States encouraged to maintain health benefits for temporary census workers

The Acting Director of the Center for Medicaid and CHIP Services (CMCS) encouraged states, to the extent permitted under the law, to exclude temporary income from employment in the 2020 Decennial Census when determining eligibility for public benefit programs. A new bulletin provides guidance on existing flexibility under state plans for modified adjusted gross income (MAGI) based systems and non-MAGI based systems. This includes the option of submitting a state plan amendment (SPA) to CMS (CMCS Bulletin, July 3, 2019).

Census workers and health benefits

The Census provides low-income individuals with an opportunity for employment and skills training. Many of these workers are eligible for Medicaid or in a household with Medicaid or CHIP eligible individuals. One element of successful recruiting efforts by the Census Board is ensuring the continued availability for Medicaid and CHIP coverage for workers and their families. During previous censuses, state Medicaid and CHIP agencies have been encouraged to ensure that temporary census workers and their families do not lose eligibility due to temporary census income. Previously, states were able to disregard temporary census income for all Medicaid and CHIP eligibility groups, but a move to a MAGI-based methodology no longer permits the use of income disregards. The bulletin describes existing authorities that may be used to exclude or minimize the impact from temporary census employment.

Existing State Plan Options

Under section 1902(e)(14)(D) of the Social Security Act, for non-MAGI populations, states may disregard in whole or in part, temporary census income and many states have already elected to disregard temporary census income for multiple eligibility groups in their state plan. States wishing to apply disregards of temporary census income for the first time or wish to add or modify the non-MAGI groups affected must submit an SPA to CMS.

Under MAGI-based methodologies, temporary census income is taxable as employment income and Medicaid and CHIP regulations prohibits the use of income disregards and this prohibition cannot be waived. States may elect under 42 C.F.R. §435.603(h)(3) to use a reasonable method for determining a prorated portion of reasonably predictable changes (RPC) to income as they do for fluctuating income such as from seasonal work or self-employment. States with approved RPC methodology for seasonal work may include temporary census income within its scope such that a new SPA submission would not be necessary. States that do not have an existing state plan authority to implement an RPC methodology may elect to do so through an SPA, although the methodology cannot be limited only to temporary census income.

Parents and Other Caretaker Relatives may retain specific coverage protections due to increased earned income through Transitional Medical Assistance (TMA). TMA is a required eligibility protection that states must apply, even under increased earnings due to temporary census employment. If census employment income triggers a transition to TMA, the Medicaid agency would redetermine the individual’s eligibility when census employment ends.

CMS is offering technical assistance on the options and requirements included in the informational bulletin as well as assistance on submitting the required state plan amendments.

Rural hospitals hit hard by reductions in Medicare disbursements, declining population

Approximately 3 percent of all rural hospitals closed in the period between 2013 and 2017, which can affect rural residents’ access to health care services. The U.S. Government Accountability Office (GAO) did a study to determine how HHS supports and monitors rural hospitals’ financial viability and rural residents’ access to hospital services. The study also details the number and characteristics of rural hospitals that have closed as well as what is known about the factors that contributed to those closures. According to the GAO report, Medicare Dependent Hospitals and for-profit hospitals were some of the hardest hit by reductions in Medicare disbursements, while hospitals in Medicaid expansion states and states with higher enrollment under the Patient Protection and Affordable Care Act (ACA) (P.L. 111-148) were the least affected (GAO Report, GAO-18-634, September 30, 2018).

Rural hospitals

In 2017, 2,250 general acute care hospitals in the United States met the definition of rural. Rural hospitals represented approximately 48 percent of hospitals nationwide and 16 percent of inpatient beds. Rural hospitals spread across 84 percent of the United States land area that is classified as rural and served 18 percent of the United State population that lived in those areas. Rural areas tend to have a higher percentage of elderly residents than urban areas, a higher percentage of residents with limitations in activities caused by chronic conditions, and a lower median household income. Rural areas also face a decreasing population and slow employment growth.

Payment policies and programs

HHS provides key financial support to rural hospitals to provide rural residents access to hospital services through a number of payment policies and programs. CMS administers five rural hospital payment designations, in which rural or isolated hospitals that meet specified eligibility criteria receive higher reimbursement for hospital services than they otherwise would have received under Medicare’s standard payment methodology. The Federal Office of Rural Health Policy (FORHP) administers multiple grant programs, cooperative agreements, and contracts that provide funding and technical assistance to rural hospitals. CMS’s Center for Medicare and Medicaid Innovation tests new ways to deliver and pay for healthcare. There are also the broader HHS payment policies and programs such as Medicare and Medicaid base payments, Medicare and Medicaid uncompensated care payments, the state innovation models initiative, as well as other targeted HHS payment policy and programs.

Rural hospital closures

An analysis of data shows that from 2013 through 2017, 64 rural hospitals closed. This is more than twice the number of rural hospitals that closed during the prior 5-year period and accounts for more than the share of urban hospitals that closed and more than the number of rural hospitals that opened. Rural hospitals in the South represented 38 percent of the rural hospitals in 2013 but accounted for 77 percent of the rural hospital closures from 2013 through 2017. Medicare dependent hospitals represented 9 percent of the rural hospitals in 2013 but accounted for 25 percent of the rural hospital closures.

For-profit hospitals are twice as likely to experience financial distress relative to government-owned and non-profit hospitals and represented 11 percent of rural hospitals in 2013 but accounted for 36 percent of closures. Bed size also seems to be a factor as rural hospitals with between 26 and 49 inpatient beds represented 11 percent of the rural hospitals in 2013 but accounted for 23 percent of the closures. While critical access hospitals (CAHs), which have 25 acute inpatient beds or less and make up a majority of the rural hospitals, were less likely than other rural hospitals to close. This may be due, in part, to the CAH payment designation.

Contributing factors

Data shows that rural hospital closures were generally preceded and caused by financial distress. This is partially due to a decrease in patients seeking inpatient care at rural hospitals. There are an increasing number of federally qualified health centers or newer hospital systems outside of the area that create increased competition for rural hospitals. Technological advances have also allowed for more services to be provided in outpatient settings. There is also data showing that the years 2010 through 2016 marked the first recorded period of rural population decline.

Rural hospitals are sensitive to changes in Medicare payments because, on average, Medicare accounted for approximately 46 percent of their gross patient revenues in 2016. Reductions in nearly all Medicare reimbursements and reductions in Medicare bad debt payments have contributed to negative margins for rural hospitals.

Medicaid expansion

According to stakeholders that were interviewed and literature that was reviewed, the strongest factor that likely strengthened the financial viability of rural hospitals was the increased Medicaid eligibility and enrollment under the ACA. A 2018 study showed that Medicaid expansion was associated with improved hospital financial performance and a substantially lower likelihood of closure, especially in rural markets. Drops in uninsured rates in 2008 through 2009 and 2014 through 2015 corresponded with states’ decisions to expand Medicaid, with small towns and rural areas seeing the largest increase in Medicaid coverage and decline in uninsured. Data shows that from 2013 through 2017, rural hospitals in states that had expanded Medicaid as of April 2018 were less likely to close compared with rural hospitals in states that had not expanded Medicaid.

CBO, JCT share methods for analyzing legislative proposals impacting health insurance coverage

The Congressional Budget Office (CBO) and the Joint Committee on Taxation (JCT) revealed in a recent report how they jointly analyze proposed legislation that would impact health insurance coverage for individuals younger than age 65, detailing how they develop analytic strategies, model a proposal’s effect, and finalize their analysis (CBO Report, February 2018).

Analytic strategy development

First, the CBO and JCT put together an analytic strategy. The agencies formally develop their strategy once the proposed legislation’s specifications become available, an official request for analysis has been made, and the CBO and JCT arrange the time to commence the analysis. However, the agencies also often work informally with Congressional staff during development of the proposal. The agencies begin by reviewing the policy specifications. The CBO and JCT consider how the proposed legislation would impact existing law and how the proposed legislation is different from earlier proposal drafts. The agencies work to verify that the Congressional staff’s intent is reflected in the language and then estimate the legislative effect by, namely, identifying how the proposal could affect health insurance coverage and the federal budget.

The CBO and JCT focus on the policy changes most likely to impact health insurance coverage or cost, ranging from the straight-forward to the more complex. Another key aspect the agencies consider is timing and what additional “administrative infrastructure” is necessary to bring about the changes of the proposed legislation—and how long it would take to do so. The timing element includes estimates of how other stakeholders (state governments, insurers, employers, etc.) would respond and how long it would take for them to implement the proposed changes. To help with their estimates, the agencies rely on past cases of legislative reform programs. Further, the agencies seek input from outside experts and existing evidence while maintaining the required confidentiality of a proposal.

Proposal effect modeling

Second, the CBO and JCT undertake modelling the impact of the proposed legislation. Primarily, the agencies rely on CBO’s health insurance simulation model (HISIM), Medicaid enrollment and cost models, and JCT’s individual tax model. These models use data on health insurance coverage information for everyone younger than 65, Medicaid enrollment and expenditures, and detailed tax return information. The agencies also draw estimates based on information HISIM cannot project, namely, the behavior of states, employers, and insurers. These initial projections are incorporated as inputs into HISIM (state, employer, and individual enrollee behavior) or assessed outside HISIM (insurer behavior). CBO and JCT also use HISIM to estimate stakeholder responses to new coverage options. Medicaid enrollment and cost projections use HISIM estimates in addition to a more detailed Medicaid model and other methods. JCT usually provides estimates of proposed tax liability changes using its individual tax model.

Review

Finally, both the CBO and JCT engage in rigorous review of their respective analysis results in order to ensure objectivity and proper analysis. Specifically, they examine results of one or more years out of the 10-year projection period to ensure that the analysis is being computed as intended and compare results against previous analyses. The agencies also inspect for programming errors or unexplained results. The CBO and JCT consider changes to the results if there were different critical inputs. The agencies prepare a formal written estimate and explanation thereof and, before releasing it to Congress and the public, agency staff carefully review the report.

Medicaid and CHIP are catching uncovered kids, the ACA helps

Due to high rates of Medicaid and Children’s Health Insurance Program (CHIP) coverage for young children, only 3.3 percent of children ages three and younger were uninsured in 2016. Coverage of both young children (age three and younger) and their parents increased under the Patient Protection and Affordable Care Act (ACA) (P.L. 111-148) in 2014 and 2015—a trend that continued in 2016. According to an Urban Institute report, young children and their families continued to rely on Medicaid and CHIP in 2016, with 48.5 percent of young children covered by Medicaid or CHIP. In comparison, only 42 percent of older children were covered by the programs.

Trends. Nearly half of young children and one-fifth of the parents of young children were covered by Medicaid and CHIP in 2015 as well. The high incidence of Medicaid and CHIP coverage is partly due to higher incidence of family characteristics among parents of younger children, including lower incomes, younger parents, and mixed immigration status.

Variance. Despite high overall levels of coverage, the prevalence of health insurance coverage for young children and their families continued to vary across state lines. Uninsurance rates were below 2 percent in 12 states but above 8 percent in three states—Alaska, Wyoming, and North Dakota. Additionally, the expansion of state Medicaid programs under the ACA continues to be a significant source of variation in state uninsurance levels for the parents of young children. For example, an estimated 8.7 percent of parents of young children in expansion states were uninsured in 2016, whereas 18 percent of parents of young children were uninsured in nonexpansion states.