Challenges in defining an optimal approach to formula-based allocations of public health funds in the United States

Abstract

Background: Controversy and debate can arise whenever public health agencies determine how program funds should be allocated among constituent jurisdictions. Two common strategies for making such allocations are expert review of competitive applications and the use of funding formulas. Despite widespread use of funding formulas by public health agencies in the United States, formula allocation strategies in public health have been subject to relatively little formal scrutiny, with the notable exception of the attention focused on formula funding of HIV care programs. To inform debates and deliberations in the selection of a formula-based approach, we summarize key challenges to formula-based funding, based on prior reviews of federal programs in the United States.

Discussion: The primary challenge lies in identifying data sources and formula calculation methods that both reflect and serve program objectives, with or without adjustments for variations in the cost of delivering services, the availability of local resources, capacity, or performance. Simplicity and transparency are major advantages of formula-based allocations, but these advantages can be offset if formula-based allocations are perceived to under- or over-fund some jurisdictions, which may result from how guaranteed minimum funding levels are set or from "hold-harmless" provisions intended to blunt the effects of changes in formula design or random variations in source data. While fairness is considered an advantage of formula-based allocations, the design of a formula may implicitly reflect unquestioned values concerning equity versus equivalence in setting funding policies. Whether or how past or projected trends are taken into account can also have substantial impacts on allocations.

Summary: Insufficient attention has been focused on how the approach to designing funding formulas in public health should differ for treatment or service versus prevention programs. Further evaluations of formula-based versus competitive allocation methods are needed to promote the optimal use of public health funds. In the meantime, those who use formula-based strategies to allocate funds should be familiar with the nuances of this approach.

Figure 1

a – AIDS cases by date of report, United States, 1984–1993 Legend: Number of AIDS cases by quarter year of report, United States, 1984–1993. AIDS surveillance criteria were modified in 1987[*] and 1993[†]). Source: Centers for Disease Control and Prevention.[15] b – AIDS cases by date of diagnosis, United States, 1986-1993 Estimated AIDS-opportunistic illness incidence (represents an estimate of AIDS trends if the surveillance definition had not been revised in 1993), adjusted for delays in reporting, by quarter year of diagnosis, United States, 1986-1993. Source: Centers for Disease Control and Prevention.[17]

Figure 2

Trends in hypothetical disease for State A and State B, 2000-2005. Number of cases of a hypothetical disease reported in two states by year of report. These data are to be used in a formula calculation to allocate public health program funds between States A and B beginning in January 2007.

Figure 3

Per capita allocation, Public Health Emergency Preparedness Funding Program, United States, 2005. For the budget period August 31, 2005 – August 30, 2006, the Centers for Disease Control and Prevention awarded $809,956,000 to states and territories using the following allocation formula: "Each State awardee and Puerto Rico will receive a base amount of $3.91 million, plus an amount equal to its proportional share of the national population as reflected in the U.S. Census estimates for July 1, 2003. The District of Columbia will receive a base amount of $10 million and New York City, Los Angles County, and Chicago will continue to receive a base amount of $5 million."[21] The graph shows the resulting per capita allocation for states and separately funded cities/counties, by the state or city/county population.