater beneficiary protection from catastrophic costs— would result in a median annual beneficiary cost-sharing responsibility  above that of the current design. For example, during year 1 of a  design with no deductible, 18 percent coinsurance, and a cap near  $10,000, we found that the median annual cost-sharing responsibility  would be $479, which is below that of the current design ($621),  despite the addition of a cap. In contrast, during year 1 of a design  with a $1,225 deductible, 20 percent coinsurance, and a cap near  $3,400, the median annual cost-sharing responsibility would be  $1,486, which is 2.4 times higher than that of the current design.  However, in exchange for this higher median annual cost-sharing  responsibility, beneficiaries would have much greater protection from  catastrophic costs, as their annual cost-sharing responsibilities would  be capped near $3,400.

By the end of 8 years, there would still be differences in the median  annual beneficiary cost-sharing responsibility across different designs,  but they would become less pronounced—despite the significantly  different levels of catastrophic protection. As beneficiaries age and  become more likely to have catastrophic costs in at least one year,  the median annual cost-sharing responsibility would increase,  regardless of the cost-sharing design. However, by the end of 8 years  the differences in the median annual cost-sharing responsibility  across different designs would become less pronounced. For  example, the median annual cost-sharing responsibility under the  design with a cap near $10,000 would increase from below that of the  current design in year 1 to 1.1 times higher than the current design by  the end of 8 years. In contrast, the median annual cost-sharing  responsibility under the design with the cap near $3,400 would  decrease from 2.4 times higher than the current design in year 1 to  only 1.6 times higher by the end of 8 years. (See app. I table 4 for  more details, including results on our other two illustrative designs and  results over 4 years.)

The same patterns held when looking at how the design trade-off affects  beneficiaries in another way: the percentage of beneficiaries with cost- sharing responsibilities lower and higher than under the current design  (see fig. 3). In examining the direct effect of our four illustrative designs,  we found the following:

During year 1, designs that feature relatively low deductibles and  relatively high caps would result in a minority of beneficiaries having  cost-sharing responsibilities that are at least $100 higher than under  the current design. In contrast, designs with relatively high deductibles  and relatively low caps would result in the majority of beneficiaries  having cost-sharing responsibilities that are higher than under the  current design. For example, during year 1 of a design with no  deductible, 18 percent coinsurance, and a cap near $10,000, 16  percent of beneficiaries would have cost-sharing responsibilities at  least $100 higher than their responsibilities under the current design.  In contrast, during year 1 of a design with a $1,225 deductible, 20  percent coinsurance, and a cap near $3,400, 69 percent of  beneficiaries would have cost-sharing responsibilities at least $100  higher than their responsibilities under the current design.

By the end of 8 years, there would still be differences across the  designs, but they would become less pronounced—despite levels of  catastrophic protection that vary significantly. Over a longer time  horizon, a larger percentage of beneficiaries would reach the cap at  least once, regardless of the cost-sharing design (ranging from 23  percent reaching the cap at least once over 8 years under the design  with a cap near $10,000 to 66 percent under the design with a cap  near $3,400). However, the subset of these beneficiaries who  nonetheless had annual cost-sharing responsibilities at least $100  higher would also increase. Whether this increase would be  augmented or offset by the changes over time in the percentage of  beneficiaries who never reached the cap and had higher cost-sharing  responsibilities would depend on the specific design. For example, the  percentage of beneficiaries with annual cost-sharing responsibilities at  least $100 higher than the current design would increase from 16  percent in year 1 to 38 percent by year 8 under the design with a cap  near $10,000. In contrast, this percentage would decrease from 69  percent in year 1 to 67 percent by year 8 under the design with a cap  near $3,400. (See app. I tables 5 and 6 for more details, including  results on our other two illustrative designs and results over 4 years.)

Modernizing Medicare Cost- sharing Design Would Affect Costs Indirectly through Behavioral Responses

Modernizing the Medicare FFS cost-sharing design would affect  beneficiaries’ costs indirectly through beneficiaries’ and supplemental  insurers’ behavioral responses to altered incentives, according to the  studies we reviewed and the experts we spoke to. These studies and  experts identified several types of behavioral responses that would  influence the net effect of a modernized design on beneficiaries’ out-of- pocket costs, including  changes in beneficiaries’ demand for, and insurers’ supply of,  supplemental insurance;  changes in beneficiaries’ utilization of services;  changes in Medicare beneficiaries’ enrollment in FFS versus MA; and  interactions among these and other behavioral responses, including  effects on the price of supplemental insurance.

According to studies we reviewed and experts we spoke to, implementing  a modernized cost-sharing design would likely trigger changes in the  demand for and supply of supplemental insurance. For example, a focus  group of current and future Medicare beneficiaries convened by MedPAC  and a report from the American Academy of Actuaries stated that the  addition of an annual cap would reduce the need of some beneficiaries to  purchase supplemental insurance. While beneficiaries who drop their  supplemental insurance would then need to pay all their Medicare cost- sharing responsibilities, those might be less than their annual premium for  supplemental insurance. Additionally, according to the same MedPAC  study and a Congressional Budget Office report, retiree coverage may change under a modernized design. For example, with a cap in place,  there would be less difference between employer-sponsored plans and  Medicare, and employers may choose to alter the supplemental  insurance they offer. CMS officials told us that this would continue the  trend of private employers reducing retiree health coverage.

Several studies we reviewed and experts we interviewed indicated that  implementing a modernized design could also trigger changes in  utilization of Medicare services, the extent of which would affect  beneficiaries’ out-of-pocket costs. For example, the RAND Health  Insurance Experiment (HIE), which some experts consider to be the most  comprehensive study on price and utilization, found that patients were  “moderately sensitive to price.” The RAND HIE found that patients  respond to increases in cost-sharing that they need to pay at least partly  out-of-pocket by decreasing their use of some services.  Similarly, CMS  officials told us that they would expect utilization to decrease as  beneficiaries’ out-of-pocket costs increased, while a study in the  American Economic Review found that the addition of a copayment led to  a decline in office visits. The RAND HIE study suggests that a 10  percent increase in cost-sharing would lead to a 1 to 2 percent decline in  patients’ use of services. In the case of the RAND HIE study, cost- sharing affected the number of contacts people initiated with their  physician, which impacted preventive care and diagnostic tests. The  study found that this could potentially affect patients’ use of both effective  and less effective services.

According to several studies and interviews with experts, design changes  could trigger other behavioral responses. For example, a study by the  Kaiser Family Foundation and a report by the Congressional Budget  Office both anticipated that a modernized design could change the  proportion of Medicare beneficiaries who decide to enroll in FFS or MA.  Similarly, officials from the American Academy of Actuaries told us that  they would expect a change in demand for MA under a modernized  design. Under the current Medicare design, all MA plans have an annual  cap that protects beneficiaries from catastrophic medical expenses.  Between 2008 and 2017, the percentage of Medicare beneficiaries who  chose to enroll in an MA plan increased from 22 to 33 percent. CMS  officials told us that the increases in MA enrollment may be due in part to  the requirement that MA plans must include an annual cost-sharing cap.  The Kaiser Family Foundation study found that a modernized design,  similar to that of an MA plan, might incentivize some MA beneficiaries to  move back to FFS.

According to experts we interviewed and studies we reviewed, different  behavioral responses described above would also likely interact and  affect beneficiaries’ out-of-pocket costs. CMS officials told us that when  all of the factors contributing to out-of-pocket costs are combined, it is  difficult to assess the net effect of a modernized cost-sharing design on  beneficiaries’ out-of-pocket costs. For example, officials with the National  Association of Insurance Commissioners emphasized that as both  demand for supplemental insurance and expected utilization changed,  supplemental premiums would also change, which would change out-of- pocket costs. Similarly, studies by both MedPAC and the Congressional  Budget Office found that changes in beneficiaries’ level of supplemental  insurance might trigger additional changes in utilization, which would also  result in changes to the pricing of supplemental insurance. Specifically,  if a number of relatively healthy beneficiaries dropped their supplemental  insurance, and the beneficiaries left were sicker (that is, more costly),  premiums for supplemental insurance might increase. Officials from the  Congressional Budget Office told us that, conversely, if the more costly  beneficiaries dropped their supplemental insurance, premiums might be  lower.

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

As agreed with your offices, unless you publicly announce the contents of  this report earlier, we plan no further distribution until 30 days from the  report date. At that time, we will send copies to appropriate congressional  committees, the Secretary of Health and Human Services, and other  interested parties. In addition, the report will be available at no charge on  the GAO website at http://www.gao.gov.

If you or your staffs have any questions about this report, please contact  me at (202) 512-7114 or cosgrovej@gao.gov. Contact points for our  Offices of Congressional Relations and Public Affairs may be found on  the last page of this report. GAO staff who made key contributions to this  report are listed in appendix II.

Appendix I: Direct Effect on Medicare Beneficiaries’ Cost-sharing Responsibilities under Four Illustrative Cost-sharing Designs

The direct effect of modernizing the Medicare fee-for-service (FFS) cost- sharing design (i.e., the effect when holding utilization and enrollment  constant) on beneficiaries’ cost-sharing responsibilities would depend on  the specific revisions and the time horizon examined. Tables 4, 5, and 6  present the direct effect of modernizing the Medicare FFS cost-sharing  design on beneficiaries’ cost-sharing responsibilities under four illustrative  designs. Each table presents the direct effect of each illustrative design  over 1-, 4-, and 8-year time horizons.

Appendix II: GAO Contact and Staff Acknowledgments

In addition to the contact named above, Greg Giusto (Assistant Director),  Alison Binkowski, George Bogart, Reed Meyer, Beth Morrison, Brandon  Nakawaki, and Brian O’Donnell made key contributions to this report.  Also contributing were Todd Anderson, Emei Li, Yesook Merrill, Vikki  Porter, and Frank Todisco.

Medicare beneficiaries must cover a portion of the costs of services they receive. The rules governing traditional Medicare’s cost-sharing have changed little since the program began in 1965, while private insurance has evolved to include features that traditional Medicare lacks, such as an annual cap on the costs for which beneficiaries are responsible.

As a result, Medicare beneficiaries can face catastrophic costs exceeding tens of thousands of dollars annually.

In this report, we analyzed four scenarios for modernizing Medicare cost-sharing rules and how such changes could affect beneficiaries' costs.


Aviation Security: TSA Uses Current Assumptions and Airport-Specific Data for Its Staffing Process and Monitors Passenger Wait Times Using Daily Operations Data

TSA employs about 43,000 TSOs who screen over 2 million passengers and their baggage each day at airports in the United States. TSA allocates TSOs to airports using both a computer-based staffing model and information from airports that are intended to provide each airport with the optimum number of TSOs. In the spring of 2016, long screening checkpoint lines at certain U.S. airports raised questions about TSA's process for allocating TSOs to airports.

The Aviation Security Act of 2016 includes a provision for GAO to review TSA's process for allocating TSOs. This report examines how (1) TSA modifies staffing assumptions and tailors staffing levels to airports' needs, (2) TSA monitors wait times and throughput and adjusts resources accordingly, and (3) TSA shares information with stakeholders about staffing and related screening procedures at airports. GAO reviewed TSA documentation describing how the agency modifies staffing assumptions and manages stakeholder coordination. GAO also analyzed passenger wait time and throughput data from January 2015 through May 2017 for the 28 airports monitored by headquarters. GAO visited eight airports selected on the basis of passenger volume and other factors and interviewed TSA officials and stakeholders at those locations.

The Transportation Security Administration (TSA) modifies staffing assumptions used in its computer-based staffing model (model) and tailors staffing levels to individual airport needs. Specifically, TSA works with a contractor annually to evaluate the assumptions used in the model and modifies the model's assumptions as needed. For example, TSA adjusted its model after contractor evaluations conducted in fiscal years 2016 and 2017 found that transportation security officers (TSO) needed more time to screen passengers and their baggage when using one type of screening equipment. Moreover, in 2016, TSA began using forecasts on the number of passengers screened at each airport's checkpoints (throughput) to better allocate staff commensurate with the expected rate of increase in passenger throughput at each airport. Furthermore, prompted by the long wait times at some airports in 2016, for the 2017 model TSA officials used actual expedited screening data, specific to each individual airport, rather than relying on the system-wide estimate used in 2016. TSA officials also use other information specific to each airport—such as staff training needs—to further tailor the TSO allocation because the initial allocation resulting from the model does not reflect the full range of operating conditions at individual airports.

TSA uses data to monitor passenger wait times and throughput on a daily basis and responds to increases. For example, TSA's Airport Operations Center (AOC) monitors daily wait times and passenger throughput from 28 airports that TSA officials say represent the majority of passenger throughput nationwide or are operationally significant. Furthermore, TSA officials at airports are required to report to the AOC when an event occurs—such as equipment malfunctions—that affects airport screening operations and results in wait times that are greater than 30 minutes in standard screening lanes. GAO analyzed wait time data for the AOC-monitored airports for the period of January 2015 through May 2017 and found that TSA's reported wait times met its standard of less than 30 minutes in standard screening 99 percent of the time. Within that time frame, two airports accounted for the longest wait times in the spring of 2016. TSA officials identified several tools, such as passenger screening canines, that they use to respond to increases in passenger wait times at these airports.

TSA has taken steps to improve information sharing with airline and airport officials (stakeholders) about staffing and related airport screening operations, and most stakeholders GAO interviewed reported improved satisfaction with information sharing. However, some stakeholders noted differences in the type and extent of information shared. According to TSA officials, stakeholders can elevate any problems they experience with information sharing within TSA to ensure information is shared regularly with stakeholders.

The Department of Homeland Security’s Transportation Security  Administration (TSA) employs about 43,000 transportation security  officers (TSOs) who screen over 2 million passengers and their  accessible and checked baggage each day at airports in the United  States. TSA allocates TSOs to airports using its Resource Allocation  Plan (RAP), which is intended to provide each airport with the optimum  number of TSOs needed to screen passengers for threats to aviation  security, such as prohibited and other potentially dangerous items. In the  spring of 2016, unusually long screening checkpoint lines at certain major  U.S. airports raised questions about TSA’s process for allocating TSOs to  airports. Identifying and deploying the right number of TSOs to meet  individual airport needs throughout the United States is a critical TSA  responsibility for carrying out the agency’s mission to protect the nation’s  transportation systems, while also ensuring the free movement of people  and commerce.

To implement passenger screening and pursue efficient operations, in  addition to relying on TSOs, TSA works with officials from airlines and  airports, as well as officials from associations that represent airlines and  airports. In this report, we refer to all of these officials as ‘stakeholders.’ At  airports, Federal Security Directors (FSDs) and their designees work with  individual airport operators and airlines to, among other things, adjust  TSA resources (i.e., TSOs and screening assets such as metal detectors)  in response to increases in the number of passengers that are screened  at each checkpoint (throughput) and monitor passenger wait times at  checkpoints.

In 2007, we reviewed the RAP (referred to as the Staffing Allocation  Model at that time) and recommended, among other things, that TSA  establish a mechanism to ensure periodic assessment of the  assumptions, such as passenger and checked baggage screening rates,  underlying the RAP. TSA agreed with the recommendation and in  December 2007 developed a plan to periodically assess the RAP’s  assumptions.

The Aviation Security Act of 2016 includes a provision for GAO to conduct  a review of TSA’s RAP. This report addresses (1) how TSA modifies  staffing assumptions and has mechanisms in place to tailor TSO staffing  levels to individual airports’ needs, (2) how TSA monitors wait times and  throughput and adjusts resources accordingly, and (3) how TSA has  shared information with stakeholders about staffing and related screening  procedures at airports, and what are the views of selected stakeholders  on these information sharing efforts.

To gather information for each of our objectives, we visited eight airports  – Chicago O’Hare International, Chicago Midway International,  Dallas/Fort Worth International, Dallas Love Field, Los Angeles  International, Hollywood Burbank International, Ronald Reagan  Washington National, and Richmond International. We selected these  airports based on a variety of factors, including the number of TSOs,  passenger volume, differences in geography, and longer-than-usual wait  times in fiscal year 2016, when passengers experienced long screening  wait times at a number of airports. At each airport, we interviewed airport- level TSA officials, TSOs, airport operators, and airline officials. The  results from our site visits cannot be generalized to all airports at which  TSA has screeners. However, they provided important context about, and  insights into, TSA’s operations and coordination with stakeholders at  airports.

To determine how TSA modifies its staffing assumptions, we reviewed  TSA guidance and policies, including the agency’s plan for assessing the  assumptions used in the RAP, such as the frequency and methods for  reviewing passenger and baggage screening processes. In addition, to  determine whether TSA modified assumptions used in the RAP, we  reviewed TSA internal reports regarding the assumptions used in the  RAP in 2016 and 2017 as well as a 2016 assessment of TSA’s approach  to staffing at airports overall. To evaluate the extent to which TSA has  mechanisms in place to tailor staffing allocations to individual airports’  needs, we analyzed TSA procedures, such as annual reviews of  individual airports’ configurations conducted by airport-level officials that  govern staffing allocation, including procedures for modifying the RAP  and tailoring staffing allocations to individual airports’ needs. We reviewed  data on TSA staffing allocations and interviewed TSA headquarters  officials responsible for modifying the RAP to confirm our understanding  of the processes used and TSA officials at the airport-level regarding any  modifications to airport staffing levels resulting from this process.

To determine how TSA monitors wait times and throughput and adjusts  resources accordingly, we reviewed TSA documentation on wait times  and throughput, such as TSA’s Operations Directive, Reporting Customer  Throughput and Wait Times, as well as TSA reports on wait times and  throughput. To better understand trends in passenger wait times, we  analyzed wait time and throughput data for the period of January 2015  through May 2017 for 28 airports that, according to TSA headquarters  officials, represent the majority of passenger throughput nationwide or are  operationally significant. According to TSA directives and TSA  headquarters officials, TSA began requiring that FSDs and their  designees collect actual instead of estimated wait times for all airports in  July 2014, so we began our analysis in 2015, the first full calendar year  after this requirement was in place. We assessed the reliability of the  data used in our analyses by checking the data for any discrepancies,  reviewing TSA reports on the quality of the data, as well as related  database documentation, and working with agency officials responsible  for compiling the data to understand the data collection and reporting  methodologies. We determined that passenger wait time data and  throughput data for the 28 airports monitored by TSA headquarters were  sufficiently reliable for the purposes of our reporting objectives.  Additionally, using the same data, we analyzed the extent to which TSA  met its wait time standards for the period of January 2015 through May  2017 at the 28 airports. We also interviewed headquarters officials  responsible for overseeing TSA’s collection and use of wait time and  throughput data. To obtain the perspective of TSA officials at airports, we  interviewed FSDs and their designees at the eight airports we visited to  determine the tools they use to respond to increases in passenger wait  times and throughput.

To determine how TSA shares information with stakeholders about airport  staffing and related screening procedures, we reviewed TSA guidance  that directs FSDs to share information with stakeholders and directs  headquarters officials to facilitate daily conference calls with  stakeholders. We also reviewed TSA documentation, such as agendas  and attendance sheets, for meetings between FSDs and airport  stakeholders held from October 2016 through March 2017 for the eight  airports we visited to verify that the meetings took place. We selected this  time period because the TSA guidance directing FSDs to meet with  stakeholders became effective in October 2016. Additionally, we  interviewed TSA headquarters officials and TSA airport-level officials  such as FSDs and their designees at the eight airports we visited to  determine how TSA shares information about staffing and related  screening procedures at airports with stakeholders. The results from the  airport-level interviews with TSA officials at these eight airports we visited  cannot be generalized to all airports at which TSA has screeners, but  provided insights on how FSDs and their designees share information  with stakeholders at their respective airports during the time of our review.

To determine the views of selected stakeholders on TSA’s information  sharing efforts, we interviewed airline and airport officials at the eight  airports we visited, as well as TSOs at those locations, to obtain their  perspectives on TSA efforts to share information consistent with the  Aviation Security Act and TSA guidance. For each of the eight airports  we visited, we interviewed airport officials representing the airport  authority that oversees airport operations and airline officials from the  airline with the greatest number of passengers at the respective airport.  The FSD or FSD designee selected the TSOs we interviewed during our  site visits based on TSO schedule availability. Furthermore, we  interviewed industry association officials from the American Association of  Airport Executives (AAAE), Airports Council International-North America  (ACI-NA), and Airlines for America to obtain their insights on both TSA’s  headquarters and airport-level information sharing. We chose these  industry associations because they work directly with TSA headquarters- level officials and the associations’ members work directly with TSA  airport-level officials such as FSDs and their designees. The results  from the interviews with airline and airport officials at the eight airports we  visited and the three industry associations cannot be generalized to all  stakeholders, but provided insights on how these select stakeholders  viewed TSA’s information sharing efforts.

We conducted this performance audit from August 2016 to January 2018  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.

TSA Processes for Allocating TSOs across Airports

At TSA headquarters, the Office of Security Operations (OSO) has  primary responsibility for operation of the RAP and allocation of TSOs  across airports. Within OSO, the Staffing and Scheduling Division  oversees the RAP. To allocate staff to the nearly 440 TSA-regulated  airports in the United States, OSO is to use a combination of computer- based modeling and line-item adjustments based on airport-specific  information. First, the agency is to work with a contractor to evaluate the  assumptions—such as rates of expedited screening—used by the  computer-based staffing allocation model (model) to determine the  optimal number of TSOs at each airport based on airport size and  configuration, flight schedules, and the time it takes to perform checkpoint  and baggage screening tasks. Second, after the model has determined  how many TSOs are required for each airport, headquarters-level staff  are to make line item adjustments to account for factors such as  differences in staff availability and training needs that affect each airport.  Figure 1 below provides additional details regarding TSA’s process to  determine the number of TSOs at airports.

TSA’s Process for Evaluating Information Used in the RAP

As previously discussed, in 2007, we recommended that TSA establish a  mechanism to periodically assess the assumptions in the RAP (prior to  fiscal year 2017, known as the Staffing Allocation Model) to ensure that  staffing allocations accurately reflect operating conditions that may  change over time. TSA implemented this recommendation by developing  an evaluation plan for regularly assessing the assumptions used in the  staffing model. Assumptions include the number of passengers or bags  that can be screened each hour by TSA equipment and the time TSOs  require to operate discrete sections of the screening process, such as  conducting pat-downs or searches of passengers’ carry-on baggage. The  evaluation plan states that TSA is to assess (1) the time it takes to screen  passengers using TSA equipment and (2) the number of staff needed to  operate the equipment. Results from these assessments are to inform the  assumptions used in the model to determine the base allocation of TSOs  to U.S. airports.

TSA uses the evaluation plan as well as airport-level characteristics to  systematically evaluate the assumptions used in the model on a regular  basis:

Evaluation plan: TSA’s evaluation plan recommends evaluating the  time it takes to perform 19 aspects of passenger and checked  baggage screening processes at least every two years and includes  detailed procedures for doing so. For instance, the evaluation of  passenger screening processes involves observing operations at  selected airports to determine the average time it takes for one  passenger to remove items of clothing and prepare his or her  belongings for screening. Similarly, the evaluation determines how  many passengers can be processed each hour during selected  aspects of screening, such as by travel document checkers or via  advanced imaging technology (AIT), often referred to as body  scanners.

Individual airport characteristics: Each year, TSA airport-level staff,  such as FSDs or their designees, are to review the information in the  model to ensure that information on the number of checkpoints and  each checkpoint configuration and the number of flights departing the  airport each day is accurate.

TSA Processes for Conducting Passenger and Checked Baggage Screening, and Collecting Wait Time Data at Airports

At the airport level, FSDs and their designees are responsible for  overseeing TSA security activities, including passenger and checked  baggage screening. TSOs at airports follow standard operating  procedures that guide screening processes and utilize technology such  as AITs or walk through metal detectors (WTMD) to screen passengers  and their accessible property. TSOs also inspect checked baggage to  deter, detect, and prevent the carriage of any unauthorized explosive,  incendiary, or weapon onboard an aircraft. Checked baggage screening  is conducted in accordance with standard operating procedures and  generally is accomplished through the use of explosives detection  systems or explosives trace detection systems. TSA employs an  expedited screening program, known as TSA Pre® that assesses  passenger risk to aviation security prior to their arrival at an airport  checkpoint. According to TSA, expedited screening involves a relatively  more efficient and convenient screening process for individuals from  whom TSA has obtained sufficient information to determine them to be of  lower risk and thus undergo an expedited screening process, compared  to the standard screening process a traveler may undergo, for whom TSA  does not have such information in advance.

Finally, at each airport, TSA is to collect throughput data on the number of  passengers screened under both expedited and standard screening and  monitor passenger wait times at screening checkpoints. TSA airport  officials are to submit passenger throughput and wait time data on a daily basis to OSO’s Performance Management Division at TSA headquarters,  which compiles the data through the Performance Measurement  Information System (PMIS), TSA’s web-based data collection system.

TSA Offices Responsible for Sharing Information with Stakeholders about Airport Operations

TSA’s OSO and the Office of Security Policy and Industry Engagement  (OSPIE) are both responsible for sharing information with stakeholders  about airport operations. In response to the Aviation Security Act, OSO  issued guidance in October 2016 intended to ensure that FSDs share  information with stakeholders. OSPIE communicates TSA information  about airport operations, such as how TSOs are allocated across airports,  to stakeholders.

TSA Modifies Its Staffing Assumptions and Relies on Airport Information to Tailor TSO Staffing Levels to Individual Airports

TSA Modifies Its Staffing Assumptions as Needed Based on Contractor and TSA Officials’ Evaluations and Passenger Throughput Forecasts

In fiscal years 2016 and 2017, TSA modified the assumptions used in its  model, as needed, to reflect changes identified through annual  evaluations performed by a contractor. The contractor is specifically  tasked with evaluating the assumptions related to the time needed to  screen passengers and their baggage. For example, TSA officials stated  that they increased the expected time needed to screen passengers for  one type of passenger screening equipment in fiscal year 2017 because  the contractor found that the actual time needed was more than the  assumption TSA used in fiscal year 2016. Similarly, in fiscal year 2016,  TSA allocated fewer staff to review images of checked baggage,  compared to previous years, because the contractor’s evaluation  determined it took TSOs less time to review the images than the time  observed in previous years.

In addition to modifying its model based on evaluations performed by  contractors, TSA officials at the headquarters level review and modify  other assumptions in the model to ensure they are accurate. For  example, prompted by the long waits in the spring of 2016, officials stated  that they modified the model for the 2017 fiscal year based on their  evaluation of the 2016 assumptions. Specifically, TSA assumed that 50  percent of airline passengers would use expedited screening in 2016, but  only an average of 27 percent of passengers used expedited screening  that year. According to the officials, TSA modified this assumption in fiscal  year 2017 and now uses TSA Pre® Program data specific to each  individual airport in the model. Similarly, officials told us that, since TSA  was established in November 2001, many employees will reach 15 years  of service with the federal government in fiscal years 2016 and 2017,  resulting in increased annual leave allowances. In response, officials  have increased the amount of annual leave they expect employees to use  and rely on airport-specific data regarding employee tenure to estimate  annual leave for the coming year.

TSA has also modified the way it develops assumptions regarding  passenger throughput at each airport. For example, beginning in fiscal  year 2016, TSA used passenger throughput forecasts to allocate staff  commensurate with the expected rate of increase in passenger  throughput at each airport. The estimated increase in passenger  throughput for each fiscal year is based primarily on national and airport- level data from the previous 3 months from PMIS, TSA’s web-based data  collection system, and flight forecast data from the airline industry, as well  as additional input from other sources. Prior to fiscal year 2016, TSA  planned for passenger throughput during the busiest 28 days from the  previous fiscal year and did not adjust the assumption for the annual  increase in passenger throughput, which increased two percent in 2014  and four percent in 2015. A TSA headquarters official responsible for  overseeing the RAP stated that the agency compared projected  passenger throughput to actual passenger throughput for fiscal year 2017  to determine the accuracy of the projections and concluded that no  significant changes to the method of forecasting were necessary for fiscal  year 2018.

TSA Uses Airport-Level Information to Tailor Staffing Levels to Individual Airport Needs Using Line Item Adjustments

According to TSA officials, each airport in the United States has unique  characteristics that make it difficult to apply a one-size-fits-all solution to  staffing security operations. For instance, officials told us that some  airports are allocated additional staff to account for the time needed to  transport TSOs to off-site training facilities. Because the staffing  allocation resulting from TSA’s model does not reflect the full range of  operating conditions at individual airports, TSA headquarters officials use  airport-specific information to further adjust allocations by changing  individual line items within the allocation after running the model on both  an annual and an ad hoc basis. TSA headquarters officials stated that  they have developed methodologies for making standard line item  adjustments such as training requirements, overtime, and annual and sick  leave. Officials told us they review the methodologies each year and  use their professional judgement to modify the methodologies to account  for changes in airport needs as well as budget constraints. We found that  through its process of tailoring staffing allocations to individual airports’  needs, TSA is able to respond to the circumstances at each individual  airport.

TSA headquarters officials also use airport-specific data on staff  availability, training needs, supervisory needs, and additional security  layers to manually adjust the model’s staffing allocation output at a line  item level. For instance, headquarters officials use the previous years’  data on staff sick leave for each airport to evaluate whether they are  allocating the appropriate amount of sick leave to their staff allocations on  an individual airport basis. According to TSA headquarters officials, sick  leave use can vary by airport and region of the country. Similarly, officials  stated that they adjust the model’s output to account for individual airport  staff’s training needs so that each airport’s staff can meet TSA’s annual  training requirements.

In addition, according to TSA officials at both the headquarters and airport  levels, airport-level officials can request exceptions—modifications to their  staffing allocation—based on unusual airport conditions that are difficult to  address, such as problematic checkpoint configurations or lack of space  for security operations. For instance, officials at one airport said that they  had been granted exceptions for one checkpoint because pillars and  curves within the checkpoint prevented the lanes in the checkpoint from  screening passengers at the rate assumed by the model. TSA officials at  the headquarters level review requests for exceptions and use their  professional judgement to determine whether the exception will be  granted.

Finally, in some cases, TSA may adjust an airport’s staffing allocation  outside of the annual staffing allocation process and may do so as the  result of significant and unforeseen changes in airport operations. For  instance, TSA officials stated that one airport was allocated additional  staff for the remainder of the fiscal year when the airport opened a new  terminal mid-year so that the additional checkpoints could be properly  staffed. Officials at another airport we visited said that they had been  allocated additional staff when an airline extended its operational hours to  ensure appropriate staffing for the additional hours of operation.

TSA Uses Data to Monitor Airport Operations and Respond to Increases in Passenger Wait Times and Throughput

TSA Uses Passenger Wait Time and Throughput Data to Monitor Airport Operations on a Daily Basis

TSA collects passenger wait time and throughput data and uses those  data to monitor daily operations at airports. TSA’s Operations Directive  (directive), Reporting Customer Throughput and Wait Times, provides  instructions for collecting and reporting wait time and passenger  throughput data for TSA screening lanes. Regarding wait time data,  according to the directive, FSDs or their designees at all Category X, I,  and II airports must measure wait times every operational hour in all  TSA expedited and standard screening lanes. The directive requires wait  times to be measured in actual time, using a verifiable system such as  wait time cards, closed circuit television monitoring, or another  confirmable method. The directive indicates that wait times should be  measured from the end of the line in which passengers are waiting to the  WTMD or AIT units. FSDs or their designees at Category III and IV  airports may estimate wait times initially, but the directive requires them  to measure actual wait times when wait times are estimated at 10 minutes  or greater. The directive also requires FSDs or their designees to collect  passenger throughput data directly from the WTMD and AIT units.  According to TSA headquarters officials, the machines have sensors that  collect the number of passengers that pass through each hour, and TSOs  retrieve the data directly from the units. All airports regardless of category  are required to enter their wait time and throughput data daily into PMIS,  TSA’s web-based data entry program, no later than 3:30 AM Eastern  Time of the next calendar day so that the data can be included in the  morning’s Daily Leadership Report (discussed in more detail below).

To monitor operations for all airports, TSA compiles a daily report utilizing  a variety of PMIS data points, including wait time and throughput data.  The Office of Security Operations’ Performance Management Division  disseminates the Daily Leadership Report to TSA officials, including  regional directors and FSDs and their designees every morning detailing  the previous day’s wait times and throughput figures, among other data  points. The Performance Management Division includes a quality  assurance addendum with each Daily Leadership Report, indicating  missing or incorrect data, to include wait time and throughput data, and  TSA has procedures in place intended to ensure officials at the airports  correct the data in PMIS within 2 weeks.

In addition to the Daily Leadership Report, TSA utilizes wait time and  throughput data to monitor airport operations at 28 airports in near real  time. In May 2016, TSA established the Airport Operations Center (AOC)  that conducts near real time monitoring of the operations of 28 airports  that, according to TSA headquarters officials, represent the majority of  passenger throughput nationwide or are operationally significant. TSA  requires the 28 airports monitored by the AOC to enter passenger wait  time data and throughput data into PMIS hourly (whereas the remaining  airports are only required to submit data once daily, by 3:30 AM Eastern  Time, as described above) so that AOC officials can monitor the  operations in near real time. In addition, TSA officials at airports are  required to report to the AOC when an event occurs—such as equipment  malfunctions, weather-related events, or unusually high passenger  throughput—that affects airport screening operations and results in wait  times that are greater than TSA’s standards of 30 minutes in standard  screening lanes or greater than 15 minutes in expedited screening  lanes.

If an airport is undergoing a period of prolonged wait times, the AOC  coordinates with the Regional Director and the FSD to assist in deploying  resources. For example, over the course of the summer of 2016, after  certain airports experienced long wait times in the spring of 2016 as  confirmed by our analysis, the AOC assisted in deploying additional  passenger screening canines and TSOs to those airports that  experienced longer wait times. The AOC disseminates a morning and  evening situational report to TSA airport-level officials and airport  stakeholders summarizing nationwide wait times, highlighting wait times  at the top airports and any hot spots (unexpected passenger volume or  other operational challenges) that may have occurred since the most  recent report was issued. In addition to the near real time monitoring of  the 28 airports, the AOC also monitors operations at all other airports and  disseminates information to airports and stakeholders as needed.

To determine the extent to which TSA exceeded its wait time standards,  we analyzed wait time data for the 28 airports monitored by the AOC for  the period of January 2015 through May 2017 for both standard and  expedited screening. Our analysis shows that TSA met its wait time  standard of less than 30 minutes in standard screening at the 28 AOC  airports 99.3 percent of the time for the period of January 2015 through  May 2017. For expedited screening for the same time period at the same  airports, we found that 100 percent of the time passengers were reported  to have waited 19 minutes or less. Additionally, our analysis confirmed  that the percentage of passengers in standard screening waiting over 30  minutes increased in 2016 during the months of March, April, and May as  compared to 2015 at all 28 airports monitored by the AOC.

TSA Airport Officials Use a Variety of Tools to Respond to Increases in Passenger Wait Times and Throughput

FSDs and their staff at the airports we visited identified a variety of tools  that they utilize to respond to increases in passenger wait times and/or  throughput.

TSOs from the National Deployment Force (NDF)—teams of  additional TSOs—are available for deployment to airports to support  screening operations during major events and seasonal increases in  passengers. For example, TSA officials at one airport we visited  received NDF officers during busy holiday seasons and officials at  another airport received officers during the increase in wait times in  the spring and summer of 2016.

TSA officials at select airports use passenger screening canines to  expedite the screening process and support screening operations  during increased passenger throughput and wait time periods. For  example, TSA officials at one airport we visited emphasized the  importance of passenger screening canines as a useful tool to  minimize wait times and meet passenger screening demands at times  when throughput is high. Officials at another airport we visited rely on  these canines in busy terminals during peak periods. According to  officials at two of the airports we visited, the use of passenger  screening canines helped them to reduce wait times due to increased  passenger volumes in the spring and summer of 2016.

TSA officials at airports also utilize part-time TSOs and overtime  hours to accommodate increases in passenger throughput and wait  times. For example, according to officials at all eight of the airports we  visited, they use overtime during peak travel times, such as during  holiday travel seasons, and officials usually plan the use of overtime  in advance. Additionally, TSA officials at four of the airports we visited  told us they use part-time TSOs to help manage peak throughput  times throughout the day.

According to TSA officials at two of the airports we visited, they move  TSOs between checkpoints to accommodate increases in passenger  throughput at certain checkpoints and to expedite screening  operations. For example, TSA officials at one airport we visited have a  team of TSOs that terminal managers can request on short notice.  Officials at the other airport estimated that they move TSOs between  terminals about 40 times per day.

TSA Has Taken Steps to Improve Information Sharing with Stakeholders and Most Stakeholders We Interviewed Reported Improved Satisfaction

TSA Improved Information Sharing with Stakeholders through Daily Conference Calls, Presentations, and Meetings

TSA headquarters has taken steps intended to improve information  sharing with stakeholders about staffing and related screening  procedures at airports. For example, TSA officials hold daily conference  calls with industry association, airline, and airport officials at the 28  airports monitored by the AOC. According to TSA headquarters officials,  TSA established the daily conference call as a mechanism intended to  ensure timely communication with stakeholders and to help identify and  address challenges in airport operations such as increases in passenger  wait times. Also, TSA headquarters officials stated that they conducted a  series of presentations and meetings with industry, airline, and airport  officials to discuss TSA’s RAP, security enhancements at airports, and  airport screening processes, among other things. For example, TSA’s  headquarters officials shared information about the fiscal year 2017 RAP  in October 2016 during a briefing at an industry conference and a meeting  with airline representatives, airline engineers, and Federal Aviation  Administration officials. Additionally, TSA headquarters officials facilitated  a stakeholder meeting in May 2017 to discuss planned improvements for  the TSA Pre® Program and met with stakeholders in June 2017 to  discuss security enhancements and changes to screening procedures for  carry-on baggage.

In addition to headquarters-level initiatives, at the eight airports we  visited, we found that FSDs shared information with airport and airline  officials by meeting on an ongoing basis to discuss TSA staffing and  related screening procedures. For example, according to the FSDs and  airline and airport officials at all eight airports we visited, FSDs met with  stakeholders on a daily, weekly, monthly, or quarterly basis. During these  meetings, FSDs and airline and airport officials told us that FSDs  discussed TSO staffing levels at the airports, instances when passenger  screening wait times were long at security checkpoints, and TSA  screening equipment performance, among other things.

Stakeholders Reported Improved Satisfaction with TSA Headquarters Information Sharing Efforts and with Most FSDs

Stakeholders told us that TSA headquarters officials and most FSDs  improved information sharing since fiscal year 2016. With regard to TSA  headquarters officials’ information sharing efforts, officials from all three  industry associations we interviewed stated that, since fiscal year 2016,  TSA headquarters improved information sharing with their association  member companies and attributed that improvement, in part, to the daily  conference call between TSA and stakeholders. For example, officials  from one industry association stated that the calls benefited members by  facilitating collaboration with TSA to more quickly identify and address  problems, such as malfunctioning screening equipment, before the  problems negatively affected passengers. An official from another  industry association told us that the daily conference call improved  communication substantially between TSA and the organization by  providing a regular opportunity to discuss airport security issues and  TSA’s plans to resolve those issues.

Additionally, stakeholders we interviewed generally reported positive  relationships or improved information sharing with FSDs, but also noted  differences in the type and extent of information that FSDs shared. For  example, officials at seven of eight airlines and all eight airports we visited  stated that they have positive relationships with their FSDs and that their  FSDs were accessible and available when needed, while the remaining  airline official noted improving access to information. Furthermore,  officials from all three industry associations cited improved information  sharing between their members at airports and FSDs since fiscal year  2016, but officials from two association noted that some FSDs still do not  regularly share information, such as changes in the number of TSOs  staffed at individual airports. According to TSA headquarters officials,  stakeholders can elevate any problems they experience with FSDs  sharing information to regional directors who are responsible for ensuring  that FSDs engage regularly with stakeholders.

We provided a draft of this product to DHS for comment. We received  technical comments which we incorporated as appropriate.

We are sending copies of this report to the Secretary of Homeland  Security, the Administrator of TSA and other interested parties. In  addition, the report is available at no charge on the GAO website at  http://www.gao.gov.

If you or your staff have questions about this report, please contact me at  (202) 512-7141 or groverj@gao.gov. Contact points for our Offices of  Congressional Relations and Public Affairs may be found on the last page  of this report. Key contributors to this report are listed in appendix I.

Appendix I: GAO Contact and Staff Acknowledgments

In addition to the contact named above, Ellen Wolfe, Assistant Director;  Joel Aldape, David Alexander, Chuck Bausell, David Beardwood, Wendy  Dye, Miriam Hill, Susan Hsu, Thomas Lombardi, Kevin Newak, Heidi  Nielson, and Natalie Swabb made significant contributions to this report.