How Much Do Medicare Beneficiaries Spend Out of Pocket on Health Care?

Data Overview

This interactive analysis is based on data from the Centers for Medicare & Medicaid Services (CMS) Medicare Current Beneficiary Survey (MCBS) Cost Supplement for 2016, the most recent year available. The MCBS is a survey of a nationally-representative sample of the Medicare population, including both aged and disabled enrollees who are living in the community as well as facility residents. The dataset integrates survey information reported directly by beneficiaries with Medicare administrative data. Survey-reported data includes the demographics of respondents, such as sex, age, race, living arrangements, income, health status, and physical functioning, the use and costs of health care services, and supplementary health insurance arrangements.

The survey also collects information on inpatient and outpatient hospital care, physician and other medical provider services, home health services, durable medical equipment, long-term and skilled nursing facility services, hospice services, dental services, and prescription drugs. Survey-reported information is matched to and supplemented by administrative records and billing and claims-level data when possible. Extensive efforts are made to verify the accuracy of survey reports and to reconcile discrepancies using administrative bill data to produce a more complete and reliable dataset.

Beneficiary Population

Our analysis includes beneficiaries in traditional Medicare for most of their enrollment in 2016, and excludes beneficiaries enrolled in Part A or Part B only, those with Medicare as a Secondary Payer, and those enrolled in Medicare Advantage plans for most of their enrollment in 2016. For Medicare Advantage enrollees, it is not possible to verify survey-reported events in the MCBS with administrative claims data, as is done for beneficiaries in traditional Medicare. This has the effect of biasing downward survey-reported out-of-pocket spending amounts for Medicare Advantage enrollees compared to beneficiaries with traditional Medicare. It is not possible to determine whether observed differences are real or due to underlying differences in the data collection, verification, and imputation process for out-of-pocket spending by beneficiaries in traditional Medicare and Medicare Advantage. Therefore, we exclude Medicare Advantage enrollees (unweighted n=2,726) to avoid introducing bias associated with underreporting of events and spending for this population.

We also excluded beneficiaries who were enrolled in only Part A or Part B (unweighted n=298) and those with Medicare as a Secondary Payer (unweighted n=231) for most of their Medicare enrollment in 2016 Because Medicare is typically not the primary payer for those who are enrolled in only Part A or Part B but not both programs, beneficiaries with only Part A or Part B also have significantly lower average total out-of-pocket spending relative to those enrolled in both Part A and B, which is the rationale for excluding them from the analysis of out-of-pocket spending.

After excluding these groups of enrollees, our sample for the analysis of spending as a share of total income included 5,369 respondents in traditional Medicare (32.7 million weighted) in 2016. We analyze out-of-pocket spending among all traditional Medicare beneficiaries and by specific beneficiary subgroups, including age (under 65, 65-74, 75-84, 85 and over), gender (female, male), age by gender, race (white non-Hispanic, black non-Hispanic, Hispanic), race by gender, race by age, marital status (married, divorced/separated, widowed, single (never married)), education level (less than high school, high school graduate, some college, college graduate), per capita income categories (increments of $10,000), self-reported health status (excellent, very good, good, fair, poor), number of chronic conditions (none, 1-2, 3-4, 5 or more), Census region (Northeast, Midwest, South, West), metropolitan area (metropolitan, rural micropolitan, rural adjacent or nonadjacent), type of residence (community, facility), supplemental coverage (employer-sponsored insurance (ESI), Medicaid, Medigap, none), hospital use (no inpatient stay, any inpatient stay, one inpatient stay, two or more inpatient stays), and specific chronic conditions.

Out-of-Pocket Health Care Spending

Out-of-pocket spending for medical and long-term care services reported in the MCBS is not the same as beneficiary liability or the Medicare cost-sharing amount for services used. Instead, out-of-pocket spending amounts are net of payments by any third-party payers, such as payments by Medicaid, Medigap, or employer-sponsored insurance. Survey-reported out-of-pocket payments are those payments made by the beneficiary or their family, including direct cash payments or in the form of Social Security or Supplemental Security Income (SSI) checks to a nursing home.

Out-of-pocket spending on premiums is derived from administrative data on Medicare Part A, Part B, and Part D premiums for each sample person along with survey-reported estimates of premium spending for other types of health insurance beneficiaries may have (including Medigap, employer-sponsored insurance, and other public and private sources). Part B premium amounts reported in the MCBS include income-related premiums paid by beneficiaries with higher incomes (more than $85,000 per individual/$170,000 per married couple). The administrative data reflect liability, not the actual payments made by beneficiaries for their premiums, which overstates actual premiums paid for certain groups of beneficiaries who are not responsible for paying their Medicare premiums. People who are dually-eligible for Medicaid are generally not liable for their Part A, Part B, or Part D premiums; those who receive the Part D low-income subsidy are eligible for full or partial coverage of their Part D premium. For these groups of beneficiaries, we adjusted the premium estimates reported in the MCBS to reflect the premium subsidies they receive. For beneficiaries reported as receiving the Part D low-income subsidy but who were not enrolled in benchmark plans (based on Part D contract IDs in the MCBS), we assigned premiums based on plan-specific data from the 2016 Part D landscape file.

The medical and long-term care services included in this analysis are:

  • Dental services: Includes cleaning, x-rays, repair, purchase or repair of dentures, and orthodontic procedures. The basic unit measuring use of these services is a single visit to the dentist, where a variety of services might be rendered.
  • Inpatient hospital services: Includes inpatient hospital stays, including emergency room visits which result in an inpatient admission. The basic unit measuring use of inpatient hospital services is a single admission.
  • Long-term care facility services: Includes individual long-term care facility events; a long-term care facility is defined as having three or more beds and providing long-term care services throughout the facility or in a separately identifiable unit. The basic unit measuring use of long-term care facility services is a “stay” in a nursing home or other long-term care facility. Stays are measured in terms of days of residence in that facility.
  • Medical providers/supplies: Includes medical doctor and practitioner visits; diagnostic laboratory and radiology; medical and surgical services; and durable medical equipment and non-durable supplies, such as eyeglasses or contact lenses and hearing aids, orthopedic items such as canes, walkers, wheelchairs and corrective shoes, diabetic supplies, oxygen supplies and equipment. The basic unit measuring use of these services is a separate visit, procedure, service, or a supplied item for a survey reported event.
  • Outpatient hospital services: Includes outpatient visits to the outpatient department or outpatient clinic of a hospital, as well as emergency room visits that do not result in a hospital admission. The basic unit measuring use of outpatient services is a separate visit to any part of the outpatient department for a survey-reported event.
  • Prescription drugs: Includes individual outpatient prescribed medicine events, including drugs provided to enrollees in Medicare Part D drug plans; excludes prescription medicines provided by the doctor or practitioner as samples and those provided in an inpatient setting. A small number of Part B drugs (physician-administered) are collected as survey-reported data in the MCBS prescription medicines data file. However, the data added from claims is only from Part D. There are no survey-reported drugs administered by a physician matched from the Part B administrative claims data. The basic unit measuring use of prescription drugs is a single purchase of a single drug in a single container.
  • Skilled nursing facility services: Includes short-term institutional stays, such as skilled nursing home stays or rehabilitation hospital stays; excludes inpatient hospital admissions and long-term care facility stays. The basic unit measuring use of these services is an admission.

The MCBS includes a measure of total income for individual respondents and their spouses, if applicable. However, the MCBS does not report all sources of income that some beneficiaries may have. As in many other surveys, income is self-reported, with beneficiaries asked to report total annual income for themselves and their spouses (where applicable) from all sources, including earnings, Social Security, pensions, and asset income. However, beneficiaries are not asked to report specific income amounts by source, and some types of income may go unreported or may be underestimated. Therefore, this measure results in an overall underreporting of income, particularly for those with relatively high incomes. This conclusion is based on a comparison of MCBS income estimates to income estimates from DYNASIM3, in which we measured the divergence of MCBS and DYNASIM income estimates at each percentile of per capita income.

We used the results of this comparison to derive adjustment factors for each percentile with which to rescale each MCBS respondent’s income. In general, this produced estimates of MCBS respondents’ income that are higher than self-reported values and that we believe are a more accurate representation of income among people on Medicare. We then combined this adjusted income estimate with per capita out-of-pocket spending estimates in the MCBS to derive a more reliable estimate of Medicare beneficiaries’ per capita out-of-pocket health care spending as a share of total income than one based on MCBS self-reported income data alone.

Overview of Methods

To estimate total out-of-pocket spending per beneficiary in traditional Medicare, we calculate for each sample person aggregate estimates of out-of-pocket spending on both insurance premiums for Medicare Parts A, B, and D and supplemental insurance coverage, and medical and long-term care services reported in the MCBS. These amounts are averaged across the entire sample of traditional Medicare beneficiaries and weighted to be representative of the traditional Medicare beneficiary population or specific subgroups of beneficiaries. Analysis of spending by type of service includes beneficiaries who did and did not use each type of service. References to “total out-of-pocket spending” in this analysis always include both premiums and service spending. We also often refer to the separate components of total spending (either out-of-pocket spending on services or premiums) in presenting results. For some beneficiary subgroups, estimates of out-of-pocket spending by service type may not add up to the total for all services due to missing data related to small sample size.

To measure per capita out-of-pocket health care spending as a share of per capita total income, we computed for each individual a ratio of out-of-pocket spending to total per capita income, arrayed the individual ratios of annual out-of-pocket spending to annual income from low to high and computed the median for the entire group of traditional Medicare beneficiaries, and by beneficiary subgroups.

Due to missing data related to small sample size, we are unable to show the median out-of-pocket spending as a share of income for beneficiaries who had Medicaid for part of the year and lived in the community. Similarly, we are unable to show the median out-of-pocket spending as a share of income for Medicare beneficiaries who are black and under the age of 65.

Issue Brief Appendix Table

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