Medicaid Formula: Differences in Funding Ability among States
Often Are Widened (10-JUL-03, GAO-03-620).
A primary goal in establishing Medicaid's statutory formula,
whereby states with lower per capita incomes (PCI) receive higher
rates of federal reimbursement for program costs, was to narrow
differences among states in their ability to fund Medicaid
services. States' ability to fund services depends on their
financial resources in relation to their number of and costs to
serve people in poverty. GAO and others have testified before
Congress that the current formula does not address wide
differences among states in their ability to fund their Medicaid
programs and that the formula's reliance on PCI is the primary
cause. GAO was asked to determine the extent to which the formula
narrows these differences and to identify factors that impede
further narrowing of differences. To evaluate the extent to which
the formula narrows differences in states' funding ability, GAO
used an alternative to PCI that more directly measures states'
resources, number of people in poverty, and cost of providing
services to this population. Using this measure, GAO determined
the effect of the current formula by comparing states' funding
ability before and after receiving their federal matching aid. If
differences in funding ability were eliminated, the formula would
have reduced differences by 100 percent.
-------------------------Indexing Terms-------------------------
REPORTNUM: GAO-03-620
ACCNO: A07511
TITLE: Medicaid Formula: Differences in Funding Ability among
States Often Are Widened
DATE: 07/10/2003
SUBJECT: Economic analysis
Federal aid programs
Health care programs
Managed health care
Health care costs
Federal/state relations
State-administered programs
Medicaid Equitable Federal Medical
Assistance Percentage Formula
Medicaid Program
******************************************************************
** This file contains an ASCII representation of the text of a **
** GAO Product. **
** **
** No attempt has been made to display graphic images, although **
** figure captions are reproduced. Tables are included, but **
** may not resemble those in the printed version. **
** **
** Please see the PDF (Portable Document Format) file, when **
** available, for a complete electronic file of the printed **
** document's contents. **
** **
******************************************************************
GAO-03-620
Report to the Honorable Dianne Feinstein, U. S. Senate
United States General Accounting Office
GAO
July 2003 MEDICAID FORMULA Differences in Funding Ability among States
Often Are Widened
GAO- 03- 620
The Medicaid formula narrows the average difference in states* funding
ability by 20 percent but often widens the gap between individual states
and the national average. Although the receipt of federal matching aid
moves 30 states closer to the national average, making the average
difference in funding ability smaller, it also moves 21 states farther
away from the average, widening the average difference. These 21 states
include 3 that are among the states with the largest populations in
poverty* California,
Florida, and New York. After federal matching aid is added, states*
funding ability ranges from 26 percent below the national average for two
states to 179 percent above for another. Because of the formula*s current
structure, in many instances, two states devoting similar proportions of
their own resources to Medicaid can spend very different amounts per
person in poverty. For example, in fiscal year 2000, California and
Wisconsin each devoted about $8 for every $1, 000 of their own state
resources toward Medicaid. However, under the current formula, Wisconsin
receives a relatively high federal matching rate despite its relatively
high ability to fund program services, whereas California receives a low
federal matching rate despite its relatively low ability to fund program
services. With the addition of federal matching aid, Wisconsin is enabled
to spend more than twice what California is able to spend per person in
poverty ($ 7, 532 versus $3, 731). Two factors constrain the formula from
further decreasing differences in
states* funding ability. First, PCI is not a comprehensive indicator of a
state*s total available resources and is a poor measure of the size of and
cost to serve a state*s people in poverty. Second, the statutory provision
that guarantees no state will receive less than a 50 percent matching rate
benefits many states that already have above- average resources to fund
health care
for their populations in poverty. For example, 2 of the 11 states that
benefit the most from the 50 percent *floor* receive matching rates that
are 35 and 20 percentage points higher, respectively, than the rates they
would receive based solely on their PCI.
GAO received comments on a draft of this report from two external
reviewers who have Medicaid formula expertise. They generally agreed with
the analysis and provided technical comments, which were incorporated as
appropriate. A primary goal in establishing
Medicaid*s statutory formula, whereby states with lower per capita incomes
(PCI) receive higher rates of federal reimbursement for program costs,
was to narrow differences among states in their ability to fund Medicaid
services. States* ability to fund services depends on their financial
resources in relation to their number of and costs to serve people in
poverty. GAO and others have testified before Congress that the current
formula does not address wide differences among states in their ability to
fund their Medicaid programs and that the formula*s reliance on PCI is the
primary cause. GAO was asked to determine the extent to which the
formula narrows these differences and to identify factors that impede
further narrowing of differences.
To evaluate the extent to which the formula narrows differences in states*
funding ability, GAO used an alternative to PCI that more directly
measures states* resources,
number of people in poverty, and cost of providing services to this
population. Using this measure, GAO determined the effect of the current
formula by comparing
states* funding ability before and after receiving their federal matching
aid. If differences in funding ability were eliminated, the formula would
have reduced differences by 100 percent. www. gao. gov/ cgi- bin/ getrpt?
GAO- 03- 620. To view the full product, including the scope
and methodology, click on the link above. For more information, contact
Kathryn G. Allen at (202) 512- 7118. Highlights of GAO- 03- 620, a report
to the
Honorable Dianne Feinstein, United States Senate
July 2003
MEDICAID FORMULA
Differences in Funding Ability among States Often Are Widened
Page i GAO- 03- 620 Medicaid Formula Letter 1 Results in Brief 4
Background 5 Medicaid Formula Narrows Differences in Some States* Funding
Ability and Widens Differences in Others 6 Use of PCI and 50 Percent Floor
Inhibits Formula*s Ability to Further Narrow Differences in States*
Funding Ability 14 Comments from External Reviewers 20 Appendix I
Legislative History and Description of the Matching
Formula 21 Legislative History of the Medicaid Formula 21 Current Medicaid
Matching Formula 22 Appendix II Methodology 25
Measuring States* Funding Ability 25 Measuring State Resources 30
Measuring People in Poverty and the Costs to Provide Them Program Services
32 Calculating States* Ability to Fund Medicaid Services without and with
Value of Federal Matching Aid Added 41 Comparing Proportion of States*
Resources Devoted to Medicaid with Their Total Spending per Person in
Poverty 43 Tables
Table 1: States Benefiting from Minimum Matching Rate Provisions, Fiscal
Year 2002, and Their Matching Rates without the Minimums 19 Table 2:
Medicaid Matching Rates for Fiscal Years 2002- 2004 23 Table 3: States*
Ability to Fund Program Services without and with
the Value of Fiscal Year 2000 Federal Matching Aid Added 28 Table 4:
Comparison of PCI with TTR, 3- Year Averages, 1996- 98 30 Table 5:
Distribution of Population in Poverty, by Age Group, 5- Year Averages,
1995- 99 33 Table 6: Weights for Age Groups to Reflect Cost Differences
and Medicaid Program Participation 35 Table 7: Comparison of Official and
Cost- Adjusted Poverty Rates, 5- Year Averages, 1995- 99 37 Table 8: Wage,
Rent, and Health Care Cost Indexes, by State 40 Contents
Page ii GAO- 03- 620 Medicaid Formula
Table 9: States* Funding Ability without and with the Value of Fiscal Year
2000 Federal Matching Aid Added 42 Table 10: Proportion of State Resources
Devoted to Medicaid per $1,000 of TTR Compared with Total Medicaid
Spending per Person in Poverty, Cost Adjusted, Fiscal Year 2000 44 Figures
Figure 1: States* Funding Ability Compared with the National Average,
without and with the Value of Federal Matching Aid Added 8 Figure 2:
Proportion of State Resources Devoted to Medicaid,
Compared with Total (State plus Federal) Medicaid Spending, Fiscal Year
2000 11 Figure 3: Proportion of State Resources Devoted to Medicaid
Compared with Program Spending per Person in Poverty, as a Percentage of
the National Average, Selected States, Fiscal Year 2000 13 Figure 4:
States* per Capita TTR and PCI, 1996- 98 15 Figure 5: Comparison of
States* PCIs with Their People in Poverty, Cost Adjusted 17
Page iii GAO- 03- 620 Medicaid Formula Abbreviations
BEA Bureau of Economic Analysis BLS Bureau of Labor Statistics CMS Centers
for Medicare & Medicaid Services CPS Current Population Survey DSH
disproportionate share hospital EPSDT Early and Periodic Screening,
Diagnostic, and Treatment FMAP Federal Medical Assistance Percentage FPL
federal poverty level GSP Gross State Product HUD Department of Housing
and Urban Development PCI per capita income PPS Prospective Payment System
SIC Standard Industrial Classification
SPI state personal income SSA Social Security Administration TTR Total
Taxable Resources
This is a work of the U. S. Government and is not subject to copyright
protection in the United States. It may be reproduced and distributed in
its entirety without further permission from GAO. It may contain
copyrighted graphics, images or other materials. Permission from the
copyright holder may be necessary should you wish to reproduce copyrighted
materials separately from GAO*s product.
Page 1 GAO- 03- 620 Medicaid Formula
July 10, 2003 The Honorable Dianne Feinstein United States Senate Dear
Senator Feinstein: Created in 1965, Medicaid is the largest federal
program assisting states in financing medical and health- related services
for certain categories of the country*s low- income population. In fiscal
year 2000, 1 Medicaid served
about 43 million beneficiaries and had expenditures totaling about $196
billion, $111 billion of which was financed by the federal government and
the rest financed by the states. 2 The federal share of total Medicaid
program costs is determined using a statutory formula that calculates the
portion of each state*s Medicaid expenditures that the federal government
will pay, known as the Federal Medical Assistance Percentage (FMAP),
referred to in this report as the federal matching rate. 3 The formula
calculates the federal matching rate for each state on the basis of its
per capita income (PCI) in relation to national PCI. States with a low PCI
receive a higher federal matching rate, and states with a high PCI receive
a lower rate. The Medicaid statute also provides for a 50 percent minimum
federal matching rate (* 50 percent floor*) that reflects a federal
commitment to fund at least half the cost of each state*s program. 4 One
of the goals of the formula has been to narrow differences among states in
their ability to fund Medicaid services, which is determined by a state*s
financial resources in relation to its low- income population. By
providing higher matching rates to states with low PCI, it was expected
that these states would be in a better position to provide health care
1 Fiscal year 2000 is the latest year for which Medicaid data on spending
and the number of beneficiaries served were available. 2 Medicaid programs
operate in the 50 states, the District of Columbia, and five U. S.
territories. In this report, *states* refers to the 50 states and the
District of Columbia. 3 Three other programs* the State Children*s Health
Insurance Program, Adoption Assistance, and Foster Care* also use the
Medicaid matching formula to establish federal
matching rates. These three programs accounted for an additional $7.49
billion in federal funding in fiscal year 2000.
4 42 U. S. C. S: 1396d( b)( 1) (2000).
United States General Accounting Office Washington, DC 20548
Page 2 GAO- 03- 620 Medicaid Formula
services to low- income populations. (App. I contains a legislative
history of the formula.)
In 1995, we and other witnesses testified before the Senate Committee on
Finance that the current Medicaid formula did not adequately address wide
differences among states in their ability to fund program services and
that the formula*s reliance on PCI is the primary cause. Witnesses
generally testified that PCI is an unreliable indicator of states* ability
to fund Medicaid programs. 5 Because the formula has not been changed
since the program*s inception
and concerns persist regarding its performance with respect to narrowing
differences in states* ability to fund program services, you asked us to
address the following questions: (1) To what extent does the Medicaid
formula reduce differences in states* ability to fund program services?
(2) What factors prevent the formula from further narrowing differences in
states* funding ability?
To evaluate the extent to which the formula narrows differences in states*
ability to fund program services, we defined a state*s ability to fund its
Medicaid programs as the financial resources potentially subject to state
taxation relative to its number of low- income residents, adjusted for the
cost of providing health care to them. 6 For state resources, we used
Total Taxable Resources (TTR), a measure of all income potentially subject
to taxation that is either produced within a state or received by state
residents from out- of- state sources. TTR is reported annually by the
5 U. S. General Accounting Office, Medicaid: Matching Formula*s
Performance and Potential Modifications, GAO/ T- HEHS- 95- 226
(Washington, D. C.: July 27, 1995); Jerry Cromwell, testimony before the
Senate Committee on Finance, Improvements in the Federal Medicaid Matching
Formula; and Robert P. Strauss, testimony before the Senate Committee on
Finance, Revising the Medicaid Reimbursement Formula in an Era of
Fiscal Austerity, 104th Congress, 1st sess., July 27, 1995. 6 We measured
states* funding ability on the basis of potentially taxable resources and
potentially eligible participants in Medicaid so that our measure of
funding ability, before federal matching aid is taken into account, does
not reflect the influence of states* individual policy choices. The
matching formula also affects states* decisions about the amount and type
of Medicaid services they provide and therefore affects the availability
of
health care to low- income individuals as well. However, we did not
evaluate the formula*s performance in terms of equalizing access to care
because of the high degree of uncertainty in predicting how individual
states* spending decisions are affected by changes in matching rates.
Page 3 GAO- 03- 620 Medicaid Formula
Department of the Treasury. 7 To determine the number of low- income
people in each state (* people in poverty*), we obtained the Bureau of the
Census*s counts of people with incomes at or below the federal poverty
level (FPL). 8 We adjusted the counts of people in poverty to reflect (1)
the higher cost of serving the elderly, who utilize health care services
at higher rates than other age groups, and (2) geographic differences in
the cost of medical personnel, facilities, and supplies used to deliver
health care services. To adjust for age differences in people in poverty,
we used data on Medicaid spending by age group from the Department of
Health and Human Services* (HHS) Centers for Medicare & Medicaid Services
(CMS). 9 We used 5- year averages of people in poverty for each age group
for 1995
through 1999 to increase the reliability of the state- level population
counts because they are subject to statistical error, especially in
smaller states. To measure geographic differences in the cost of medical
personnel, facilities, and supplies, we used data from the Department of
Labor*s Bureau of Labor Statistics (BLS) and from the Department of
Housing and Urban Development (HUD).
We compared states* funding ability from their own resources with their
funding ability after their resources have been augmented to include the
value of the federal Medicaid matching aid they receive. Throughout this
report, we refer to augmenting a state*s taxable resources this way as
state funding ability with the *value* of federal matching aid included.
If differences in funding ability were completely eliminated by adding the
value of federal matching aid, the formula would have reduced differences
in states* funding ability by 100 percent. We did our work between June
2001 and June 2003 in accordance with generally accepted government
auditing standards. (App. II provides a more detailed discussion of our
methodology.)
7 We used 3- year averages of TTR (for 1996 through 1998) to parallel the
use of 3- year averages of PCI in the current formula (see app. I for a
more detailed description of the current formula).
8 The federal government bases Medicaid eligibility on a variety of
categorical and incomerelated factors, and states may expand their
programs beyond the minimum requirements. As a result of the flexibility
given states in administering their Medicaid programs, except for children
and pregnant women, there is no federal minimum income level below which
individuals must be covered under Medicaid that can be used as a basis for
measuring potentially eligible low- income individuals. 9 We used CMS data
on average per capita Medicaid spending for elderly (aged 65 and over)
and other beneficiaries to determine how much to weight the numbers of
people in poverty who are elderly to reflect the higher cost to provide
them services.
Page 4 GAO- 03- 620 Medicaid Formula
The current Medicaid formula narrows the average differences in states*
funding ability by 20 percent, but it often widens the gap between
individual states and the national average. Although the formula moves 30
states closer to the national average funding ability after they receive
their
federal matching aid, making the average differences in funding ability
smaller, it moves 21 states farther away, including 3 states that have 30
percent of the nation*s population in poverty* California, Florida, and
New York. After the value of federal matching aid is added, states*
funding ability ranges from 26 percent below the national average for two
states to 179 percent above the national average for another. Because of
the formula*s current structure, in many instances two states devoting
roughly the same proportion of their resources to Medicaid are able to
spend very different amounts per person in poverty. For example, in fiscal
year 2000, Wisconsin and California devoted the same proportion of their
states* own
resources to fund their Medicaid programs (about $8 per $1,000 of TTR).
Yet, after receiving federal matching aid, Wisconsin*s funding ability was
almost 50 percent above the national average and California*s was 26
percent below the national average. Because the current Medicaid matching
formula does not reflect the fact that Wisconsin has fewer people in
poverty and lower costs to provide health care services to its population
in poverty than California, Wisconsin*s federal matching aid enables it to
spend more than twice what California could spend per
person in poverty*$ 7,532 compared with $3,731. Two factors prevent the
Medicaid formula from further narrowing differences in states* funding
abilities. First, the formula uses PCI to calculate the federal matching
rate, but it is a poor proxy measure for the components of funding
ability* states* resources and the size of and costs to serve their
populations potentially eligible for Medicaid services. Second, the 50
percent minimum federal matching rate disproportionately benefits states
that already have above- average resources to fund health
care for their populations in poverty. The 50 percent *floor* thus
prevents further narrowing of funding abilities by giving some states
federal matching rates significantly higher than they would otherwise
receive without the floor.
We received comments on a draft of this report from two external reviewers
with Medicaid formula expertise. They generally agreed with our analysis
and provided technical comments, which we incorporated as appropriate.
Results in Brief
Page 5 GAO- 03- 620 Medicaid Formula
Medicaid eligibility is determined by several factors, including an
individual*s or a family*s income in relation to the FPL, age, and
eligibility for certain other federal program benefits. For example,
federal law requires state programs to cover pregnant women and children
under age 6 if their family income is at or below 133 percent of the FPL,
children under age 19 in families with incomes at or below the FPL, and
individuals who receive Supplemental Security Income because they have
disabling conditions. 10 For most covered populations, state Medicaid
programs are required to offer certain benefits, such as physician
services, inpatient and outpatient hospital services, and nursing facility
and home health services. State Medicaid programs must provide Early and
Periodic Screening, Diagnostic, and Treatment (EPSDT) services for most
children, 11 intended as comprehensive, periodic evaluations of children*s
health and
developmental history, that include vision, hearing, and dental screening.
States* Medicaid programs can differ dramatically because states may
expand their programs beyond the minimum requirements to cover, for
example, individuals whose incomes exceed federally mandated eligibility
thresholds and optional services, such as prosthetic devices and
prescription drugs. For example, a state may extend Medicaid eligibility
to certain population groups, such as pregnant women who have family
incomes above 133 percent of the FPL, or make optional services such as
prescription drugs available to its entire covered population.
Since the Medicaid program began, total program costs have been
apportioned between states and the federal government using a formula that
provides more generous federal matching aid to states with lower PCI. 12
The use of PCI in federal grant formulas dates to 1946, when it was
10 In the majority of states, individuals who receive SSI are
automatically eligible for Medicaid. Eleven states have more restrictive
Medicaid eligibility standards through section 1902( f) of the Social
Security Act. These 11 states are often referred to as *209( b) states*
because the origin of this authority was section 209( b) of the Social
Security Amendments of 1972. Pub. L. No. 92- 603, 86 Stat. 1329, 1381
(codified as amended at 42 U. S. C. S: 1396a( f) (2000)).
11 EPSDT services are optional for the medically needy population, a
category of individuals who generally have too much income to qualify for
Medicaid but have *spent down* their income by incurring medical care
expenses. See 42 U. S. C. S: 1396( a)( 10)( C) (2000). 12 Matching rates
are calculated using the following formula: 2
PCI U. S. PCI State 0.45 1.00 Rate Matching Federal . .
. .
. . . . =
Background
Page 6 GAO- 03- 620 Medicaid Formula
chosen as a proxy for a state*s ability to fund public services.
Consistent with the purpose described in the formula*s legislative
history, PCI is used as a proxy for both state resources and the low-
income population. As a state*s PCI increases, relative to the national
average, the formula provides for a decreasing federal matching rate,
meaning the federal government shares a smaller portion of a state*s
costs. By statute, the federal matching rate may range from 50 percent to
83 percent. 13 The formula*s multiplier,
currently 0.45, represents the state*s share of its total Medicaid costs
for a state with PCI equal to the national average, and the federal
government thus pays a 55 percent share of total costs.
The Medicaid formula reduces by 20 percent the differences among states in
their ability to fund program services, compared with the national average
funding ability. While the formula narrows differences for 30 states,
making the average difference in funding ability smaller, it moves 21
states farther away from the national average, making the average
difference wider. These 21 states include 3 that are among those with the
largest populations in poverty* California, Florida, and New York. Because
of the formula*s current structure, in many instances, two states devoting
the same proportion of their own resources toward funding Medicaid
services are unable, after receiving federal matching aid, to spend the
same amounts per person in poverty, adjusted for cost
differences related to age and geographic location. Because state
resources, numbers of people in poverty, and the cost of serving this
population vary widely across the states, there also are wide differences
in states* ability to fund health care services. Considering these
indicators of state funding ability, Alaska has the highest funding
ability* exceeding the national average by 119 percent* and Mississippi
has the lowest funding ability* 46 percent below the national average, as
measured using states* TTR and the number of people in poverty, adjusting
the poverty count for age and geographic cost differences (see fig. 1).
Nationwide, the average difference between a state*s funding ability and
13 In fiscal year 2003, Mississippi had the highest federal matching rate
of any state* 76.6
percent. Medicaid Formula Narrows Differences
in Some States* Funding Ability and Widens Differences in Others
Formula Reduces Overall Differences in States* Funding Ability by 20
Percent
Page 7 GAO- 03- 620 Medicaid Formula
that of the average state is 22.7 percent. 14 Nineteen states have funding
ability 25 percent or more above the national average, and 10 states have
funding ability 25 percent or more below the national average.
After the value of federal matching aid is added to states* own resources,
the average difference in states* funding ability drops from 22.7 percent
to 18.1 percent. This represents a 20 percent reduction of aggregate
differences in states* funding ability. 15 After the receipt of federal
matching aid, differences in states* funding abilities ranged from 26
percent below the national average for California and New York to 179
percent above for Alaska.
14 The average difference in states* funding ability is calculated by
comparing each state*s funding ability with the average funding ability of
all states and calculating the average difference (both positive and
negative), weighting each state by its number of people in
poverty. 15 In an absolute sense, the federal matching rate enhances the
funding ability of all states. By comparing each state*s funding ability
with the average funding ability for all states, our
measure of funding ability is a relative, rather than an absolute, measure
of differences in funding ability. As a consequence, while states with low
funding ability receiving a relatively low federal match are helped in an
absolute sense, in a relative sense they move farther below a new, higher
national average funding ability, resulting in relatively larger
differences in states* funding ability.
Page 8 GAO- 03- 620 Medicaid Formula
Figure 1: States* Funding Ability Compared with the National Average,
without and with the Value of Federal Matching Aid Added
Page 9 GAO- 03- 620 Medicaid Formula
Note: GAO analysis of data from HHS, HUD, and the Departments of Commerce,
Labor, and the Treasury.
The aggregate 20 percent reduction of differences in states* funding
ability under the formula masks the effect of the formula on individual
states. For example, as shown in figure 1, consistent with the formula*s
goals, the onequarter of states with the lowest funding ability before the
match move closer to the average state*s funding ability after the value
of the federal match is added. 16 In total, 30 states move closer to the
national average
after adding the federal match. However, as the right panel of figure 1
shows, adding the value of federal matching aid often has inconsistent
effects. For example, including the value of federal matching aid moves
Alaska*s and Utah*s funding ability farther above, rather than closer to,
the national average funding ability. This happens because PCI does not
adequately reflect that these two states have fewer people in poverty than
the national average. In addition, Utah has lower- than- average costs to
provide health care services. The current formula actually moves 21 states
farther above or below the average: Four of the 21 states* California,
Florida, Hawaii, and New York* have
below- average funding ability before federal matching aid is added and
move farther below the average after federal matching aid is added. These
4 states have approximately 31 percent of the nation*s people in poverty.
For example, California*s funding ability drops from 15 percent below the
average to 26 percent below the average and New York*s funding ability
drops from 12 percent below the average to 26 percent below the average.
These two states thus rank last in terms of state funding ability after
the value of federal matching aid is added. Thirteen states that have
above- average funding ability before adding the
value of federal matching aid move farther above the average after it is
added. 17 For example, Utah*s funding ability is 73 percent above the
national average before the federal match is added but increases to 155
percent above the national average after the match. Of the 4 remaining
states, 3* Idaho, Maine, and North Dakota* have
below- average funding ability before the match is added and above 16 In
decreasing order of funding ability before adding the value of the federal
match, these states are Tennessee, Kentucky, Oklahoma, Montana, Arizona,
South Carolina, Louisiana, District of Columbia, Alabama, Arkansas, West
Virginia, New Mexico, and Mississippi.
17 The states, listed from highest to lowest funding ability, are Alaska,
Utah, Wisconsin, Indiana, Wyoming, Iowa, Kansas, Missouri, Nebraska,
Vermont, Ohio, Oregon, and South Dakota. Funding Ability of 21 States
Moves Farther from
Average State*s Funding Ability after Federal Match Is Added
Page 10 GAO- 03- 620 Medicaid Formula
average funding ability after the match is added. For the fourth state*
Rhode Island* the reverse is true: Rhode Island has above- average funding
ability before the match and below- average funding ability after the
match is added.
States commit widely varying proportions of their own financial resources
to fund Medicaid benefits. For example, in fiscal year 2000, New York
devoted $18.16 per $1,000 of its TTR toward its Medicaid program, 18
roughly 5 times the proportion of resources that Utah devoted ($ 3.74 per
$1,000) (see left panel of fig. 2). States* Medicaid cost- adjusted
spending per person in poverty varies as well. For example, Alaska*s
combined federal and state spending was over $10,000 per person in
poverty, while Nevada*s spending was approximately $2,500 per person in
poverty (see right panel of fig. 2).
18 The TTR amount used in these calculations is a 3- year average, 1996-
98. Many States Devoting the
Same Proportion of Their Own Resources to Medicaid Cannot Spend Comparable
Amounts per Person
Page 11 GAO- 03- 620 Medicaid Formula
Figure 2: Proportion of State Resources Devoted to Medicaid, Compared with
Total (State plus Federal) Medicaid Spending, Fiscal Year 2000
Page 12 GAO- 03- 620 Medicaid Formula
Note: GAO analysis of data from HHS, HUD, and the Departments of Commerce,
Labor, and the Treasury. a Medicaid spending per person is total spending
(state and federal) per person in poverty after
adjusting for cost differences related to age and geographic location.
Because the federal matching formula does not fully eliminate differences
in states* funding ability, states devoting similar proportions of their
own resources to Medicaid cannot spend the same amounts per person in
poverty, cost adjusted, with federal matching aid factored in. In
addition, because the formula further increases the already high funding
ability of
some states and decreases the low funding ability of others, these
spending differences can be quite large. For example, in fiscal year 2000,
both California and Wisconsin devoted roughly the same proportion of
their own resources to fund program benefits* about $8 per $1,000 of
taxable resources* which was close to the national average ($ 8.37)
proportion of resources states devoted to Medicaid that year. However, the
current formula moved California*s below- average funding ability farther
below the national average and increased Wisconsin*s aboveaverage funding
ability farther above. This occurred because Wisconsin receives a high
federal match despite its relatively high funding ability, whereas
California receives a low federal match despite its relatively low
funding ability. Once federal matching aid was factored in, with their
nearly identical funding effort, Wisconsin is enabled to spend more than
twice what California could spend per person in poverty*$ 7,532 compared
with $3,731. Similarly, Florida and Iowa each devoted $6.48 per $1,000 in
state resources toward their Medicaid programs. After adding the federal
match, Iowa could spend $6,729 per person in poverty, cost adjusted, while
Florida could spend just $3,160 per person. (See fig. 3.)
Page 13 GAO- 03- 620 Medicaid Formula
Figure 3: Proportion of State Resources Devoted to Medicaid Compared with
Program Spending per Person in Poverty, as a Percentage of the National
Average, Selected States, Fiscal Year 2000
Notes: Spending per person in poverty includes cost adjustments for
differences in age and geographic location. GAO analysis of data from HHS,
HUD, and the Departments of Commerce, Labor, and the Treasury.
Page 14 GAO- 03- 620 Medicaid Formula
Two factors prevent the Medicaid formula from further reducing differences
in states* funding ability. First, PCI* the single measure used to
establish federal matching rates* is not a comprehensive measure of state
resources and is a poor proxy for the size of and cost to serve a state*s
population in poverty. Second, special statutory provisions, including the
minimum 50 percent federal matching rate, give several states with already
high funding ability a higher federal matching rate than they would
receive without these provisions.
PCI is an inadequate measure of states* funding ability because it is an
incomplete measure of states* resources, it is a poor proxy for the size
of a state*s population in poverty, and it does not take into account
differences in the cost of providing health care services to people in
poverty. As an
indicator of state resources, PCI measures income received by state
residents, such as wages, rents, and interest income, but it does not
include other sources of income potentially subject to state taxation,
such as corporate income produced within the state but not received by
state residents. For example, PCI especially understates the taxable
resources
in energy- exporting states, such as Alaska and Wyoming, and in states
that house numerous corporate headquarters, such as Delaware.
By comparison, because TTR comprises the income included in PCI as well as
income from other sources, such as corporate income and capital gains,
states* TTR exceeds PCI by about 32 percent nationwide. 19 As shown
in figure 4, which compares states* TTR with PCI, states whose resources
are particularly poorly represented by PCI include the District of
Columbia, Delaware, Alaska, and Wyoming.
19 For a discussion of TTR, see Department of the Treasury, Office of
Economic Policy,
Treasury Methodology for Estimating Total Taxable Resources, TTR
(Washington, D. C.: Oct. 1, 1998; revised November 2002). http:// www.
treas. gov/ offices/ economicpolicy/ resources/ index. html? IMAGE. X=
28\& IMAGE. Y= 9 (See *Summary of Current Methodology for Estimating TTR*)
(downloaded June 4, 2003). Use of PCI and 50
Percent Floor Inhibits Formula*s Ability to Further Narrow Differences in
States* Funding Ability
PCI Is Not a Comprehensive Measure of States* Resources and Is a Poor
Proxy for the Size of and Cost to Provide Services to Their People in
Poverty
Page 15 GAO- 03- 620 Medicaid Formula
Figure 4: States* per Capita TTR and PCI, 1996- 98
Notes: TTR comprises the income included in PCI as well as income from
other sources, such as corporate income and capital gains. GAO analysis of
data from the Departments of Commerce and the Treasury.
0 10,000 20,000 30,000 40,000 50,000 60,000 Mississippi West Virginia
Montana New Mexico Arkansas Idaho Utah Oklahoma Alabama Kentucky Louisiana
South Carolina North Dakota Maine South Dakota Arizona Tennessee
Vermont Wyoming Iowa Indiana North Carolina Texas Missouri Kansas Georgia
Oregon Nebraska Wisconsin Ohio Michigan
Florida Pennsylvania Hawaii Rhode Island California Virginia Washington
Alaska Minnesota New Hampshire Delaware Colorado
Nevada Illinois Maryland New York Massachusetts New Jersey Connecticut
District of Columbia
Dollars
TTR PCI Sources: Departments of Commerce and the Treasury.
Page 16 GAO- 03- 620 Medicaid Formula
Using PCI to measure the size of a state*s low- income population assumes
that the lower a state*s PCI, the greater its population in poverty.
However, two states with similar PCIs may differ widely in their
percentages of
people in poverty. In addition, PCI is not a good proxy for the
differences in the cost of providing health care services that are related
to the ages of the population served and the geographic area in which
services are provided. Persons who are elderly typically use health care
services at higher rates than adults and children and therefore cost more
to serve. Two states with low PCIs may have very different proportions of
elderly persons potentially eligible for Medicaid. In addition, costs to
provide health care services vary widely depending on geographic location
because wages and other costs of office space vary regionally. For
example, the District of Columbia and Connecticut have similar PCIs, but
the share of the District*s population in poverty is more than twice
Connecticut*s. Health care costs also are 10 percent higher in the
District than in Connecticut. (Fig. 5 compares state rankings by PCI and
by people in poverty, adjusted for cost differences related to age and
geographic location.)
Page 17 GAO- 03- 620 Medicaid Formula
Figure 5: Comparison of States* PCIs with Their People in Poverty, Cost
Adjusted Note: GAO analysis of data from HHS, HUD, and the Departments of
Commerce, Labor, and the Treasury.
Page 18 GAO- 03- 620 Medicaid Formula
a People in poverty refers to people with incomes at or below the FPL,
adjusted for cost differences related to age and geographic location.
Because of the 50 percent floor, 11 states received higher federal
matching rates in fiscal year 2002 than they would have if their rates had
been based only on their PCI. Two others* Alaska and the District of
Columbia* received special federal matching rates set in statutes that
gave them higher matching rates than they would have received solely on
the basis of PCI. 20 (See table 1.)
20 Alaska*s current higher matching rate was authorized by the Medicare,
Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 to
address inadequacies in the national calculation and establish more
equitable matching rates for the state. Pub. L. No. 106- 554, App. F, S:
706, 114 Stat. 2763, 2763A- 577. The District of Columbia*s higher
matching rate was authorized by the Balanced Budget Act of 1997 at the
time comprehensive policy changes realigning the financial relationship
between the District
and federal government also were enacted. Pub. L. No. 105- 33, S: 4725 and
tit. XI, 111 Stat. 251, 518 and 712. Minimum Federal Match
Generally Helps States That Already Have High Funding Ability
Page 19 GAO- 03- 620 Medicaid Formula
Table 1: States Benefiting from Minimum Matching Rate Provisions, Fiscal
Year 2002, and Their Matching Rates without the Minimums Numbers in
percent
State Funding ability
without federal match (as a percentage of
national average)
Minimum federal matching
rate Federal
matching rate without minimum
match Percentage
point difference
Alaska 219 57.38 53.01 -4.37 New Hampshire 179 50.00 47.36 -2.64
Connecticut 176 50.00 14.99 -35.01 Colorado 165 50.00 46.22 -3.78 Delaware
162 50.00 48.13 -1.87 New Jersey 160 50.00 29.60 -20.40 Maryland 143 50.00
42.32 -7.68 Minnesota 143 50.00 48.03 -1.97 Illinois 131 50.00 46.09 -3.91
Massachusetts 131 50.00 32.27 -17.73 Nevada 126 50.00 46.62 -3.38 New York
88 50.00 37.14 -12.86 District of Columbia 71 70.00 12.99 -57.01
Source: HHS. Notes: States are listed in decreasing order of funding
ability. GAO analysis of data from HHS.
Eleven of these 13 states (all except the District of Columbia and New
York) had above- average funding ability in fiscal year 2002. Their
receipt of a higher federal matching rate than they would have received
without statutory minimums increases the overall differences in funding
ability among the states. Connecticut and New Jersey benefit the most from
the statutory minimums, receiving* as a result of the 50 percent floor*
matching rates that are 35 and 20 percentage points higher, respectively,
than the rates they would have received based solely on their PCI.
Receiving a higher matching rate than what the formula provides on the
basis of PCI enables these states to spend more on program benefits per
person in poverty than states with less funding ability that devote a
higher percentage of their resources to funding program benefits.
The statutory minimums benefit the District of Columbia and New York by
providing them a higher matching rate than they would otherwise have.
Because these two states have below- average funding ability, the minimum
matching provisions have the effect of moving them closer to the funding
ability of the average state and thus help to reduce overall differences
in
Page 20 GAO- 03- 620 Medicaid Formula
funding ability among the states. For example, New York*s funding ability
without the value of federal matching aid added is 12 percent below the
average funding ability; with the value of federal matching aid added, its
funding ability is farther from the average funding ability* 26 percent
below the average. Without the floor, New York*s matching rate would be 37
percent, rather than 50 percent. Therefore, the 50 percent minimum brings
New York*s funding ability closer to the average funding ability than
it would be with the matching rate it would receive without the minimum.
We received comments on our draft report from two external reviewers who
have Medicaid formula expertise. The reviewers generally agreed with our
analysis and provided technical comments, which we incorporated as
appropriate.
As agreed with your office, unless you publicly announce its contents
earlier, we plan no further distribution of this report until 30 days
after its issue date. At that time, we will send copies of this report to
appropriate congressional committees and will make copies available to
others on request. In addition, the report will be available at no charge
on the GAO Web site at http:// www. gao. gov.
If you or your staff have any questions about this report, please call me
at (202) 512- 7118 or Jerry Fastrup at (202) 512- 7211. Major contributors
to this report include Richard Horte, Robert Dinkelmeyer, Michael
Williams, Elizabeth T. Morrison, and Michael Rose.
Sincerely yours, Kathryn G. Allen Director, Health Care* Medicaid
and Private Health Insurance Issues Comments from
External Reviewers
Appendix I: Legislative History and Description of the Matching Formula
Page 21 GAO- 03- 620 Medicaid Formula
This appendix summarizes the legislative history that led to the use of
per capita income (PCI) in the Medicaid matching formula and describes how
matching rates are calculated.
The current formula is an outgrowth of variable rate matching formulas
first discussed by Congress in the late 1940s. Senate reports accompanying
the Social Security Act Amendments of 1946 first articulated, in the case
of
public assistance, the rationale for a variable rate matching formula
based on state PCI: Federal grants- in- aid for public assistance are
intended to help in aiding the aged and blind
persons and dependent children in all parts of the country and to some
extent to equalize the financial burden throughout the Nation. . . . The
present 50 percent basis of Federal participation does not recognize
differences in the ability of States to finance public assistance, nor
does it recognize the greater incidence of poverty in States with low
economic resources. To assist their needy people, the low income States
must make greater tax effort than States with larger resources where
relatively fewer persons are in need. 1 The Social Security Amendments of
1958 established a PCI- based variable rate matching formula, with certain
maximums, for public assistance and
reimbursement of medical providers. Under this formula, federal matching
rates ranged from a minimum of 50 percent for high- income states to a
maximum of 65 percent for low- income states. 2 The Social Security
Amendments of 1960 increased the maximum matching rate from 65 percent to
80 percent. 3 1 S. Rep. No. 79- 1862, at 15 (1946), reprinted in 1946 U.
S. C. C. A. N. 1510, 1525. In conference,
a variable rate was adopted, but not one based on state PCI. S. Conf. Rep.
No. 79- 2724, at 8 (1946), reprinted in 1946 U. S. C. A. N. N. 1552, 1555.
2 Pub. L. No. 85- 840, S: 505, 72 Stat. 1013, 1050. Before this, payments
to medical providers were reimbursed up to a certain maximum dollar amount
at a uniform rate of 50 percent for all states. S. Rep. No. 85- 2388, at
39 (1958), reprinted in 1958 U. S. C. C. A. N. 4212, 4259.
3 Pub. L. No. 86- 778, sec. 601( f), S: 6( c), 74 Stat. 924, 991. Appendix
I: Legislative History and
Description of the Matching Formula Legislative History of the Medicaid
Formula
Appendix I: Legislative History and Description of the Matching Formula
Page 22 GAO- 03- 620 Medicaid Formula
When Medicaid was created in 1965, it (1) was structured as an openended
entitlement for eligible low- income individuals without limits on the
maximum dollar amount subject to reimbursement, as in predecessor
programs; 4 (2) increased the federal government*s total nationwide share
financed from 50 to 55 percent; and (3) raised the maximum federal
matching rate from 80 to 83 percent. 5 The statutory matching formula,
known as the Federal Medical Assistance Percentage (FMAP), used for
calculating matching rates is
2 PCI U. S.
PCI State 0.45 1.00 FMAP . . . .
. . . . =
The current matching formula is calibrated with a 0.45 *multiplier.* The
value of the multiplier determines the percentage of a state*s Medicaid
spending for which the state is responsible. For example, using the 0.45
multiplier, a state with a PCI equal to the U. S. average would receive a
federal matching rate of 55 percent (1 - 0.45 = 0.55). A smaller
multiplier of 0.40 would raise the federal matching rate for all states
and would raise the matching rate for a state with the national average
PCI from 55 percent to 60 percent, whereas a higher multiplier of 50
percent would reduce the federal matching rate for a state with average
PCI from 55 percent to 50 percent.
Relative PCI is intended to represent states* funding ability, which is a
combination of states* resources and states* people in poverty. 6
Consistent with this intent, squaring PCI has the effect of making PCI
appear in the formula twice, thus reflecting both state resources and
people in poverty. Squaring PCI magnifies the difference between the
state*s and the national average PCI. For example, if a state*s PCI is 90
percent of the national average, the squared value of its relative PCI
would be 81 percent (0.9 x 0.9 = 0.81), resulting in a federal matching
rate of 64 percent (that is, 1.00 - 0.45 x 0.81 = 0.64), rather than the
60 percent rate the state would receive if relative income was not squared
(that is, 1.00 - 0.45 x 0.9 = 0.60). If PCI
4 Social Security Amendments of 1965, Pub. L. No. 89- 97, sec. 121, S:
1905( b), 79 Stat. 286, 344. 5 See U. S. General Accounting Office,
Changing Medicaid Formula Can Improve Distribution of Funds to States,
GAO/ GGD- 83- 27 (Washington, D. C.: Mar. 9, 1983) for a more complete
description of the legislative history of the Medicaid formula.
6 A state*s relative PCI is its PCI when expressed as a percentage of the
U. S. average PCI. Current Medicaid
Matching Formula
Appendix I: Legislative History and Description of the Matching Formula
Page 23 GAO- 03- 620 Medicaid Formula
were a good proxy for people in poverty, squaring would be appropriate
since squaring would reflect the effect on states* funding ability of both
resources and people in poverty. However, to the extent that PCI does not
accurately reflect state resources and people in poverty, squaring
magnifies this inaccuracy.
The Department of Health and Human Services (HHS) is responsible for
calculating matching rates under the formula. HHS is required to calculate
matching rates 1 year before the fiscal year in which they are effective,
using a 3- year average of the most recently available PCI data reported
by the Department of Commerce. Thus, fiscal year 2003 matching rates were
calculated at the beginning of fiscal year 2002 using a 3- year average of
PCI for 1998 through 2000. Publicly announcing matching rates a year in
advance of their use allows states time to make program changes in
response to changes in the rate at which the federal government will
reimburse eligible program costs. However, the combination of a 1- year
lag between the computation of state matching rates and their
implementation, coupled with the fact that a 3- year average of PCI is
used, also means that the distribution of states* matching rates reflects
economic conditions that existed several years earlier. Federal matching
rates for fiscal years 2002 through 2004 are shown in table 2. Table 2:
Medicaid Matching Rates for Fiscal Years 2002- 2004
Fiscal year State 2002 2003 2004
Alabama 70.45 70.60 70.75 Alaska 57.38 58.27 58.39 Arizona 64.98 67.25
67.26 Arkansas 72.64 74.28 74.67 California 51.40 50.00 50.00 Colorado
50.00 50.00 50.00 Connecticut 50.00 50.00 50.00 Delaware 50.00 50.00 50.00
District of Columbia 70.00 70.00 70.00 Florida 56.43 58.83 58.93 Georgia
59.00 59.60 59.58 Hawaii 56.34 58.77 58.90 Idaho 71.02 70.96 70.46
Illinois 50.00 50.00 50.00 Indiana 62.04 61.97 62.32 Iowa 62.86 63.50
63.93 Kansas 60.20 60.15 60.82 Kentucky 69.94 69.89 70.09
Appendix I: Legislative History and Description of the Matching Formula
Page 24 GAO- 03- 620 Medicaid Formula
Fiscal year State 2002 2003 2004
Louisiana 70.30 71.28 71.63 Maine 66.58 66.22 66.01 Maryland 50.00 50.00
50.00 Massachusetts 50.00 50.00 50.00 Michigan 56.36 55.42 55.89 Minnesota
50.00 50.00 50.00 Mississippi 76.09 76.62 77.08 Missouri 61.06 61.23 61.47
Montana 72.83 72.96 72.85 Nebraska 59.55 59.52 59.89 Nevada 50.00 52.39
54.93 New Hampshire 50.00 50.00 50.00 New Jersey 50.00 50.00 50.00 New
Mexico 73.04 74.56 74.85 New York 50.00 50.00 50.00 North Carolina 61.46
62.56 62.85 North Dakota 69.87 68.36 68.31 Ohio 58.78 58.83 59.23 Oklahoma
70.43 70.56 70.24 Oregon 59.20 60.16 60.81 Pennsylvania 54.65 54.69 54.76
Rhode Island 52.45 55.40 56.03 South Carolina 69.34 69.81 69.86 South
Dakota 65.93 65.29 65.67 Tennessee 63.64 64.59 64.40 Texas 60.17 59.99
60.22 Utah 70.00 71.24 71.72 Vermont 63.06 62.41 61.34 Virginia 51.45
50.53 50.00 Washington 50.37 50.00 50.00 West Virginia 75.27 75.04 75.19
Wisconsin 58.57 58.43 58.41 Wyoming 61.97 61.32 59.77
Source: HHS. Note: GAO compiled data from HHS.
Appendix II: Methodology Page 25 GAO- 03- 620 Medicaid Formula
This appendix describes our methodology for measuring the extent to which
the current Medicaid matching formula reduces differences in states*
funding abilities and the data, and their sources, we used to measure the
elements of states* funding ability. While we considered alternative
indicators of state resources, people in poverty, and the cost of health
care, and we chose those indicators we believed were most appropriate, we
did not perform an exhaustive comparative analysis of other potential
indicators, nor did we attempt to develop new indicators.
We defined a state*s ability to fund Medicaid services as the economic
resources a state is potentially able to tax to fund its Medicaid program
relative to the number of persons with incomes below the federal poverty
level (FPL), adjusted for the cost of providing health care to them.
Specifically, we took into account differences in the utilization of
health care services by children, adults, and the elderly, and we
developed an index for the differences in the cost of health care
personnel and the cost of medical facilities and supplies used to provide
the services. We calculated state funding ability according to the
following formula:
. . . .
. . . .
=
. . . . .
. . . . .
state state state
c P Y
Resources Own From Ability
Funding State
state where Y = State resources potentially subject to state taxation P =
People with incomes below the FPL, adjusted for differences in service
utilization by children, adults, and the elderly
c = Index of the cost of factors in the provision of health care services
(e. g., health care personnel, medical facilities, and supplies). Appendix
II: Methodology
Measuring States* Funding Ability
Funding Ability from State Resources
Appendix II: Methodology Page 26 GAO- 03- 620 Medicaid Formula
We explain later in this appendix how we adjusted the counts of people in
poverty for differences in service utilization and in the cost of
personnel, facilities, and supplies.
Federal matching aid, in effect, adds to a state*s ability to fund program
costs from its own resources. For example, when federal matching aid pays
for half the cost of a state*s program, it effectively doubles that
state*s
ability to fund program services. The higher the federal matching rate,
the more federal matching aid contributes to a state*s ability to fund
Medicaid services. In general, a state*s funding ability after the value
of its federal matching aid is added can be determined using the following
formula:
. . . .
. . . .
. . . .
. . . .
= . . . .
. . . .
state state state
state state c P Y
FMAP 1 1
Aid Matching Federal with Ability Funding Medicaid
where FMAP = State*s federal matching rate Y = State resources potentially
subject to state taxation
P = People with incomes below the FPL, adjusted for differences in service
utilization by children, adults, and the elderly
c = Index of the cost of factors in the provision of health care services
(e. g., health care personnel, medical facilities, and supplies).
The first term after the equals sign represents the multiple by which a
state*s matching rate increases the state*s funding ability. For example,
if a state receives a federal match of 75 percent, its funding ability is
increased by a factor of 4 [( 1/( 1 - 0.75) = 4].
To measure the effect of the current formula in reducing differences in
states* funding ability, we compared differences between each state*s
funding ability before and after the value of federal matching aid is
added and calculated the percentage reduction in these differences. In
performing these calculations, we measured each state*s funding ability
relative to the average funding ability of all states. The resulting
indexes of states* funding abilities provide a means of comparing relative
differences State Funding Ability with
the Value of Federal Matching Aid Added
Calculating the Reduction of Differences in States* Funding Ability
Appendix II: Methodology Page 27 GAO- 03- 620 Medicaid Formula
in states* ability to fund their Medicaid programs. We used the weighted
absolute mean deviation as a quantitative measure of differences in
states* funding ability. This statistic is a measure of average
differences in states* funding ability. It is calculated by taking the
absolute value of each state*s
index of relative funding ability and computing the arithmetic average of
these differences, using the following formula:
. .
= =
= 51
1 s 51
1 s s s
w X X w
Deviation Absolute Mean AVG
s where X s = A state*s funding ability index X AVG = Weighted average of
all states* funding ability indexes w s = A state*s weighting factor
(people in poverty). In calculating the mean absolute deviation, we took
into account differences in the potential size of state programs by using
the number of people living in poverty in each state. We chose the mean
absolute deviation rather than the more commonly
used weighted standard deviation because the latter, by squaring
differences between each state*s funding ability and the national average
funding ability, gives much greater weight to states at the extreme ends
of the distribution of states* funding abilities, resulting in a measure
that is more sensitive to extreme values and thus less likely to reflect
the norm. We calculated the mean absolute deviation in states* funding
ability both
without and with the value of federal matching aid added. Calculating the
percentage change in the two mean absolute deviations measures the extent
to which the current formula reduces differences in states* funding
ability. For example, if the current formula completely eliminated
differences in states* funding ability, total funding ability of all
states would equal the average of all states, and the mean absolute
deviation would be zero, representing a 100 percent reduction in
differences in states* funding ability (the maximum possible).
Alternatively, if the formula had no effect in reducing differences in
states* funding ability, the
Appendix II: Methodology Page 28 GAO- 03- 620 Medicaid Formula
mean absolute deviation in states* funding ability with the value of
federal matching aid taken into account would be the same as the mean
absolute deviation in states* funding ability from their own resources. In
this case, there would be no change in the mean absolute deviation,
meaning that the matching formula had no effect in reducing relative
differences in
states* funding ability. Table 3 shows each state*s index of Medicaid
funding ability without and with the value of its federal matching aid.
Table 3: States* Ability to Fund Program Services without and with the
Value of Fiscal Year 2000 Federal Matching Aid Added State Medicaid
funding ability
(percentage of national average) State
(1) Without federal
matching aid a (2)
With FY 2000 federal matching aid
Alabama 65 89 Alaska 219 279 Arizona 73 98 Arkansas 61 94 California 85 74
Colorado 165 138 Connecticut 176 147 Delaware 162 136 District of Columbia
71 102 Florida 81 78 Georgia 96 101 Hawaii 98 84 Idaho 94 131 Illinois 131
110 Indiana 148 162 Iowa 147 166 Kansas 126 132 Kentucky 79 112 Louisiana
72 101 Maine 95 117 Maryland 143 120 Massachusetts 131 110 Michigan 111
103 Minnesota 143 123 Mississippi 54 97 Missouri 123 130 Montana 73 119
Appendix II: Methodology Page 29 GAO- 03- 620 Medicaid Formula
State Medicaid funding ability (percentage of national average)
State (1)
Without federal matching aid a
(2) With FY 2000 federal
matching aid
Nebraska 122 131 Nevada 126 106 New Hampshire 179 150 New Jersey 160 134
New Mexico 55 88 New York 88 74 North Carolina 94 105 North Dakota 92 132
Ohio 111 112 Oklahoma 76 112 Oregon 111 117 Pennsylvania 108 98 Rhode
Island 101 92 South Carolina 73 102 South Dakota 105 152 Tennessee 80 91
Texas 86 93 Utah 173 255 Vermont 121 134 Virginia 125 108 Washington 141
123 West Virginia 56 92 Wisconsin 150 153 Wyoming 147 174
Sources: HHS and the Departments of Commerce, Labor, and the Treasury.
Note: GAO calculations are based on data from HHS and the Departments of
Commerce, Labor, and the Treasury. a Funding ability without federal
matching aid was calculated using an average of state taxable
resources for 1996 through 1998. The mean absolute deviation of states*
funding ability before taking into account the value of federal matching
aid (column 1 of table 3) yielded an average difference in states*
relative funding ability of 22.7 percent. The mean absolute deviation in
states* funding ability after taking into account the value of federal
matching aid (column 2 of table 3) yielded an average difference of 18.1
percent. This difference represents a 20 percent overall
reduction in differences in states* funding ability as a result of adding
federal matching aid.
Appendix II: Methodology Page 30 GAO- 03- 620 Medicaid Formula
As the indicator of state resources in the formula, PCI includes income
received by state residents (* personal income*), such as wages, rents,
and interest income, but excludes other important taxable income. For
example, PCI excludes corporate income not received as income by state
residents, such as undistributed corporate profits and dividends received
by people who reside out- of- state. An ideal resources measure would
count all income that states are able to tax. Even certain types of income
that states exempt from taxation or tax at preferential rates should be
counted as potentially taxable income because these enhance taxpayers*
ability to pay all taxes levied in the state.
We used Total Taxable Resources (TTR), as reported by the Department of
the Treasury, to measure state resources because it comprises the income
included in PCI as well as income from other sources, such as corporate
income and capital gains, and thus it is a more comprehensive indicator of
income than PCI alone. 1 TTR includes personal income received by state
residents as well as income produced within a state but received by
individuals who reside out- of- state (which is considered a portion of
the Gross State Product (GSP)). As indicated in table 4, nationwide, the
TTR measure of income is 32 percent larger than PCI. Table 4: Comparison
of PCI with TTR, 3- Year Averages, 1996- 98
State PCI TTR per capita Percentage difference
Alabama $21,194 $26,884 27 Alaska 27,001 42,755 58 Arizona 22,842 29,947
31 Arkansas 20,310 26,324 30 California 26,867 35,057 30 Colorado 28,014
36,340 30 Connecticut 35,507 48,047 35 Delaware 27,872 47,020 69 District
of Columbia 36,067 51,503 43 Florida 25,756 32,267 25 Georgia 24,756
33,364 35 Hawaii 26,209 35,220 34 Idaho 21,035 27,399 30
1 Another possible measure of a state*s resources is the Representative
Tax System developed by the Advisory Commission on Intergovernmental
Relations. We did not use this measure in our analysis because data on
this measure are not available on an annual basis. Measuring State
Resources
Appendix II: Methodology Page 31 GAO- 03- 620 Medicaid Formula
State PCI TTR per capita Percentage difference
Illinois 28,442 37,421 32 Indiana 23,902 31,493 32 Iowa 23,785 32,282 36
Kansas 24,388 32,456 33 Kentucky 21,241 28,774 35 Louisiana 21,272 31,520
48 Maine 22,376 28,205 26 Maryland 29,305 38,019 30 Massachusetts 31,448
41,141 31 Michigan 25,608 31,558 23 Minnesota 27,773 35,996 30 Mississippi
18,981 24,480 29 Missouri 24,251 32,314 33 Montana 20,291 25,436 25
Nebraska 24,832 33,481 35 Nevada 28,383 38,887 37 New Hampshire 27,776
39,760 43 New Jersey 32,492 44,438 37 New Mexico 20,296 29,533 46 New York
30,661 41,470 35 North Carolina 24,194 32,076 33 North Dakota 21,577
29,298 36 Ohio 24,897 32,450 30 Oklahoma 21,152 26,412 25 Oregon 24,817
34,477 39 Pennsylvania 26,096 33,239 27 Rhode Island 26,589 35,002 32
South Carolina 21,444 27,809 30 South Dakota 22,603 31,700 40 Tennessee
23,450 30,323 29 Texas 24,201 32,931 36 Utah 21,135 29,010 37 Vermont
23,487 30,344 29 Virginia 26,869 36,788 37 Washington 26,912 35,271 31
West Virginia 19,400 25,379 31 Wisconsin 24,863 32,456 31 Wyoming 23,615
41,920 78 United States $25,949 $34,299 32
Source: Departments of Commerce and the Treasury. Notes: Data reflect 3-
year averages of TTR and PCI. GAO analysis of data from the Departments of
Commerce and the Treasury.
Appendix II: Methodology Page 32 GAO- 03- 620 Medicaid Formula
While TTR is a more comprehensive measure of state resources than PCI,
recent definitional changes to GSP and state personal income (SPI) data
made by the Bureau of Economic Analysis (BEA) may have implications for
the methodology used by the Department of the Treasury to calculate TTR.
For example, BEA has changed its treatment of the value of services
provided by government- owned fixed assets that are now included in GSP
and benefit payments of government employee pension plans, which are
now excluded from SPI. Since the Treasury initially developed the TTR
methodology, it has not reported why definitional changes made by BEA
should or should not be reflected in TTR. In the case of the changes to
government pension plans, the Treasury has reported it is currently
studying whether they necessitate any modifications to the TTR
methodology.
To measure people in poverty, we adjusted the Bureau of the Census*s
estimates of people in households with incomes at or below the FPL for (1)
differences in the cost of providing health care services to children,
adults, and the elderly (to account for the higher health care costs for
the elderly) and (2) geographic differences in the cost of providing
health care services (such as wages and salaries of health care
professionals and the rental cost of medical facilities). 2 We obtained
estimated counts of people living in poverty from the Bureau
of the Census*s Current Population Survey (CPS). Because the CPS sample
sizes for individual states are especially small when disaggregated by age
cohorts, they are subject to greater statistical error than a sample
representing all age groups. To improve the accuracy of these estimates,
we averaged poverty counts over the 5- year period 1995 through 1999. We
used the FPL as a basis for making cross- state comparisons of the number
of people in poverty. (See table 5.) 2 We have excluded disproportionate
share hospital (DSH) payments from this analysis. These hospitals receive
additional Medicaid reimbursement because they serve a disproportionate
number of Medicaid and other low- income patients. We have excluded these
payments from our analysis because the federal government uses a different
distribution formula from the regular Medicaid program. Measuring People
in Poverty and the Costs
to Provide Them Program Services
Measuring the Number of People in Poverty
Appendix II: Methodology Page 33 GAO- 03- 620 Medicaid Formula
Table 5: Distribution of Population in Poverty, by Age Group, 5- Year
Averages, 1995- 99
Percentage who are State
Official poverty
count Children a Adults b Elderly c
Alabama 684,401 44 44 11 Alaska 52,434 47 50 3 Arizona 773,651 49 44 7
Arkansas 418,593 43 44 14 California 5,213,675 48 46 6 Colorado 356,379 42
52 6 Connecticut 307,435 46 44 10 Delaware 73,643 47 43 11 District of
Columbia 111,071 43 46 12 Florida 2,040,854 41 47 12 Georgia 1,024,452 47
44 9 Hawaii 138,433 42 49 9 Idaho 166,135 49 44 7 Illinois 1,335,576 49 42
9 Indiana 485,926 39 50 10 Iowa 273,851 44 47 9 Kansas 275,646 45 44 12
Kentucky 568,739 41 48 10 Louisiana 811,417 47 44 10 Maine 132,323 39 47
14 Maryland 437,917 42 44 14 Massachusetts 653,754 43 46 11 Michigan
1,064,367 47 43 10 Minnesota 437,201 46 43 11 Mississippi 518,149 45 44 11
Missouri 554,936 42 46 11 Montana 143,838 46 47 7 Nebraska 176,270 42 44
13 Nevada 181,524 46 45 9 New Hampshire 91,519 42 45 12 New Jersey 680,727
39 47 13 New Mexico 411,507 51 42 8 New York 2,945,784 45 45 10 North
Carolina 931,440 42 46 12 North Dakota 81,831 44 44 12 Ohio 1,308,010 46
45 9 Oklahoma 486,474 42 47 11 Oregon 410,697 45 49 7
Appendix II: Methodology Page 34 GAO- 03- 620 Medicaid Formula
Percentage who are State
Official poverty
count Children a Adults b Elderly c
Pennsylvania 1,322,801 42 47 12 Rhode Island 107,019 40 43 17 South
Carolina 539,744 46 42 12 South Dakota 86,713 45 42 13 Tennessee 784,910
43 47 10 Texas 3,149,475 48 44 9 Utah 163,467 51 44 5 Vermont 61,026 42 49
9 Virginia 686,279 39 48 13 Washington 584,612 43 50 7 West Virginia
299,257 36 50 14 Wisconsin 448,444 46 45 10 Wyoming 57,957 45 45 9 United
States 35,052,282 45 45 10
Source: Department of Commerce. Note: Percentages may not add to 100
across age groups because of rounding. a Population under age 21 with
income at or below the FPL.
b Population aged 21 to 64 with income at or below the FPL. c Population
aged 65 and over with income at or below the FPL.
Official poverty counts are not a good proxy for the low- income
population because they do not take into account the higher cost of
serving elderly individuals. For example, elderly individuals represented
27 percent of Medicaid beneficiaries in fiscal year 2000, the latest year
for which data are available. However, because they are more intensive
users of the health care system and utilize more expensive long- term care
services, elderly persons accounted for 66 percent of all Medicaid
spending that year.
To account for differences in costs to serve each group, we weighted the
numbers of children, adults, and the elderly. We calculated Medicaid
spending per beneficiary for each age group nationwide, then compared
spending per beneficiary for each age group with average spending per
beneficiary for all age groups. We used a 5- year average of Medicaid
spending per beneficiary derived from data reported by the Centers for
Medicare & Medicaid Services (CMS) for fiscal years 1995 through 1999. The
results suggest that, nationwide, elderly beneficiaries utilize health
Adjusting Poverty Counts
for Differences in Costs to Serve Children, Adults, and the Elderly
Appendix II: Methodology Page 35 GAO- 03- 620 Medicaid Formula
care services at about two- and- one- half times the rate of the average
Medicaid beneficiary, and children utilize services at less than half the
rate of the average beneficiary. (See the cost weight index column in
table 6.) Table 6: Weights for Age Groups to Reflect Cost Differences and
Medicaid Program
Participation Age group
Average annual spending per
beneficiary Cost weight (index) a
Average participation
rate (index) b Adjusted
cost weight c
Elderly (aged 65 or older) $9,005 2. 5 1.4 3. 5 Adults (aged 21- 64)
$4,729 1. 3 0.7 1. 0 Children (under age 21) $1,483 0. 4 1.2 0. 5 All
groups $3,532 1. 0 1.0 1. 0
Sources: Department of Commerce and HHS. Note: GAO analysis of data from
the Department of Commerce for 1995 through 1999 and data from HHS for
1994 through 1998. a Index is spending per recipient for each age group
divided by average spending per recipient for all age groups. b Index is
the percentage of people in each age group receiving Medicaid benefits,
expressed as a
ratio to the average of all groups. c Calculated by multiplying the cost
weight index by the participation rate index.
To adjust for differences in program participation across age groups, we
compared the number of Medicaid beneficiaries by age group with the number
of people in poverty. We compared these counts with the national average
participation rates for all Medicaid beneficiaries. We calculated the
adjusted cost weight by multiplying the cost weight index by the average
participation rate index. We calculated a weighted count of people in
poverty for each state by applying the adjusted cost weights in the last
column of table 6 to poverty counts by age group, according to the
following formula:
. . . . .
. . . . .
+
. . . . .
. . . . .
+
. . . . . . .
. . . . . . .
=
. . . . .
. . . . .
21 Age Under Poverty
in Number 0.5 64 to 21 Aged Poverty
in Number 1.0
65 Age Over
Poverty in Number
3.5 Count Poverty
Weighted
In table 7, the columns representing official poverty rates report the
percentage of people in poverty based on the official government poverty
Appendix II: Methodology Page 36 GAO- 03- 620 Medicaid Formula
statistics reported by the Bureau of the Census. The age- weighted columns
are the percentages of people in poverty after weighting children, adults,
and the elderly. Comparing the percentages in the official poverty rate
columns with the percentages after age- weighting illustrates the effect
of differences in utilization rates by age cohort. For example, Florida*s
official poverty rate is revised upward from 14.0 percent to 15.3 percent
when weighted for age differences. Similarly, the District of Columbia*s
poverty rate increases from about 21.1 percent to about 22.7 percent after
weighting. 3 3 The age and health care use cost- adjusted poverty rates in
table 7 will be discussed in the next section, in which we describe the
cost adjustments made for differences in medical
care costs.
Appendix II: Methodology Page 37 GAO- 03- 620 Medicaid Formula
Table 7: Comparison of Official and Cost- Adjusted Poverty Rates, 5- Year
Averages, 1995- 99 Official poverty rate Age- weighted poverty rate Age
and health care use
cost- adjusted poverty rate State Percentage of people in poverty
Percentage of U. S. poverty rate Percentage in
poverty Percentage
of U. S. poverty rate Percentage
in poverty Percentage
of U. S. poverty rate
Alabama 15.9 122 16.9 128 16.0 121 Alaska 8.2 63 6.9 52 7.2 54 Arizona
16.5 126 15.2 115 15.7 119 Arkansas 16.3 125 18.3 138 16.4 124 California
15.9 122 14.2 108 15.7 118 Colorado 9.0 69 8.4 63 8.5 64 Connecticut 9.3
71 9.4 71 10.4 78 Delaware 9.9 75 10.2 77 11.1 84 District of Columbia
21.1 162 22.7 172 27.7 209 Florida 14.0 108 15.3 116 15.6 118 Georgia 13.6
104 13.6 103 13.4 102 Hawaii 11.6 89 11.9 90 13.7 104 Idaho 13.6 104 12.6
95 11.3 85 Illinois 11.1 85 11.0 83 11.0 83 Indiana 8.4 64 8.9 68 8.3 63
Iowa 9.6 74 9.7 73 8.5 64 Kansas 10.7 82 11.4 86 10.1 76 Kentucky 14.7 112
15.4 117 14.2 107 Louisiana 19.0 145 19.2 145 17.1 130 Maine 10.7 82 12.5
94 11.6 87 Maryland 8.6 66 9.9 75 10.3 78 Massachusetts 10.7 82 11.3 86
12.1 92 Michigan 10.8 83 10.9 83 10.9 82 Minnesota 9.2 71 9.8 74 9.7 73
Mississippi 18.9 145 19.6 149 17.5 132 Missouri 10.4 80 11.2 85 10.3 78
Montana 16.0 123 15.0 114 13.1 99 Nebraska 10.6 81 11.8 90 10.4 79 Nevada
10.5 80 10.4 79 11.9 90 New Hampshire 7.7 59 8.5 64 8.5 64 New Jersey 8.5
65 9.6 73 10.8 82 New Mexico 22.6 173 21.2 161 19.8 150 New York 16.1 123
16.5 125 17.9 136 North Carolina 12.8 98 13.9 105 13.6 103 North Dakota
13.0 99 14.1 106 12.4 94 Ohio 11.6 89 11.7 88 11.2 85 Oklahoma 14.8 114
15.7 119 13.5 102 Oregon 12.5 95 11.8 89 11.9 90 Pennsylvania 11.1 85 12.0
91 11.9 90
Appendix II: Methodology Page 38 GAO- 03- 620 Medicaid Formula
Official poverty rate Age- weighted poverty rate Age and health care use
cost- adjusted poverty rate State Percentage of
people in poverty Percentage
of U. S. poverty rate Percentage in
poverty Percentage
of U. S. poverty rate Percentage
in poverty Percentage
of U. S. poverty rate
Rhode Island 11.2 86 13.6 103 13.6 103 South Carolina 14.3 109 15.1 114
14.9 113 South Dakota 12.3 94 13.5 102 12.0 90 Tennessee 14.2 109 14.5 110
14.2 107 Texas 16.1 124 15.8 119 14.8 112 Utah 7.9 61 7.0 53 6.5 49
Vermont 10.3 79 10.6 80 9.6 73 Virginia 10.4 79 11.8 89 11.6 88 Washington
10.4 79 10.0 75 9.7 73 West Virginia 17.0 131 20.1 152 18.0 136 Wisconsin
8.6 66 8.7 66 8.3 62 Wyoming 12.0 92 12.1 91 10.8 82 United States 13.1
100 13.2 100 13.2 100
Sources: HHS, and the Departments of Commerce, Housing and Urban
Development (HUD), and Labor. Note: GAO analysis of data from HHS, HUD,
and the Departments of Commerce and Labor.
The cost of providing health care services is affected by three factors:
(1) the cost of the personnel who provide the services (wages, for
example), (2) the rental cost of facilities in which the services are
provided, and (3) the cost of medical equipment and supplies.
We used the average wage per worker in the health industry (Standard
Industrial Classification (SIC) code 8000), produced by the Bureau of
Labor Statistics (BLS), to measure the cost of personnel for 1996 through
1998. The BLS cost data cover personnel in a wide variety of settings,
including offices, clinics, hospitals, and medical and dental
laboratories, as well as health care providers who work for home health
agencies.
To measure the cost of facilities through which services are delivered, we
used apartment rents as reported by the Department of Housing and Urban
Development (HUD) because data on commercial office space rental rates in
the health sector of the economy were not available. Apartment rental
rates were an appropriate alternative because the same factors that affect
the cost of office space (for example, population density
and income) affect housing rental rates, and apartment rental rates are
likely to more closely mimic office space costs than would owneroccupied
housing units. In addition, data are available for apartment Adjusting
Poverty Counts
for Differences in the Cost of Providing Health Care Services
Appendix II: Methodology Page 39 GAO- 03- 620 Medicaid Formula
rentals by the size of the unit, which allowed us to take size differences
into account.
Data on the geographic differences in the cost of medical equipment and
supplies were not readily available. Because medical equipment and
supplies generally are purchased in national markets, we assumed that the
costs of these items do not vary across states.
We calculated an index of health industry wage rates and apartment rents
(our proxy for the rental cost of medical facilities). For medical
supplies, we used a cost index of 1.0 for all states to reflect the
assumption that these costs do not vary across states. We then combined
the three factors into an overall index of the cost of health care
services by state, weighting each factor on the basis of its respective
proportion of the total cost of health care services. Personnel costs
represent the greatest share of health care costs, as much as 75 percent
of total costs, according to one study. 4 We constructed our cost index
conservatively by reducing the personnel
cost weight to 60 percent. We applied a cost weight of 30 percent for
medical equipment and supplies and other miscellaneous costs that are
assumed to be the same across states. The remaining 10 percent is the cost
weight for rent. Using these cost weights is likely to understate cross-
state cost differences.
Nineteen states had health care costs estimated to be at least 10 percent
above or below the national average. The states with costs 10 percent or
more above the national average were California, Connecticut, the District
of Columbia, Hawaii, Nevada, and New Jersey. States with lower costs
tended to be southern or midwestern states. (See table 8.)
4 Gregory Pope, Adjusting the Alcohol, Drug Abuse, and Mental Health
Services Block Grant for Allocations for Poverty Population and Cost of
Service (Needham, Mass.: Health Economics Research, Inc., Mar. 30, 1990).
Appendix II: Methodology Page 40 GAO- 03- 620 Medicaid Formula
Table 8: Wage, Rent, and Health Care Cost Indexes, by State Percentage of
national average
State Wage index
(3- year averages, 1996- 98) Rent index
(FY 2000) Health care cost index
Alabama 96 70 95 Alaska 104 124 105 Arizona 106 98 103
Arkansas 88 67 89 California 112 127 110
Colorado 101 107 101
Connecticut 113 125 110
Delaware 114 104 109
District of Columbia 131 133 122
Florida 103 100 102 Georgia 100 91 99
Hawaii 119 139 115 Idaho 87 75 90
Illinois 100 104 100 Indiana 92 82 93
Iowa 83 74 87 Kansas 85 77 89
Kentucky 92 69 92
Louisiana 87 72 89
Maine 90 88 93 Maryland 105 113 104 Massachusetts 106 131 107 Michigan 101
93 100 Minnesota 99 93 99
Mississippi 87 66 89
Missouri 91 74 92
Montana 82 77 87 Nebraska 84 77 88 Nevada 122 110 114
New Hampshire 99 112 100
New Jersey 114 134 112
New Mexico 92 81 93 New York 109 132 109 North Carolina 99 84 98
North Dakota 85 71 88
Ohio 96 85 96
Oklahoma 83 69 86
Oregon 101 99 101 Pennsylvania 99 94 99
Appendix II: Methodology Page 41 GAO- 03- 620 Medicaid Formula
Percentage of national average State
Wage index (3- year averages,
1996- 98) Rent index (FY 2000) Health care cost
index
Rhode Island 99 108 100 South Carolina 101 79 99
South Dakota 85 77 89
Tennessee 100 76 98 Texas 92 90 94 Utah 90 95 93 Vermont 85 97 91 Virginia
98 98 99 Washington 94 106 97
West Virginia 88 66 90
Wisconsin 95 85 95 Wyoming 87 76 90 United States 100 100 100
Sources: HHS, HUD, and the Department of Labor. Notes: States in bold have
health care costs estimated to be 10 percent or more above or below the
national average. GAO analysis of data from HHS, HUD, and the Department
of Labor.
We compared states* ability to fund Medicaid services without and with the
value of federal matching aid added. Column 1 of table 9 shows states*
funding ability: states* TTR per person in poverty adjusted for
differences
in the cost of providing them health care services. Column 2 shows states*
effective fiscal year 2000 federal matching rates used in the analysis 5
and column 3 shows the resulting *multipliers* (i. e., 1/( 1 - FMAP)) that
reflect the effect of federal matching on states* funding ability. Funding
ability with federal aid is shown in column 4.
5 To calculate effective matching rates we divided each state*s federal
matching aid by its total Medicaid spending, net of DSH and certain other
costs. Calculating States* Ability to Fund
Medicaid Services without and with Value of Federal Matching Aid Added
Appendix II: Methodology Page 42 GAO- 03- 620 Medicaid Formula
Table 9: States* Funding Ability without and with the Value of Fiscal Year
2000 Federal Matching Aid Added State
(1) Funding ability from
state resources (dollars per person in
poverty) a (2)
Effective FY 2000 FMAP (percentage)
(3) FMAP multiplier
(4) Funding ability with federal matching aid
(col. 1 x col. 3)
Alabama $169,683 69.64 3.29 $558,840 Alaska 570,409 67.26 3.05 1,742,447
Arizona 189,505 69.19 3.25 615,081 Arkansas 158,718 73.11 3.72 590,165
California 222,437 52.06 2.09 463,963 Colorado 429,969 50.08 2.00 861,380
Connecticut 459,835 50.02 2.00 920,046 Delaware 422,823 50.20 2.01 848,991
District of Columbia 184,951 70.93 3.44 636,309 Florida 211,705 56.60 2.30
487,803 Georgia 251,548 60.01 2.50 628,961 Hawaii 256,566 51.03 2.04
523,891 Idaho 244,092 70.29 3.37 821,587 Illinois 341,369 50.15 2.01
684,770 Indiana 386,661 61.84 2.62 1,013,136 Iowa 382,676 63.14 2.71
1,038,320 Kansas 328,243 60.09 2.51 822,538 Kentucky 205,683 70.62 3.40
700,085 Louisiana 187,290 70.37 3.38 632,139 Maine 246,614 66.31 2.97
732,052 Maryland 374,141 50.18 2.01 750,931 Massachusetts 342,550 50.13
2.01 686,922 Michigan 289,686 55.17 2.23 646,136 Minnesota 372,580 51.69
2.07 771,185 Mississippi 140,227 76.89 4.33 606,653 Missouri 320,009 60.58
2.54 811,740 Montana 190,431 74.49 3.92 746,413 Nebraska 319,214 61.00
2.56 818,427 Nevada 327,582 50.45 2.02 661,158 New Hampshire 467,893 50.08
2.00 937,274 New Jersey 417,976 50.07 2.00 837,128 New Mexico 142,227
74.19 3.87 551,081 New York 229,337 50.11 2.00 459,721 North Carolina
244,355 62.61 2.67 653,542 North Dakota 238,866 70.97 3.45 822,897 Ohio
289,509 58.72 2.42 701,375 Oklahoma 198,643 71.63 3.53 700,263 Oregon
288,765 60.42 2.53 729,556 Pennsylvania 281,796 53.84 2.17 610,540
Appendix II: Methodology Page 43 GAO- 03- 620 Medicaid Formula
State (1)
Funding ability from state resources (dollars per person in
poverty) a (2)
Effective FY 2000 FMAP (percentage)
(3) FMAP multiplier
(4) Funding ability with federal matching aid
(col. 1 x col. 3)
Rhode Island 264,602 53.77 2.16 572,326 South Carolina 189,300 70.18 3.35
634,851 South Dakota 274,528 71.07 3.46 948,856 Tennessee 209,859 63.19
2.72 570,142 Texas 224,158 61.54 2.60 582,883 Utah 452,178 71.65 3.53
1,595,085 Vermont 315,610 62.39 2.66 839,259 Virginia 325,551 51.90 2.08
676,811 Washington 367,374 52.08 2.09 766,584 West Virginia 145,611 74.80
3.97 577,734 Wisconsin 392,390 58.88 2.43 954,178 Wyoming 383,724 64.63
2.83 1,084,827 United States $260,851 56.83 2.32 $624,935
Sources: HHS and the Department of the Treasury. Notes: Calculations were
done with unrounded numbers, not the rounded numbers shown in the table.
GAO analysis of data from HHS and the Department of the Treasury. a
Funding ability without federal matching aid was calculated using an
average of TTR for 1996 through 1998.
The data used to show the relationship between a state*s effort to fund
Medicaid benefits from its own financial resources and its total Medicaid
spending per person in poverty, shown in figure 2, are displayed in table
10. Comparing
Proportion of States* Resources Devoted to Medicaid with Their Total
Spending per Person in Poverty
Appendix II: Methodology Page 44 GAO- 03- 620 Medicaid Formula
Table 10: Proportion of State Resources Devoted to Medicaid per $1,000 of
TTR Compared with Total Medicaid Spending per Person in Poverty, Cost
Adjusted, Fiscal Year 2000
State State financial resources per $1,000 of TTR Total Medicaid spending
per person in poverty
Alabama $6.08 $3,397 Alaska 5.84 10,178 Arizona 4.64 2,851 Arkansas 6.35
3,747 California 8.04 3,731 Colorado 6.26 5,391 Connecticut 8.99 8,274
Delaware 7.35 6,242 District of Columbia 8.51 5,417 Florida 6.48 3,160
Georgia 6.15 3,869 Hawaii 7.51 3,935 Idaho 5.07 4,166 Illinois 7.79 5,332
Indiana 6.07 6,153 Iowa 6.48 6,729 Kansas 6.23 5,127 Kentucky 7.40 5,179
Louisiana 5.59 3,533 Maine 10.93 7,999 Maryland 7.38 5,544 Massachusetts
11.43 7,849 Michigan 9.12 5,895 Minnesota 9.20 7,094 Mississippi 6.19
3,757 Missouri 7.82 6,345 Montana 5.13 3,826 Nebraska 7.26 5,941 Nevada
3.83 2,533 New Hampshire 7.32 6,864 New Jersey 7.00 5,857 New Mexico 6.12
3,370 New York 18.16 8,347 North Carolina 7.77 5,075 North Dakota 6.64
5,467 Ohio 7.77 5,449 Oklahoma 5.12 3,586 Oregon 7.26 5,299 Pennsylvania
11.29 6,891
Appendix II: Methodology Page 45 GAO- 03- 620 Medicaid Formula
State State financial resources per $1,000 of TTR Total Medicaid spending
per person in poverty
Rhode Island 14.27 8,170 South Carolina 6.40 4,061 South Dakota 4.92 4,671
Tennessee 11.04 6,296 Texas 5.58 3,252 Utah 3.74 5,964 Vermont 10.32 8,661
Virginia 5.10 3,455 Washington 8.71 6,679 West Virginia 7.22 4,170
Wisconsin 7.89 7,532 Wyoming 3.85 4,171 United States $8.37 $5,056
Sources: HHS and the Departments of Commerce, Housing and Urban
Development, and the Treasury. Note: GAO analysis of data from HHS and the
Departments of Commerce, Housing and Urban Development, and the Treasury.
(290010)
The General Accounting Office, the audit, evaluation and investigative arm
of Congress, exists to support Congress in meeting its constitutional
responsibilities and to help improve the performance and accountability of
the federal government for the American people. GAO examines the use of
public funds; evaluates federal programs and policies; and provides
analyses, recommendations, and other assistance to help Congress make
informed oversight, policy, and funding decisions. GAO*s commitment to
good government is reflected in its core values of accountability,
integrity, and reliability.
The fastest and easiest way to obtain copies of GAO documents at no cost
is through the Internet. GAO*s Web site (www. gao. gov) contains abstracts
and fulltext files of current reports and testimony and an expanding
archive of older products. The Web site features a search engine to help
you locate documents using key words and phrases. You can print these
documents in their entirety, including charts and other graphics.
Each day, GAO issues a list of newly released reports, testimony, and
correspondence. GAO posts this list, known as *Today*s Reports,* on its
Web site daily. The list contains links to the full- text document files.
To have GAO e- mail
this list to you every afternoon, go to www. gao. gov and select
*Subscribe to daily E- mail alert for newly released products* under the
GAO Reports heading.
The first copy of each printed report is free. Additional copies are $2
each. A check or money order should be made out to the Superintendent of
Documents. GAO also accepts VISA and Mastercard. Orders for 100 or more
copies mailed to a single address are discounted 25 percent. Orders should
be sent to: U. S. General Accounting Office 441 G Street NW, Room LM
Washington, D. C. 20548 To order by Phone: Voice: (202) 512- 6000
TDD: (202) 512- 2537 Fax: (202) 512- 6061
Contact: Web site: www. gao. gov/ fraudnet/ fraudnet. htm E- mail:
fraudnet@ gao. gov Automated answering system: (800) 424- 5454 or (202)
512- 7470 Jeff Nelligan, Managing Director, NelliganJ@ gao. gov (202) 512-
4800
U. S. General Accounting Office, 441 G Street NW, Room 7149 Washington, D.
C. 20548 GAO*s Mission Obtaining Copies of
GAO Reports and Testimony
Order by Mail or Phone To Report Fraud, Waste, and Abuse in Federal
Programs Public Affairs
*** End of document. ***