Ryan White Care Act of 1990: Opportunities to Enhance Funding Equity
(Letter Report, 11/13/95, GAO/HEHS-96-26).
Pursuant to a congressional request, GAO reviewed the funding formulas
established under the Ryan White Care Act, focusing on: (1) whether the
existing formulas distribute funds equitably to states and eligible
metropolitan areas (EMA); (2) the factors that inhibit greater funding
equity; and (3) formula changes that are needed to improve funding
equity.
GAO found that: (1) although Ryan White Care Act funding formulas
include factors used in equity-based formulas, they result in per-case
funding discrepancies because EMA cases are double counted; (2) states
without EMA do not benefit from double counting and receive
significantly less funding than states with EMA; (3) the indicators used
to target funds to needy states and EMA fail to take geographic cost
differences into consideration; (4) EMA funding levels are based on the
cumulative number of reported acquired immunodeficiency syndrome (AIDS)
cases, resulting in the oldest EMA receiving the most funding; (5)
better cost indicators could be used to target more funds to states and
EMA where resources are the most strained by AIDS; and (6) funding
equity could be improved by eliminating the inappropriate double
counting of AIDS cases and by using more appropriate measures of EMA and
state funding needs.
--------------------------- Indexing Terms -----------------------------
REPORTNUM: HEHS-96-26
TITLE: Ryan White Care Act of 1990: Opportunities to Enhance
Funding Equity
DATE: 11/13/95
SUBJECT: Acquired immunodeficiency syndrome
Funds management
Health care services
Health care costs
Public health legislation
Formula grants
Health care programs
Federal aid to states
Intergovernmental fiscal relations
Health resources utilization
IDENTIFIER: Medicare Hospital Wage Cost Index
Dallas (TX)
Oakland (CA)
New York (NY)
San Francisco (CA)
Miami (FL)
AIDS
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Cover
================================================================ COVER
Report to Congressional Requesters
November 1995
RYAN WHITE CARE ACT OF 1990 -
OPPORTUNITIES TO ENHANCE FUNDING
EQUITY
GAO/HEHS-96-26
Ryan White Funding Formulas
(118109)
Abbreviations
=============================================================== ABBREV
AIDS - acquired immunodeficiency syndrome
CARE - Comprehensive AIDS Resources Emergency
CDC - Centers for Disease Control and Prevention
EMA - eligible metropolitan area
GSP - Gross State Product
HHS - Department of Health and Human Services
HIV - human immunodeficiency virus
HCFA - Health Care Financing Administration
MHWC - Medicare Hospital Wage Cost (Index)
PCI - per capita income
PPS - prospective payment system
SPNS - Special Projects of National Significance
TTR - total taxable resources
Letter
=============================================================== LETTER
B-265841
November 13, 1995
The Honorable Nancy Kassebaum
Chairman, Committee on Labor
and Human Resources
United States Senate
The Honorable Hank Brown
United States Senate
The human immunodeficiency virus (HIV) epidemic has become one of the
most serious health threats to the American public. The HIV
infection rate is estimated to be as high as 1 in every 250 persons
nationwide. Metropolitan areas are especially affected by HIV with
rates as high as 1 in 25. By December 1994, nearly 450,000 people
with HIV had been reported to have progressed to acquired
immunodeficiency syndrome (AIDS), and more than 270,000 had been
reported to have died of the disease. Currently, only one federal
program provides funds specifically for medical and support services
to individuals with AIDS and HIV. Established by the Ryan White
Comprehensive AIDS Resources Emergency (CARE) Act of 1990, the
program distributed more than $579 million in fiscal year 1994 to
eligible metropolitan areas (EMA) through title I of the act and to
states through title II.
Citing examples of disparities in per-case funding, you expressed
concerns that the existing title I and II funding formulas may lead
to an inequitable distribution of funds to states and EMAs. For this
reason, you asked us to determine (1) how equitably the existing
formulas are distributing title I and II funds, (2) which factors
inhibit the formulas from achieving greater equity, and (3) what
formula changes could improve equity.
To assess the title I and II formulas, we reviewed the enacting
legislation and conducted interviews to examine the basic rationale
for the factors used in the current CARE Act formulas. We compared
the funding distributions resulting from the existing formulas
against two widely recognized equity criteria.
The first criterion--beneficiary equity--considers the degree to
which a formula allocates funds to ensure that EMAs and states are
able to purchase a comparable level of services for their HIV
populations. Under this criterion, dollars would be distributed
according to two indicators: (1) the potential number of people with
AIDS (that is, caseload) and (2) the cost of providing services. The
second criterion--taxpayer equity--considers the degree to which EMAs
and states are able to finance a comparable level of services with
comparable burdens on their taxpayers. This second standard is
broader than the first one. In addition to including the two
indicators used in the first standard (caseload and cost), it uses a
measure of each EMA's and state's capacity to fund AIDS and HIV
services from its own resources.\1
On the basis of interviews with experts and a review of available
literature, we identified data with which to apply these standards to
assess the equity of the title I and II formulas.\2
We used Centers for Disease Control and Prevention (CDC) data to
develop a proxy measure of people living with AIDS, Health Care
Financing Administration (HCFA) data to measure differences in
service costs, and Department of Treasury data to determine fiscal
capacities. We used regression analysis to determine how closely the
distribution of CARE Act funds reflected our equity standards.
We conducted our work from February 1994 through October 1995 in
accordance with generally accepted government auditing standards.
--------------------
\1 See the bibliography for other studies that describe these
criteria.
\2 The experts we interviewed were officials of the Agency for Health
Care Policy and Research, the Centers for Disease Control and
Prevention, the Health Care Financing Administration, and the Health
Resources and Services Administration.
RESULTS IN BRIEF
------------------------------------------------------------ Letter :1
Although the title I and II funding formulas currently include some
factors used in equity-based formulas, they result in wide variations
in per-case funding for several reasons. The most important is that
EMAs' AIDS cases are double counted; once when calculating funding
for EMA medical services under title I and again when calculating
funding for state medical and other services under title II. A state
without an EMA does not benefit from double counting and receives
substantially less funding than a state with an EMA.
In addition to double counting, the indicators used to target funds
to high-need states and EMAs are inaccurate and could be improved.
For example, we found evidence of large geographic differences in the
cost of serving AIDS patients, yet neither the title I nor the title
II formula takes these differences into account. Also, the title I
formula targets funding to EMAs on the basis of their cumulative
number of reported AIDS cases, yet over 60 percent of these reported
cases have since died. As a result, the oldest EMAs receive the most
generous funding, and newly emerging EMAs with more recent growth in
AIDS cases receive less funding.
Finally, both title I and title II attempt to target more funds to
states and EMAs where resources are most strained by the epidemic.
However, the indicators used in both formulas are inadequate. The
indicator used in the title I formula (AIDS incidence rate) does not
directly take into account an EMA's tax base, which determines the
area's own capacity to provide services to people with HIV. The
opposite is true for the title II formula. A tax base indicator is
used (state per capita income), but the effect of a high AIDS
incidence rate on the tax base is ignored.
Funding equity can be improved by changing the structure of the two
formulas to eliminate the inappropriate double counting of AIDS cases
and by using more appropriate measures of EMA and state funding
needs.
BACKGROUND
------------------------------------------------------------ Letter :2
The Congress enacted the Ryan White CARE Act on August 18, 1990, to
"improve the quality and availability of care for individuals and
families with HIV disease." The CARE Act makes funds available
through four titles to states, EMAs, and nonprofit entities for
developing, organizing, coordinating, and operating more effective
and cost-efficient service delivery systems. The Health Resources
and Services Administration, part of the Department of Health and
Human Services' U.S. Public Health Service, administers the program.
Over $579 million in CARE Act funds were appropriated in fiscal year
1994 for services to people with AIDS and HIV. About $326 million
(56 percent) of these funds were appropriated for title I, which
provides "emergency assistance" to EMAs--metropolitan areas
disproportionately affected by the HIV epidemic. Half of title I
funds are distributed by formula, and half are distributed
competitively. To be eligible, a metropolitan area must have a
cumulative count of more than 2,000 cases of AIDS since reporting
began in 1981 or a cumulative count of AIDS cases that exceeds
one-quarter of 1 percent of its population. In fiscal year 1994,
there were a total of 34 EMAs in 17 states, the District of Columbia,
and Puerto Rico. Since fiscal year 1991, the number of EMAs has more
than doubled.
For title II, $184 million (32 percent of total CARE Act funds) were
appropriated in fiscal year 1994. Title II provides funds to states
to improve the quality, availability, and organization of health care
and support services for people with HIV. Of the title II funds
distributed to the states in fiscal year 1994, 90 percent were
distributed by formula, and 10 percent were distributed competitively
through Special Projects of National Significance.\3
The remaining titles--titles IIIb and IV--were funded at about $48
million (8 percent) and $22 million (4 percent), respectively, in
fiscal year 1994. Title IIIb funds are intended for early
intervention programs, and title IV funds are intended for pediatric
AIDS programs. Under both of these titles, funds are awarded
competitively.
--------------------
\3 Special Projects of National Significance (SPNS) are competitive
grants awarded to public and nonprofit organizations to advance
knowledge and skills in the delivery of health and support services
to people with HIV.
THE EXISTING FORMULAS MEET
NEITHER EQUITY CRITERION
------------------------------------------------------------ Letter :3
Our examination of the existing title I and II formulas indicates
that neither formula meets the beneficiary and taxpayer equity
criteria. Per-case funding is not systematically related to either
EMA or state service costs or their fiscal capacity. (See app. II
for details of our analysis.)
THE TITLE I FORMULA DOES NOT
MEET EITHER EQUITY CRITERION
---------------------------------------------------------- Letter :3.1
The title I formula does not meet the beneficiary equity criterion
because per-case funding is not systematically related to the cost of
treating people with HIV. Specifically, our analysis of fiscal year
1994 funding for EMAs showed that per-case funding ranged from $818
to $2,663--a difference of over 200 percent. However, only 10
percent of this variation was related to cost differences\4 --though
the cost differences themselves were significant. As an
illustration, the Dallas and Oakland EMAs each received title I
allocations of approximately $1,200 per person with AIDS, but the
cost of providing health care services in Oakland is about 37 percent
higher than in Dallas.
The title I formula also does not meet the taxpayer equity criterion
because, in addition to not being systematically related to cost
differences, EMA grant amounts are not highly related to the EMAs'
fiscal capacity. Our analysis of fiscal year 1994 funding for all
EMAs showed that more than 40 percent of the variation in EMAs'
per-case funding was unrelated to differences in cost and fiscal
capacity. For example, the Dallas and Oakland EMAs received about
the same per-case funding, but Oakland's funding capacity when
measured in terms of its tax base, costs, and concentration of AIDS
cases is about 17 percent lower than that of Dallas.
--------------------
\4 The two EMAs located in Puerto Rico--Ponce and San Juan--were
excluded from this analysis. With these EMAs included in the
analyses, cost differences account for only 2 percent of the
variation in per-case funding.
COMBINED TITLE I AND II
FUNDING MEETS NEITHER EQUITY
CRITERION
---------------------------------------------------------- Letter :3.2
The distribution of combined title I and II funds across states does
not meet either the beneficiary or the taxpayer equity criterion.\5
Total per-case funding for California and New York is about 20
percent and 30 percent above the national average, respectively,
while Hawaii, Ohio, and Vermont have total per-case funding levels
about 50 percent below the national average. These funding
differences are not strongly related to differences in states' costs
and fiscal capacity to provide services. Our statistical analysis
found that differences in service costs and fiscal capacity account
for 33 percent of these differences in per-case funding.\6 That is,
67 percent of the variation in state funding per AIDS case is
unrelated to states' funding needs. (See app. II for details.)
--------------------
\5 We compared the total amount of title I and II funds within each
state to assess interstate funding equity. We did not conduct a
separate assessment of title II funds because of the difference in
the purposes of these funds between states with and without EMAs.
\6 To develop a more valid estimate, we excluded from our analysis
those states that received the minimum title II grant amount of
$100,000.
FUNDING INEQUITIES RESULT FROM
THE STRUCTURE AND COMPONENTS OF
THE FORMULAS
------------------------------------------------------------ Letter :4
Several features of the title I and II formulas contribute to the
funding inequities we have identified. Specifically, inequities
occur because EMA cases are counted in both the title I and II
formulas, an inappropriate caseload measure is included in the title
I formula, an inappropriate measure of EMAs' and states' fiscal
capacity is included in both formulas, and neither formula includes a
measure of EMAs' and states' service costs. (See appendixes for
details.)
DOUBLE COUNTING EMA CASES
---------------------------------------------------------- Letter :4.1
Our analysis of differences in states' per-case funding amounts
indicates that about half of the variation is due to the double
counting of EMA cases in both the title I and II formulas rather than
differences in funding needs (that is, cost or fiscal capacity
differences). States where most cases live in EMAs receive the
largest amounts per case, since larger proportions of their caseloads
are double counted. For example, per-case funding was about $1,100
in states without an EMA, $1,700 in states where less than half the
state's caseload lived in an EMA, and $2,200 in states where more
than half of the caseload lived in an EMA (see fig. 1). Thus, most
of the variation in per-case funding can be explained by the extent
to which a state's caseload is double counted rather than by the
state's funding needs.
Figure 1: State Funding by
Proportion of AIDS Cases
Residing in an EMA
(See figure in printed
edition.)
INAPPROPRIATE TITLE I
CASELOAD MEASURE
---------------------------------------------------------- Letter :4.2
The title I caseload measure is based on the cumulative number of
people with AIDS that EMAs reported to CDC since 1981 when reporting
began. By the end of 1993, however, two-thirds of these people had
been reported to have died and were, therefore, no longer using
services funded by title I.
Because the formula includes deceased persons, the EMAs that
experienced the first outbreak of AIDS receive substantially more
per-case funding than do newer EMAs. For example, in fiscal year
1994, the 18 EMAs that were eligible to receive title I funds in the
first 2 years of eligibility--1991 and 1992--were funded at about
$1,500 per case. In contrast, the 16 EMAs that became eligible in
1993 and 1994 were funded at only about $1,000 per case--one-third
less than the older EMAs (see fig. 2).
Figure 2: Fiscal Year 1994
Funding per Case
(See figure in printed
edition.)
Note: Early EMAs are the 18 that entered the program during 1991 and
1992; later EMAs are the 16 that entered in 1993 and 1994.
ABSENCE OF A COST MEASURE
---------------------------------------------------------- Letter :4.3
While the cost of providing AIDS and HIV services varies among EMAs
and states, neither the title I nor title II formula includes a
factor to measure those differences. Information on the actual costs
of providing health and support services to people with AIDS and HIV
within different geographic areas is not available. However, most of
the delivery costs appear to be associated with the personnel who
provide the labor-intensive outpatient health, support, and case
management services titles I and II primarily fund. A proxy measure
for these labor costs is available through the Medicare Hospital Wage
Cost Index.\7
Using this index for title I cities, we estimated that the cost of
providing medical services was about 30 percent above the national
average in the New York, Oakland, and San Francisco EMAs and about 10
percent below the national average in the Miami EMA--a difference of
about 40 percent. This suggests that the New York, Oakland, and San
Francisco EMAs must spend much more than the Miami EMA to provide a
comparable level of services to their patients. Similarly, under
title II, we estimated that the cost of providing medical services
was more than 15 percent above the national average in the states of
Alaska, California, and New York, about 15 percent below the national
average in Alabama and Arkansas, and about 20 percent below the
national average in Mississippi.
--------------------
\7 The Medicare Hospital Wage Cost Index was designed to reflect
personnel costs in hospitals subject to the Medicare prospective
payment system; it was derived from hospital salary surveys.
INAPPROPRIATE FISCAL
CAPACITY MEASURES
---------------------------------------------------------- Letter :4.4
State and EMA fiscal capacity depends on the size of the tax base and
the service demands placed on that tax base. The current title I
formula measures the demand for services through the use of an AIDS
incidence rate factor, but the strength of each EMA's tax base is not
included. As a result, the title I formula does not adequately
adjust EMAs' allocations to target those with smaller tax bases and
fewer resources to draw upon to meet the needs of the cases they must
serve.
The title II formula does measure the strength of each state's tax
base through the use of per capita personal income. However, it does
not consider the demand for services that is placed on state tax
bases. As a result, the title II formula does not adequately adjust
state allocations to target states with tax bases that are burdened
by a heavy demand for services.
GREATER FUNDING EQUITY CAN BE
ACHIEVED
------------------------------------------------------------ Letter :5
Greater funding equity can be achieved by changing the formulas'
structure and components. The formulas can be modified to make their
funding distribution meet either the beneficiary equity criterion or
the taxpayer equity criterion. Alternatively, although no formula
can completely satisfy both criteria simultaneously, the formulas
could be modified to partly meet both criteria, emphasizing
beneficiary equity over taxpayer equity or vice versa. Regardless of
which criterion is emphasized, however, the following changes could
make the title I and II formulas more equitable. (See appendixes for
details.)
INEQUITIES CREATED BY DOUBLE
COUNTING COULD BE AVOIDED
---------------------------------------------------------- Letter :5.1
The current title I and II structure could be revised to avoid
inequities created by counting EMA cases in both formulas.
Presently, funding for titles I and II does not always reflect the
division of service responsibilities between EMAs and state
governments. Through title I, EMAs provide medical and support
services to people who reside in their areas of coverage. Through
title II, states provide medical and support services to people
living outside EMAs and commonly provide these services to people
living in EMAs as well. In addition, through title II, states
administer services such as medication assistance and insurance
continuation statewide for cases both within and outside of their
EMAs.\8 Nonetheless, while EMAs typically provide the bulk of medical
services to people living within their areas, title II provides
funding as if states were providing both medical and statewide
services to the EMA cases. This results in a higher level of
per-case funding for states with EMAs because the EMA cases are
double counted.
A more equitable structure would, in effect, double count all cases.
Cases would be counted once for the statewide services such as
medication assistance and insurance continuation, and again for
medical services that are jointly provided by states and EMAs.
One means for achieving this would be to make separate appropriations
for the major activities funded by the CARE Act. One appropriation
would be made for services that state governments provide statewide,
and a second appropriation would be made for medical services that
are jointly provided by states and their EMAs (see fig. 3).\9
Figure 3: Proposed Structure
(See figure in printed
edition.)
Funding for statewide services would be allocated to state
governments on the basis of each state's total AIDS caseload.
Funding for medical services would be divided into two separate
allocations for state governments and EMAs. The allocation to state
governments would be based on AIDS cases living outside a state's
EMAs. The allocation to EMAs would be based on AIDS cases living in
their service delivery areas. With this method, each state's entire
caseload is counted twice: once for funding statewide services and
again for funding state-EMA medical services.
The approach would only be a means of allocating federal funds to the
entities responsible for delivering services and would not change the
latitude currently afforded local governments and states in deciding
how to best use those funds. Consequently, this approach should have
only a minimal effect on existing service delivery structures because
it leaves EMA and state responsibilities essentially unchanged.
--------------------
\8 In some cases, EMAs provide funds to the state for the statewide
medication assistance program.
\9 A third appropriation could be made for discretionary purposes
(that is, for competitive grants, evaluations, and technical
assistance).
BETTER INDICATORS OF
CASELOAD, COST, AND CAPACITY
WOULD IMPROVE EQUITY
---------------------------------------------------------- Letter :5.2
In addition to changing the structure of the formulas, funding equity
could be improved by changing the formulas' components.
Specifically, funding equity could be improved by modifying the
existing caseload and fiscal capacity measures, and by including a
cost measure.
First, funding equity could be improved by including a caseload
measure that better reflects the number of people living with AIDS
and excludes deceased persons. We have developed a proxy measure of
people living with AIDS from existing CDC data.
Funding equity could also be improved by including a cost measure,
such as the Medicare Hospital Wage Cost Index. Use of such a measure
would better compensate the EMAs and states that must pay more to
provide services to their patients because of their higher private
sector health care costs.
Finally, to increase resources in states and EMAs with poorer fiscal
capacity, the current fiscal capacity factors could be revised to
better measure the EMAs' and states' AIDS incidence rates and tax
bases. Currently, the title I fiscal capacity factor lacks a measure
of EMAs' tax bases, and the title II factor lacks a measure of
states' AIDS incidence rates. By having more complete measures of
EMA and state fiscal capacities, the formulas could adjust grants on
the basis of both the demand for services and the strength of tax
bases. In addition, using total taxable resources (TTR) in the state
formula instead of personal income could result in a more
comprehensive measure of state tax bases. (For the effects of these
changes on specific state and EMA grants, see app. V.)
CONCLUSIONS
------------------------------------------------------------ Letter :6
Our analysis of the existing formulas demonstrates that federal
funding under titles I and II of the CARE Act can be made more
equitable. An important purpose of the Ryan White CARE Act was to
target emergency funding to areas of greatest need. At the time the
law was enacted, high incidences of HIV were found in fewer areas of
the country, service delivery networks were just beginning to form,
and these service delivery systems had to rely primarily on private
and volunteer resources. In the past 5 years, however, the HIV
epidemic has become more widespread and less localized. Hence, areas
where the AIDS caseload has burgeoned recently need per-case funding
levels comparable to those in areas where AIDS was initially
concentrated.
RECOMMENDATIONS TO THE CONGRESS
------------------------------------------------------------ Letter :7
To achieve greater equity in the distribution of funds, we recommend
that the Congress modify the funding formulas to
reduce the double counting of EMA cases so that comparable medical
services funding is available for people with AIDS, regardless
of where they live,
adopt a caseload indicator that better reflects the number of
people living with AIDS who are in need of services, and
include an indicator that reflects the relative differences across
states and EMAs in the cost of serving people with AIDS.
MATTERS FOR CONGRESSIONAL
CONSIDERATION
------------------------------------------------------------ Letter :8
If the Congress wishes to target more aid to states and EMAs with
limited fiscal capacity, then it may consider adopting an indicator
that reflects the relative strength of local tax bases and
concentrations of people with AIDS. Alternatively, the Congress may
wish to discontinue the use of AIDS incidence rates in the title I
formula and per capita income in the title II formula because of the
funding inequities that these components produce.
Finally, modifying the formulas to achieve a more equitable
distribution of funds will involve significant changes in grants to
some EMAs and states. To avoid possible disruption of service
delivery, the Congress may wish to consider phasing in formula
modifications. This should minimize, if not avoid, disruption for
the service delivery networks the CARE Act has made possible over the
last 5 years.
---------------------------------------------------------- Letter :8.1
If you or your staff have any questions regarding this report, please
contact me on (202) 512-7119 or Jerry Fastrup, Assistant Director, on
(202) 512-7211. Major contributors to this report are listed in
appendix VII.
William J. Scanlon
Associate Director,
Health Financing Issues
ASSESSING THE EQUITY OF THE
FUNDING FORMULAS
=========================================================== Appendix I
To determine how equitably title I and II funds are distributed, we
examined the existing formulas, applied two widely recognized equity
criteria, and determined whether the existing or alternative formula
factors would best allocate funds according to these standards.
EXISTING FORMULAS
--------------------------------------------------------- Appendix I:1
Title I funds are distributed on the basis of the cumulative number
of AIDS cases EMAs report and their cumulative AIDS incidence rate.
where
In this formula,
Casesi = the cumulative number of AIDS cases in the ith EMA,
REMA = the per capita incidence of cumulative AIDS cases in an EMA,
RAll EMAs = the per capita incidence of cumulative AIDS cases in all
EMAs.
Note: i ranges over all EMAs.
Title II funds are distributed to states on the basis of the number
of AIDS cases they reported in the 2 most recent fiscal years and
their per capita income.
where
In this formula,
Casesi = the number of cases reported by the ith state in the 2 most
recent fiscal years,
PCI = the average per capita income of the ith state/the United
States.
Note: i ranges over all states, the District of Columbia, and
territories.
EQUITY CRITERIA
--------------------------------------------------------- Appendix I:2
The two standards of equity that we applied were the beneficiary and
taxpayer equity criteria. To meet the beneficiary equity criterion,
funding should be distributed in a way that enables EMAs and states
to purchase comparable levels of AIDS and HIV medical and support
services. In other words, per-case funding should be about the same
in each of the EMAs and states after adjusting for cost differences.
The formula for producing a funding distribution that meets the
beneficiary equity criterion is
In this formula,
Casesi = the number of people in need of services in the ith EMA or
state,
Cost Indexi = an index measuring relative differences in the per-case
cost of serving recipients in the ith EMA or state,
A = the total amount of funds to be allocated.
Note: i ranges over all EMAs/the District of Columbia, all states
and territories.
To meet the taxpayer equity criterion, funding should be distributed
in a way that enables EMAs and states to purchase comparable levels
of AIDS and HIV services with comparable burdens on their taxpayers.
Therefore, under this criterion, per-case funding should be about the
same in each of the EMAs and states, once adjusted for differences in
their service costs and fiscal capacities. Per-case funding should
only differ to the extent that costs and fiscal capacities do. The
formula for producing a funding distribution that meets the taxpayer
equity criterion is
In this formula, cases and costs are the same as in the beneficiary
equity formula and represent an EMA's or state's funding need. The
federal percentage represents the share of an EMA's or state's
funding need that will be counted in the formula and varies with
EMAs' and states' fiscal capacity according to the following
formula:\10
The fiscal capacity index represents the ability of grantees to fund
services from state and local resources. We applied a weight of 0.20
to this index because that is the weight implicitly applied to fiscal
capacity through the AIDS incidence rate found in the existing title
I formula.\11
As shown in the preceding figures, to meet the beneficiary equity
standard, the funding formula would base its allocation on states' or
EMAs' cases and costs, and to meet the taxpayer equity standard, the
formula would also include a fiscal capacity factor. Hence, in
determining whether the formulas distribute title I and II funds in
accordance with the beneficiary and taxpayer equity criteria, we
sought indicators that were reflective of these three factors and
were appropriate for use in grant allocation formulas.
--------------------
\10 Equalizing taxpayer burdens requires the mathematical form shown
here. See Maternal and Child Health: Block Grant Funds Should Be
Distributed More Equitably (GAO/HRD-92-5, Apr. 2, 1992), pp. 55-62,
for a more detailed discussion and derivation of this formula.
\11 The existing title II fiscal capacity factor does not adjust
states' per capita income by their AIDS incidence, which results in a
perverse allocation of title II funds. Because of this, we did not
use the weight associated with the existing title II fiscal capacity
factor.
CASELOADS
--------------------------------------------------------- Appendix I:3
We considered four approaches to estimating the number of people
living with AIDS in each of the EMAs and states:
cumulative AIDS cases,
AIDS cases less reported deaths,
AIDS cases reported in the 2 most recent years, and
weighted AIDS cases.
The first approach--cumulative AIDS cases--is the caseload measure
found in the current title I formula. In the context of our equity
criteria, this approach assumes that the number of people currently
living with AIDS can be estimated by using the cumulative number of
AIDS cases reported since 1981. About 66 percent of these AIDS cases
are no longer living, however, and the likelihood of death increases
substantially the longer one has AIDS. As a result, this measure
would direct funds more to where the epidemic occurred initially
rather than to where it appeared more recently.
The second approach--AIDS cases less reported deaths--subtracts each
state's and EMA's total reported deaths from their total reported
AIDS cases for the 10 most recent years. The total number of living
cases is then determined by adding each year's surviving cases.
While this approach appears to potentially provide a reasonable
estimate of the number of people living with AIDS, it is not an
appropriate caseload measure for allocating funds. Our interviews
with experts and our review of the literature indicated that this
estimate would be biased because AIDS-related deaths are more
extensively and quickly reported in some states and EMAs than in
others, and this results in measurement errors. Furthermore, since
funds are based on the number of people living with AIDS, those
states and EMAs that underreport AIDS-related deaths would be
rewarded, while others with more reliable reporting would, in effect,
be penalized. Many of the experts we interviewed expressed concerns
that this method could introduce incentives to purposely underreport
deaths. Consequently, states and EMAs might delay or not even report
these deaths, which could lead to another bias to the caseload
measure and result in less reliable information on the lifespans of
people with the disease.
The third approach that we considered uses the number of AIDS cases
reported in the most recent 2 years to estimate the number of living
AIDS cases. This is the caseload measure currently used in the title
II formula, and it appears to reasonably estimate the number of
living cases. However, because this measure consists of cases from a
narrow time frame, we believe it could be too sensitive to sudden
caseload changes and disrupt the continuity of funding over time.
Also, the expected lifespans for people with AIDS could increase over
time. If this occurs in the future, the cases reported in a 2-year
interval may not accurately reflect the number of people living with
the disease.
The final approach--weighted AIDS cases--is a proxy measure of living
AIDS cases. This approach estimates the number of AIDS cases living
in an EMA or state on the basis of on the number of AIDS cases
reported to CDC for each of the most recent 10 years and national
average survival rates since a case was first reported.
Specifically, the number of AIDS cases that an EMA or a state had
reported for each of these 10 years would be weighted by the national
percentage of cases estimated to be living as of the first day of the
most recent year of that period.\12 These percentages would be
estimated from national data on the number of people reported to have
AIDS during a 10-year period who had not been reported to have died
of the disease.
Table I.1 shows the cumulative survival rates for each of 10 years as
of fiscal year 1992. According to these data, 88 percent of the
cases reported in 1992 were estimated to have survived at least 1 day
in that year, and 57 percent of the prior year's cases were estimated
to still be alive as of that date.
Table I.1
Cumulative AIDS Survival Rates for a 10-
Year Period
Proportion
surviving
Year reported with AIDS into FY 1992
------------------------------------ --------------------
FY 1992 .88
FY 1991 .57
FY 1990 .37
FY 1989 .24
FY 1988 .16
FY 1987 .10
FY 1986 .08
FY 1985 .06
FY 1984 .06
FY 1983 .06
----------------------------------------------------------
This approach appears to be the most appropriate. Unlike the
cumulative AIDS cases measure, it has been adjusted to account for
people with AIDS who are no longer living and thus better reflects
the intended service population. In contrast to the second approach,
this one averages out differences in reporting mortality and avoids
incentives to underreport deaths. Specifically, since the algorithm
for estimating living cases would be based on national data, any
uniqueness in how states and EMAs report mortality would not affect
the amount of funds that they would receive. Finally, this measure
applies differential weights to cases from a wide time frame. As a
result, sudden caseload changes should not significantly disrupt
funding continuity over time. Also, this measure can be adjusted to
recognize changes in AIDS mortality.
--------------------
\12 Basing our estimate on the number of people who survived as of
this date means that it includes the largest number of people that
could potentially need services during the last year of that period.
In contrast, an estimate based on the number of people who had
survived the entire last year of that period would tend to
underestimate the population in need of services. This is because
people who had survived part, but not all, of the last year would be
omitted from the population even though they had potentially used
services sometime during that last year.
CURRENT CASELOAD MEASURES COULD
BE IMPROVED
--------------------------------------------------------- Appendix I:4
Table I.2 compares the proxy measure of people living with AIDS based
on weighted-AIDS cases and the proxy measure based on cumulative AIDS
cases--the existing title I case measure--for each of the EMAs as of
December 1993. Also shown is each EMA's caseload share based on
these measures. Since funds are distributed on the basis of caseload
shares rather than number of cases, the former is actually the more
relevant measure from a formula perspective.
The extent to which the cumulative case measure distorts EMAs' demand
for services is shown by the differences in weighted and cumulative
caseload shares. For example, the cumulative case measure
overestimates caseload shares for the New York City, San Francisco,
Newark, and Jersey City EMAs from 7.85 to 15.52 percent. Conversely,
the cumulative case measure underestimates demand for services in
EMAs such as Riverside-San Bernardino, Orlando, St. Louis, Tampa-St.
Petersburg, and Phoenix from 13.22 to 18.39 percent. These
differences reflect the distortions created by the large number of
deceased persons in the case counts for the older and larger EMAs.
Table I.2
Title I Caseload Counts
Coun Shar Coun Shar Percentage
t e t e difference
EMA (#) (%) (#) (%) \a
---------------------- ---- ---- ---- ---- ----------
New York, NY 23,4 21.4 58,8 23.2 8.12
84 6 96
San Francisco, CA 7,23 6.61 18,1 7.13 7.85
8 07
Los Angeles, CA 9,51 8.69 22,7 8.95 2.93
2 10
Miami, FL 5,11 4.67 10,9 4.32 -7.51
3 70
Newark, NJ 3,24 2.97 8,20 3.23 8.98
6 7
Houston, TX 3,94 3.61 9,53 3.76 4.17
8 9
Washington, DC 4,37 4.00 10,1 3.99 -0.24
6 27
Chicago, IL 4,27 3.91 9,78 3.85 -1.36
6 4
Atlanta, GA 3,09 2.83 7,18 2.83 0.17
2 4
Fort Lauderdale, FL 2,33 2.13 5,53 2.18 2.25
2 0
Philadelphia, PA 3,72 3.40 7,93 3.12 -8.18
5 3
Dallas, TX 2,70 2.47 6,08 2.40 -3.09
8 8
Boston, MA 3,28 3.01 7,06 2.78 -7.36
9 8
Jersey City, NJ 1,19 1.09 3,20 1.26 15.52
4 0
San Diego, CA 2,44 2.23 5,29 2.09 -6.60
5 8
Oakland, CA 1,89 1.73 4,32 1.70 -1.84
9 3
Baltimore, MD 2,51 2.29 5,02 1.98 -13.77
0 1
New Orleans, LA 1,28 1.17 3,10 1.22 4.44
2 7
Seattle, WA 1,64 1.50 3,70 1.46 -2.67
0 2
Tampa-St. Petersburg, 2,04 1.86 4,06 1.60 -13.99
FL 0 9
Orange County, CA 1,28 1.17 2,96 1.17 -0.51
5 6
Nassau-Suffolk, NY 1,45 1.33 3,36 1.32 -0.24
3 3
Detroit, MI 1,80 1.65 3,65 1.44 -12.71
3 0
West Palm Beach, FL 1,39 1.28 3,18 1.26 -1.59
7 8
Denver, CO 1,47 1.35 3,09 1.22 -9.46
5 8
Orlando, FL 1,25 1.15 2,39 0.94 -18.09
8 1
Riverside-San 1,58 1.45 3,00 1.18 -18.39
Bernardino, CA 7 4
Bergen-Passaic, NJ 1,11 1.02 2,64 1.04 2.27
3 1
Kansas City, MO 1,08 0.99 2,29 0.90 -8.77
3 2
New Haven, CT 1,35 1.24 2,85 1.12 -9.08
4 5
Phoenix, AZ 1,12 1.03 2,27 0.89 -13.22
9 2
St. Louis, MO 1,23 1.13 2,39 0.94 -16.18
3 8
San Juan, PR 3,24 2.97 7,29 2.87 -3.23
8 1
Ponce, PR 676 0.62 1,59 0.63 1.79
5
----------------------------------------------------------
\a While the data in the table have been rounded to two decimal
positions, the percentage differences were computed based on
additional decimal positions.
Table I.3 compares our proxy measure of people living with AIDS that
is based on weighted living cases and the existing title II case
measure--2 years of cases--for each of the states and territories as
of December 1993. The table also shows the caseload shares based on
these two measures. Once again, an examination of caseload shares
under these two methods demonstrates the distortions that result from
using only 2 years of cases to estimate the number of people living
with AIDS. The measure overestimates caseload shares for Delaware
and South Dakota from 9.61 to 17.94 percent and underestimates
caseload shares for Hawaii, Montana, and New Jersey from 5.22 to 7.18
percent.
Table I.3
Title II Caseload Counts
Case Shar Case Shar Percentage
s e s e difference
State (#) (%) (#) (%) \a
---------------------- ---- ---- ---- ---- ----------
Alabama 1,16 0.73 1,17 0.76 4.82
4 3
Alaska 90 0.06 87 0.06 0.89
Arizona 1,58 0.99 1,62 1.05 6.05
9 1
Arkansas 664 0.41 684 0.44 7.16
California 28,2 17.6 27,3 17.7 0.49
99 7 46 6
Colorado 1,77 1.11 1,73 1.12 1.61
3 2
Connecticut 2,37 1.48 2,40 1.56 5.20
5 3
Delaware 483 0.30 509 0.33 9.61
District of Columbia 2,42 1.52 2,28 1.49 -2.07
9 8
Florida 16,5 10.3 16,0 10.4 0.43
74 5 07 0
Georgia 4,36 2.73 4,12 2.68 -1.84
9 4
Hawaii 556 0.35 496 0.32 -7.18
Idaho 111 0.07 112 0.07 4.55
Illinois 4,96 3.10 4,86 3.16 2.05
0 8
Indiana 1,34 0.84 1,35 0.88 4.73
3 3
Iowa 305 0.19 313 0.20 6.85
Kansas 524 0.33 546 0.35 8.26
Kentucky 548 0.34 537 0.35 1.99
Louisiana 2,35 1.47 2,21 1.44 -1.88
1 8
Maine 207 0.13 193 0.13 -3.27
Maryland 3,73 2.33 3,73 2.42 3.84
5 0
Massachusetts 3,69 2.31 3,57 2.32 0.64
2 3
Michigan 2,56 1.60 2,56 1.67 4.14
0 4
Minnesota 897 0.56 877 0.57 1.71
Mississippi 739 0.46 722 0.47 1.58
Missouri 2,46 1.54 2,45 1.59 3.72
1 5
Montana 58 0.04 53 0.03 -5.55
Nebraska 242 0.15 240 0.16 3.12
Nevada 896 0.56 887 0.58 2.95
New Hampshire 184 0.11 171 0.11 -3.13
New Jersey 8,19 5.12 7,46 4.85 -5.22
5 9
New Mexico 414 0.26 401 0.26 0.80
New York 27,5 17.2 25,8 16.7 -2.62
93 3 39 8
North Carolina 2,01 1.26 1,95 1.27 0.42
9 0
North Dakota 20 0.01 20 0.01 1.85
Ohio 2,39 1.49 2,33 1.52 1.57
1 6
Oklahoma 962 0.60 989 0.64 6.93
Oregon 1,09 0.69 1,06 0.69 1.00
9 7
Pennsylvania 4,66 2.91 4,53 2.95 1.25
0 7
Rhode Island 452 0.28 454 0.29 4.44
South Carolina 1,81 1.13 1,86 1.21 6.99
7 9
South Dakota 31 0.02 35 0.02 17.94
Tennessee 1,58 0.99 1,60 1.04 5.32
9 9
Texas 11,0 6.90 10,4 6.79 -1.68
55 52
Utah 408 0.25 399 0.26 1.72
Vermont 96 0.06 100 0.06 8.11
Virginia 2,43 1.52 2,40 1.56 2.60
9 6
Washington 2,25 1.41 2,12 1.38 -2.20
5 1
West Virginia 175 0.11 160 0.10 -5.13
Wisconsin 947 0.59 960 0.62 5.37
Wyoming 49 0.03 46 0.03 -1.76
Puerto Rico 5,20 3.25 4,81 3.13 -3.88
6 2
Virgin Islands 70 0.04 66 0.04 -2.55
----------------------------------------------------------
\a While the data in the table have been rounded to two decimal
positions, the percentage differences were computed based on
additional decimal positions.
COSTS
--------------------------------------------------------- Appendix I:5
Neither the title I nor title II formula includes a factor that
reflects differences in the cost of serving AIDS cases. We were not
able to locate existing information on the actual cost of providing
health and support services to people with AIDS and HIV within
different geographic areas. As a result, we constructed a proxy for
the cost of serving AIDS cases.
The major factors that typically affect service costs are the
personnel who supply the service, capital costs such as office rent,
and supply costs such as for medications. Titles I and II primarily
fund outpatient health, support, and case management services, which
are labor-intensive. Hence, most of the service delivery costs for
services funded by titles I and II would be associated with the
personnel who provide the services.
Furthermore, from our discussions with experts, we determined that an
existing measure of health labor costs--the Medicare Hospital Wage
Cost (MHWC) Index--might be an appropriate indicator of differences
in labor costs among EMAs and states. This wage index was derived by
HCFA from hospital salary surveys and was designed to reflect
personnel costs in hospitals subject to the Medicare prospective
payment system (PPS). Accordingly, the index is based on the
salaries of nurses, therapists, technicians, physicians, and
administrative staff. In addition to being used for PPS, the MHWC
Index has been used to estimate cost variation for ambulatory service
centers, home health care providers, and skilled nursing facilities.
An underlying assumption in our using the MHWC Index to estimate
costs for the personnel who deliver services funded by the CARE Act
is that the relative differences in these costs should mirror the
relative differences in costs of hospital personnel. That is, in
places where hospital personnel costs are high, costs should also be
high for the personnel who provide services funded by the CARE Act.
Likewise, in places where hospital personnel costs are low, the costs
for the personnel providing services funded by the CARE Act should
also be low.
HCFA collects nationwide data on hospitals participating in PPS, so
cost data are readily available for each of the EMAs and non-EMA
areas. HCFA publishes these data for metropolitan areas, and using
HCFA's automated MHWC database, we were able to construct a wage
index for each of the states.
We were unable to locate existing data on the second major cost
category--capital costs. High-cost areas, however, tend to have high
costs both for salaries and capital (for example, rent for office
space). In our view, therefore, the MHWC Index would appear to be a
reasonable proxy for differences in both personnel and capital costs.
The third major cost category--the cost of supplies such as
medications--is assumed not to systematically vary by location. This
is because the amount an EMA or state pays for supplies like
medications is determined by a number of factors, including the price
that they are able to negotiate with suppliers.
For our analysis, we constructed a cost index assuming 30 percent of
costs do not systematically vary by location and 70 percent do. The
MHWC Index served as a proxy for the variation of these costs.
We applied a weight of 30 percent for costs that do not
systematically vary because that is the approximate percentage of
title II funds typically expended on medications.
Tables I.4 and I.5 display our estimated service costs for each of
the EMAs and states. As shown in these tables, costs can vary by as
much as 100 percent. For example, service costs in Oakland are twice
those in Ponce and San Juan, and 48 percent higher than in Miami.
Similarly, service costs in Alaska are over 50 percent higher than in
Mississippi.
Table I.4
Title I Cost Factor
GAO cost index (.3
MHWC Index + .7 * MHWC)
EMA (average = 1.00) (average = 1.00)
------------------ ------------------ ------------------
Oakland, CA 1.47 1.33
New York, NY 1.41 1.29
San Francisco, CA 1.41 1.29
Nassau-Suffolk, NY 1.31 1.21
Los Angeles, CA 1.25 1.18
New Haven, CT 1.23 1.16
San Diego, CA 1.21 1.14
Boston, MA 1.17 1.12
Riverside-San 1.17 1.12
Bernardino, CA
Bergen-Passaic, NJ 1.15 1.10
Philadelphia, PA 1.11 1.08
Newark, NJ 1.11 1.08
Jersey City, NJ 1.11 1.08
Washington, DC 1.11 1.08
Seattle, WA 1.10 1.07
Detroit, MI 1.09 1.06
Chicago, IL 1.07 1.05
Fort Lauderdale, 1.06 1.04
FL
Denver, CO 1.06 1.04
Atlanta, GA 1.03 1.02
Phoenix, AZ 1.01 1.01
West Palm Beach, 1.00 1.00
FL
Orange County, CA 1.00 1.00
Houston, TX 0.99 0.99
Baltimore, MD 0.99 0.99
Dallas, TX 0.95 0.97
New Orleans, LA 0.95 0.96
Kansas City, MO 0.95 0.96
Orlando, FL 0.94 0.96
Tampa-St. 0.94 0.96
Petersburg, FL
St. Louis, MO 0.91 0.94
Miami, FL 0.86 0.90
Ponce, PR 0.45 0.62
San Juan, PR 0.44 0.61
----------------------------------------------------------
Table I.5
Title II Cost Factor
GAO cost index (.3
MHWC Index + .7 * MHWC)
State (average = 1.00) (average = 1.00)
------------------ ------------------ ------------------
Alaska 1.29 1.20
California 1.25 1.18
New York 1.24 1.17
District of 1.21 1.15
Columbia
Connecticut 1.21 1.15
Massachusetts 1.16 1.11
Hawaii 1.13 1.09
New Jersey 1.12 1.08
Nevada 1.11 1.08
Rhode Island 1.09 1.06
Washington 1.05 1.04
Michigan 1.05 1.04
Oregon 1.05 1.03
Delaware 1.03 1.02
New Hampshire 1.02 1.01
Pennsylvania 1.01 1.01
Minnesota 1.00 1.00
Maryland 1.00 1.00
Illinois 0.98 0.99
Arizona 0.98 0.98
Colorado 0.97 0.98
Utah 0.95 0.96
Florida 0.95 0.96
Ohio 0.94 0.96
Vermont 0.93 0.95
Indiana 0.92 0.94
New Mexico 0.91 0.94
Maine 0.91 0.94
Georgia 0.91 0.94
Texas 0.91 0.93
Wisconsin 0.90 0.93
Virginia 0.89 0.92
Nebraska 0.89 0.92
Missouri 0.88 0.92
North Carolina 0.88 0.92
Kansas 0.88 0.91
Louisiana 0.87 0.91
Tennessee 0.86 0.91
South Carolina 0.86 0.90
Idaho 0.85 0.90
Montana 0.84 0.89
Kentucky 0.84 0.89
North Dakota 0.84 0.89
West Virginia 0.83 0.88
Iowa 0.83 0.88
Alabama 0.80 0.86
Wyoming 0.80 0.86
Oklahoma 0.80 0.86
South Dakota 0.78 0.84
Arkansas 0.76 0.83
Mississippi 0.70 0.79
Puerto Rico 0.44 0.61
Virgin Islands N/A N/A
----------------------------------------------------------
Note: N/A = Not applicable.
FISCAL CAPACITY
--------------------------------------------------------- Appendix I:6
A comprehensive indicator of an EMA's or state's fiscal capacity to
provide AIDS and HIV health and support services is one that includes
both a measure of the resource base (that is, tax base) and the
potential demand placed on these resources to fund AIDS and HIV
services.
For the title I formula, we used per capita income (PCI) as the proxy
measure for EMA resources. PCI data are compiled by the Department
of Commerce and are used to measure the income received by a
jurisdiction's residents, including wages and salaries, rents,
dividends, interest earnings, and income from nonresident corporate
business. PCI also includes an adjustment for the rental value of
owner-occupied housing on the grounds that such ownership is similar
to the interest income earned from alternative financial investments.
While PCI does not measure all taxable income, it is the most
comprehensive measure of EMA residents' income currently available.
As a proxy for the level of demand placed on EMAs' resources, we used
AIDS incidence rates based on our estimate of living AIDS cases.
AIDS incidence indicates the proportion of each EMA's population that
has been reported to have AIDS. As such, AIDS incidence considers
the relative rather than the absolute demand placed on an EMA's
resources. Those EMAs with larger proportions of their populations
having the disease are expected to have greater demands on their
resources than are EMAs with smaller proportions of their populations
infected.
A complete title I fiscal capacity measure was constructed by first
producing cost-adjusted income amounts for each EMA through dividing
their PCI by their MHWC Index values. This adjustment ensured that
EMAs were compared in terms of income that was of comparable
purchasing power. Next, we divided these cost-adjusted values by
each EMA's AIDS incidence rate.
We followed similar steps in constructing the title II fiscal
capacity measure, with the exception of using total taxable resources
(TTR)\13 to measure income. TTR is a broader measure of income than
PCI because it considers all income potentially subject to a state's
taxing authority. TTR is an average of PCI and per capita Gross
State Product (GSP). GSP measures all income produced or received
within a state, whether received by residents, nonresidents, or
retained by business corporations. Below is the the title II fiscal
capacity measure.
--------------------
\13 TTR data are only available at the state level, so they cannot be
used to estimate the fiscal capacity of EMAs.
CURRENT FISCAL CAPACITY
MEASURES COULD BE IMPROVED
--------------------------------------------------------- Appendix I:7
Under the current formulas, fiscal capacity is incompletely measured.
The title I formula includes a measure of EMAs' AIDS incidence but
omits a measure of their resources, which creates a bias against
those EMAs with relatively low tax bases. In table I.6, we show
EMAs' fiscal capacity as measured by the complete indicator that we
constructed--real PCI per weighted case--and by the existing
measure--AIDS incidence. This table also shows the percentage
difference or disparity between these two measures.
As shown in this table, fiscal capacity for the Riverside-San
Bernardino EMA is estimated to be 147 percent of the EMA average when
measured with a complete indicator--PCI per weighted case. When only
AIDS incidence is considered, however, the EMA's fiscal capacity is
estimated to be 245 percent of the average. Hence, when demand for
services is considered relative to available resources, Riverside-San
Bernardino's fiscal capacity is estimated to be 67 percent lower than
what is estimated under the existing formula. Conversely, when
measured with a complete indicator, San Francisco's fiscal capacity
is estimated to be about 21 percent higher than is estimated under
the current formula. This occurs because of the EMA's relatively
high tax base.
Table I.6
Title I Fiscal Capacity Factors
Current
GAO's real title I AIDS
PCI per wtd. incidence
case index index\a
(average = (average = Percentage
EMA 100) 100) difference\b
---------------- ------------ ------------ ------------
New York, NY 41 38 -8.46
San Francisco, 29 23 -20.68
CA
Los Angeles, CA 94 104 10.67
Miami, FL 40 48 17.95
Newark, NJ 83 61 -26.16
Houston, TX 106 96 -8.93
Washington, DC 134 112 -16.46
Chicago, IL 218 201 -7.82
Atlanta, GA 118 114 -3.42
Fort Lauderdale, 67 61 -8.36
FL
Philadelphia, PA 156 162 4.26
Dallas, TX 129 120 -7.68
Boston, MA 200 209 4.21
Jersey City, NJ 50 45 -9.31
San Diego, CA 102 128 24.75
Oakland, CA 112 129 15.12
Baltimore, MD 119 126 6.40
New Orleans, LA 103 109 6.03
Seattle, WA 168 149 -11.34
Tampa-St. 113 135 19.20
Petersburg, FL
Orange County, 258 218 -15.33
CA
Nassau-Suffolk, 226 204 -9.59
NY
Detroit, MI 265 307 16.10
West Palm Beach, 108 74 -31.71
FL
Denver, CO 138 144 4.26
Orlando, FL 108 142 30.96
Riverside-San 147 245 66.79
Bernardino, CA
Bergen-Passaic, 169 127 -24.53
NJ
Kansas City, MO 176 184 4.61
New Haven, CT 167 149 -11.08
Phoenix, AZ 211 267 26.45
St. Louis, MO 255 273 7.01
San Juan, PR 33 67 103.54
Ponce, PR 17 56 236.48
----------------------------------------------------------
Note: The average values are based on the average for all EMAs.
\a A high AIDS incidence rate value reflects a lower fiscal capacity
while a high PCI value reflects a higher fiscal capacity.
Consequently, we inverted the AIDS incidence rate to make it
comparable with the other indicator.
\b While the data in the table have been rounded to two decimal
positions, the percentage differences were computed on the basis of
additional decimal positions.
In contrast to the title I formula, the title II formula measures
states' income and omits their AIDS incidence rates. This omission
creates a bias against those states with relatively high service
demands on their resources. Table I.7 shows states' fiscal capacity
when measured by a complete indicator--real TTR per weighted
case--followed by the existing measure--nominal per capita income.
Also, the table shows the percentage difference or disparity between
these two measures.
Table I.7
Title II Fiscal Capacity Factors
Current
GAO's real title II
TTR per wtd. nominal PCI
case index index
(average = (average = Percentage
State 100) 100) difference\a
---------------- ------------ ------------ ------------
Alabama 208 82 -60.68
Alaska 544 109 -80.00
Arizona 129 86 -33.05
Arkansas 209 78 -62.72
California 64 107 68.81
Colorado 124 101 -18.43
Connecticut 101 136 34.43
Delaware 106 108 1.87
District of 18 133 618.07
Columbia
Florida 48 98 103.41
Georgia 96 91 -5.23
Hawaii 134 107 -19.97
Idaho 545 81 -85.13
Illinois 162 109 -32.86
Indiana 257 91 -64.66
Iowa 610 92 -84.88
Kansas 314 98 -68.95
Kentucky 405 83 -79.40
Louisiana 111 79 -28.89
Maine 354 92 -74.01
Maryland 90 116 28.24
Massachusetts 109 121 11.03
Michigan 213 98 -53.74
Minnesota 321 101 -68.54
Mississippi 198 71 -64.18
Missouri 135 95 -29.74
Montana 777 81 -89.58
Nebraska 431 96 -77.67
Nevada 92 102 11.09
New Hampshire 397 116 -70.90
New Jersey 71 133 87.34
New Mexico 199 77 -61.06
New York 42 119 182.77
North Carolina 214 89 -58.48
North Dakota 1,910 85 -95.55
Ohio 283 94 -66.87
Oklahoma 199 82 -58.89
Oregon 147 92 -37.39
Pennsylvania 157 102 -34.97
Rhode Island 129 102 -20.47
South Carolina 113 81 -28.43
South Dakota 1,461 83 -94.29
Tennessee 193 87 -54.66
Texas 101 90 -11.05
Utah 226 77 -65.80
Vermont 362 95 -73.78
Virginia 185 104 -43.83
Washington 141 103 -26.84
West Virginia 548 76 -86.15
Wisconsin 337 94 -71.99
Wyoming 754 88 -88.35
Puerto Rico N/A N/A N/A
Virgin Islands N/A N/A N/A
----------------------------------------------------------
Notes: The average values are based on the average for the United
States.
N/A = Not applicable.
\a While the data in the table have been rounded to two decimal
positions, the percentage differences were computed on the basis of
additional decimal positions.
As shown in table I.7, Kentucky's fiscal capacity is estimated to be
17 percent below the national average when only PCI is considered.
When income is adjusted by AIDS incidence rates, however, the state's
fiscal capacity is estimated to be more than four times the national
average. This occurs because of the relatively low AIDS incidence
rate in Kentucky as compared with the state's available resources.
Conversely, while the District of Columbia has a relatively large
resource base (33 percent above the national average), its AIDS
incidence is also relatively high. Consequently, when measured with
a complete indicator, the District of Columbia's fiscal capacity is
found to be 72 percent below the national average.
TITLE I FUNDING AND COMBINED
TITLES I AND II FUNDING MEET
NEITHER EQUITY CRITERION
========================================================== Appendix II
We compared the distribution of title I funding and the combined
title I and II funding against the beneficiary and taxpayer equity
criteria. These comparisons indicated that the current formulas do
not distribute funding in accordance with either of the equity
criteria.
EQUITY OF TITLE I FUNDING
-------------------------------------------------------- Appendix II:1
Under the beneficiary equity standard, the size of the grant award
depends on two factors: the number of cases and the cost of
services. If the grant is expressed on a per-case basis, this
implies that per-case funding should vary only with differences in
the cost of services. To determine how well the current distribution
of title I funds meets the beneficiary equity standard, we performed
a regression analysis\14 to determine the extent to which cost
differences can account for differences in nominal per-case
funding.\15
If the current distribution of title I funds reflected the
beneficiary equity standard, then a substantial share of the
variation in per-case funding could be explained by cost differences.
Our statistical analysis, however, indicates the current distribution
of title I funds bears little relation to the variation in costs.
The strength of a relationship is commonly measured by a statistic
known as R\2 . In this case, the R\2 is 0.10, meaning that
differences in cost account for only 10 percent of the variation in
per-case funding for EMAs. Hence, 90 percent of the variation is
related to other factors.
Examples of the inequities that result from this low R\2 are
displayed in figure II.1. If differences in per-case funding and
costs were perfectly correlated, all EMAs would fall along the
straight line shown in this figure. The wide scatter around the
line, however, demonstrates that per-case funding and costs are not
systematically related. For example, the service costs for the
Oakland and San Francisco EMAs are about the same; yet, per-case
funding for San Francisco is about twice that for Oakland. If
per-case funding and costs were more strongly correlated, both EMAs
would be positioned closer to the straight line. Furthermore,
Oakland's per-case funding would even be slightly higher than San
Francisco's rather than vice versa.
Figure II.1: Nominal Title I
Funding Per Case and Cost
(See figure in printed
edition.)
Note: The two EMAs located in Puerto Rico--Ponce and San Juan--are
excluded from this figure.
This relationship is also illustrated by other pairs of EMAs. For
example, New York City's service costs are about 20 percent higher
than Jersey City's, but their per-case funding is about the
same--about 30 percent above the EMA average. Consequently, at their
current funding levels, the Jersey City EMA can purchase more
services for its patients than can New York City.
From the perspective of beneficiary equity, therefore, the current
per-case funding distribution is inequitable. However, if these
differences can be accounted for by differences in fiscal capacity,
then the grant distribution may reflect our taxpayer equity
criterion.
The taxpayer equity standard implies that per-case funding should be
related to both cost differences and differences in fiscal capacity.
Thus, to determine if the formula meets the taxpayer equity standard,
we performed a regression analysis to determine the extent to which
differences in per-case funding can be explained by both cost and
fiscal capacity differences. We used per-case funding (measured in
nominal dollars) as the dependent variable and used both cost and
fiscal capacity (also measured in nominal dollars) as independent
variables.
Our statistical results show that the current distribution of title I
funds does more closely reflect the taxpayer equity standard. The
R\2 is 0.56, meaning that differences in cost and fiscal capacity
account for 56 percent of the variation in EMAs' per-case funding.
Nonetheless, a considerable amount of unexplained variation in
per-case funding--44 percent--
remains.
The tendency to allocate more aid to low-capacity EMAs is shown
graphically in figure II.2. San Francisco's funding capacity is the
lowest of all the EMAs and its cost-adjusted per-case real funding is
high--nearly 40 percent above the average. West Palm Beach has
approximately average funding capacity and receives an average
per-case real funding amount. Detroit, Orange County, and St. Louis
have high funding capacities and receive relatively lower per-case
funding amounts. Thus, there is a clear tendency to target more aid
to EMAs with lower funding capacities.
Figure II.2: Real Title I
Funding Per Case and Tax Base
(See figure in printed
edition.)
Note: The two EMAs located in Puerto Rico--Ponce and San Juan--are
excluded from this figure.
However, there are many exceptions to this general tendency. For
example, while the San Francisco and New York City EMAs' funding
capacities are comparable, they receive very different per-case real
funding amounts. Real per-case funding is 40 percent above the
average for San Francisco and only about average for New York City.
Since the grant amounts have already been adjusted for cost
differences, we would conclude that the New York City EMA is
underfunded compared to San Francisco. Similarly, both West Palm
Beach and Tampa have average funding capacities, but West Palm Beach
receives about 25 percent more title I funds than Tampa. Based on
examples like these and our regression results, we conclude that
while title I funding demonstrates a tendency to target more aid to
low-capacity EMAs, substantial inequities exist.
--------------------
\14 Regression analysis is a statistical technique used to measure
the degree to which variation in a variable can be explained by
variation in other variables.
\15 When we refer to nominal dollars or funds, we mean an amount that
has not been adjusted for service cost differences among EMAs and
states. In contrast, when we refer to real dollars or funds, we mean
an amount that has been cost-adjusted.
EQUITY OF COMBINED TITLE I AND
II FUNDING
-------------------------------------------------------- Appendix II:2
The beneficiary equity standard for the combined distribution of
title I and II funds uses caseload and cost measures that encompass
the entire state rather than just an EMA. Using state rather than
EMA data, we estimated the same regression models to assess the
equity of the combined title I and II funding.\16
These results show that the current distribution of title I and II
funds, in combination, does not meet either equity standard. If
beneficiary equity were fully realized, cost differences would
account for all of the variation in per-case funding, but costs
explain only 14 percent of this variation. To express this another
way, under the beneficiary equity model, states with the same
relative cost of services should receive equal funding on a per-case
basis. As shown in figure II.3, however, states with dramatically
different service costs received comparable per-case funding amounts.
For example, service costs for both Georgia and New Mexico are about
average; but Georgia's per-case funding is 69 percent higher than New
Mexico's. A similar situation exists for Ohio and Texas. Both the
regression results and these examples indicate that title I and II
funds, in combination, are not distributed in a way that meets the
beneficiary equity criterion.
Figure II.3: Nominal Title I
and II Per-Case Funding and
Cost
(See figure in printed
edition.)
Note: States receiving the minimum title II grant amount of $100,000
and the territories are excluded from this figure.
Under the taxpayer equity model, cost and fiscal capacity should
account for 100 percent of the variation in per-case funding. Our
regression analysis indicates these two factors account for only 33
percent of the variation in per-case funding. By implication, about
67 percent of the variation in per-case funding is unrelated to need
as reflected by differences in cost and fiscal capacity.
Specific examples of the inequities are illustrated in figure II.4.
For example, Massachusetts and New Hampshire receive comparable
per-case funding amounts, but New Hampshire's tax base is about four
times that of Massachusetts. Similar situations exist for the states
of Connecticut and Kentucky and for Delaware and Maine. In contrast,
Hawaii receives a grant that is about half the amount that Missouri
receives; yet, the states' tax bases are comparable. This is also
the case for the states of Georgia and Nevada and for Illinois and
Oregon. On the basis of this analysis, we conclude that the combined
title I and II funding does not meet the taxpayer equity criterion.
Figure II.4: Real Title I and
II Per-Case Funding and Tax
Base
(See figure in printed
edition.)
Note: States receiving the minimum title II grant amount of $100,000
and the territories are excluded from this figure.
--------------------
\16 States receiving the minimum title II grant amount of $100,000
are excluded from these analyses because their funds are not
distributed by formula and cannot be related to an equity analysis.
FUNDING INEQUITIES RESULT FROM THE
STRUCTURE OF THE TITLE I AND II
FORMULAS
========================================================= Appendix III
When funding for titles I and II is considered jointly, the major
cause of funding inequities is that EMA cases are counted in both
formulas but cases outside EMAs are not. As a result, states with
few or no cases in an EMA receive disproportionately less per-case
funding than do states with large proportions of their caseloads in
EMAs.
The following two-state example demonstrates how the current
structure produces funding inequities between a state with an EMA and
one without an EMA. For this example, we will assume that $1,000 has
been appropriated for each of titles I and II. Also, the two states
are assumed to be alike in terms of their costs and funding capacity;
however, they differ in the number of cases they must serve and
whether these cases live in an EMA.
State A has 200 cases, all living in an EMA while State B has 100
cases and no EMA. Hence, State A has two-thirds and State B has
one-third of the total cases. Since title I funds are allocated
based on each state's share of EMA cases, the entire $1,000 would be
distributed to the EMA in State A, and none of the funds would be
distributed in State B (see fig. III.1).
Figure III.1: Calculation of
Title I Grant
(See figure in printed
edition.)
Title II funding is allocated in proportion to each state's total
caseload. Since State A has two-thirds of all cases, it would
receive two-thirds ($667) of the title II appropriation. State B
would receive one-third ($333) of the appropriation.
Each state's total grant is then determined by summing their title I
and II grants (see fig. III.2).
Figure III.2: Total Funding
(See figure in printed
edition.)
To determine the states' per-case funding amounts, their total grant
amounts are divided by their total caseloads (see fig. III.3).
Figure III.3: Per-Case Funding
(See figure in printed
edition.)
In this example, the current title structure produced differences in
per-case funding for these two states that amounts to about 150
percent. Moreover, this difference is unrelated to the states'
funding needs and occurs solely because of the existing title
structure.
DOUBLE COUNTING EMA CASES
ACCOUNTS FOR MOST OF THE
FUNDING INEQUITIES
------------------------------------------------------- Appendix III:1
To determine the extent to which the current structure accounts for
per-case funding differences, we compared two regression models. The
first model was our earlier one that examined the effects of
differences in cost and fiscal capacity on states' combined title I
and II per-case funding amounts. For the second model, we examined
these effects along with the effect of the percentage of AIDS cases
in an EMA on states' combined title I and II per-case funding
amounts.
As discussed in appendix II, the cost and fiscal capacity model
explains only 33 percent of the variation in nominal title I and II
per-case funding. In contrast, however, the model that also includes
the percentage of EMA AIDS cases as a factor explains 85 percent of
this variation.
The relationship between the percentage of EMA AIDS cases and
per-case funding is displayed in figure III.4. As shown in this
figure, the states with fewer cases in EMAs, for example, Hawaii,
Ohio, and West Virginia receive the smallest grants, and the states
with larger percentages of cases in EMAs, for example, California,
the District of Columbia, and New York, tend to receive the largest
grants. As demonstrated by the regression analysis and this figure,
the funding differences result from the structure of the formulas
rather than funding needs as measured by cases, costs, and fiscal
capacity. Consequently, these differences are inequitable.
Figure III.4: Nominal Combined
Title I and II Per-Case Funding
and Percentage of EMA Cases
(See figure in printed
edition.)
Notes: States receiving the minimum title II grant amount of
$100,000 and the territories are excluded from this figure.
Of the states without an EMA, only the two that received the smallest
and largest grants are displayed.
STRUCTURAL CHANGES CAN IMPROVE
EQUITY
========================================================== Appendix IV
While improvements in funding equity can be achieved by adopting
better indicators of caseload, cost, and funding capacity in the
allocation formulas, greater improvement could result from changing
the allocation structures to avoid inequities created by counting EMA
cases in both formulas. A variety of approaches could be used that
vary in terms of how they would affect existing service delivery
responsibilities and structures.
CONSOLIDATED GRANTS
-------------------------------------------------------- Appendix IV:1
The simplest way to improve funding equity is to consolidate titles I
and II into a single grant and distribute funds to the state
governments through an equity-based formula. State governments would
be the political entity responsible for using the aid provided for
serving those in need. The funds would be allocated based on each
state's total cases, thus avoiding any double counting of EMA cases.
Two implications of the consolidated grant approach, however, are the
potential infringement on the autonomy currently afforded EMAs in
delivering services and changes in existing service responsibilities
and structures. Currently, EMAs are responsible for delivering
services within their areas, and they have service delivery networks
already in place. Under a consolidated grant, all funds would be
distributed to the states. Hence, a state could potentially assume
total responsibility for service delivery in EMAs or continue to
allow the EMAs to administer the programs they now operate, funding
them from its consolidated grant.
GEOGRAPHIC DIVISION OF SERVICE
RESPONSIBILITIES
-------------------------------------------------------- Appendix IV:2
A second corrective approach maintains the two distinct titles--title
I for EMAs and title II for states--however, the EMAs would become
responsible for all services in their areas, including those services
currently under the purview of the states through title II. Hence,
EMAs and states would continue to be funded under separate titles,
but the services funded under these titles would be identical. Both
title I and II funds would be allocated through equity-based
formulas. Title I funds would be distributed to EMAs on the basis of
their respective shares of cases, and title II funds would be
distributed to states on the basis of their respective shares of the
non-EMA cases.
Like the previous approach, this one avoids the inequities currently
caused by counting EMA cases in both formulas. Furthermore, as do
the existing formulas, this approach maintains the EMAs' autonomy in
the delivery of services. In addition, this approach allows
comparable per-case funding levels among the states and EMAs.
However, this approach would lead to significant changes in service
delivery responsibilities. Because EMAs are not currently
responsible for providing services such as insurance continuation and
medication assistance, they would have to develop the capacity to
administer these services in addition to the medical and support
services they now provide.
FUNDING BY TYPES OF SERVICE
-------------------------------------------------------- Appendix IV:3
A third corrective approach involves allocating funds for medical and
support services separately from those services that states provide
statewide. This approach avoids inequities produced by double
counting EMA cases, continues the existing autonomy afforded EMAs,
and requires no changes in existing service delivery
responsibilities. Furthermore, the approach ensures that comparable
per-case funding is available across EMAs and states and between EMA
and non-EMA areas.
The following example, using the same two states from the example in
appendix III, illustrates how this approach would improve funding
equity. The two states are alike in terms of their costs and funding
capacity, but they differ in the number of cases they serve and
whether the cases live in an EMA.
In this example, a total of $2,000 is appropriated: $1,500 for
medical services and $500 for statewide services. As will be shown
through this example, dividing funds in this way would result in
funding amounts for title I and II activities that are comparable to
what was found in the earlier example in which both titles each had a
$1,000 appropriation. That is, $1,000 would still be available for
the EMA, and $1,000 would still be available for the states because
state funding would be determined by adding together the $500 for
non-EMA medical services and $500 for statewide services.
State A has 200 cases, all living in an EMA, and State B has 100
cases and no EMA. Hence, once again, State A has 100 percent of the
EMA cases and two-thirds of total cases. State B has 100 percent of
the non-EMA cases and one-third of total cases. Expressed
differently, two-thirds of all cases live in an EMA and one-third of
all cases do not.
Under this approach, the medical services appropriation would be
divided between EMA and non-EMA areas on the basis of their
respective caseloads. Since two-thirds of all cases live in an EMA,
two-thirds of the medical services appropriation ($1,000) would be
set aside for the EMA. The remaining one-third of the medical
services appropriation ($500) would be set aside for distribution to
states on the basis of the number of cases living outside an EMA.
EMA medical services funds are allocated based on the shares of cases
living in an EMA. Since State A contains all EMA cases, all of these
funds ($1,000) would be allocated within State A. None of these
funds would be allocated within State B as it has no EMA. Non-EMA
medical services funds would be allocated based on states' shares of
cases living outside an EMA. Since State A has no non-EMA cases, it
would receive none of these funds. State B would receive the entire
$500 of non-EMA medical services funds because it contains all
non-EMA cases.
The statewide services appropriation ($500) would be allocated based
on each state's share of total cases. Since State A has two-thirds
of the total cases, it would receive $334; State B would receive the
remaining one-third of funds ($167).
The states' total grants would be the sum of their EMA medical
services grant, non-EMA medical services grant, and statewide
services grant. In this case, State A would receive a total of
$1,334 and State B would receive a total of $667 (see fig. IV.1).
Figure IV.1: Total Grants
(See figure in printed
edition.)
As before, the states' per-case funding amounts would be obtained by
dividing their total grant amounts by their total caseloads. Figure
IV.2 shows the per-case funding amounts for the two states.
Figure IV.2: Per-Case Funding
(See figure in printed
edition.)
Under our proposed approach, each state would receive identical
per-case funding. This contrasts significantly with the current
approach, which produces highly unequal per-case funding that is
unrelated to either costs or funding capacity and is therefore
inequitable.
COMPARISON OF EMA AND STATE CARE
ACT GRANTS UNDER CURRENT AND
EQUITY-BASED FORMULAS
=========================================================== Appendix V
In this appendix, we describe how title I and II funding would be
distributed if the formulas were changed to meet either the
beneficiary or taxpayer equity criterion. Both the beneficiary and
taxpayer equity formulas were described in greater detail in appendix
I, which also provided more detailed discussion of the caseload,
cost, and fiscal capacity factors used in these formulas.
Depending on the amount of title I and II funds appropriated or the
use of funding-loss mechanisms such as hold-harmless provisions,
formula modifications could decrease funding to some EMAs and states
and increase funding to others. Whether and how funding losses
should be prevented would be the decision of the Congress; however,
in this appendix, we show the effects of formula changes when title I
and II appropriations remain constant and no funding-loss mechanisms
are employed.
BENEFICIARY EQUITY FORMULAS
--------------------------------------------------------- Appendix V:1
Table V.1 displays each EMA's title I fiscal year 1995 funding under
both the existing and the beneficiary equity formulas, along with the
difference in funding that would be received under these formulas.
Relative to the existing formula, changes in EMAs' allocations under
the beneficiary equity formula would range from a decrease of 33.57
percent to an increase of 58.72.
Table V.1
Title I FY 1995 Funding Under the
Existing and Beneficiary Equity Formulas
Beneficiar
Existing y equity
formula FY formula FY
1995 1995 Percenta
EMA allocation allocation Dollars ge
-------------- ---------- ---------- -------- --------
Atlanta, GA $4,007,435 $4,081,413 $73,978 1.85
Austin, TX 1,085,663 1,288,596 202,933 18.69
Baltimore, MD 2,691,832 3,377,671 685,839 25.48
Bergen- 1,452,105 1,605,315 153,210 10.55
Passaic, NJ
Boston, MA 3,456,473 4,830,099 1,373,62 39.74
5
Chicago, IL 4,924,568 6,270,043 1,345,47 27.32
5
Dallas, TX 3,385,351 3,472,214 86,863 2.57
Denver, CO 1,668,174 2,043,282 375,107 22.49
Detroit, MI 1,716,243 2,377,827 661,584 38.55
Dutchess 359,357 391,211 31,854 8.86
County, NY
Fort 3,635,539 3,318,715 - -8.71
Lauderdale, 316,825
FL
Houston, TX 5,803,257 5,715,983 -87,273 -1.50
Jacksonville, 1,214,884 1,307,390 92,506 7.61
FL
Jersey City, 2,406,293 1,759,633 - -26.87
NJ 646,659
Kansas City, 1,145,290 1,235,732 90,442 7.90
MO
Los Angeles, 12,998,478 15,329,003 2,330,52 17.93
CA 5
Miami, FL 8,079,775 6,585,215 - -18.50
1,494,56
0
Nassau- 1,676,365 2,441,033 764,668 45.61
Suffolk, NY
New Haven, CT 1,484,228 2,143,285 659,057 44.40
New Orleans, 1,798,493 1,728,625 -69,868 -3.88
LA
New York, NY 48,636,026 42,538,803 - -12.54
6,097,22
3
Newark, NJ 5,559,872 4,883,141 - -12.17
676,731
Oakland, CA 2,321,637 3,197,753 876,117 37.74
Orange County, 1,490,021 1,841,089 351,068 23.56
CA
Orlando, FL 1,286,590 1,522,576 235,986 18.34
Philadelphia, 4,124,036 5,528,896 1,404,86 34.07
PA 0
Phoenix, AZ 1,096,350 1,332,987 236,637 21.58
Portland, OR 986,510 1,278,214 291,704 29.57
Riverside-San 1,485,035 2,357,024 871,988 58.72
Bernardino,
CA
St. Louis, MO 1,137,857 1,385,224 247,367 21.74
San Antonio, 960,778 1,119,605 158,827 16.53
TX
San Diego, CA 2,861,916 3,702,743 840,827 29.38
San Francisco, 19,126,679 12,705,987 - -33.57
CA 6,420,69
2
Santa Rosa- 574,580 745,241 170,661 29.70
Petaluma, CA
Seattle, WA 1,920,227 2,430,507 510,280 26.57
Tampa-St. 2,172,534 2,538,261 365,727 16.83
Petersburg,
FL
Vineland, NJ 197,896 207,866 9,970 5.04
Washington, DC 5,623,294 6,411,647 788,354 14.02
West Palm 1,961,600 1,849,331 - -5.72
Beach, FL 112,269
Caguas, PR 489,261 529,640 40,379 8.25
Ponce, PR 1,020,387 885,680 - -13.20
134,707
San Juan, PR 4,662,110 4,390,498 - -5.83
271,612
==========================================================
Total $174,685,0 $174,685,0
00 00
----------------------------------------------------------
Table V.2 displays the distribution of title II fiscal year 1995
funding under both the existing and the beneficiary equity formulas.
Relative to the existing formula, changes in states' allocations
under the beneficiary equity formula would range from a decrease of
69.84 percent to an increase of 247.33 percent.\17
Table V.2
Title II FY 1995 Funding Under the
Existing and Beneficiary Equity Formulas
Existing Beneficiar
formula FY y equity
State or 1995 FY 1995 Percenta
territory allocation allocation Dollars ge
-------------- ---------- ---------- -------- --------
Alabama $1,349,942 $3,175,846 $1,825,9 135.26
04
Alaska 100,000 337,517 237,517 237.52
Arizona 1,759,313 1,552,919 - -11.73
206,394
Arkansas 753,038 1,649,752 896,714 119.08
California 27,867,193 21,249,330 - -23.75
6,617,86
3
Colorado 1,980,699 1,381,805 - -30.24
598,894
Connecticut 2,404,858 4,096,894 1,692,03 70.36
6
Delaware 585,604 1,646,242 1,060,63 181.12
8
District of 2,532,524 763,706 - -69.84
Columbia 1,768,81
8
Florida 17,780,752 13,052,493 - -26.59
4,728,25
9
Georgia 4,731,696 4,778,646 46,950 0.99
Hawaii 499,350 1,734,379 1,235,02 247.33
9
Idaho 138,867 324,283 185,416 133.52
Illinois 5,577,650 2,981,750 - -46.54
2,595,90
0
Indiana 1,536,770 3,873,203 2,336,43 152.04
3
Iowa 333,360 792,428 459,068 137.71
Kansas 568,263 903,092 334,829 58.92
Kentucky 643,697 1,618,407 974,710 151.42
Louisiana 2,785,044 3,389,561 604,517 21.71
Maine 228,492 599,407 370,915 162.33
Maryland 4,684,012 1,984,893 - -57.62
2,699,11
9
Massachusetts 3,776,077 2,777,381 - -26.45
998,696
Michigan 2,675,943 2,904,689 228,746 8.55
Minnesota 973,550 2,649,145 1,675,59 172.11
5
Mississippi 954,192 1,909,469 955,277 100.11
Missouri 2,504,335 1,680,127 - -32.91
824,208
Montana 100,000 158,978 58,978 58.98
Nebraska 267,083 636,498 369,415 138.31
Nevada 964,174 2,910,751 1,946,57 201.89
7
New Hampshire 175,763 210,839 35,076 19.96
New Jersey 8,958,831 9,072,667 113,836 1.27
New Mexico 479,074 1,126,763 647,689 135.20
New York 29,093,044 16,378,152 - -43.70
12,714,8
92
North Carolina 2,414,668 6,292,042 3,877,37 160.58
4
North Dakota 100,000 89,715 -10,285 -10.28
Ohio 2,623,138 7,170,372 4,547,23 173.35
4
Oklahoma 1,050,786 2,242,488 1,191,70 113.41
2
Oregon 1,300,587 1,126,733 - -13.37
173,854
Pennsylvania 5,177,510 5,825,048 647,538 12.51
Rhode Island 554,753 1,618,244 1,063,49 191.71
1
South Carolina 2,679,771 5,747,815 3,068,04 114.49
4
South Dakota 100,000 89,241 -10,759 -10.76
Tennessee 1,846,877 4,406,616 2,559,73 138.60
9
Texas 12,636,414 10,282,829 - -18.63
2,353,58
5
Utah 428,266 1,094,580 666,314 155.58
Vermont 103,727 272,789 169,062 162.99
Virginia 2,642,609 4,722,057 2,079,44 78.69
8
Washington 2,310,797 2,180,920 - -5.62
129,877
West Virginia 184,768 418,183 233,415 126.33
Wisconsin 1,063,650 2,510,890 1,447,24 136.06
0
Wyoming 100,000 123,698 23,698 23.70
Guam 2,902 10,411 7,509 258.76
Puerto Rico 7,682,087 3,962,806 - -48.41
3,719,28
1
Virgin Islands 0 277,015 277,015 N/A
==========================================================
Total $174,766,5 $174,766,5
00 00
----------------------------------------------------------
Note: N/A = Not applicable.
--------------------
\17 This range excludes Guam.
TAXPAYER EQUITY FORMULAS
--------------------------------------------------------- Appendix V:2
Table V.3 displays title I fiscal year 1995 funding under both the
existing and the taxpayer equity formulas. Relative to the existing
formula, changes in EMAs' title I allocations under the taxpayer
equity formula would range from a decrease of 37.18 percent to an
increase of 38.90 percent.
Table V.3
Title I FY 1995 Funding Under the
Existing and Taxpayer Equity Formulas
Existing Taxpayer
formula FY equity FY
1995 1995 Percenta
EMA allocation allocation Dollars ge
-------------- ---------- ---------- -------- --------
Atlanta, GA $4,007,435 $3,875,802 - -3.28
$131,633
Austin, TX 1,085,663 1,316,251 230,588 21.24
Baltimore, MD 2,691,832 3,222,078 530,246 19.70
Bergen- 1,452,105 1,296,500 - -10.72
Passaic, NJ 155,605
Boston, MA 3,456,473 3,487,398 30,925 0.89
Chicago, IL 4,924,568 4,520,122 - -8.21
404,446
Dallas, TX 3,385,351 3,219,764 - -4.89
165,587
Denver, CO 1,668,174 1,852,549 184,375 11.05
Detroit, MI 1,716,243 1,223,021 - -28.74
493,222
Dutchess 359,357 380,235 20,879 5.81
County, NY
Fort 3,635,539 3,612,284 -23,256 -0.64
Lauderdale,
FL
Houston, TX 5,803,257 5,798,947 -4,309 -0.07
Jacksonville, 1,214,884 1,307,433 92,549 7.62
FL
Jersey City, 2,406,293 1,997,181 - -17.00
NJ 409,111
Kansas City, 1,145,290 926,488 - -19.10
MO 218,801
Los Angeles, 12,998,478 15,608,417 2,609,93 20.08
CA 8
Miami, FL 8,079,775 7,618,124 - -5.71
461,651
Nassau- 1,676,365 1,669,138 -7,226 -0.43
Suffolk, NY
New Haven, CT 1,484,228 1,783,837 299,609 20.19
New Orleans, 1,798,493 1,739,789 -58,704 -3.26
LA
New York, NY 48,636,026 49,293,321 657,295 1.35
Newark, NJ 5,559,872 5,153,909 - -7.30
405,962
Oakland, CA 2,321,637 3,041,615 719,978 31.01
Orange County, 1,490,021 1,145,238 - -23.14
CA 344,783
Orlando, FL 1,286,590 1,469,051 182,461 14.18
Philadelphia, 4,124,036 4,793,757 669,721 16.24
PA
Phoenix, AZ 1,096,350 851,132 - -22.37
245,218
Portland, OR 986,510 997,508 10,999 1.11
Riverside-San 1,485,035 2,062,696 577,660 38.90
Bernardino,
CA
St. Louis, MO 1,137,857 714,755 - -37.18
423,102
San Antonio, 960,778 974,770 13,992 1.46
TX
San Diego, CA 2,861,916 3,659,542 797,626 27.87
San Francisco, 19,126,679 15,050,088 - -21.31
CA 4,076,59
1
Santa Rosa- 574,580 765,980 191,399 33.31
Petaluma, CA
Seattle, WA 1,920,227 2,065,044 144,817 7.54
Tampa-St. 2,172,534 2,432,673 260,139 11.97
Petersburg,
FL
Vineland, NJ 197,896 212,618 14,722 7.44
Washington, DC 5,623,294 5,885,978 262,684 4.67
West Palm 1,961,600 1,805,503 - -7.96
Beach, FL 156,098
Caguas, PR 489,261 534,078 44,817 9.16
Ponce, PR 1,020,387 893,101 - -12.47
127,286
San Juan, PR 4,662,110 4,427,284 - -5.04
234,826
==========================================================
Total $174,685,0 $174,685,0
00 00
----------------------------------------------------------
Title II funding for fiscal year 1995 under the existing and taxpayer
equity formulas is shown in table V.4. Relative to the existing
formula, changes in states' allocations under the taxpayer equity
formula would range from a decrease of 77.14 percent to an increase
of 290.91 percent.
Table V.4
Title II FY 1995 Funding Under the
Existing and Taxpayer Equity Formulas
Taxpayer
Existing equity
formula FY formula FY
State or 1995 1995 Percenta
territory allocation allocation Dollars ge
-------------- ---------- ---------- -------- --------
Alabama $1,349,942 $3,419,706 $2,069,7 153.32
64
Alaska 100,000 270,771 170,771 170.77
Arizona 1,759,313 1,394,264 - -20.75
365,049
Arkansas 753,038 1,761,699 1,008,66 133.95
1
California 27,867,193 20,848,641 - -25.19
7,018,55
2
Colorado 1,980,699 1,131,187 - -42.89
849,512
Connecticut 2,404,858 4,397,664 1,992,80 82.87
6
Delaware 585,604 1,926,550 1,340,94 228.99
6
District of 2,532,524 915,525 - -63.85
Columbia 1,616,99
9
Florida 17,780,752 14,238,085 - -19.92
3,542,66
7
Georgia 4,731,696 4,912,075 180,379 3.81
Hawaii 499,350 1,952,008 1,452,65 290.91
8
Idaho 138,867 260,849 121,982 87.84
Illinois 5,577,650 1,582,396 - -71.63
3,995,25
4
Indiana 1,536,770 3,990,018 2,453,24 159.64
8
Iowa 333,360 588,194 254,834 76.44
Kansas 568,263 724,849 156,586 27.56
Kentucky 643,697 1,505,770 862,073 133.93
Louisiana 2,785,044 3,601,976 816,932 29.33
Maine 228,492 568,826 340,334 148.95
Maryland 4,684,012 1,561,736 - -66.66
3,122,27
6
Massachusetts 3,776,077 2,273,689 - -39.79
1,502,38
8
Michigan 2,675,943 2,126,388 - -20.54
549,555
Minnesota 973,550 2,547,146 1,573,59 161.63
6
Mississippi 954,192 2,085,536 1,131,34 118.57
4
Missouri 2,504,335 1,279,436 - -48.91
1,224,89
9
Montana 100,000 96,946 -3,054 -3.05
Nebraska 267,083 534,883 267,800 100.27
Nevada 964,174 3,408,013 2,443,83 253.46
9
New Hampshire 175,763 67,697 - -61.48
108,066
New Jersey 8,958,831 9,696,998 738,167 8.24
New Mexico 479,074 1,195,562 716,488 149.56
New York 29,093,044 16,787,811 12,305,2 -42.30
33
North Carolina 2,414,668 6,826,133 4,411,46 182.69
5
North Dakota 100,000 33,846 -66,154 -66.15
Ohio 2,623,138 7,253,179 4,630,04 176.51
1
Oklahoma 1,050,786 2,373,374 1,322,58 125.87
8
Oregon 1,300,587 950,165 - -26.94
350,422
Pennsylvania 5,177,510 5,283,271 105,761 2.04
Rhode Island 554,753 1,868,964 1,314,21 236.90
1
South Carolina 2,679,771 6,725,031 4,045,26 150.96
0
South Dakota 100,000 22,856 -77,144 -77.14
Tennessee 1,846,877 4,778,344 2,931,46 158.73
7
Texas 12,636,414 9,992,376 - -20.92
2,644,03
8
Utah 428,266 1,129,611 701,345 163.76
Vermont 103,727 254,367 150,640 145.23
Virginia 2,642,609 4,808,147 2,165,53 81.95
8
Washington 2,310,797 1,815,450 - -21.44
495,347
West Virginia 184,768 301,237 116,469 63.04
Wisconsin 1,063,650 2,358,029 1,294,37 121.69
9
Wyoming 100,000 76,242 -23,758 -23.76
Guam 2,902 10,475 7,573 260.97
Puerto Rico 7,682,087 3,973,781 3,708,30 -48.27
6
Virgin Islands 0 278,726 278,726 N/A
==========================================================
Total $174,766,5 $174,766,5
00 00
----------------------------------------------------------
Note: N/A = Not applicable.
As demonstrated by these tables, changing the existing title I and II
formulas would redistribute funds across EMAs and states. Compared
with the existing formulas, either the beneficiary or the taxpayer
equity formula would increase funding for more EMAs and states than
it would decrease it (see table V.5).
Table V.5
Number of Grantees Experiencing Funding
Increases and Decreases
Increased Decreased
Type of formula funding funding
-------------------------- -------------- --------------
Title I beneficiary equity 31 11
Title II beneficiary 37 16
equity
Title I taxpayer equity 22 20
Title II taxpayer equity 33 20
----------------------------------------------------------
Nonetheless, under either formula, funding would decrease for some
EMAs and states if appropriations remained stable. A number of
mechanisms could be employed, however, to avoid EMA and state funding
losses when funding equity is improved. Appropriations could be made
to a level that obviates funding losses, hold-harmless provisions
could be applied, or a limit could be placed on the amount of funds
eligible for redistribution. For example, funding losses could be
avoided by only redistributing funds that were appropriated in excess
of a previous year's amount.
COMMENTS FROM THE DEPARTMENT OF
HEALTH AND HUMAN SERVICES
========================================================== Appendix VI
We solicited comments on our report from the Department of Health and
Human Services (HHS) through the Director, Office of HIV/AIDS Policy,
Health Education and Human Services. He provided us his comments,
along with those of the Division of HIV Services, Health Resources
Services Administration, which administers titles I and II of the
CARE Act. We also received comments from officials of the Centers
for Disease Control and Prevention (CDC).
In their general comments, the HHS officials stated that moving to a
more equitable funding formula could cause significant funding
changes and potential disruption to service delivery structures. We
share these concerns and have discussed methods to avoid these kinds
of difficulties in our report.
The HHS officials also raised questions about the appropriateness of
the Medicare Hospital Wage Cost (MHWC) Index as a proxy for
estimating labor costs for AIDS and HIV services among EMAs and
states. While we believe a wage index that is more closely related
to these services would be preferable to the MHWC Index, we were
unable to locate such an index. On the basis of our discussions with
experts, however, we determined that the MHWC Index would be an
appropriate alternative to a wage index that is specific to AIDS and
HIV services.
In addition, the HHS officials expressed concerns about the adequacy
of both the level of funding and the health care infrastructure for
AIDS and HIV services. While problems may exist with regard to
funding and infrastructure, these issues were not within the scope of
our study. The HHS officials provided specific comments about our
report, which have been incorporated as appropriate.
The CDC officials indicated that they agreed that a caseload
indicator based on an estimate of living cases was preferable to the
existing measure; however, they recommended the use of the number of
AIDS cases reported during the previous 2 years rather than our
proposed measure of weighted cases. These officials stated that our
caseload measure would require annual revision, would serve as an
incentive to states to underreport AIDS-related mortality, would be
technically difficult to compute, and was not a standard method for
estimating living AIDS cases.
We agree that our caseload measure might periodically need revision,
as would any such measure, in accordance with significant changes in
AIDS mortality. However, our caseload measure, when adjusted over
time, would more appropriately reflect the impact of changes in AIDS
mortality on the number of people living with AIDS than would a
measure based on cases reported in the previous 2 years. We do not
believe our proposed measure would serve as an incentive to
underreport AIDS-related mortality because states' funding would not
be directly affected by their reported mortality data. As discussed
in appendix I, we propose the use of weighted AIDS cases as a proxy
measure rather than an actual estimate of living AIDS cases to avoid
this potential incentive. Finally, we do not believe that our
proposed measure would be technically difficult to compute.
GAO CONTACTS AND STAFF
ACKNOWLEDGMENTS
========================================================= Appendix VII
GAO CONTACTS
Jerry Fastrup, Assistant Director, (202) 512-7211
Greg Dybalski, Senior Economist, (202) 512-7210
Mark Vinkenes, Senior Social Science Analyst, (202) 512-6841
ACKNOWLEDGMENTS
In addition to those named above, the following individuals made
important contributions to this report: David Bieritz, Evaluator;
Leslie Albin, Reports Analyst; Ann McDermott, Publishing Adviser.
BIBLIOGRAPHY
============================================================ Chapter 0
Federal Security Agency, Social Security Administration. The
Principle of Equalization Applied to the Allocation of Grants-in-Aid.
Memorandum No. 66. September 1947.
Institute for Health and Aging, University of California, San
Francisco. Review and Evaluation of Alcohol, Drug Abuse, and Mental
Health Services Block Grant Allotment Formulas, Final Report. 1986.
Office of Education Research and Improvement, U.S. Department of
Education. Poverty, Achievement, and the Distribution of
Compensatory Education Services. 1986.
Office of State and Local Finance, Department of the Treasury.
Federal-State-Local Fiscal Relations: Report to the President and
Congress. September 1985.
U.S. General Accounting Office. Older Americans Act: Funding
Formula Could Better Reflect State Needs (GAO/HEHS-04-41, May 12,
1994).
U.S. General Accounting Office. Maternal and Child Health: Block
Grant Funds Should Be Distributed More Equitably (GAO/HRD-92-5, Apr.
2, 1992).
U.S. General Accounting Office. Highway Funding: Federal
Distribution Formulas Should Be Changed (GAO/RCED-86-114, Mar. 31,
1986).
U.S. General Accounting Office. Changing Medicaid Formula Can
Improve Distribution of Funds to States (GAO/GGD-83-27, Mar. 9,
1983).
*** End of document. ***