About the Calculator

Overview
In response to the U.S. Supreme Court "Olmstead" decision, many states are now considering how best to strengthen their home- and community-based infrastructure, in order to provide improved personal care services to Medicaid-eligible individuals within the "most integrated setting possible." President Bush's New Freedom Initiative and the CMS Real Choices Systems Change Grants support these state efforts.

Many states have experimented with increased wages for personal assistance workers as one means of reducing high turnover rates and, thereby, strengthening their personal care programs*. Though anecdotal evidence suggests that these increases have a beneficial impact on the workforce and the availability of services for consumers, it has been difficult for states to quantify the economic and social benefits.

Consequently, with funding from the Centers of Medicaid and Medicare Services (CMS), the Paraprofessional Healthcare Institute (PHI) has created a return-on-investment (ROI) model that allows all states and the District of Columbia to analyze the potential impact of additional investment in the wages of personal assistance workers serving Medicaid clients.

The model, which has been developed into an easy-to-use on-line calculator, allows states to consider a wide range of factors -- including the size of a proposed wage increase, staff turnover costs and retention rates, and issues related to implementation design -- in assessing the economic and social impact of a wage increase for publicly funded personal assistance workers. Policymakers can use this information as they consider how to allocate resources most effectively in order to stabilize their direct-care workforce and, thereby, strengthen their personal care service infrastructure.

Analysis
The on-line calculator provides a first-level analysis for those seeking to understand the potential economic and social impact of additional state investments in wages for their home- and community-based personal assistance workforce. The calculator produces outputs in three areas for the user's consideration -- state budgetary consequences, affects on state economic activity, and non-economic social benefits.

1. The Federal Medicaid Match
2. Issues Related to Program Design and Financing
3. Public Assistance Savings
4. Increases in State Tax Revenues

Of these four, the dominant factor affecting state budgets is the federal share of the state's Medicaid expenditures. Depending on the state, the federal match ranges from 50 to nearly 77 percent. Thus, before any other factors are taken into consideration at least half the cost of a potential increase is born by the federal government.

The second factor in analyzing the cost to the state relates to program design. In many states there is an insufficient supply of workers to meet the demand for services. This means that some states have waiting lists for their personal assistance services programs because they do not have enough workers to serve clients. The ROI model assumes that if wages are raised, the supply of workers will increase because new workers will be attracted to the field and turnover among existing workers will be reduced. As a result more consumers will be able to be served in the community.

How much the workforce expands, however, depends to a large extent on how the state system of home- and community-based services is designed and financed. If these services are funded under a Medicaid waiver or if spending is constrained by a dollar budget amount, workforce growth may be constrained. For this reason, the calculator allows the user to adjust the variable defining workforce growth. To the extent that the state's program design permits workforce expansion, the tool calculates an estimate of the increased cost in wages for these new workers. These costs, however, are offset by the federal Medicaid match as well as the savings the state would accrue from serving more consumers in their homes rather than nursing facilities.

Increasing personal assistance worker wages affects other aspects of the state's budget as well. For example, a percentage of the wage increase may return to the state in income and sales tax. The amount of this offset depends on the state's tax rate. In addition, a number of current workers have earnings so low that they, or their children, qualify for Medicaid. In some instances, the wage increase will make them ineligible for Medicaid; the ROI model incorporates these anticipated savings. Where new workers find employment serving consumers whose needs are not currently being met, the ROI model assumes that there will be additional savings to the state's Transitional Aid to Needy Families (TANF) and Medicaid programs, since some of these new workers would otherwise be receiving public assistance benefits.

The federal match offsets a significant portion of the overall cost of the proposed wage increase, but with the addition of other savings, the state may end up shouldering only a fraction of the burden of the increased wages. The estimated cost to the state must take into account any anticipated savings from averted nursing facility placements, decreased utilization of a state's TANF and Medicaid programs, and increased revenue from income and sales tax.

Economic Multiplier Benefits
As noted above, a state's decision to increase the amount it spends on the wages of personal assistance workers brings in new dollars from the federal Medicaid match. While these dollars have a direct impact on the workers who receive higher salaries and on the state's budget, they also have a broader impact on the state's economy. The state's output of good and services increases, more dollars circulate through the economy, creating a multiplier effect. Workers spend these dollars on goods and services, allowing others to acquire additional goods and services in subsequent rounds of transactions. This spending translates into increased local retail sales; entertainment purchases at local restaurants, theaters and sporting facilities; service sector purchases (health, beauty, cleaning, repair, and other personal services), and major purchases such as automobiles and homes. The ROI model estimates the impact only on state business activity -- the increase in the output of goods and services -- but these dollars also generate new jobs and higher wages, stimulating the state's overall economic growth**.

Other Social Benefits
Given the current economic climate and the difficult budgetary situation faced by many states, policymakers are necessarily concerned about the immediate fiscal impact of increasing wages for personal assistance workers. It is important to understand, however, that increasing wags for these workers may result in significant long-term social benefits.

Investments in wages will help to stabilize the home- and community-based services system and reduce turnover among workers, potentially resulting tangible benefits for both providers and consumers. For instance, money that employers are currently using for recruiting, screening, hiring, and training new workers just to maintain a constant number of workers could be redeployed into other worker benefits such as health insurance or advanced training. For providers this could mean both greater efficiency for their organization and greater stability for their workforce.

Although not quantified within the ROI model, consumers also realize benefits from this reduction in turnover. With greater stability, consumers would likely face fewer instances when workers would be unavailable to provide services. In addition, the longer workers stay in the direct-care field, the greater their opportunity to form a longstanding relationships with their clients -- which is critical to both consumer satisfaction and quality of care.

By investing in workers, policymakers may make inroads against poverty in their state as well. Many personal assistance workers have incomes at or below federal poverty levels. Policymakers may wish to consider the number of families and children who are lifted out of poverty by an increase in personal assistance worker wages and how the investment per family or per child compares to other programs intended to reduce poverty.

Investment in personal assistance worker wages is an investment in the state's home- and community-based services infrastructure. Such investment has the potential to both stabilize and expand this workforce, allowing the home- and community-based services system to better serve consumers with disabilities who wish to remain in their own homes and communities. It may reduce the instances where consumers must be admitted to a nursing facility merely because of insufficient capacity to serve them in their communities. It may help states rebalance program expenditures to be more responsive to consumer preferences for services. Policymakers may wish to consider the cost of wage increases in relation to the number of new clients served in the community and the value they place on being able to serve consumers in the most integrated setting possible.

Model Structure
To assess net impact on each individual state of raising personal assistance workers wages, the ROI model calculates the impact on state income taxes, sales taxes, and public assistance. To do so, a single data sample was created and adjusted to reflect the circumstances in each state as detailed below:

• A representative sample of home care workers was composed from the 1999, 2000, 2001 and 2002 March Current Population Survey (CPS). The data from this sample included their hours of work, their wage, their family structure, and their family income.
  
  
• These national wage figures were then adjusted up or down to reflect the median wage for home care workers in each state, using data from the Bureau of Labor Statistics.***
  
  
• Family income was likewise adjusted up or down by average state-level family income of health care workers.
  
  
• Hours of work were uniformly scaled down so that the mean was 29 hours, which matches administrative data on work weeks of home care workers.
  
  
• Each family was then assigned a state and federal tax rate, based on the TAXSIM model available through the National Bureau of Economic Research.
  
  
• Wages are then increased by the user-defined amount.
  
  
• Based on hours of work, this yields a corresponding increase to family income, which affects tax revenues and other factors.
  
  
• When new workers join the home care sector due to induced demand, they are assumed to be the same as a random set of workers drawn from our existing sample.
  
  

Conclusion
The on-line calculator allows users to consider the wide-ranging ramifications of investing in their state's home- and community-based services workforce. The tool allows users to analyze the implications for their state budget by breaking down the total cost and identifying offsetting savings and returns. It illustrates the broad impact that an investment in wages may have on the state's economy, but equally importantly highlights benefits to workers, consumers, and providers -- those most directly affected by the state's home- and community-based services system.

* The national average for turnover of long-term care workers is estimated to be between 40 and 100 percent, depending on the facility or service type. See Katherine Mesirow et al. Improving certified nurse aide retention: A long-term care management challenge. The Journal of Nursing Administration 28(3) (March 1998): 56-61. Also Paraprofessional Healthcare Institute, Personal assistance services and direct-support workforce: A literature review (Bronx, NY, June 2003), available at http://www.directcareclearinghouse.org/download/CMS_Lit_Rev_FINAL_6.12.03.pdf.

** For more information on the stimulative effect of Medicaid spending see, FamiliesUSA, Medicaid:Good Medcine for State Economies. (Washington, DC: January 2003) available at http://www.familiesusa.org/site/DocServer/GoodMedicineReport.pdf?docID=275

*** U.S. Department of Labor. Bureau of Labor Statistics. 2002 OES National Industry-Specific Occupational Employment and Wage Estimates. (Washington, DC: November 2003) available at http://stats.bls.gov/oes/2002/oessrci.htm