The Health Care Industry and La Crosse County

The Health Care Industry and La Crosse County
THE HEALTH CARE INDUSTRY AND LA CROSSE COUNTY:
    The Health Care Industry and La Crosse County:
  Will Medicaid and BadgerCare Budget Reduction Impact the Local Economy?




                                                    Mary Meehan‐Strub
                                       Professor, Department of Family Development
                                                    Family Living Agent
                                              La Crosse County UW‐Extension
                                            mary.meehan‐strub@ces.uwex.edu


                                                     Steven Deller
                             Professor, Department of Agricultural and Applied Economics
                                    Community Economic Development Specialist
                                      University of Wisconsin‐Madison/Extension
                                                   scdeller@wisc.edu


                                                    Karl Green
                      Associate Professor, Department of Community Resource Development
                                   Community Resource Development Educator
                                         La Crosse County UW‐Extension
                                            karl.green@ces.uwex.edu


                                                              January 2012


 Issued in furtherance of Cooperative Extension work, Acts of May 8, and June 30, 1914, in cooperation with the U.S. Department of Agriculture.
 Rick Klemme, Cooperative Extension, University of Wisconsin‐Extension. University of Wisconsin‐Extension, U.S. Department of Agriculture and
 Wisconsin counties cooperating. UW‐Extension provides equal opportunities in employment and programming, including Title IX and ADA.
The Health Care Industry and La Crosse County
The Health Care Industry and La Crosse County:
         Will Medicaid and BadgerCare Budget Reductions Impact the Local Economy?1

                              Mary Meehan‐Strub, Steven Deller and Karl Green

Executive Summary

With rising health care costs and rapidly expanding Medicaid and BadgerCare enrollment the State of Wisconsin is
facing significant budget deficits in these programs. The Walker Administration has proposed a total of about $554
million in Medicaid cuts to address these significant budget shortfalls. The changes sought may result in 65,000
poor adults and children leaving state health insurance programs because they would no longer be eligible or able
to afford coverage. While it is unclear how the federal government will respond to the Wisconsin proposals, it is
clear that the flow of Medicaid and BadgerCare funds into La Crosse County will be reduced.

To help local officials and concerned citizens of La Crosse County think through the potential impacts of these
program cuts we explore the importance of the health care sector to the County economy. This report has three
main parts: (1) a broad discussion of the County economy over time with a focus on the health care industry,
(2) the contribution of the health industry to the County economy, and (3) the potential economic impacts of
reductions in Medicaid and BadgerCare reimbursements. The latter part of the analysis provided in this report is
the most difficult to undertake because it is not clear what those reductions might be or how hospitals, medical
clinics and other health care providers will respond to these proposed cuts. Because Medicaid reimbursement
rates are significantly below cost of services, health care providers lose money by accepting Medicaid patients.
In addition to the ripple effect cuts to Medicaid & BadgerCare will create, these cuts do not necessarily eliminate
the expenditures or the need for expenditures. The cost of these expenditures shifts from the federal and state
government to local (La Crosse County) health care providers and health care clients.

The extent to how much cost‐shifting occurs, whether hospitals pick up 100% of the cost shifting, hold their
business entity harmless and pass the cost on to patients, or a combination of these, is unknown. Hospital
administrators may have concern with this type of analysis, as hospitals must maintain a base or minimum
number of staff regardless of their patient bed census. This dynamic makes an assessment of the economic
impact of a reduction in Medicaid payments difficult.

As a result of this dynamic, the third part of the analysis presented in this report should be viewed as a starting
point for further community discussions about the economic impacts of reduced Medicaid and BadgerCare funding
on the business community as well as the health care industry‐‐a dominant economic force within La Crosse
County, the impact on health care needs for individuals and families affected by the reduction, to ultimately come
up with better solutions.




     1
      The report has benefited from the helpful comments of Lorie Graff‐ Economic Support Manager, Jason Witt‐
     La Crosse County Human Services Director, Dean Ruppert‐ Operations Administrator, with La Crosse County
     Human Services.
     January 2012


                                                                                                                      1
Introduction

With rising health care costs and rapidly expanding Medicaid and BadgerCare enrollment the State of Wisconsin is
facing significant budget deficits in these programs. The Walker Administration has proposed a total of about $554
million in Medicaid cuts to address these significant budget shortfalls. The changes sought may result in 65,000
poor adults and children leaving state health insurance programs because they would no longer be eligible or able
to afford coverage. While it is unclear how the federal government will respond to the Wisconsin proposals, it is
clear that the flow of Medicaid and BadgerCare funds into La Crosse County will be reduced.

To help local officials and concerned citizens
of La Crosse County think through the
potential impacts of these program cuts we
explore the importance of the health care
sector to the County economy. This report
has three main parts: (1) a broad discussion
of the County economy over time with a
focus on the health care industry, (2) the
contribution of the health industry to the
County economy, and (3) the potential
economic impacts of reductions in Medicaid
and BadgerCare reimbursements. The latter
part of the analysis provided in this report is
the most difficult to undertake because it is
not clear what those reductions might be or
how hospitals, medical clinics and other
health care providers will respond to these
proposed cuts.            Because Medicaid                             *See Resources (Page 10)
reimbursement rates are significantly below cost of services, health care providers lose money by accepting
Medicaid patients. This dynamic makes an assessment of the economic impact of a reduction in Medicaid
payments difficult. As a result of this dynamic the third part of the analysis presented in this report should be
viewed as a starting point for further discussion.

General County Economic Trends

There are several ways to measure the
growth of the local economy ranging from
population and employment to income
levels, among others. La Crosse County has
experienced stable population growth and
for the past 30 years has largely paralleled
the population growth of Wisconsin
(Figure 1). For the most recent few years,
however, the population growth of La
Crosse County has accelerated slightly.
Upon closer examination it appears that
from 2003 to 2006 there was a slow‐down
in the growth rate and the most recent time
period has returned to the longer‐term
growth trends. Note that for the past 20
years the growth for La Crosse County has
lagged behind the growth rate for the U.S.
Not surprising, much of the U.S. population
                                                                        *See Resources (Page 10)



                                                                                                                     2
growth has occurred in warmer climate southern states such as Florida and Texas. Naturally, as the population of
La Crosse County and the surrounding area grows the demand for health care services will also grow.
Over the whole of the time period examined (1969‐2009) employment has grown strongly in La Crosse County
outpacing not only the employment growth rate of Wisconsin but also the growth rate of the U.S. (Figure 2). The
downturn in employment during the recent “Great Recession” is clearly evident at the end of the time period
examined. When growth in population, which was a little over 40 percent from 1969 to 2009, is compared to
growth in employment, which is about 130
percent over the same time period, it is
clear that job growth far outpaces
population growth.

This difference in population and
employment growth can be readily seen by
examining the population: employment
ratio which is simply the number of people
in the community for each job (Figure 3).
In 1969 there were about 2.2 people for
every job, but over time that ratio has
declined significantly. In 2009, the ratio is
about 1.4 people for every job in La Crosse
County. This represents a 34.4 percent
decline in the ratio. Also note how the
population: employment ratio for the
County is consistently below either the
national or state average. This can easily be                            *See Resources (Page 10)
explained by the fact that La Crosse County, and in particular, the City of La Crosse and the immediately surround
communities such as Onalaska, serves as a regional hub for retail and services (e.g., health care, financial,
education, transportation).

The large differences in population and
employment growth, best reflected in the
population: employment ratio can be
explained by two concurrent trends. First,
much of the job growth has been in the
form       of     part‐time      employment
opportunities. This is reflected in the
strong job growth in retail and personal
services. It also is reflected in the growing
size of the “working class” which speaks to
the growing number of persons who are
working multiple part‐time jobs. The larger
question this raises is if these jobs can
provide sustainable growth. The second
concurrent trend helping understand the
patterns in Figure 3 is the significant
increase in the labor force participation rate
for women. In 1969 the women labor force
participation rate was about 42.7 and in
                                                                             *See Resources (Page 10)
2009 the rate increased to 59.2 percent. This
significant increase in women in the labor force provided the pool of labor to fill many of those increasing jobs.
This growth peaked, however, in 1999 at 60.0 percent. This peaking of the growth in the women labor force
participation rate raises the question of who will fill the jobs as the economy grows.




                                                                                                                     3
More important to this study is the job growth in the health care sector. Unfortunately, the annual data at our
disposal for these long‐term analyses aggregates health care and social services (NAICS Code 62). In addition to
including traditional health care industries such as hospitals, medical clinics, dentist offices and resident care
facilities it also includes individual and family services, community relief services (e.g., food banks, emergency
housing, etc.) and day care centers. It is clear, that for La Crosse County this category is dominated by traditional
health care services.

Total employment growth over 1969 to
2009 for La Crosse County was about 130
percent (Figure 3) but for the health care     Total employment growth over 1969 to 2009
sector employment growth for the County         for La Crosse County was about 130 percent
was just over 390 percent (Figure 4) . This      but for the health care sector employment
growth in La Crosse County health care             growth for the County was just over 390
employment outpaces both Wisconsin                                     percent.
(about 280 percent) and the U.S. (also
about 280 percent). More remarkable the rate of growth in health care employment in La Crosse County appears
to be accelerating in the growth rate.

This increase is a reflection of the overall growth in the health care sector for both the U.S. and Wisconsin. As we
age as a society and income grows the demand for health care services will continue to grow and this is reflected
in the very strong employment growth.
Second, as identified in a recent
Wisconsin Hospitals Association (WHA)
study by Deller (2011) La Crosse County
has the highest level of dependency on
hospitals     for    economic      activity
compared to all other Wisconsin
counties.2 The strong growth in health
care employment coupled with the
results of the WHA study one could
reasonably conclude that the health
care sector is a “cluster” industry for the
County.        Here       clusters      are
concentrations       of    interconnected
industries that create what economists
call “agglomeration economies” or
“external economies of scale.” The
strength of the industry cluster creates
an environment where the industry
feeds off itself and grows more rapidly.                                 *See Resources (Page 10)
(See Appendix A for a more detailed discussion of La Crosse County Clusters.)

The current unemployment situation and the slow recovery from the “Great Recession” has made job growth the
focal point of nearly all economic growth and development policy discussions. But increasingly the quality of the
jobs including wage and salary pay levels has become an equally important element. If we examine the inflation
adjusted (i.e., real) average earnings per job for the health care and social services industry along with the average
earnings per job for the County we see that since the late 1970s jobs in the health care sector have provided


    2
     Deller, Steven C. 2011. “The Economic Contribution of Hospitals to Wisconsin.” Department of Agricultural
    and Applied Economics Miscellaneous Publications (November).
    http://www.aae.wisc.edu/pubs/misc/docs/deller.hospital.impacts.10.26.11.pdf




                                                                                                                         4
higher wages and salaries than the typical
job in La Crosse County (Figure 5). Over the
past ten years, particularly the period
between 2000 and 2004, the pay scale for
health care jobs has grown significantly
higher than the average job.

Since 2003, adjusted for inflation earnings
per job has been flat and declining. The
effects of the “Great Recession” are evident
in 2009, particularly for health care, but the
decline in average per job earnings for the
typical job is particularly troublesome.
After a peak in 2003 at $37,500 the overall
average has declined to $35,800 in 2009.
This decline cannot be attributed to the
“Great Recession” and is more a reflection
of structural shifts in the economy toward
more part‐time jobs that offer lower pay. A                            *See Resources (Page 10)
comparison of health care and social services sector average earnings per job for La Crosse County to Wisconsin
and the U.S. reveals that La Crosse County tracks Wisconsin fairly closely and has been slightly above Wisconsin
since 2002 (Figure 6). But the stagnation of earnings per job growth in health care does not appear to be unique
to La Crosse County. For Wisconsin and the U.S. there is a noticeable decline in earnings per health care job prior
                                                       to the beginning of the “Great Recession”.

     La Crosse County’s economy has                      Generally, we have found that La Crosse County’s
    been fairly strong and the health                    economy has been fairly strong and the health care sector
                                                         appears to be a major source of job growth for the
    care sector appears to be a major
                                                         County. In addition, the average earnings for jobs created
       source of job growth for the                      within the health care sector appear to be above the
                  County.                                county‐wide average.



Economic Contribution of the Health Care Sector

In the trend analysis presented above it becomes clear that the health care sector is a source of strong
employment growth and pays above average wages. Unfortunately, the health care data examined above (as well
as in Appendix A) includes social service industries (e.g., child care, emergency family services, etc.). In other
words, the annual data examined above does not allow us to separate traditional health care industries (e.g.,
hospitals and medical clinics) and social service industries (e.g., child care, etc.). To refine our thinking we will
build on the Wisconsin Hospitals Association (WHA) recently released study on the contributions of hospitals to
the Wisconsin and local economies.3 Here we use a detailed input‐output model of the La Crosse County economy
using data for 2009 (See Appendix B for an overview of input‐output analysis and the logic of a multiplier.)

For this analysis of the contribution of the health care sector to the La Crosse County economy we explore three
specific sectors:
     Hospitals,
     Offices of physicians, dentists, and other health practitioners,
     Nursing and residential care facilities


    3
        Deller (2011).


                                                                                                                        5
We select these sectors primarily because of the structure of the La Crosse County economic model. One sector
that we do not include is retail trade associated with health services such as pharmacists and medical supply
companies (e.g., stores that specialize in selling items such as wheel chairs, walkers, etc.). Unfortunately, a large
part of retail pharmacy sales now occur in general merchandise stores (e.g., Wal‐Mart and Target among others)
and the health care component cannot be separated out for analysis.
Table 1: Impact of Health Care Industries on La Crosse County 2009
                                                Employment      Labor Income        Total Income      Industry Sales
Hospitals
Direct Effect                                          8,310    $616,954,903        $658,536,059     $1,262,158,976
Indirect Effect                                        2,281     $77,851,199        $153,779,911       $246,319,692
Induced Effect                                         3,819    $128,291,337        $224,157,875       $372,494,617
 Total Effect                                         14,409    $823,097,438      $1,036,473,845     $1,880,973,285
Multiplier                                             1.734            1.334              1.574              1.490

Total County                                          78,554    $3,371,922,291    $5,024,037,474     $9,686,179,903
Percent of County Total Economy                        18.3%             24.4%             20.6%              19.4%
Impact on Neighboring WI Counties                        439       $13,962,912       $24,494,194        $44,993,578

Offices of physicians, dentists, and other
health practitioners
Direct Effect                                          1,394      $88,292,484        $94,096,904       $165,414,224
Indirect Effect                                          313      $11,381,020        $18,824,069        $31,939,605
Induced Effect                                           548      $18,421,068        $32,188,463        $53,487,532
 Total Effect                                          2,255     $118,094,572       $145,109,437       $250,841,361
Multiplier                                             1.618            1.338              1.542              1.516

Percent of County Total Economy                         2.9%              3.5%               2.9%              2.6%
Impact on Neighboring WI Counties                         60        $1,887,990         $3,334,425        $5,913,822

Nursing and residential care facilities
Direct Effect                                          1,250       $34,431,542       $37,178,352        $67,941,984
Indirect Effect                                          133        $4,540,952        $8,176,267        $13,904,799
Induced Effect                                           217        $7,270,186       $12,712,172        $21,117,121
 Total Effect                                          1,599       $46,242,680       $58,066,791       $102,963,904
Multiplier                                             1.279             1.343             1.562              1.515

Percent of County Total Economy                         2.0%              1.4%               1.2%              1.1%
Impact on Neighboring WI Counties                         25          $807,100         $1,394,756        $2,664,564

All Sectors Combined
Direct Effect                                         10,954     $739,678,928       $789,811,315     $1,495,515,184
Indirect Effect                                        2,727      $93,824,622       $180,856,364       $292,316,524
Induced Effect                                         4,588     $154,136,484       $269,322,729       $447,549,665
 Total Effect                                         18,269     $967,640,034     $1,239,990,408     $2,235,381,373
Multiplier                                             1.668            1.335              1.570              1.495

Percent of County Total Economy                        23.3%             29.3%             24.7%              23.1%
Impact of Neighboring WI Counties                        525       $16,658,002       $29,223,375        $53,571,965

In our impact analysis we use four measures of economic activity: (1) employment, (2) labor income, (3) total
income, and (4) industry sales/revenue. Employment includes both part‐ and full‐time employment and is not full‐
time equivalent. Labor income is defined as income derived from work related activities and includes wages,
salary and proprietor income. Total income includes labor income plus all other sources of income including
income from dividends, interest and rent as well as transfer payments such as social security and unemployment
payments. Total income could be considered akin to gross county product in the spirit of gross domestic product.
Industry sales/revenues are simply business sales.



                                                                                                                        6
A summary of the analysis is provided in Table 1. Consider first the three components of the health care industry
taken together. In 2009, the health care sector accounted for about 18,269 jobs, which is about 23.3 percent of all
employment in the county. The computed employment multiplier is 1.668 which can be interpreted as for every
additional ten jobs in the health care sector an additional 6.68 jobs
will be created elsewhere in the County economy. This level of
employment supports $987.6 million in labor income (wages,                       …for every additional ten
salaries and proprietor income), or about 29.3 percent of the               jobs in the health care
County total. The higher share of labor employment attributed to            sector an additional 6.68
the health care industry above employment is a strong indicator of          jobs will be created
the pay scale within the health care industry. As noted above in            elsewhere in the County.
the historical descriptive analysis, the wages/salaries paid in the
health care industry tend to be higher than the County average.
The labor income multiplier is 1.335 suggesting that for every $100 of additional labor income in health care will
generate an additional $33.5 of labor income elsewhere in the local economy. The health care industry accounts
for about $1.24 billion of total income (all forms of income), or 24.7 percent of the County total, and $2.33 billion
in industrial sales or revenue, which is about 23.1 percent of the County total.

La Crosse County is not an isolated economy and as noted above is a regional retail and service hub providing
services to neighboring counties. The economic linkages that are captured in multipliers can also be used to
measure the linkages La Crosse County has with its neighboring counties.4 For the whole of the health care sector,
there are 525 jobs, $16.6 million in labor income, $29.2 million in total income, and $53.6 million in industries sales
generated in neighboring counties. This is economic activity above and beyond the impacts within La Crosse
County itself. Thus the contribution of the health care sector within La Crosse County is not just a concern for La
Crosse County officials and residents, but also a concern for the surrounding communities.

The economic activity that is generated and supported by the health care industry is also a source of revenues for
state and local governments. Retail sales activity, for example, generates sales tax revenues, employment
generates income tax revenues, and workers and businesses supported by the health care industry also pay
property taxes. The over 18,000 jobs and nearly a $1 billion in income generated by the health care industry also
generates about $82 million in state and local government revenues (Table 2). $17 million takes the form of sales
tax, some of which (about $1.9 million) flows to the County government, $24 million in property taxes which nearly
all of which flows to local governments in La Crosse County, about $18 million in income taxes which goes to state
government, and $22 million in miscellaneous other taxes, fees and charges. This analysis does not include
revenues flowing to the federal government.

Table 2: State and Local Government Revenues Generated in La Crosse Co. by Health Care Industry Impacts 2009
                                                 Offices of
                                            physicians, dentists      Nursing and
                                             and other health           residential
                            Hospitals          practitioners         care facilities  All Sectors Combined
Sales Taxes                $14,370,836          $1,782,650             $1,021,724          $17,185,483
Property Taxes             $20,229,136          $2,517,722             $1,432,078          $24,193,199
Income Taxes               $14,947,468          $2,145,456                $847,860         $17,945,573
Other                      $18,973,040          $2,485,270             $1,084,917          $22,553,377
Total                      $68,520,480          $8,932,098             $4,386,579          $81,877,632

If we decompose the total economic impact of the health care sector into its three components as defined for this
study (hospitals, clinics/offices, resident care) it becomes readily clear that for La Crosse County the industry is


4
 Unfortunately, we cannot include neighboring Minnesota counties in the analysis. For this study, neighboring
counties are those that are adjacent to La Crosse County in Wisconsin.


                                                                                                                          7
dominated by hospitals. Consider just employment, hospitals account for 14,400 jobs while the offices of
physicians, dentists and other health care practitioners account for about 2,250 jobs, while nursing and resident
care facilities account for about 1,600 jobs once the multiplier effect is accounted for. A similar pattern applied to
the three other metrics of economic activity: labor income, total income and industrial sales. Indeed, when one
considered the amount of revenues flowing from the economic activity generated by these three components of
the health care industry a similar pattern is observed. Also note that the value of the multipliers varies across each
of the three health care sectors. These differences in the size of the multipliers reflect how well “connected” the
sector is to the local economy. Higher pay scales along with more purchases from local businesses will enlarge the
multiplier. Conversely, lower pay scales and fewer purchases from local business will drive the multiplier to
smaller values.

If we combine the insights we have gained from the historical analysis along with the economic impact assessment
we can make several observations.
         The health care sector is a significant source of economic activity for La Crosse County and the
           surrounding area.
         The rate of growth of the health care sector for La Crosse County in terms of employment and income
           far outpaces other local industries.
         The wages offered in the health care industry tends to be above the typical job in the County.

The Potential Economic Impact of Reductions to Medicaid and BadgerCare

One of the unique aspects of the health care industry that makes it difficult to fully understand the economic
contribution of the industry to the local or regional economy is the flow of funds from the federal and state
government in the forms of Medicare, Medicaid, BadgerCare and a range of other programs. The reimbursement
rates paid for covered persons varies significantly across programs and services rendered. For some programs
and services costs are adequately covered but for others costs are not covered and the health care provider
sustains an economic loss.

Consider, for example, a farmer who is selling their products on the open market and generating significant
revenues to the farm. But, if these revenues are not sufficient to cover operating costs, the farm is said to be
operating at a loss. In a sense, this farmer is representing a drag on the local economy and if these losses continue
indefinitely, the farm will eventually go out of business. If the operating losses are sufficiently large the
multipliers, such as those provided in Table 1, can actually become negative.

                                       This creates a challenge for assessing the potential economic impact of
                                       reductions in these federal and state programs. If there are budget cuts to
     If there are budget               a program that less than fully reimburses the cost of services rendered, will
      cuts to a program                this result in a net loss or gain to the regional economy? To proceed we
     that less than fully              assume that Medicaid and BadgerCare reimbursements represent new
   reimburses the cost of              money coming into the economy that would not be available if it were not
     services rendered,                for these programs. In order for this assumption to make sense we must
     will this result in a             presume that Medicaid and BadgerCare patients will be receiving health
   net loss or gain to the             care services regardless of participation in the programs. This care can take
     regional economy?                 many forms ranging from last minute emergency care which may be more
                                       costly or charity care. Regardless, care must be taken when interpreting the
                                       impact results.

In 2009 the Medicaid and BadgerCare programs put $127,101,486 dollars into the health care sector in La Crosse
County and in 2010 the amount was $125,661,772. There are any number of proposals being offered to offset
deficits in these two programs offered by the Walker Administration and other interested parties. Complicating
matters is that any final proposal must be approved by the federal government which may accept the whole
proposal, parts of the proposal or reject the whole proposal. Thus, the exact level of reduction in Medicaid and



                                                                                                                         8
BadgerCare funds flowing into La Crosse County is unknown at this time. The best that can be accomplished at this
time is to explore what the potential magnitude of economic impacts might be.

We try to provide insights into these magnitudes in three ways: (1) the impact of the whole of the payments to La
Crosse County health care providers to establish a base‐line, (2) a 25 percent reduction and (3) a 10 percent
reduction. To carry out the analysis we used the current (2011 to date) payment schedule to describe how these
payments flow into the County health care industry. This breakout is provided in Table 3 and uses an average of
the 2009 and 2010 total payments.

   Table 3: Medicaid and BadgerCare payments to La Crosse Health Care Provider Type
   Industry Sector                                               Share             Direct MA Payment
   Pharmacy                                                      22.81%                $28,829,310
   Hospitals                                                     24.62%                $31,116,675
   Doctors Offices                                               17.10%                $21,605,285
   Individual and family services                                 2.51%                 $3,172,777
   Nursing and residential care facilities                       22.54%                $28,480,500
   Other ambulatory care services                                 6.58%                 $8,314,532
   Home health care services                                      3.85%                 $4,862,551
                                                                  TOTAL               $126,381,630

The results of the analysis are provided in Table 4. The economic contribution of the whole of the Medicaid and
BadgerCare program payments to health care providers in La Crosse County is about 1,800 jobs and $72 million in
labor income, $93 million in total income and $159 million in industrial sales. Now consider a 25 percent
reduction. If health care providers respond to this cut in reimbursements by reducing staff the total economic
impact could be as many as 460 jobs and $18 million in labor income.

   Table 4: Potential Economic Impacts of MA Reductions
                                           Employment          Labor Income     Total Income     Industry Sales
   Impact of $126,381,629 MA Payment           1,839            $72,197,936      $92,716,986      $159,414,567
   Impact of 25% Reduction                       460            $18,049,484      $23,179,247       $39,853,642
   Impact of 10% Reduction                       184             $7,219,794        $9,271,699      $15,941,457

What we do not fully understand, however, is how
health care providers will respond to the
reimbursement reductions. It is unlikely that medical        The cost of these expenditures shifts
staff will be reduced but support staff such as in food           from the federal and state
services, janitorial staff, or office support staff may be     government to local (La Crosse
trimmed or hours reduced.                                     County) health care providers and
                                                                      health care clients.
Conclusions

The information and analysis presented in this report confirms the relative importance of the health care sector to
the economy in La Crosse County and the surrounding area. The rate of growth in the health care industry, in
terms of employment and income, creates a high level of dependency in La Crosse County‐‐ because of its
economic activity.

It is feasible that cuts to Medicaid and BadgerCare funding, at whatever level, can have the greatest state‐wide
impact in La Crosse County‐‐‐‐as La Crosse County has the largest multiplier effect due to the strength of the
health care industry here. 5

    5
        Deller (2011).


                                                                                                                      9
Any decisions to reduce or eliminate Medicaid and/or BadgerCare funding must consider more than the initial
dollar savings of the program budget reduction to determine the economic and social impact. Reductions in these
programs will naturally impact the health care sector in La Crosse County, and in turn have an impact to La Crosse
County’s local employment, labor income, total income, and industry sales.

In addition to the ripple effect cuts to Medicaid and BadgerCare will create, these cuts do not necessarily eliminate
the expenditures, or the need for the expenditures. Instead, the cost of these expenditures shifts from the federal
and state government to local (La Crosse County) health care providers and health care clients. Individuals,
families, and businesses will be required to spend more for health care and/or health insurance, resulting in less
money available to reinvest in business and the community, less building projects, less job opportunities, less
consumer purchases, etc.

The proposed changes for these two programs present more questions than answers:

       Will the cost of care for individuals/families currently receiving Medicaid or BadgerCare benefits, who lose
        access to health care coverage and still need care, be higher?
       How will individuals/families who currently receive health care coverage through their own or employer
        provided health insurance or private pay be impacted? If costs for health insurance or health care
        increases, how will their diminished consumer spending affect the local economic activity?
       Will health care businesses be able to continue to provide under‐funded or non‐funded services? Will the
        need for uncompensated and charity care increase? Will the cost for under‐funded or non‐funded
        services be shifted to other patients, government, taxpayers, or other patients through hyper inflated
        health insurance?
       Will health care costs increase? Will employees lose jobs and/or benefits? Will patients lose services?
       How will combining the loss of these program revenues with the costs for mental health and emergency
        care costs impact the local tax levy and program viability?

In these politically challenging times, one can be criticized for supporting publicly funded health care programs
when they are overspending by $500+ million, yet supporting the elimination and/or reduction of programs results
in impacts that ripple through La Crosse County’s economy, effecting more than just the financially disadvantaged.
Ultimately, we need to understand the systemic issues in our health care system that creates high costs, and find
the creative answers to the question—who will bear the costs of access to and for health care in Wisconsin?




                                                                                                                        10
Resources

The data for this analysis come from three sources:

The historical trend analysis (Figures 1 through 6 as well as the cluster analysis in Appendix A) is from Woods and
Poole, Inc, Washington DC. The core data upon which Woods and Poole builds their data is the Bureau of
Economic       Analysis,    Regional       Economic     Information       System       (BEA‐REIS)     available  at:
http://www.bea.gov/regional/index.htm

The economic impact analysis is conducted using IMPLAN, a regional economic modeling system originally
developed by the USDA Forest Service and now operated by the IMPLAN Group. Details of the modeling system
and supporting data bases can be viewed at: http://implan.com/V4/Index.php

La Crosse County medical transfer payments were obtained from the 2011‐2012 Blue Book
(http://legis.wisconsin.gov/lrb/bb/11bb/Stats_SocialServices.pdf, pages 811‐812) and the Wisconsin Fiscal Bureau
(Eric Peck, Fiscal Analyst).




                                                                                                                       11
Appendix A: Cluster Analysis

In 2003 the Wisconsin Office of the Governor embraced the notion of cluster development as the foundation of
economic development policies. Forward Wisconsin defines clusters as:

                  . . . geographic concentrations of interconnected companies, specialized suppliers,
                  service providers and associated institutions in a particular field. Clusters develop
                  because they increase the productivity with which companies can compete in an
                  increasingly more competitive global market, and they are the source of jobs, income
                  and export growth. The philosophy behind clusters is that large and small companies
                  in a similar industry achieve more by working together than they would
                  individually. Clusters give businesses an advantage by providing access to more
                  suppliers and customized support services, skilled and experienced labor pools, and
                  knowledge transfer through informal social exchanges. In other words, clusters
                  enhance competitiveness.

The state initially identified 10 existing and potential clusters, including dairy and food processing. Other clusters
include paper and wood products, biotechnology, plastics, medical devices, information technology and wind
energy. Methods of identifying clusters vary widely, but an approach suggested by Harvard business economist
Michael Porter is growing in popularity. The approach is built on the notion of location quotients: current values of
the location quotient, changes in the location quotient over time, and relative size of the industry coupled with
other industry characteristics. The location quotient (LQ) is an indicator of self‐sufficiency, or relative strength, of
a particular industry. The LQ is computed as:

                                            Percent of local economic activity in sector i
                                  i
                             LQ   s   = ‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐

                                        Percent of national economic activity in sector i


The proportion of national economic activity in sector i located in the region (state or community) measures the
region's production of product i, assuming equal labor productivity. The proportion of national economic activity in
the region proxies’ local consumption, assuming equal consumption per worker. The difference between local
production and consumption is an estimate of production for export (i.e. production > consumption).
The key assumptions to operationalize the location quotient approach are that the regional production technology
is identical to national production technology (i.e. equal labor productivity) and that local tastes and preferences
are identical to national tastes and preferences (i.e. equal consumption per worker). Assuming the national
economy is self‐sufficient, the comparison between the community and the national benchmark gives an
indication of specialization or self‐sufficiency.

Three important location quotient values derive from the self‐sufficiency interpretation of location quotients. A
location quotient of 1 means the region has the same proportion of economic activity in sector i as the nation. The
region just meets local consumption requirements through local production of the specified good or service. If the
location quotient is less than 1, the region is not producing enough to meet local needs. If the location quotient is
greater than 1, the region has a larger proportion of its economy in sector i than does the nation.
The Porter notion of clusters evaluates levels and changes of the location quotient coupled with the absolute size
of the industry and other characteristics that may make the industry desirable as a source of employment
opportunities. Consider the simple mapping of the level and change of the LQ as outlined in Figure A1. There are
four potential combinations.




                                                                                                                                            12
First, if the industry has a LQ less
than 1 and is declining, this industry
is considered a “weakness and
declining” industry and generally
should not be considered a potential
cluster. Second, if the LQ is less than
1 but increasing, the industry can be
considered a “weakness and
growing” industry and may be a
possible industry of focus for
economic development. Third, if the
LQ is greater than 1 but is declining
over time, it is considered “strength
and declining.” Industries in this
category might be considered at risk
and       deserving     of      special
consideration to understand why a
strong industry (i.e. LQ>1) is
weakening (i.e. ΔLQ
Table A1: Cluster Analysis for La Crosse County Using Employment Data
                                                                                      ∆LQ     Share of
                                                                                    1990‐      County
                                                                        LQ 2009      2009   Employment
Farm Employment                                                            0.743   ‐0.097       1.1%
Forestry, Fishing related activities and other employment                  0.541   ‐0.014       0.3%
Mining Employment                                                          0.039    0.000       0.0%
Utilities Employment                                                       0.694    0.120       0.2%
Construction Employment                                                    0.758   ‐0.034       4.0%
Manufacturing Employment                                                   1.349    0.094       9.7%
Wholesale Trade Employment                                                 1.082   ‐0.458       3.8%
Retail Trade Employment                                                    1.229    0.150       12.6%
Transportation and Warehousing Employment                                  0.873    0.107       2.8%
Information Employment                                                     0.712   ‐0.123       1.4%
Finance and Insurance Employment                                           1.019    0.333       4.9%
Real Estate and Rental and Lease Employment                                0.650    0.052       2.9%
Professional and Technical Services Employment                             0.505   ‐0.020       3.5%
Management of Companies and Enterprises Employment                         1.953    0.546       2.1%
Administrative and Waste Services Employment                               0.557   ‐0.145       3.2%
Educational Services Employment                                            0.779    0.007       1.8%
Health Care and Social Assistance Employment                               1.669    0.151       18.9%
Arts, Entertainment, and Recreational Employment                           0.870   ‐0.195       1.9%
Accommodation and Food Services Employment                                 1.190   ‐0.122       7.6%
Other services, except Public Administrative Employment                    0.892   ‐0.133       5.2%
Federal Civilian Government Employment                                     0.343   ‐0.022       0.6%
Federal Military Employment                                                0.338   ‐0.050       0.4%
State and Local Government Employment                                      0.964   ‐0.062       11.2%
Data represented in Figure A2




                                                                                                         14
Appendix B: The Logic of a Multiplier

The analysis, as presented, considers the total economic contribution of the health care sector to La Crosse
County, Wisconsin. Specifically, how do the approximately 11,000 health care sector jobs and the economic
activity associated with those jobs (i.e., industry sales and labor income) impact the remainder of the La Crosse
County economy? For example, hospital workers spend their wages and salaries in the local economy: they spend
money in local grocery stores, local restaurants and go out to the movies. In addition hospitals pay utility bills, buy
office equipment and supplies, and pay taxes among other expenses. This spending by hospital employees and the
hospital itself in the local economy generates what is referred to as a multiplier effect.

To answer this question we use a family of regional economic models referred to input‐output analysis. An input‐
output model can be described as a “spreadsheet of the economy” capturing the demand and supply of the
different actors (industries and institutions such as households, government or imports/exports) that make up that
economy. Demanders or consumers are across the columns of the “spreadsheet” and suppliers or sellers are
down the rows. Any individual cell of the “spreadsheet” captures the flow of money from demanders (consumers
or buyers) to suppliers (sellers). Thus reading down the column of any particular demander (e.g., industry) outlines
how the demander spends money. For an industry, such as hospitals, reading down the column reveals the
“production function” of the industry. For a given level of production how much labor or electricity or accounting
services do hospitals need to purchase? At the same time reading across the row of a supplier tells us who that
industry is selling to. Grain farmers, for example, could be selling to dairy farmers, food processors, directly to
households or exporting their product out of the region.

Given that the economy is in “equilibrium” or more specifically supply must equal demand for all industries we can
use this “spreadsheet” representation of the economy to capture how changes in one part of the economy
influence or impact other parts of the economy. For example, if a medical clinic expands operations it must
purchase more inputs (e.g., labor, utilities, accounting services) and the industry that supplies those inputs must
increase their own production to meet that new demand. This “ripple” effect is commonly referred to as the
multiplier effect. Not only can we measure the total impact or contribution of any given industry on the whole of
the economy but also what industries are impacted and to what extent.

The size of an economic multiplier hinges on two concepts. The first is the level of linkages an industry has with
other businesses within the local economy. The second is the notion of “leakages” and the ability of the local
economy to retain dollars. How many inputs that a particular business purchases can and are purchased in the
local economy. For example, can a mining company buy the specialized equipment that it requires from local
businesses or does the company buy that equipment from businesses from outside the local area? Because so
much of the larger pieces of equipment the mining companies will require are so specialized, the likelihood of
buying this equipment in the local economy is small. This represents a “leakage” from the local economy.

Consider a simple visual representation of the logic of a multiplier (Figure B1). Consider a newly employed worker
at a medical clinic is paid $1. This worker spends this new income in the local economy. Suppose, for example,
this worker spends that $1 at a local grocery store. The question is how much of that dollar spent at the grocery
store stays in the local economy. In this example, 60¢ leaks out of the economy and goes to pay for the
vegetables from California, the canned goods from Texas, and the boxed goods from Illinois. In other words, the
grocer must pay for the stock in the store. Here the grocer keeps 40¢ and uses that 40¢ to pay, perhaps the utility
bill. That represents 40¢ going to the local utility company. Now suppose the local utility company uses Montana
coal to create the electricity the grocer is buying. In this example, 24¢ of that 40¢ immediately leaves (or leaks
out) the local economy and goes to Montana. Suppose the utility company uses the remaining 16¢ to pay its
employees. Now suppose that utility worker takes that 16¢ and takes the family to the movies. Part of that 16¢
immediately leaves the local economy and goes to Hollywood to pay for the movie itself. This respending
continues till all of the money leaks out of the economy. In this example, the economic multiplier is 1.66: for every
dollar of new activity creates $1.66 in economic activity, the original dollar plus 66¢ through the multiplier effect.



                                                                                                                          15
Generally, the size of the
multiplier will reflect the size of                                  Figure B1: Multiplier Logic
the local economy.          Larger
more urban economies tend to
                                                                                                         Initial impact:$ 1.00
have larger multipliers than
                                                                                                                            .40
                                                      60¢ leakage
smaller more rural economies.                                                                                               .16
The key here is the ability of                                                                                              .06
                                                                                                                            .03
larger economies to capture                                                                                                 .01
                                      Initial $1.00
and retain those dollars being         of exports
                                                                                                                      ----------
                                                                                                         Full impact:   $ 1.66
spent. For smaller economies,
like    much        of    western                                   24¢ leakage
Wisconsin, the ability to retain
                                                      40¢ respent
those dollars is weaker, money                          locally
                                                                                  10¢ leakage
will leak out of the local                                          16¢ respent                                 2¢ leakage
                                                                      locally
economy faster, and the                                                           6¢ respent    3¢ leakage
                                                                                                                             1¢ respent
                                                                                    locally     3¢ respent
                                                                                                                               locally
multiplier will be smaller.               (a)             (b)           (c)           (d)          (e)            (f)




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