Nursing Homes
Private Investment Homes Sometimes Differed from Others in Deficiencies, Staffing, and Financial Performance Gao ID: GAO-11-571 July 15, 2011Private investment (PI) firms' acquisition of several large nursing home chains led to concerns that the quality of care may have been adversely affected. These concerns may have been in part due to PI firms' business strategies and their lack of financial transparency compared to publicly traded companies. In September 2010, GAO reported on the extent of PI ownership of nursing homes and firms' involvement in the operations of homes they acquired. In this report, GAO examined how nursing homes that were acquired by PI firms changed from before acquisition or differed from other homes in: (1) deficiencies cited on state surveys, (2) nurse staffing levels, and (3) financial performance. GAO identified nursing homes that had been acquired by PI firms from 2004 through 2007 and then used data from CMS's Online Survey, Certification, and Reporting system and Medicare Skilled Nursing Facility Cost Reports to compare these PI homes to other forprofit and nonprofit homes. For PIacquired homes, GAO also compared homes for which the operations and real estate were owned by the same firm to those that were not. Because research has shown that other variables influence deficiencies, staffing, and financial performance, GAO statistically controlled--that is adjusted--for several factors, including the percent of residents for whom the payer is Medicare, facility size, occupancy rate, market competition, and state. Any differences GAO found cannot necessarily be attributed to PI ownership or acquisition.
On average, PI and other for-profit homes had more total deficiencies than nonprofit homes both before (2003) and after (2009) acquisition. PI-acquired homes were also more likely to have been cited for a serious deficiency than nonprofit homes before, but not after, acquisition. Serious deficiencies involve actual harm or immediate jeopardy to residents. From 2003 to 2009, total deficiencies increased and the likelihood of a serious deficiency decreased in PI homes; these changes did not differ significantly from those in other homes. Reported average total nurse staffing ratios (hours per resident per day) were lower in PI homes than in other homes in both 2003 and 2009, but the staffing mix changed differently in PI homes. Staffing mix is the relative proportion of registered nurses (RN), licensed practical nurses (LPN), and certified nurse aides (CNA). RN ratios increased more from 2003 to 2009 in PI homes than in other homes, while CNA ratios increased more in other homes than in PI homes. The increase in RN ratios in PI homes from 2003 to 2009 was greater if the same PI firm acquired both operations and real estate than if not. The financial performance of PI homes showed both cost increases from 2003 to 2008 and higher margins in those years when compared to other for-profit or nonprofit homes. Facility costs as well as capital-related costs for PI homes increased more, on average, from 2003 to 2008 than for other ownership types. The increase was less if the same PI firm acquired both the operations and real estate than if it did not. In 2008, PI homes reported higher facility costs than other for-profit homes (but lower costs than nonprofit homes) and higher capital-related costs than other ownership types. Despite increased costs, PI homes also showed increased facility margins and the increase was not significantly different from that of other for-profit homes. In contrast, the margins of nonprofit homes decreased. Although the acquisition of nursing homes by PI firms raised questions about the potential effects on quality of care, GAO's analysis of data from before and after acquisition did not indicate an increase in the likelihood of serious deficiencies or a decrease in average reported total nurse staffing. The performance of these PI homes was mixed, however, with respect to the other quality variables GAO examined. We found differences among PI-acquired homes that reflected management decisions made by the firms and, to varying degrees, some of the changes in the PI firms we studied were consistent with attempts to increase their homes' attractiveness to higher paying residents. HHS provided CMS's observations on our methodology. CMS suggested an alternative to our "before and after" acquisition methodology to take into account the fact that PI firms acquired nursing homes at different points in time during 2004 through 2007. One of the studies we cited used such a methodology and we believe that the use of different methodologies enhances the understanding of an issue. CMS also identified a number of additional approaches for exploring the relationship between PI ownership and quality. We agree that such approaches merit future attention. CMS also acknowledged that the report is an important step toward better understanding the effect of nursing home ownership on the quality of care provided to residents.
GAO-11-571, Nursing Homes: Private Investment Homes Sometimes Differed from Others in Deficiencies, Staffing and Financial Performance
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United States Government Accountability Office:
GAO:
Report to Congressional Requesters:
July 2011:
Nursing Homes:
Private Investment Homes Sometimes Differed from Others in
Deficiencies, Staffing, and Financial Performance:
GAO-11-571:
GAO Highlights:
Highlights of GAO-11-571, a report to congressional requesters.
Why GAO Did This Study:
Private investment (PI) firms‘ acquisition of several large nursing
home chains led to concerns that the quality of care may have been
adversely affected. These concerns may have been in part due to PI
firms‘ business strategies and their lack of financial transparency
compared to publicly traded companies. In September 2010, GAO reported
on the extent of PI ownership of nursing homes and firms‘ involvement
in the operations of homes they acquired. In this report, GAO examined
how nursing homes that were acquired by PI firms changed from before
acquisition or differed from other homes in: (1) deficiencies cited on
state surveys, (2) nurse staffing levels, and (3) financial
performance.
GAO identified nursing homes that had been acquired by PI firms from
2004 through 2007 and then used data from CMS‘s Online Survey,
Certification, and Reporting system and Medicare Skilled Nursing
Facility Cost Reports to compare these PI homes to other for-profit
and nonprofit homes. For PI-acquired homes, GAO also compared homes
for which the operations and real estate were owned by the same firm
to those that were not. Because research has shown that other
variables influence deficiencies, staffing, and financial performance,
GAO statistically controlled-”that is adjusted”-for several factors,
including the percent of residents for whom the payer is Medicare,
facility size, occupancy rate, market competition, and state. Any
differences GAO found cannot necessarily be attributed to PI ownership
or acquisition.
What GAO Found:
On average, PI and other for-profit homes had more total deficiencies
than nonprofit homes both before (2003) and after (2009) acquisition.
PI-acquired homes were also more likely to have been cited for a
serious deficiency than nonprofit homes before, but not after,
acquisition. Serious deficiencies involve actual harm or immediate
jeopardy to residents. From 2003 to 2009, total deficiencies increased
and the likelihood of a serious deficiency decreased in PI homes;
these changes did not differ significantly from those in other homes.
Reported average total nurse staffing ratios (hours per resident per
day) were lower in PI homes than in other homes in both 2003 and 2009,
but the staffing mix changed differently in PI homes. Staffing mix is
the relative proportion of registered nurses (RN), licensed practical
nurses (LPN), and certified nurse aides (CNA). RN ratios increased
more from 2003 to 2009 in PI homes than in other homes, while CNA
ratios increased more in other homes than in PI homes. The increase in
RN ratios in PI homes from 2003 to 2009 was greater if the same PI
firm acquired both operations and real estate than if not.
The financial performance of PI homes showed both cost increases from
2003 to 2008 and higher margins in those years when compared to other
for-profit or nonprofit homes. Facility costs as well as capital-
related costs for PI homes increased more, on average, from 2003 to
2008 than for other ownership types. The increase was less if the same
PI firm acquired both the operations and real estate than if it did
not. In 2008, PI homes reported higher facility costs than other for-
profit homes (but lower costs than nonprofit homes) and higher capital-
related costs than other ownership types. Despite increased costs, PI
homes also showed increased facility margins and the increase was not
significantly different from that of other for-profit homes. In
contrast, the margins of nonprofit homes decreased.
Although the acquisition of nursing homes by PI firms raised questions
about the potential effects on quality of care, GAO‘s analysis of data
from before and after acquisition did not indicate an increase in the
likelihood of serious deficiencies or a decrease in average reported
total nurse staffing. The performance of these PI homes was mixed,
however, with respect to the other quality variables GAO examined. We
found differences among PI-acquired homes that reflected management
decisions made by the firms and, to varying degrees, some of the
changes in the PI firms we studied were consistent with attempts to
increase their homes‘ attractiveness to higher paying residents.
HHS provided CMS‘s observations on our methodology. CMS suggested an
alternative to our ’before and after“ acquisition methodology to take
into account the fact that PI firms acquired nursing homes at
different points in time during 2004 through 2007. One of the studies
we cited used such a methodology and we believe that the use of
different methodologies enhances the understanding of an issue. CMS
also identified a number of additional approaches for exploring the
relationship between PI ownership and quality. We agree that such
approaches merit future attention. CMS also acknowledged that the
report is an important step toward better understanding the effect of
nursing home ownership on the quality of care provided to residents.
View [hyperlink, http://www.gao.gov/products/GAO-11-571] or key
components. For more information, contact John E. Dicken at (202) 512-
7114 or dickenj@gao.gov.
[End of section]
Contents:
Letter:
Background:
PI Homes Had More Total Deficiencies than Nonprofit Homes and Were
More Likely to Have Had a Serious Deficiency Before but Not After
Acquisition:
Reported Total Nurse Staffing Ratios Were Lower in PI Homes, but
Reported RN Ratios Increased More in PI Homes than Other Homes:
PI Homes' Financial Performance Showed Cost Increases and Higher
Facility Margins Compared to Other Homes:
Concluding Observations:
Agency Comments and Our Evaluation:
Appendix I: Scope and Methodology:
Appendix II: Comments from the Department of Health and Human Services:
Appendix III: GAO Contact and Staff Acknowledgments:
Related GAO Products:
Tables:
Table 1: Scope and Severity of Deficiencies Identified during Nursing
Home Surveys:
Table 2: Variables Included in Our Datasets:
Table 3: Unadjusted Average Reported RN Ratios (Hours per Resident per
Day):
Table 4: Results of Analysis of Reported RN Ratios Using a Panel Model
without Adjusting for Control Variables:
Table 5: Results of Analysis of Reported RN Ratios Using a Panel Model
When Adjusting for Control Variables:
Table 6: Differences in Deficiencies, Nurse Staffing Ratios, and
Financial Performance Identified in Comparisons of Adjusted Data:
Figures:
Figure 1: Total Deficiencies in PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2009:
Figure 2: Serious Deficiencies in PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2009:
Figure 3: Total Reported Nurse Staffing Ratios for PI, Other For-
Profit, and Nonprofit Homes, 2003 and 2009:
Figure 4: RN Ratios Reported for PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2009:
Figure 5: RN Ratios for Homes for which the Same PI Firm Acquired Both
the Operations and the Real Estate Compared to Homes for which the
Same PI Firm Did Not Acquire Both, 2003 and 2009:
Figure 6: CNA Ratios Reported for PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2009:
Figure 7: Facility Costs per Resident Day for PI, Other For-Profit,
and Nonprofit Homes, 2003 and 2008:
Figure 8: Facility Costs per Resident Day for Homes for which the Same
PI Firm Acquired Both the Operations and the Real Estate Compared to
Homes for which the Same PI Firm Did Not Acquire Both, 2003 and 2008:
Figure 9: Capital-Related Costs per Resident Day for PI, Other For-
Profit, and Nonprofit Homes, 2003 and 2008:
Figure 10: Capital-Related Costs per Resident Day for Homes for which
the Same PI Firm Acquired Both the Operations and the Real Estate
Compared to Homes for which the Same PI Firm Did Not Acquire Both,
2003 and 2008:
Figure 11: Facility Margins for PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2008:
Abbreviations:
CMS: Centers for Medicare & Medicaid Services:
CNA: certified nurse aide:
HHS: Department of Health and Human Services:
LPN: licensed practical nurse:
OSCAR: Online Survey, Certification, and Reporting system:
PI: private investment:
RN: registered nurse:
SNF: skilled nursing facility:
[End of section]
United States Government Accountability Office:
Washington, DC 20548:
July 15, 2011:
The Honorable Max Baucus:
Chairman:
Committee on Finance:
United States Senate:
The Honorable Charles E. Grassley:
Ranking Member:
Committee on the Judiciary:
United States Senate:
The Honorable Pete Stark:
Ranking Member:
Subcommittee on Health:
Committee on Ways and Means:
House of Representatives:
The acquisition by private investment (PI) firms of several large
nursing home chains led to congressional and media attention in 2007
stemming from concerns that the quality of resident care may have been
adversely affected.[Footnote 1] For example, a 2007 New York Times
article reported that PI firms had reduced nursing home costs and
increased profitability by cutting registered nurse (RN) staffing.
[Footnote 2] These concerns may have been due in part to PI firms'
business strategies and their lack of financial transparency compared
to publicly traded companies. PI firms may hold their investments for
relatively short time frames while they attempt to improve financial
and operating performance. In addition, they may place large levels of
debt on the acquired company. Since the ownership interests of PI
firms generally are not publicly traded on a stock exchange, the
nursing home companies acquired by such firms are not subject to the
same federal financial disclosure requirements, making their finances
and management less transparent than publicly traded companies.
[Footnote 3]
Together, the Medicare and Medicaid programs funded about $89 billion
for nursing home care for elderly and disabled individuals in 2009.
[Footnote 4] Medicaid, which funds about two-thirds of all nursing
home resident days, pays for individuals who typically require long-
term custodial care, such as help with bathing and toileting.
Medicare, which funds about 12 percent of nursing home resident days,
pays for individuals who require more intensive skilled care for a
relatively short period of time following a hospital stay.[Footnote 5]
The Centers for Medicare & Medicaid Services (CMS) oversees both
programs and contracts with state survey agencies to conduct
inspections, known as standard surveys, and complaint investigations
to determine whether nursing homes that participate in the Medicare
and Medicaid programs are complying with federal quality standards.
State surveyors cite deficiencies when a nursing home is found to be
out of compliance with these standards, which include a requirement
that homes have sufficient nursing staff. Research has shown both
deficiencies and nurse staffing levels to be indicators of the quality
of care in nursing homes.[Footnote 6]
You asked us to examine the impact of PI ownership on the quality of
care provided and on nursing homes' financial performance. This report
builds on our September 2010 report, which addressed the extent of PI
ownership of nursing homes and the involvement of PI firms in the
operations of homes they acquired.[Footnote 7] We reported that PI
firms acquired about 1,900 unique nursing homes from 1998 through
2008.[Footnote 8] In this report, we examine how nursing homes that
were acquired by PI firms changed from before acquisition or differed
from other homes with regard to (1) health deficiencies cited on state
surveys, (2) nurse staffing levels, and (3) financial performance.
To determine whether PI-owned nursing homes changed from before
acquisition or differed from other nursing homes in deficiencies,
nurse staffing levels, or financial performance, we (1) identified
nursing homes that had been acquired by PI firms from 2004 through
2007 and (2) compared data from before and after PI acquisition of
these homes to data from other for-profit and nonprofit homes.
[Footnote 9] The PI homes we studied were acquired by the top 10 PI
acquirers of nursing homes we identified in our September 2010 report
and were still owned by the same PI firm in 2009.[Footnote 10] We
included homes for which a PI firm acquired the operations, the real
estate, or both. We obtained data for our outcome variables from CMS:
deficiency and nurse staffing data came from CMS's Online Survey,
Certification, and Reporting system (OSCAR) and data regarding
financial performance came from Medicare Skilled Nursing Facility
(SNF) Cost Reports.[Footnote 11] OSCAR is the only national, uniform
data source that contains data on nursing home deficiencies and nurse
staffing. Medicare SNF Cost Reports are the only publicly available
source of financial data on most Medicare providers.
* Deficiencies. We examined total deficiencies and whether there were
any "serious" deficiencies using data from both standard surveys and
complaint investigations.[Footnote 12] Deficiencies are categorized
into levels according to the number of residents potentially or
actually affected and the degree of relative harm involved. Serious
deficiencies are those at the levels indicating actual harm or
immediate jeopardy (actual or potential death or serious injury). As
we have noted in prior reports, state surveys may underestimate
deficiencies.[Footnote 13]
* Nurse staffing. We examined the total number of nursing hours per
resident per day (nurse staffing ratios), as well as ratios for each
of three types of nursing staff separately--RNs, licensed practical
nurses (LPN), and certified nurse aides (CNA). Nurse staffing data are
self-reported by nursing homes.
* Financial performance. We examined (1) facility costs per resident
day, defined as the total facility costs--including both operating and
capital costs--divided by total resident days; (2) capital-related
costs per resident day, defined as capital-related costs allocated to
nursing home resident care divided by nursing home resident days; and
(3) facility margins, defined as the amount of total facility revenues
exceeding total facility costs, divided by total facility revenues.
[Footnote 14] Financial data are self-reported by nursing homes.
Data analyses. To determine whether the PI, other for-profit, and
nonprofit homes we studied differed from one another, we analyzed data
from two points in time, one before and one after our target
acquisition period of 2004 to 2007. In general, we analyzed data from
2003 and 2009 (for deficiencies and staffing) or 2003 and 2008 (for
financial performance).[Footnote 15] The 2008 and 2009 data were the
latest available, which allowed as much time as possible for any
changes associated with PI acquisition to take effect. We included
data from before PI acquisition so we could determine whether the post
acquisition data reflected preexisting differences. Throughout this
report, we refer to the homes that were acquired by PI firms as "PI
homes," even when referring to 2003, which preceded our target
acquisition period. We included data from other types of nursing homes
so we could determine whether any changes from before to after
acquisition reflected changes that occurred regardless of type of
ownership. For PI-acquired homes, we also compared homes for which the
operations and real estate were owned by the same firm to those that
were not. Because research has shown that other variables can
influence deficiencies, staffing, and financial performance, we
statistically controlled--that is adjusted--for these variables when
analyzing our data. This adjustment allowed us to examine data from
homes with different types of ownership after neutralizing the effect
of these variables. Our control variables included membership in a
chain, payer mix (i.e., the percent of residents for whom the payer is
Medicare, Medicaid, or another source), facility size (number of
beds), occupancy rate, market competition (based on the number of beds
in each county), and geographic location (state).[Footnote 16] Payers
other than Medicare and Medicaid include private insurance, religious
organizations, the Department of Veterans Affairs, residents who pay
for their own care, and others. Unless otherwise specified, all
results that we present are based on our adjusted analyses and are
statistically significant at the 0.05 level. To provide context, we
show the unadjusted values in our figures and also describe the key
differences that were significant in our analyses of adjusted data.
In addition, to determine whether there were systematic differences
among nursing homes acquired by PI firms from 2004 to 2007 in outcomes
we studied, we conducted a series of analyses in which we separately
compared each of five PI firms' homes to all other PI-acquired nursing
homes in our study. We restricted our analyses to those PI firms and
homes for which we could identify both the PI owner of operations and
real estate and those PI firms for which we determined we had data
from a sufficient number of homes.[Footnote 17]
* For three PI firms' homes, the same PI firm acquired both operations
and real estate.
* For two PI firms that acquired nursing home operations, a different
PI firm acquired the real estate.
In each of five separate analyses, we compared the homes owned by a PI
firm to all other PI homes in our larger aggregate analysis, including
homes owned by the other firms we studied and any other homes owned by
that PI firm (e.g., those for which we could not identify the real
estate owner). Again, we adjusted for other variables that can
influence deficiencies, staffing, and financial performance. Unless
otherwise specified, all results that we present were statistically
significant at the 0.05 level in analyses of adjusted data. We also
interviewed representatives of PI firms that acquired nursing home
operations, real estate, or both, and representatives of companies
that operate PI-owned homes and, if their homes were part of our firm
level analyses, we discussed the results for their homes.
For all analyses, we excluded nursing homes when extreme values
suggested data entry or other reporting errors. We performed data
reliability checks on the list of PI homes we compiled and on data we
used from OSCAR, Medicare's Provider of Services, and Medicare SNF
Cost Reports. We also reviewed relevant documentation and discussed
these data sources with knowledgeable officials and industry experts.
In addition to our statistical analyses, we reviewed published
research on the quality and costs of nursing home care, our prior work
on nursing homes, and other relevant documentation. We interviewed
officials from CMS and experts on nursing home quality and costs. We
reviewed all data for soundness and consistency and determined that
they were sufficiently reliable for our purposes.
Limitations. Our analyses have several important limitations. Our
findings cannot be generalized beyond the PI-acquired nursing homes we
studied, which were limited to only those homes acquired from 2004 to
2007 by the 10 largest PI acquirers of nursing homes. Because they may
have been caused by other uncontrolled and unquantified variables, the
differences between PI-acquired and other nursing homes that we
observed cannot necessarily be attributed to PI ownership and the
differences we observed from before to after acquisition cannot
necessarily be attributed to PI acquisition. Despite these
limitations, our analyses do provide a reasonable basis for comparing
deficiencies, nurse staffing, and financial performance of the PI-
owned homes we studied to each other and to other types of nursing
homes at two points in time.
We conducted this performance audit from January 2010 to July 2011 in
accordance with generally accepted government auditing standards.
Those standards require that we plan and perform the audit to obtain
sufficient, appropriate evidence to provide a reasonable basis for our
findings and conclusions based on our audit objectives. We believe
that the evidence obtained provides a reasonable basis for our
findings and conclusions based on our audit objectives. A more
detailed description of our scope and methodology can be found in
appendix I.
Background:
Over the last decade, nursing home ownership and operating structures
have continued to evolve, including an increase in private investment
ownership of nursing homes and the development of more complex
structures.
Nursing Home Ownership and Operations:
Nursing home ownership varies in terms of profit status, level of
management involvement, number of homes owned, and whether the real
estate of homes is owned or leased.
* Profit status. Owners may be for-profit, nonprofit, or government
entities; about two-thirds of nursing homes are for-profit businesses.
In general, for-profit businesses, which may be publicly traded or
privately owned, have a goal of making profits that are distributed
among the owners and stockholders. In contrast, a nonprofit entity
receives favorable tax status because it may not operate for the
benefit of nor distribute revenues to private interests.
* Management involvement. Nursing home owners vary in terms of their
involvement in management of the business: they may be the operators,
and hold the state license, or they may contract with separate
licensed entities to manage the day-to-day operations.
* Number of homes owned. Owners or operators may have only one
facility or they may have multiple facilities across one or more
states that are part of a chain. Owners or operators may also have
multiple chains. According to a study conducted for the Department of
Health and Human Services, about half of nursing homes are part of a
chain.[Footnote 18]
* Real estate. Owners or operators do not necessarily own the real
estate where care is delivered, but instead may lease it. The
separation of real estate assets from the operations may be done to
obtain financing or in an attempt to protect real estate assets from
malpractice claims. Furthermore, the owners, leaseholders, and
operators may or may not be owned by the same or related entities.
PI firm nursing home ownership. In general, PI firms use a combination
of investment capital and debt financing to acquire companies,
including nursing home companies, with a goal of making a profit and
eventually returning that profit to investors and the firm. As we
noted in our prior report, some of the 10 PI firms we studied acquired
both the operations and the real estate of nursing home chains while
others only acquired the real estate.[Footnote 19] The former firms
sit on the chains' boards of directors and told us that their role is
to provide strategic direction rather than directing day-to-day
operations. In contrast, PI firms we studied that only purchased real
estate do not sit on the nursing home chains' boards of directors.
[Footnote 20] Among the PI firms that shared their reasons for
investing in the nursing home industry, most cited the increased
demand for long-term care due to an aging population. We also reported
that the investment time horizons and objectives of PI firms vary.
Some PI firms purchased the homes with a planned short-term "exit
strategy" and others intended to hold the investment over the long
term.[Footnote 21] PI firm managers said they are able to make
business improvements that their publicly traded competitors may be
less willing to make because they generally are not subject to
periodic disclosure requirements about their financial performance and
therefore are not tied to producing profits on a quarterly basis. In
addition, PI firms have said that they increase the operator's access
to funding that can be used to increase staff wages, enhance
operations, or modernize facilities and which ultimately may result in
improved quality of care.
PI firm business strategies. PI firms may pursue different business
strategies with respect to the types of residents they want to attract
and the efficiency of their operations. Researchers have found that
some nursing homes may specialize in caring for residents with certain
care needs or Medicare residents. Care for such residents may result
in higher levels of reimbursement. Indeed, prior to and after
acquisition, PI homes we studied had a higher average percentage of
residents whose care was reimbursed by Medicare compared to other for-
profit and nonprofit homes.[Footnote 22] After acquisition, the
percentage of residents in PI homes whose care was paid for by a
source other than Medicare or Medicaid was higher on average than in
other for-profit homes, but lower than in nonprofit nursing homes.
Prior to acquisition, the average occupancy rates in PI homes were not
significantly different from other homes.[Footnote 23] However, after
acquisition in 2009, the average occupancy rates in PI homes were
higher than other for-profit homes, although they did not differ
significantly from nonprofit homes' occupancy rates.
Federal Oversight of Nursing Home Quality:
The Social Security Act requires all nursing homes that participate in
Medicare and Medicaid to undergo periodic assessments of compliance
with federal quality standards.[Footnote 24] It also includes certain
ownership reporting requirements.[Footnote 25] Under contract with
CMS, state survey agencies conduct standard surveys, which occur once
a year, on average, and complaint investigations as needed. A standard
survey involves a comprehensive assessment of about 200 federal
quality standards.[Footnote 26] In contrast, complaint investigations
generally focus on a specific allegation regarding resident care or
safety made by a resident, family member, or nursing home staff
member.[Footnote 27] Deficiencies identified during either standard
surveys or complaint investigations are classified in 1 of 12
categories according to their scope (i.e., the number of residents
potentially or actually affected) and severity (i.e., the potential
for or occurrence of harm to residents). Serious deficiencies indicate
care problems that have resulted in actual harm or immediate jeopardy
(actual or potential for death or serious injury) for one or more
residents.
We, CMS, and other researchers have examined the rates of deficiency
citations, by state and among groups of nursing homes, to track trends
in the proportion of homes with serious deficiencies and better
understand recurring care problems.[Footnote 28] Our prior reports
identified considerable interstate variation in citations for serious
deficiencies on standard surveys and the understatement of serious
deficiencies on those surveys.[Footnote 29] Although several studies
have shown that for-profit nursing homes generally have a greater
number of total deficiency citations than nonprofit homes, others have
found no statistical difference in total deficiency citations between
for-profit and nonprofit homes.[Footnote 30] Similarly, research that
examined differences in the citations for serious deficiencies has not
consistently found a difference between for-profit and nonprofit
homes.[Footnote 31] One study examined the effect of PI acquisition on
total and serious deficiencies; it did not find a significant
difference from before to after PI acquisition.[Footnote 32] A
different study that examined the impact of ownership of nursing home
operations and real estate found that deficiency rates were similar
across homes regardless of whether or not ownership was split between
different entities.[Footnote 33]
Nursing Home Staffing:
Nursing homes employ three types of nursing staff--RNs, LPNs, and
CNAs.[Footnote 34] The responsibilities and salaries of these three
types of staff are related to their level of education. The staffing
mix--that is, the balance a nursing home maintains among RNs, LPNs,
and CNAs--is generally related to the needs of the residents served.
For example, a higher proportion of RNs may be employed to meet
residents' needs in homes that serve greater numbers of residents with
acute care needs or those with specialty care units (such as units for
residents who require ventilators). However, homes may not be able to
pursue their ideal staffing mix because of RN shortages in certain
geographic areas. High turnover among licensed nurses and CNAs may
also affect staffing mix.
[Text box:
Licensed Nurses and Nurse Aides:
* RNs have at least a 2-year degree and are licensed in a state. Due
to their advanced training and ability to provide skilled nursing
care, RNs are paid more than other nursing staff. Generally, RNs are
responsible for managing residents' nursing care and performing
complex procedures, such as starting intravenous feeding or fluids;
* LPNs have a 1-year degree, are also licensed by the state, and
typically provide routine bedside care, such as taking vital signs;
* CNAs are nurse aides or orderlies who work under the direction of
licensed nurses, have at least 75 hours of training, and have passed a
competency exam. CNAs' responsibilities usually include assisting
residents with eating, dressing, bathing, and toileting. In a typical
nursing home, CNAs have more contact with residents than other nursing
staff and provide the greatest number of hours of care per resident
per day. CNAs generally are paid less than RNs and LPNs. End of text
box]
Researchers have found that higher total and RN staffing levels are
typically associated with higher quality of care as shown by a wide
range of indicators, including deficiencies and health outcomes. Lower
total nurse staffing levels and lower levels of RN staffing have been
linked to higher rates of deficiency citations. In addition, higher
total nurse staffing ratios (hours per resident per day), and higher
levels of RN staffing in particular, have been associated with better
health outcomes (such as fewer cases of pressure ulcers, urinary tract
infections, malnutrition, and dehydration) as well as improved
residents' functional status.[Footnote 35] A home's management of its
nurse staffing has the potential to affect the quality of resident
care, as well. For example, nursing staff turnover complicates nursing
homes' efforts to train their staff and can contribute to quality
problems.
There are no federal minimum standards linking nurse staffing to the
number of residents but a number of states have such standards. By
statute, nursing homes that participate in Medicare and Medicaid are
required to have sufficient nursing staff to provide nursing and
related services to allow each resident to attain or maintain the
highest practicable physical, mental, and psychosocial well-being.
[Footnote 36] In addition to this general requirement, every nursing
home must have 24 hours of licensed nurse (RN or LPN) coverage per
day, including one RN on duty for at least 8 consecutive hours per
day, 7 days per week. In contrast, one researcher reported that, as of
2010, 34 states had established minimum requirements for the number of
nurse aide or direct care hours, which ranged from about 0.4 to 3.5
hours per resident per day.[Footnote 37]
In 2000, CMS examined the impact of nurse staffing on quality of care
in nursing homes.[Footnote 38] CMS concluded that a minimum nurse
staffing ratio of 2.75 hours per resident day was needed to maintain
quality of care, while also noting a preferred ratio of 3 hours and an
optimal ratio of 3.9 hours. For RNs, CMS concluded that the minimum
ratio should be 0.2 hours, with a preferred ratio of 0.45 hours. The
average acuity of nursing home residents has increased since that
report was issued. CMS did not recommend establishing minimum federal
nurse-staffing standards, in part because staffing needs vary with
residents' care needs and management or nursing practices (such as
training or policies affecting the retention of nursing staff) can
influence the quality of care.
Studies of trends in nurse staffing in the last few years have noted
an increase in total nurse staffing and in licensed nurse staffing.
[Footnote 39] In addition, several studies have shown that for-profit
nursing homes generally have lower nurse staffing ratios, and lower RN
ratios, than nonprofit homes.[Footnote 40] One study examined the
effect of PI ownership on nurse staffing; it found that RN staffing
declined after PI acquisition, but this decline had begun prior to
acquisition.[Footnote 41] This study also found an increase in CNA
staffing after PI acquisition. A different study that examined the
impact of ownership of nursing home operations and real estate on
nurse staffing found that RN staffing was higher when real estate was
owned than when it was leased or when ownership arrangements were
mixed.[Footnote 42]
Costs of Care and Profitability:
Nursing home costs are determined by the mix of residents and the
management of a home's resources to meet its residents' needs. The
costs of caring for any particular nursing home resident vary with the
type of services and amount of care needed. Residents who require low-
intensity nursing and therapy or custodial care, like the typical
Medicaid resident, are less costly, in part because their care needs
are not as heavily dependent on the services of licensed nurses.
Medicare beneficiaries are typically more costly than Medicaid
residents, have shorter stays, and are admitted with the expectation
that they will rehabilitate, recover, and return to their residences.
A growing share of nursing home residents requires rehabilitation
therapies and intensive skilled nursing care, such as parenteral
feeding and ventilator care that previously were provided primarily in
hospital settings; these residents are more costly because they
require more skilled nursing and therapy staff and specialized
equipment.
Salaries and labor-related costs for nursing and other staff account
for more than half of a nursing home's operating costs. Therefore a
home's decisions about its staffing mix are a key determinant of the
home's costs. To a lesser extent, the nursing home's management of its
capital assets--buildings, land, and equipment--also influences the
home's costs. New nursing homes and those that have been recently
renovated may have additional expenses associated with facility
construction and renovation that older buildings do not.
In addition to a home's occupancy rate, profitability is influenced by
several other factors, including payment rates, the mix of residents,
and the nursing homes' management of resources. Medicare's and 21
states' Medicaid payment rates are prospectively set per diem amounts
that take into account the relative care needs of the resident.
[Footnote 43] Under such payment systems, nursing homes have an
incentive to provide care at a cost below the payment amount because
they can retain any excess revenue not spent providing care. Although
Medicare generally pays for the care of the nursing home residents
with the most complex care needs, Medicare and private insurance have
the highest payment rates for nursing home care and, on average,
reimburse homes more than the costs of care. On the other hand,
industry representatives perennially express concerns that Medicaid
payment rates in many states are so low that they do not cover the
costs of providing care. Some nursing homes trying to increase their
profitability may focus on reducing their costs, by providing fewer or
less expensive services. Other homes trying to increase their
profitability may staff their homes and renovate their buildings to
attract the better-paying Medicare and private insurance residents
that will enhance their revenues or profits. We and the Medicare
Payment Advisory Commission have reported that for-profit nursing
homes have a greater profit on their Medicare line of business than
nonprofit homes, on average.[Footnote 44]
The relationship between costs, profitability, and quality of care in
nursing homes differs depending on how the home's resources are
deployed. A home that increases its nurse staffing or adopts a new
technology to improve the quality of care may also reduce its
profitability because it increased costs without increasing revenues.
However, some expenditures may prevent additional costs or increase
revenues and therefore lead to improved profitability. For example, an
expense can prevent subsequent, costly care needs, such as when higher
levels of RN staffing result in reduced levels of infections. As
another example, expenses that boost the attractiveness of the home to
better paying residents may also improve the home's profitability,
whether or not such expenses improve the quality of care.
PI Homes Had More Total Deficiencies than Nonprofit Homes and Were
More Likely to Have Had a Serious Deficiency Before but Not After
Acquisition:
PI homes, like other for-profit homes, had more total deficiencies
than nonprofit homes in both 2003 and 2009.[Footnote 45] In 2009, PI
homes did not differ significantly from nonprofit homes in the
likelihood of a serious deficiency, but in 2003 the likelihood was
higher in homes that were subsequently acquired by PI than in
nonprofit homes.[Footnote 46] From 2003 to 2009, total deficiencies
increased and the likelihood of a serious deficiency decreased in PI
homes; the changes in these deficiency measures from 2003 to 2009 in
other for-profit and nonprofit homes did not differ significantly from
the changes in PI homes.
PI Homes Had More Total Deficiencies than Nonprofit Homes:
On average, PI homes had more total deficiencies than nonprofit homes
in both 2003 and 2009. (See figure 1.) PI homes did not differ
significantly from other for-profit homes in total deficiencies in
either year. Total deficiencies in PI homes increased from 2003 to
2009; this change was not significantly different from the change in
other homes. Among PI homes, total deficiencies did not differ
significantly as a function of whether the same firm acquired the
operations and real estate or not.[Footnote 47]
Figure 1: Total Deficiencies in PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2009:
[Refer to PDF for image: vertical bar graph]
PI-acquired:
Average total deficiencies, 2003: 8;
Average total deficiencies, 2009: 9.
Other for-profit:
Average total deficiencies, 2003: 8;
Average total deficiencies, 2009: 9.
Nonprofit:
Average total deficiencies, 2003: 6;
Average total deficiencies, 2009: 7.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant (except where noted)
after adjusting for control variables.
Total deficiencies:
* Were higher in PI homes than in nonprofit homes in both 2003 and
2009.
* Increased from 2003 to 2009 in PI homes, and this change did not
differ significantly from the change in other for-profit or nonprofit
homes.
[End of figure]
Our examination of total deficiencies in each of five PI firms' homes
indicated some differences between PI firms, but the differences we
observed generally existed prior to acquisition and persisted after
acquisition. For example, in comparison to other homes acquired by PI
firms, total deficiencies were lower in both 2003 and 2009 in homes of
one firm and were greater in both years in homes of a second firm.
Compared to Nonprofit Homes, PI Homes Were More Likely to Have Had a
Serious Deficiency Before but Not After Acquisition:
In 2009, PI homes did not differ significantly from nonprofit homes in
the likelihood of a serious deficiency when we controlled for other
explanatory factors, even though PI homes were more likely than
nonprofit homes to have had a serious deficiency in 2003.[Footnote 48]
(See figure 2.) The likelihood of a serious deficiency in other for-
profit homes was not significantly different from PI homes in either
year. The likelihood of a serious deficiency decreased from 2003 to
2009 in PI homes, and this change was not significantly different from
the change in other for-profit and nonprofit homes. In addition, the
likelihood that a PI home would have had a serious deficiency in 2009
did not differ significantly as a function of whether the same firm
owned both the operations and real estate or not, although in 2003,
the likelihood was significantly lower in homes for which the same PI
firm acquired both operations and real estate.
Figure 2: Serious Deficiencies in PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2009:
[Refer to PDF for image: vertical bar graph]
PI-acquired:
Proportion of homes with a serious deficiency, 2003: 0.29;
Proportion of homes with a serious deficiency, 2009: 0.24.
Other for-profit:
Proportion of homes with a serious deficiency, 2003: 0.27;
Proportion of homes with a serious deficiency, 2009: 0.25.
Nonprofit:
Proportion of homes with a serious deficiency, 2003: 0.21;
Proportion of homes with a serious deficiency, 2009: 0.20.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data and
show the proportion of PI, other for-profit, and nonprofit homes with
any serious deficiencies. However, we found that the following key
differences in the likelihood of a serious deficiency were significant
(except where noted) after adjusting for control variables.
The likelihood of a serious deficiency:
* Decreased from 2003 to 2009 in PI homes, and this change did not
differ significantly from the change in other for-profit or nonprofit
homes.
* Was higher in PI homes than in nonprofit homes in 2003.
* Did not differ significantly in PI and nonprofit homes in 2009.
[End of figure]
Our examination of serious deficiencies in each of five PI firms'
homes indicated some differences between PI firms, but these
differences existed prior to acquisition and persisted after
acquisition. In comparison to other homes acquired by PI firms, the
likelihood was lower in both 2003 and 2009 in homes of one firm and
was greater in both years in homes of a second firm.
Reported Total Nurse Staffing Ratios Were Lower in PI Homes, but
Reported RN Ratios Increased More in PI Homes than Other Homes:
On average, total reported nurse staffing ratios (hours per resident
per day) were lower for PI homes than for other types of homes in both
2003 and 2009, but PI homes' reported RN ratios--the most skilled
component of total nurse staffing--increased more from 2003 to 2009.
On average, reported ratios for LPNs--the other type of licensed
nurse--also increased from 2003 to 2009 in PI homes; this change was
not significantly different from the change from 2003 to 2009 in other
for-profit and nonprofit homes. In contrast, reported CNA ratios for
PI homes did not change significantly from 2003 to 2009, but increased
for other types of homes.
Average Reported Total Nurse Staffing Ratios Were Lower for PI Homes
than Other Homes in Both 2003 and 2009:
In both 2003 and 2009, PI homes reported lower average total nurse
staffing ratios than other types of homes. (See figure 3.) Average
reported total nurse staffing ratios for PI homes increased from 2003
to 2009; this change was not significantly different from either other
for-profit or nonprofit homes.[Footnote 49] The unadjusted average
total nurse staffing ratios reported in 2009 for each ownership type
exceeded the ratio identified as "preferred" by CMS in its 2000
report, but fell short of the level CMS identified as "optimal."
[Footnote 50]
Figure 3: Total Reported Nurse Staffing Ratios for PI, Other For-
Profit, and Nonprofit Homes, 2003 and 2009:
[Refer to PDF for image: stacked vertical bar graph]
PI-acquired:
Average reported total nurse staffing ratio, 2003:
CNA: 2.1 hours;
LPN: 0.7 hours;
RN: 0.3 hours;
Average reported total nurse staffing ratio, 2009:
CNA: 2.1 hours;
LPN: 0.8 hours;
RN: 0.4 hours.
Other for-profit:
Average reported total nurse staffing ratio, 2003:
CNA: 2.2 hours;
LPN: 0.7 hours;
RN: 0.3 hours;
Average reported total nurse staffing ratio, 2009:
CNA: 2.4 hours;
LPN: 0.8 hours;
RN: 0.3 hours.
Nonprofit:
Average reported total nurse staffing ratio, 2003:
CNA: 2.4 hours;
LPN: 0.7 hours;
RN: 0.4 hours;
Average reported total nurse staffing ratio, 2009:
CNA: 2.6 hours;
LPN: 0.8 hours;
RN: 0.4 hours.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant (except where noted)
after adjusting for control variables. The average reported total
nurse staffing ratio:
* Was lower for PI homes than other for-profit and nonprofit homes in
both 2003 and 2009.
* Increased from 2003 to 2009 in PI homes, and this change did not
differ significantly from the change in other for-profit or nonprofit
homes.
[End of figure]
Our examination of reported average total nurse staffing ratios for
each of five PI firms indicated some differences between firms. We
found that the change in these ratios from 2003 to 2009 in one PI
firm's homes was not as great as the increase for other PI-acquired
homes; in 2009, total nurse staffing ratios for that firm's homes were
lower than for other PI-acquired homes. Representatives of the nursing
home operator for homes of this PI firm told us that they had focused
on and reduced staff turnover since 2003.
Staffing Mix Changed, with Average Reported RN Ratios Increasing More
for PI Homes than Other Homes but CNA Ratios Increasing More for Other
Homes than PI Homes:
The staffing mix in PI homes--the balance of RNs, LPNs, and CNAs--
changed from 2003 to 2009, and the changes in staffing were different
in PI homes than in other types of homes. Average reported ratios for
RNs (one type of licensed nursing staff) increased more from 2003 to
2009 in PI homes than other types of homes. Average ratios for LPNs
(the other type of licensed nursing staff) also increased in PI homes
from 2003 to 2009, but the change in PI homes did not differ
significantly from the change in other for-profit and nonprofit homes.
In contrast, average reported ratios for CNAs (who are not licensed)
did not change significantly from 2003 to 2009 for PI homes, but
increased for both other types of homes.
RN ratios. In 2009, average reported RN ratios for PI homes were
greater than other for-profit homes and were also greater than
nonprofit homes, when we controlled for other explanatory factors.
[Footnote 51] (See figure 4.) Average reported RN ratios for PI homes
increased from 2003 to 2009, and this increase was greater than the
change for both other types of homes. In 2003, average reported RN
ratios for PI homes did not differ significantly from other for-profit
homes when we controlled for other explanatory factors and were lower
than for nonprofit homes. These ratios were greater for nonprofit
homes than for other for-profit homes in both 2003 and 2009. The
unadjusted average RN ratios reported in 2009 for each ownership type--
PI, other for-profit, and nonprofit homes--fell short of the ratios
identified as "preferred" by CMS in its 2000 report.[Footnote 52]
Figure 4: RN Ratios Reported for PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2009:
[Refer to PDF for image: vertical bar graph]
PI-acquired:
Average reported RN ratio, 2003: 0.30 hours;
Average reported RN ratio, 2009: 0.40 hours.
Other for-profit:
Average reported RN ratio, 2003: 0.27 hours;
Average reported RN ratio, 2009: 0.30 hours.
Nonprofit:
Average reported RN ratio, 2003: 0.36 hours;
Average reported RN ratio, 2009: 0.39 hours.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant (except where noted)
after adjusting for control variables. The average reported RN ratio:
* Was higher for PI homes than other for-profit and nonprofit homes in
2009.
* Increased from 2003 to 2009 in PI homes, and increased more in PI
homes than other for-profit and nonprofit homes.
* Did not differ significantly for PI and other for-profit homes in
2003.
* Was lower for PI homes than nonprofit homes in 2003.
[End of figure]
In 2009, average reported RN ratios were higher if the same PI firm
acquired both operations and real estate than if not. The increase in
these ratios from 2003 to 2009 for PI homes was greater if the same PI
firm acquired both operations and real estate than if not. (See figure
5.) In 2003, average reported RN ratios did not differ significantly
as a function of whether the same PI firm acquired both operations and
real estate or not when we controlled for other explanatory factors.
Figure 5: RN Ratios for Homes for which the Same PI Firm Acquired Both
the Operations and the Real Estate Compared to Homes for which the
Same PI Firm Did Not Acquire Both, 2003 and 2009:
[Refer to PDF for image: vertical bar graph]
The same firm acquired both operations and real estate:
Average reported RN ratio, 2003: 0.33 hours;
Average reported RN ratio, 2009: 0.45 hours.
The same firm did not acquire both operations and real estate:
Average reported RN ratio, 2003: 0.25 hours;
Average reported RN ratio, 2009: 0.31 hours.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant (except where noted)
after adjusting for control variables. The average reported RN ratio:
* Was higher in 2009 if the same PI firm acquired both operations and
real estate than if not.
* Increased more from 2003 to 2009 if the same PI firm acquired both
operations and real estate than if not.
* Was not significantly different in 2003 as a function of whether the
same PI firm acquired both operations and real estate.
[End of figure]
Our examination of RN ratios for five PI firms' homes indicated some
differences between firms. We found that the increase from 2003 to
2009 was greater for homes of two firms than for other homes acquired
by PI. Representatives of the owners and operators of these homes told
us that these homes generally had high levels of RN staff before
acquisition either because they served a large proportion of short-
term residents with high acuity or rehabilitation needs in one case,
or because they treated residents in specialized care units (such as
ventilator units). Representatives of each firm also said that
increasing RN staff was part of an ongoing strategy to expand their
capacity to care for such residents. For homes of the third PI firm,
the change from 2003 to 2009 in RN ratios was not as great as the
increase for other PI homes. This firm's representatives told us that
training can be more important than the number of staff and so they
have focused their efforts on training and reducing staff turnover.
The change in average reported RN ratios from 2003 to 2009 for two
sets of homes for which different PI firms acquired the operations and
real estate was less than the increase for other PI homes. The
operator of one of these sets of homes told us that they had focused
on promoting stable nursing leadership.
LPN ratios. Average reported LPN ratios were lower for PI homes than
other homes in both 2003 and 2009 when we controlled for other
explanatory factors.[Footnote 53] For PI homes, these ratios increased
from 2003 to 2009; this increase was not significantly different than
the change for either other type of homes. Among PI homes, LPN ratios
did not differ significantly as a function of whether the same firm
acquired the operations and real estate or not.
CNA ratios. Average reported CNA ratios were lower for PI homes than
other homes in both 2003 and 2009. (See figure 6.) Average reported
CNA ratios for PI homes did not change significantly from 2003 to
2009, but increased for both other types of homes. Among PI homes, CNA
ratios did not differ significantly as a function of whether the same
firm acquired the operations and real estate or not when we controlled
for other explanatory factors.[Footnote 54]
Figure 6: CNA Ratios Reported for PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2009:
[Refer to PDF for image: vertical bar graph]
PI-acquired:
Average reported CNA ratio, 2003: 2.10 hours;
Average reported CNA ratio, 2009: 2.14 hours.
Other for-profit:
Average reported CNA ratio, 2003: 2.25 hours;
Average reported CNA ratio, 2009: 2.37 hours.
Nonprofit:
Average reported CNA ratio, 2003: 2.45 hours;
Average reported CNA ratio, 2009: 2.57 hours.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant (except where noted)
after adjusting for control variables. The average reported CNA ratio:
* Was lower for PI homes than other for-profit and nonprofit homes in
both 2003 and 2009.
* Did not change significantly from 2003 to 2009 in PI homes, but
increased in other for-profit and nonprofit homes.
[End of figure]
Our examination of the CNA ratios for five PI firms' homes indicated
some differences between firms. In comparison to other homes acquired
by PI firms, we found that for one set of homes where different PI
firms acquired the operations and real estate these ratios were lower
in 2009, but did not differ significantly in 2003. For another set of
homes where different PI firms acquired the operations and real
estate, these ratios were higher in 2009, but did not differ
significantly in 2003. Representatives of the operator for the nursing
homes with lower CNA ratios in 2009 told us that they had acquired
labor-saving technology and focused on reducing turnover. They
reported that turnover of nursing staff that provide direct care to
residents in their homes had been 90 percent in 2003, but was 59
percent in 2009.
PI Homes' Financial Performance Showed Cost Increases and Higher
Facility Margins Compared to Other Homes:
The financial performance of PI homes showed both cost increases and
higher margins when compared to other for-profit or nonprofit homes.
Specifically, facility costs per resident day for PI homes increased
more, on average, from before acquisition (2003) to after acquisition
(2008) than other for-profit and nonprofit homes. Among PI-acquired
homes, we observed less of an increase if the same PI firm owned the
operations and real estate than if not. The results were similar when
we examined capital-related costs, a component of facility costs.
Despite increased costs, PI homes also showed increased facility
margins but the increase was not significantly different from the
change in other for-profit homes. In contrast to PI and other for-
profit homes, the margins of nonprofit homes decreased.
Facility Costs, Including Capital-Related Costs, Increased for PI
Homes and This Increase Was Greater than for Other Homes:
Both facility costs per resident day and a component of those costs--
capital related costs per resident day--increased in PI homes from
2003 to 2008 and this increase was greater than for other for-profit
and nonprofit homes.
Facility costs. In both 2003 and 2008, PI homes reported lower
facility costs per resident day, on average, than nonprofit homes even
though these costs increased more in PI homes from 2003 to 2008 than
in both nonprofit homes and other for-profit homes. (See figure 7.)
Facility costs include all costs associated with maintaining and
operating a nursing home, such as staff salaries, administrative
costs, and capital-related costs. While PI homes did not differ
significantly from other for-profit homes in 2003 when we controlled
for other explanatory factors, they reported higher costs in 2008.
[Footnote 55]
Figure 7: Facility Costs per Resident Day for PI, Other For-Profit,
and Nonprofit Homes, 2003 and 2008:
[Refer to PDF for image: vertical bar graph]
PI-acquired:
Average facility costs per resident day, 2003: $189;
Average facility costs per resident day, 2008: $220.
Other for-profit:
Average facility costs per resident day, 2003: $182;
Average facility costs per resident day, 2008: $203.
Nonprofit:
Average facility costs per resident day, 2003: $209;
Average facility costs per resident day, 2008: $232.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant (except where noted)
after adjusting for control variables. The average facility costs per
resident day:
* Were lower for PI homes than nonprofit homes in both 2003 and 2008.
* Increased from 2003 to 2008 in PI homes, and increased more in PI
homes than in other for-profit and nonprofit homes.
* Were not significantly different than other for-profit homes in 2003.
* Were higher for PI homes than other for-profit homes in 2008.
[End of figure]
The increase in facility costs per resident day from 2003 to 2008 was
less, on average, if the same PI firm acquired both the operations and
real estate than if it did not. (See figure 8.) While the latter group
of homes reported lower costs in 2003, these two groups reported costs
in 2008 that did not differ significantly after we controlled for
other explanatory factors.
Figure 8: Facility Costs per Resident Day for Homes for which the Same
PI Firm Acquired Both the Operations and the Real Estate Compared to
Homes for which the Same PI Firm Did Not Acquire Both, 2003 and 2008:
[Refer to PDF for image: vertical bar graph]
The same firm acquired both operations and real estate:
Average facility costs per resident day, 2003: $194;
Average facility costs per resident day, 2008: $223.
The same firm did not acquire both operations and real estate:
Average facility costs per resident day, 2003: $181;
Average facility costs per resident day, 2008: $216.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant (except where noted)
after adjusting for control variables. The average facility costs per
resident day:
* Increased less from 2003 to 2008 if the same PI firm acquired both
operations and real estate than if not.
* Were higher in 2003 if the same PI firm acquired both operations and
real estate than if not.
* Were not significantly different in 2008 as a function of whether
the same PI firm acquired both operations and real estate.
[End of figure]
Our examination of facility costs for each of five PI firms indicated
some differences among firms. In comparison to other homes acquired by
PI, the increase in facility costs from 2003 to 2008 was greater in
one set of homes where different PI firms owned the operations and
real estate but the change was not as great in another PI firm's homes.
Capital-related costs. Average capital-related costs per resident day
in PI homes increased from 2003 to 2008 and this change was greater
for PI homes than for other types of homes. (See figure 9.) Capital-
related costs are a component of total facility costs that capture
mortgage payments, rents, depreciation, taxes and insurance, as well
as land and building improvements, including upgrades to equipment.
[Footnote 56] Although capital-related costs were lower in PI homes
than in other for-profit and nonprofit homes in 2003 when we
controlled for other explanatory factors, they were higher than both
other types of homes in 2008.[Footnote 57]
Figure 9: Capital-Related Costs per Resident Day for PI, Other For-
Profit, and Nonprofit Homes, 2003 and 2008:
[Refer to PDF for image: vertical bar graph]
PI-acquired:
Average capital-related costs per resident day, 2003: $14;
Average capital-related costs per resident day, 2008: $18.
Other for-profit:
Average capital-related costs per resident day, 2003: $15;
Average capital-related costs per resident day, 2008: $16.
Nonprofit:
Average capital-related costs per resident day, 2003: $15;
Average capital-related costs per resident day, 2008: $14.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant after adjusting for
control variables. The average capital-related costs per resident day:
* Were lower for PI homes than other for-profit and nonprofit homes in
2003.
* Were higher for PI homes than other for-profit and nonprofit homes
in 2008.
* Increased from 2003 to 2008 in PI homes, and increased more in PI
homes than in other for-profit and nonprofit homes.
[End of figure]
The average increase in capital-related costs from 2003 to 2008 was
less if the same PI firm acquired both operations and real estate than
if not. (See figure 10.) Additionally, capital-related costs were
lower in both years if the same PI firm acquired both the operations
and real estate than if not, when we controlled for other explanatory
factors.
Figure 10: Capital-Related Costs per Resident Day for Homes for which
the Same PI Firm Acquired Both the Operations and the Real Estate
Compared to Homes for which the Same PI Firm Did Not Acquire Both,
2003 and 2008:
[Refer to PDF for image: vertical bar graph]
The same firm acquired both operations and real estate:
Average capital-related costs per resident day, 2003: $14;
Average capital-related costs per resident day, 2008: $18.
The same firm did not acquire both operations and real estate:
Average capital-related costs per resident day, 2003: $14;
Average capital-related costs per resident day, 2008: $19.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant after adjusting for
control variables. The average capital-related costs per resident day:
* Increased less from 2003 to 2008 if the same PI firm acquired both
operations and real estate than if not.
* Were lower in 2003 and 2008 if the same PI firm acquired both
operations and real estate than if not.
[End of figure]
Our examination of capital-related costs for each of five PI firms'
homes indicated some differences between firms. Two PI firms' homes
showed increases that were greater than other homes acquired by PI
firms: (1) one of these sets of homes, for which different PI firms
acquired the operations and real estate, reported lower capital-
related costs in 2003 than other PI homes, but higher costs in 2008
and (2) the other firm's homes reported higher capital-related costs
than other PI homes in both 2003 and 2008. A representative of the
latter PI firm told us that they had secured a $100 million line of
credit for the modernization of the firm's nursing homes. Investment
in the homes had been ongoing prior to acquisition, this
representative said, but the homes' access to capital had increased
after acquisition. In contrast, the change in capital-related costs
for the remaining three firms' homes was not as great as the increase
in other PI homes. Two of these three firms' homes reported lower
capital-related costs in both 2003 and 2008. Representatives from a
nursing home chain owned by one of these firms commented that the
majority of investments were in staffing. They noted that, in
contrast, their peers had invested in their own facilities to attract
the highest paying residents. Representatives from another firm that
owned nursing home real estate, but not operations commented that,
depending on the resident population served and the location of the
home, renovations aimed at attracting more acute (and higher paying)
residents may not pay off. For example, homes in a rural area might
not be able to attract the appropriate staff and mix of residents to
make renovations aimed at treating more acute-care residents worth the
costs. However, they told us that these older, rural homes still
effectively serve a segment of the market despite the lower level of
capital investment.
Facility Margins for PI Homes Increased and Were Higher on Average
than for Other Homes:
Facility margins for PI homes were, on average, higher in 2003 and
2008 than for other for-profit and nonprofit homes.[Footnote 58] (See
figure 11.) Facility margins in PI homes increased from 2003 to 2008;
this increase was not significantly different from the average change
for other for-profit homes, but was greater than the change in margins
for nonprofit homes. In fact, facility margins for nonprofit homes
decreased from 2003 to 2008. The increase in facility margins among PI
homes from 2003 to 2008 was not significantly different, on average,
if the same PI firm acquired both the homes' operations and the real
estate than if it did not. However, facility margins for the former
were, on average, higher both in 2003 and 2008.[Footnote 59]
Figure 11: Facility Margins for PI, Other For-Profit, and Nonprofit
Homes, 2003 and 2008:
[Refer to PDF for image: vertical bar graph]
PI-acquired:
Average facility margins, 2003: 4.5%;
Average facility margins, 2008: 6.3%.
Other for-profit:
Average facility margins, 2003: 0.5%;
Average facility margins, 2008: 2.1%.
Nonprofit:
Average facility margins, 2003: 0.06%;
Average facility margins, 2008: -1.1%.
Source: GAO analysis of OSCAR data.
The numbers presented in this figure are based on unadjusted data, but
the following key differences were significant (except where noted)
after adjusting for control variables. The average facility margins:
* Were higher for PI homes than other for-profit and nonprofit homes
in both 2003 and 2008.
* Increased from 2003 to 2008 in PI homes, and this change did not
differ significantly from the change in other for-profit homes.
* Decreased from 2003 to 2008 in nonprofit homes.
[End of figure]
Our examination of facility margins for each of five PI firms' homes
indicated some differences between firms. We found that two firms'
homes showed an increase in facility margins that was greater than
other homes acquired by PI we studied. Representatives of one of these
firms told us that increased margins were the result of increased
spending in the homes with a focus on investments in technology,
staffing, and treating higher acuity residents. They told us that the
strategy of the nursing home chain they acquired had not changed and
that both increased spending and margins were present before the
acquisition. Two firm's homes showed a change in facility margins that
was less than other PI homes. Representatives for the nursing home
chain operating one of these two sets of homes commented that they had
not been focused on the margins; the chain's chief executive officer
noted that he was evaluated by its PI owner based on the quality of
care provided, not margins.
Concluding Observations:
The acquisition of nursing homes by private investment firms has
raised questions about the potential effects on the quality of care.
Our analyses did not find an increase in the likelihood of serious
deficiencies or a decrease in average reported total nurse staffing
for the PI-acquired homes we studied. In fact, reported RN staffing
increased more in PI-acquired homes than other homes. However, the
performance of these PI homes was mixed with respect to the other
quality variables we examined. For example, PI-acquired homes had more
total deficiencies and lower total nurse staffing ratios than
nonprofit homes, both before and after acquisition. Also, despite
concerns that PI firms might cut costs to improve profitability, we
found that reported facility costs increased in the PI-acquired homes
we studied. Margins also increased in the PI-acquired homes we studied
from before to after acquisition, while they decreased in nonprofit
homes. It is possible to increase both costs and margins because
certain expenditures may prevent subsequent, costly care, or increase
a home's attractiveness to better paying residents. PI-acquired homes
were more similar to for-profit than to nonprofit homes with respect
to the change in margins and total deficiencies, but were like neither
for-profit nor nonprofit homes with respect to the change in staffing
mix and capital-related costs. In addition, compared to homes for
which the same PI firm acquired both operations and real estate, PI-
acquired homes for which ownership was split had lower reported RN
ratios, higher reported capital-related costs, and lower reported
facility margins in the period after acquisition.
Our findings were consistent with the fact that PI firms we studied
are to varying degrees attempting to increase the attractiveness of
their homes to higher paying residents, including those whose care is
reimbursed by Medicare. The homes acquired by the PI firms we studied
had a higher average proportion of Medicare residents both before and
after acquisition. Our analyses and interviews with PI firm officials
revealed differences in their management approaches. For example:
* Officials at two PI firms noted that they were continuing the
existing strategy of the homes they acquired by expanding the capacity
to care for residents with high acuity or specialized needs.
Consistent with their strategies, both firms' homes reported a greater
increase in RN staffing from 2003 to 2009 than other PI-acquired
homes. One of these firms indicated that facility modernization, which
was associated with its strategy, had continued since acquisition and
in fact access to capital for such improvements had increased after
acquisition. Both firms' homes showed an increase in facility margins
that was greater than the other PI homes we studied.
* Officials at a third PI firm stated that training can be more
important than the number of staff and so focused on training and
reducing staff turnover. They also stated that they did not focus on
facility improvements to the same degree as other PI firms. The
increase in facility margins for this firm's homes was less than for
other PI firms. We also found that the likelihood of a serious
deficiency for this firm's homes was lower than for other PI firms'
homes in both 2003 and 2009.
Agency Comments and Our Evaluation:
We provided a draft of this report to the Department of Health and
Human Services (HHS) for comment and also invited the PI firms from
which we obtained information for this report to review the draft.
[Footnote 60] In its written comments, HHS provided CMS's observations
on our methodology. HHS's comments are reproduced in appendix II. CMS
suggested an alternative to our "before and after" acquisition
methodology to take into account the fact that PI firms acquired
nursing homes at different points in time during 2004 through 2007. In
addition, CMS identified a number of alternative analyses that it
believed could help to explore the relationship between PI ownership
and quality. CMS also acknowledged that the report is an important
step toward better understanding the effect of nursing home ownership
on the quality of care provided to residents. In general,
representatives of the PI firms commented that the report handled a
complex topic well and that its conclusions were fair and balanced.
Several also commented that our acknowledgment of limitations to our
analyses was important.
CMS:
The alternative methodology presented in CMS's comments would tailor a
pre and post analysis to the year prior to each PI firm's acquisition
of a nursing home chain and to a time point after the acquisition. One
of the studies we cited used such a methodology.[Footnote 61] We chose
to use a different methodology and believe that the use of different
methodologies enhances the understanding of an issue. Our methodology
used 2003 (pre) and 2008/2009 (post) for nursing homes acquired by PI
firms from 2004 to 2007, irrespective of the specific year in which
the acquisition occurred.[Footnote 62] We selected the 2004 through
2007 timeframe because it was the period of heaviest PI acquisition of
nursing home chains. Finally, CMS said that the exclusion of homes
acquired from 2004 through 2007 but sold by PI firms by 2009 could
have biased our results. However, only 6 homes were excluded because
they were sold and another 55 were excluded because we could not
verify they were still owned by the acquiring PI firm in 2009. These
exclusions represented less than 5 percent of the PI homes we studied.
We believe these exclusions were appropriate and that it is unlikely
that such a small share of homes would have notably affected our
findings.
CMS also suggested a number of alternative approaches for exploring
the relationship between private investment and quality of care, such
as (1) using measures derived from its Five-Star Quality Rating
System, (2) examining the citation of serious deficiencies on
successive surveys, and (3) studying the association between aggregate
staffing payroll and quality of care. We agree that there are other
approaches that can be used to study the relationship between
ownership and nursing home quality of care. We chose well-defined
measures of deficiencies and nurse staffing that we and others have
used to study nursing home quality.
In a few instances, CMS's comments did not accurately describe our
findings. For example, CMS stated that the increase in capital-related
costs at PI-acquired homes from 2003 to 2008 was related largely to
improving the attractiveness of facilities--facility modernization--to
higher paying residents. However, we concluded that the increase in RN
staffing from 2003 to 2009 was a key aspect of PI firms' strategies to
attract higher acuity, higher paying residents. In addition, CMS
states that our study shows that CNA and total nurse staffing ratios
decreased in PI homes. Rather, we report that average reported CNA
ratios for PI homes did not change significantly from 2003 to 2009 and
that average reported total nurse staffing ratios for PI homes
increased from 2003 to 2009. Finally, we did not find that average
total staffing ratios for any PI firms' homes decreased or were
unchanged from 2003 to 2009. Instead, we reported that average total
staffing increased in PI homes, although the increase in one firm's
homes was not as great as in other PI homes.
PI Firms:
Representatives of most of the PI firms who provided oral comments
generally told us that the report handled a complex topic well and
they appreciated our statement of limitations of our methodology.
However, several were concerned that the presentation of the report
over-emphasized results that reflected poorly on PI firms.
Representatives of two firms specifically mentioned that the report
presented negative findings first, saving the more positive results
for later and suggested that not everyone would read far enough to
learn about the positive findings relative to the PI firms we studied
or to read GAO's conclusions. For example, we discuss total
deficiencies and staffing before turning our attention to subsets of
these measures--serious deficiencies and RN staffing. In serious
deficiencies, PI firms' homes were comparable to nonprofit homes and
in RN staffing they compared favorably to nonprofit homes. However, we
believe we present the findings fairly and in a logical order.
In addition, representatives of several PI firms provided specific
comments on our findings about deficiencies and staffing. Regarding
deficiencies cited on standard surveys and complaint investigations,
one PI firm representative stated that the survey process resulted in
more scrutiny of for-profit homes than nonprofit nursing homes. We
consider cited deficiencies, particularly serious deficiencies,
important measures of quality of nursing home care and our research
has found that they represent real lapses in the care provided.
Regarding our analysis of staffing ratios, the representatives of one
firm stated that our analysis did not take into account staff
efficiency. These representatives said that they had invested in labor
saving technology. While staff efficiency may offset the need for more
staff, in our analyses we could not measure or control for differences
in staff efficiency using our datasets. The representatives of a
different firm commented that we did not address changes in therapy
staffing, noting that therapy staff had increased in its homes and
that this increase offset some of the need for CNA staff. In our
analysis of staffing, we chose to focus on nurse staffing because
other research has associated it with quality of care.
In general, representatives of the PI firms said that our findings on
facility costs and margins were consistent with their own analyses.
However, representatives of one firm explained that what we called
"costs" they considered "investments." They said that money spent to
train staff, modernize facilities, and adopt electronic medical
records reduced errors, prevented subsequent costs, and also improved
care. On Medicare cost reports, such expenditures are generally known
as costs. A different PI firm commented that our finding that capital-
related costs were higher when ownership was split was logical because
rents for an operator are generally higher than mortgage payments and
may result in lower margins and discourage investments in RN staffing.
A few PI firms also stated that the Medicare cost reports were not
necessarily accurate with respect to capital-related costs. We
acknowledged that the data in the Medicare cost reports are self-
reported and have limitations, but all nursing homes are subject to
the same reporting requirements and limitations and thus these data
are comparable across the groups we analyzed.
We incorporated technical comments provided by CMS and the
representatives of PI firms as appropriate.
As agreed with your offices, unless you publicly announce the contents
of this report earlier, we plan no further distribution until 30 days
from the report date. At that time, we will send copies to the
Secretary of Health and Human Services, the Administrator of the
Centers for Medicare & Medicaid Services, and other interested
parties. In addition, the report will be available at no charge on the
GAO Web site at [hyperlink, http://www.gao.gov].
If you or your staff have any questions about this report, please
contact me at (202) 512-7114 or at dickenj@gao.gov. Contact points for
our Offices of Congressional Relations and Public Affairs may be found
on the last page of this report. GAO staff who made key contributions
to this report are listed in appendix III.
Signed by:
John E. Dicken:
Director, Health Care:
[End of section]
Appendix I: Scope and Methodology:
To determine whether nursing homes that are owned by private
investment (PI) firms differ from other nursing homes in deficiencies
cited on state surveys, nurse staffing levels, or financial
performance, we (1) identified nursing homes for which PI firms had
acquired the operations or the real estate or both from 2004 through
2007 and (2) compared data from before and after acquisition of these
homes to data from other nursing homes, including other for-profit
homes and nonprofit homes. In addition, we reviewed published research
on the quality and costs of nursing home care, our prior work on
nursing homes, and other relevant documentation. We interviewed
officials from the Centers for Medicare & Medicaid Services (CMS);
representatives of PI firms that acquired nursing home operations,
real estate, or both; representatives of companies that operate PI-
owned nursing homes; and experts on nursing home quality and costs.
This appendix provides information about (1) our data sources and the
development of our analytic datasets, (2) our analytic approach, and
(3) data reliability and limitations.
Data Sources and Development of Analytic Datasets:
Based on our earlier work identifying the top 10 PI acquirers of
nursing homes, we developed a list of homes acquired by PI firms from
2004 through 2007.[Footnote 63] We chose 2004 through 2007 as our
target acquisition interval because these were the years during which
PI firms acquired the greatest number of nursing homes.[Footnote 64]
We obtained data for our outcome variables from CMS. We used CMS's
Online Survey, Certification, and Reporting system (OSCAR) as our
source of data regarding deficiencies, nurse staffing, and
characteristics of all the nursing homes we analyzed, including PI,
other for-profit, and nonprofit homes. OSCAR is the only national,
uniform data source that contains this information. We used Medicare
Skilled Nursing Facility (SNF) Cost Reports as our source of data
regarding the financial performance of nursing homes. These reports
are the only publicly available source of financial data on most
Medicare providers and are a primary source of data used by CMS and
others to examine nursing homes' financial performance.
Identification of Homes with Different Types of Ownership:
We identified nursing homes with three types of ownership: PI-owned,
other for-profit, and nonprofit.
PI-owned nursing homes. We developed a list of nursing homes owned by
the top 10 PI acquirers of nursing homes identified in our September
2010 report using information that these firms provided and other
sources, such as nursing home chain Web sites.[Footnote 65] These 10
PI firms accounted for almost 90 percent of the nursing homes that
were acquired by PI firms from 1998 through 2008. We included homes
for which a PI firm acquired operations, real estate, or both, and
were still owned by the acquiring PI firm in 2009.[Footnote 66] To
compare data from before and after acquisition, we excluded homes
acquired before 2004 or after 2007. We also reviewed information from
the PI firms and other sources to determine whether the same PI firm
acquired both the operations and real estate of these homes. When we
could not determine whether the same PI firm owned both the operations
and the real estate for a particular home--for example, when we knew
that a PI firm owned the real estate for most, but not all, of the
homes for which it owned operations, but we did not know which
specific homes those were--we assigned it to the group with that
firm's usual ownership pattern.[Footnote 67]
Other for-profit and nonprofit homes. We used OSCAR to identify the
for-profit and nonprofit nursing homes that we compared to PI homes.
To ensure that our comparison groups were appropriate, we excluded
homes that were hospital-based or government-owned in 2009 (because
they differ from other nursing homes in important ways, including
resident needs and financial performance) and homes that were not
certified by Medicare in 2009 (because almost all homes owned by the
PI firms in our review were Medicare-certified).[Footnote 68] We also
excluded homes for which we could not identify data from both before
and after our target acquisition interval.
Identification of Nursing Home Characteristics:
OSCAR also includes data on nursing home characteristics, including
profit status; chain affiliation; facility size as indicated by the
number of beds certified by Medicare, Medicaid, or both; and state.
[Footnote 69] OSCAR also includes information about the number of
residents and their payers, which we used to calculate the percentage
of residents whose care was paid by Medicare, Medicaid, or a source
other than Medicare or Medicaid, and occupancy rate.[Footnote 70]
Identification of Datasets for Our Outcome Measures:
We identified separate datasets for our analyses of deficiencies,
nurse staffing, and financial performance.
Deficiencies. To examine deficiencies, we used OSCAR data. OSCAR
includes data about deficiencies that were cited during standard
surveys of nursing homes (which are to be conducted, on average, every
12 months) and during complaint investigations, along with the dates
of those surveys and investigations, allowing comparison of data from
different points in time. Deficiencies identified during either type
of survey are placed into 1 of 12 categories, identified by letter,
according to the number of residents potentially or actually affected
and the degree of relative harm involved. (See table 1.) Throughout
this report, we refer to deficiencies at the actual harm and immediate
jeopardy levels as serious deficiencies.
Table 1: Scope and Severity of Deficiencies Identified during Nursing
Home Surveys:
Severity: Immediate jeopardy[A];
Scope: Isolated: J;
Scope: Pattern: K;
Scope: Widespread: L.
Severity: Actual harm;
Scope: Isolated: G;
Scope: Pattern: H;
Scope: Widespread: I.
Severity: Potential for more than minimal harm;
Scope: Isolated: D;
Scope: Pattern: E;
Scope: Widespread: F.
Severity: Potential for minimal harm;
Scope: Isolated: A;
Scope: Pattern: B;
Scope: Widespread: C.
Source: CMS.
[A] Actual or potential for death or serious injury.
[End of table]
To examine deficiencies, we sought OSCAR data from a single standard
survey of each home from both 2003 and 2009, but used data from
alternate years in a small proportion of the nursing homes in our
analyses.[Footnote 71] Specifically, if no state standard survey was
available from 2003 or 2009, we substituted data from 1 year later, if
available; otherwise, we used data from 1 year before--with the
constraint that the data for PI-acquired homes had to be from before
the acquisition and at least 1 year after acquisition. For example, if
2009 data were not available for a particular home, we sought 2010
data, if available; otherwise, we used 2008 data with the constraint
that the data must be from 1 year after acquisition for PI-acquired
homes. We also collected OSCAR data on deficiencies cited during
complaint investigations in calendar years 2003 and 2009. To avoid
double counting, we excluded any complaint deficiencies that matched a
deficiency cited in a standard survey that was conducted within 15
days of the complaint investigation. We refer to all data used in our
analyses of deficiencies as having been from 2003 or 2009.
We included data from 12,956 nursing homes in our analyses of
deficiencies, of which 1,270 were PI-owned in 2009 and had been
acquired from 2004 through 2007. Because we used data from 2003 and
2009 for homes acquired anytime from 2004 through 2007, the amount of
time between the surveys that identified any deficiencies and PI
acquisition varied. In most cases, the surveys were within 3 years of
acquisition.
Nurse staffing. We calculated four different staffing ratios, that is,
nursing hours per resident per day: registered nurse (RN) ratios,
licensed practical nurse (LPN) ratios, certified nurse aid (CNA)
ratios, and total nurse staffing ratios (i.e., the total number of
nursing hours, whether by RNs, LPNs, or CNAs, per resident per day).
[Footnote 72] In each case, we included full-time, part-time, and
contract hours, but we excluded hours reported for performing
administrative duties or as Directors of Nursing. When calculating CNA
staffing, we also included two other types of nursing staff--nurse
aides in training and medication aides.
We used the same set of nursing homes included in our analyses of
deficiencies to analyze nurse staffing, but excluded homes from the
staffing analyses if the data related to staffing appeared to
represent data entry or other reporting errors. Specifically, we
excluded facilities that, in either 2003 or 2009, reported:
* more residents than beds,
* more than 10 percent of the home's beds as not certified for
Medicare or Medicaid,[Footnote 73]
* 0 total nursing hours per resident per day,
* 24 or more total nursing hours per resident per day, or:
* staffing and census data that resulted in nurse staffing ratios that
were three or more standard deviations above the mean, indicating that
they were statistical outliers.
We included data from 11,522 nursing homes in our analyses of staffing
ratios, of which 1,176 were PI-owned in 2009 and acquired from 2004
through 2007.
Financial performance. To examine nursing homes' financial
performance, we used Medicare SNF cost reports to compute three
measures:
* Facility costs per resident day, defined as the total facility
costs--including both operating and capital costs--divided by total
resident days.[Footnote 74]
* Capital-related costs per resident day, defined as capital-related
costs allocated to nursing home resident care divided by total
resident days.[Footnote 75]
* Facility margins, defined as the amount of total facility revenues
exceeding total facility costs, divided by total facility revenues.
[Footnote 76]
All Medicare-certified nursing homes--or SNFs--must submit cost
reports on an annual basis to CMS. The cost report contains provider
information--such as facility characteristics, utilization data,
costs, and financial data--generally covering a 12-month period of
operations based on the provider's fiscal year.[Footnote 77] The cost
report contains utilization and cost information on Medicare-covered
services, and also contains information for services provided to all
residents, regardless of payer.
We used cost report data for the provider's fiscal years 2003 and 2008
because fiscal year 2009 Medicare SNF cost reports were not available
at the time we collected our data. For PI-acquired homes, we ensured
that these data were from before and after acquisition.[Footnote 78]
Our analyses of financial data also required information from OSCAR
about facility characteristics such as the percentage of residents
whose care was paid by Medicare or Medicaid and occupancy rate. We
sought OSCAR data from calendar years 2003 and 2008, and if these data
were not available, we substituted data from 1 year after, if
available, otherwise 1 year before.[Footnote 79] We refer to all data
used in our analyses of financial performance as having been from 2003
or 2008.
We created different datasets to examine our three calculated measures
of financial performance. For each measure, we excluded nursing homes
if the cost report covered less than 10 or more than 14 months and
those that did not have Medicare SNF cost reports or OSCAR data from
both time periods.[Footnote 80] We also excluded nursing homes for
which the data appeared to represent data entry or other reporting
anomalies or were statistical outliers.
* Facility costs. Data for our analyses of facility costs were from
9,616 nursing homes, of which 1,089 were PI-owned in 2009 and acquired
from 2004 through 2007. We excluded homes that, in either 2003 or
2008, reported:
- no facility costs or:
- facility costs per resident day that were more than two times the
interquartile range below the 25th or above the 75th percentile.
* Capital costs. Data for our analyses of capital-related costs were
from 9,707 nursing homes, of which 1,088 were PI-owned in 2009 and
acquired from 2004 through 2007. We excluded facilities that, in
either 2003 or 2008, reported:
- no capital-related costs or:
- capital costs per resident day that were more than two times the
interquartile range below the 25th or above the 75th percentile.
* Facility margins. Data for our analyses of facility margins were
from 8,630 nursing homes, of which 955 were PI-owned in 2009 and
acquired from 2004 through 2007. We excluded facilities that, in
either 2003 or 2008, reported:
- no facility revenues or missing margins or:
- facility margins that were in the top or bottom 1 percent of all
homes we studied, regardless of type of ownership.[Footnote 81]
Table 2 lists the variables we included in our datasets, describes our
operational measures of these variables, and identifies the sources of
the data we used to calculate these measures.
Table 2: Variables Included in Our Datasets:
Outcome variables:
Variable: Deficiencies;
Operational measure: Count of total deficiencies; Whether a home was
cited for a serious deficiency or not (serious deficiencies are those
at the G-level or higher, that is, at the actual harm or immediate
jeopardy levels);
Data source: OSCAR.
Variable: Nurse staffing;
Operational measure: RN ratios (i.e., hours per resident per day);
LPN ratios; CNA ratios; Total nurse staffing ratios (including RNs,
LPNs, and CNAs);
Data source: OSCAR.
Variable: Financial performance;
Operational measure: Facility costs per resident day, defined as total
facility costs (including both operating and capital costs) divided by
total resident days, adjusted for inflation; Capital costs per
resident day, a subset of facility costs, defined as capital-related
costs allocated to nursing home resident care divided by total
resident days, adjusted for inflation; Facility margins, defined as
the amount of total facility revenues exceeding total facility costs,
divided by total facility revenues;
Data source: Medicare SNF Cost Reports.
Independent variables:
Variable: PI ownership;
Operational measure: PI ownership of a nursing home's operations, real
estate, or both;
Data source: Information generally provided by PI firms.
Variable: Profit status;
Operational measure: For-profit or nonprofit;
Data source: OSCAR.
Variable: Year;
Operational measure: 2003 and 2009 (for deficiencies and nurse
staffing) or 2008 (for financial performance);
Data source: OSCAR and Medicare SNF Cost Reports.
Control variables:
Variable: Case mix (the average acuity of the residents in a nursing
home);
Operational measure: Nursing case mix index based on (a) assignment of
residents into Medicare payment categories and (b) estimates of the
relative staff time associated with caring for the average resident in
each category;
Data source: Brown University Center for Gerontology and Healthcare
Research: Residential History File[A].
Variable: Chain affiliation;
Operational measure: Individually owned or chain-affiliated, where a
chain is defined as two or more homes under one ownership or operation;
Data source: OSCAR.
Variable: Facility size;
Operational measure: Number of beds certified by Medicare, Medicaid,
or both;
Data source: OSCAR.
Variable: Geographic location;
Operational measure: State (coded as a set of dummy variables);
Data source: OSCAR.
Variable: Market competition;
Operational measure: Herfindahl index based on the number of beds in a
nursing home's county that were certified by Medicare or Medicaid[B];
Data source: CMS's Provider of Services File[C].
Variable: Occupancy rate;
Operational measure: Number of residents divided by number of
certified beds;
Data source: OSCAR.
Variable: Other revenue sources;
Operational measure: Percent of revenue from lines of business other
than the nursing home (e.g., home health or hospice);
Data source: Medicare SNF Cost Reports.
Variable: Payer mix;
Operational measure: Percent of residents in certified beds whose care
was paid by Medicare; Percent of residents in certified beds whose
care was paid by Medicaid; Percent of residents in certified beds
whose care was paid by a source other then Medicare or Medicaid[D];
Data source: OSCAR.
Source: GAO analysis of information from CMS, PI firms, and the Brown
University Center for Gerontology and Healthcare Research.
[A] Shaping Long Term Care in America Project at Brown University
funded in part by the National Institute on Aging (grant number
1P01AG027296).
[B] The Herfindahl index (also known as a Herfindahl-Hirschman index)
is an index of market competition. It is based on market shares, in
this case, the number of beds in the county as of 2003 or 2008 that
had been certified by Medicare or Medicaid. The Herfindhal-Hirschman
Index ranges from 0 to 1, with 0 indicating perfect competition and 1
indicating monopoly. See A. O. Hirschman, National Power and the
Structure of Foreign Trade (Berkeley and Los Angeles: University of
California Press, 1945).
[C] CMS's Provider of Services File includes information about each
Medicare-approved provider.
[D] The percent of residents in certified beds whose care was paid by
Medicaid provided a reference group in our analyses.
[End of table]
Analytic Approach:
We conducted both aggregated data analyses and analyses of data from
specific PI firms' homes. Unless otherwise specified, all results that
we present were statistically significant at the 0.05 level in
analyses of adjusted data.
Aggregate Data Analyses:
We used panel regression models to determine, at the aggregate level,
whether nursing homes that were acquired by PI firms from 2004 through
2007 differed significantly, before and/or after the acquisition, from
other nursing homes in our outcome variables--deficiencies, nurse
staffing levels, or financial performance.[Footnote 82] Using these
models, we compared outcome data from homes with different types of
ownership (PI, other for-profit, and nonprofit) at each of two points
in time (2003 and 2009 for deficiencies and staffing, and 2003 and
2008 for financial performance) and we examined whether there were
differences between years for PI homes and whether any such
differences were similar to any differences between years in the other
for-profit and nonprofit homes. We included data from before PI
acquisition so we could determine whether the postacquisition data
reflected preexisting differences. We included data from other types
of nursing homes so we could determine whether any changes from before
to after acquisition reflected changes that occurred regardless of
type of ownership. We also compared data from PI homes for which the
same firm acquired both operations and real estate to data from PI
homes for which the same firm did not acquire both operations and real
estate.
Our panel regression models statistically controlled for variables
that research has shown can influence nursing home deficiencies,
staffing, and financial performance. These variables were (1) the
percentage of residents for whom the payer was Medicare in 2003 and
2009; (2) the percentage of residents for whom the payer was neither
Medicare nor Medicaid in 2003 and 2009; (3) chain affiliation in 2009;
(4) facility size as indicated by the number of beds certified by
Medicare, Medicaid, or both in 2009; (5) occupancy rate in 2003 and
2009; (6) market competition in 2003 and 2008; and (7) geographic
location (state).[Footnote 83]
We used random effects models rather than fixed effects models to
measure not only the change in outcomes for the same nursing home
groups over time, but also the difference between groups at each point
in time. Moreover, we wanted to accurately reflect the change over
time in our control variables and their effects on our outcome
variables--something that can be accomplished using a random effects
model, but not a fixed effects model.
Illustration. To illustrate our analytic strategy, consider the
example of reported RN ratios. Unadjusted average (or mean) reported
RN ratios are presented in table 3, along with the number of homes in
our analyses.
Table 3: Unadjusted Average Reported RN Ratios (Hours per Resident per
Day):
Type of ownership (number of nursing homes): PI homes (1,176);
2003: 0.298;
2009: 0.397;
Change from 2003 to 2009: 0.100.
Type of ownership (number of nursing homes): Other for-profit homes
(7,677);
2003: 0.275;
2009: 0.307;
Change from 2003 to 2009: 0.032.
Type of ownership (number of nursing homes): Nonprofit homes (2,669);
2003: 0.365;
2009: 0.393;
Change from 2003 to 2009: 0.029.
Source: GAO analysis of OSCAR data.
[End of table]
Our panel models analyze the data to identify the size and statistical
significance of differences between means. Statistical significance is
indicated by the probability (P-value) of coefficients calculated by
the panel regression for the comparisons it tests. The specific
comparisons tested by our panel regressions are based on independent
variables and their interactions. Our panel regression models included
a main effect for year and a main effect for ownership type (PI, other
for-profit, and nonprofit). The models also included an interaction
between year and ownership type, which allowed for the comparison of
data between different types of ownership at each point in time as
well as the difference between years.[Footnote 84] Therefore, the five
terms in the model are year, other for-profit homes, nonprofit homes,
year by other for-profit homes, and year by nonprofit homes. The
interpretation of the model terms are as follows: (1) the main effect
year measures the difference between 2003 and 2009 for PI homes, (2)
the main effect for other for-profit measures the difference between
PI and other for-profits in 2003, (3) the main effect for nonprofit
measures the difference between PI and nonprofits in 2003, (4) the
interaction effect of year by other for-profit measures the difference
between PI and other for-profits in the change from 2003 to 2009, and
(5) the interaction effect year by nonprofit measures the difference
between PI and nonprofits in the change from 2003 to 2009.[Footnote 85]
Table 4 shows the results of our panel regression analysis of reported
RN ratios without including control variables--that is, the
coefficients and associated P-values for tested comparisons. With
unadjusted data, the coefficients calculated by the panel regression
can be calculated directly from the means in table 3. For example, the
coefficient shown in table 4 for the difference between other for-
profit homes and PI homes in 2003 is -0.023, which is the difference
between the relevant means shown in table 3: 0.275 minus 0.298. As
another example, the coefficient shown in table 4 for the change from
2003 to 2009 for PI homes is 0.100, which is the change from 2003 to
2009 for PI homes shown in table 3. Similarly, the coefficient of -
0.068 in table 4 indicates the difference in the change in RN ratio
from 2003 to 2009 between other for-profit and PI homes and is equal
to the difference between the change for other for-profit homes and
the change for PI homes shown in table 3: (0.032 minus 0.100).
Table 4: Results of Analysis of Reported RN Ratios Using a Panel Model
without Adjusting for Control Variables:
Comparison: Difference between other for-profit and PI homes in 2003;
Coefficient: -0.023;
P-value: 0.001.
Comparison: Difference between nonprofit and PI homes in 2003;
Coefficient: -0.067;
P-value: 0.000.
Comparison: For PI homes, change from 2003 to 2009;
Coefficient: 0.100;
P-value: 0.000.
Comparison: Difference between other for-profit and PI homes in the
change from 2003 to 2009;
Coefficient: -0.068;
P-value: 0.000.
Comparison: Difference between nonprofit and PI homes in the change
from 2003 to 2009;
Coefficient: -0.071;
P-value: 0.000.
Source: GAO analysis of OSCAR data.
[End of table]
In contrast, table 5 shows the results of a parallel panel analysis of
the reported RN ratios using the same independent variables described
above, but in this second analysis, we included our control variables.
When the regression model includes control variables, coefficients can
not be calculated directly from means. The change in key results
between table 4 and table 5 reflects the impact of control variables
on RN ratios. For example, when we controlled for these variables, we
found that the average reported RN ratios for PI homes did not differ
significantly from those of other for-profit homes in 2003.
Table 5: Results of Analysis of Reported RN Ratios Using a Panel Model
When Adjusting for Control Variables:
Comparison: Difference between other for-profit and PI homes in 2003;
Coefficient: 0.003;
P-value: 0.651.
Comparison: Difference between nonprofit and PI homes in 2003;
Coefficient: 0.043;
P-value: 0.000.
Comparison: For PI homes, change from 2003 to 2009;
Coefficient: 0.090;
P-value: 0.000.
Comparison: Difference between other for-profit and PI homes in the
change from 2003 to 2009;
Coefficient: -0.069;
P-value: 0.000.
Comparison: Difference between nonprofit and PI homes in the change
from 2003 to 2009;
Coefficient: -0.072;
P-value: 0.000.
Source: GAO analysis of OSCAR data.
Note: Control variables were (1) the percentage of residents for whom
the payer was Medicare in 2003 and 2009; (2) the percentage of
residents for whom the payer was neither Medicare nor Medicaid in 2003
and 2009; (3) chain affiliation in 2009; (4) facility size as
indicated by the number of beds certified by Medicare, Medicaid, or
both in 2009; (5) occupancy rate in 2003 and 2009; (6) market
competition in 2003 and 2008; and (7) geographic location (state).
Coefficients and P-values associated with the control variables are
not presented.
[End of table]
To examine differences between means that were not directly addressed
in our panel regressions, we conducted chi-square tests.[Footnote 86]
For example, after applying our panel regressions, we used chi-square
tests to determine whether there were significant differences between
other for-profit and nonprofit homes.
Deficiencies. To apply a panel model regression to deficiencies, we
first examined the data to select an appropriate statistical model and
ensure that the data were consistent with relevant statistical
assumptions. Our measure of total deficiencies was a count of how many
deficiencies were cited in the nursing home. Count variables can be
modeled by a negative binomial regression. Coefficients from a
negative binomial model represent the expected log-count of an event
and can be transformed into incidence-rate ratios, which represent how
much more or less the expected incidence rate is for one group in
comparison to another. In this report, we refer to these ratios as
total deficiencies.
When we examined the data regarding whether a home was cited for a
serious deficiency or not, we determined that a different panel
regression model was most appropriate. Because a relatively small
proportion of nursing homes were cited for serious deficiencies, and
most homes with any serious deficiency had no more than two, our
measure was whether or not a home had been cited for any serious
deficiencies. For such binary outcomes, a logistic regression model is
appropriate. Logistic regression model coefficients represent log-odds
ratios and can be transformed to odds ratios, which indicate how much
more or less likely the odds are for a binary (yes/no) event to occur
for one group in comparison to another. In this report, we refer to
these ratios as the likelihood of a serious deficiency.
Nurse staffing. After excluding nursing homes with staffing ratios
that appeared to represent data entry or other reporting errors, the
distribution of each staffing ratio approximated a normal
distribution, so we used an Ordinary Least Squares panel regression
model to analyze these data.
Financial performance. After excluding nursing homes with extreme
values, the distributions of facility costs per resident day and
capital-related costs per resident day were highly positively skewed,
that is, they were not distributed normally or symmetrically around
the average. We transformed these variables by taking their natural
logarithms; the resultant distributions were consistent with the
relevant statistical assumptions. We used Ordinary Least Squares panel
regression models to analyze the log-transformed values.
After excluding nursing homes with extreme values, facility margins
approximated a normal distribution, so we used an Ordinary Least
Squares panel regression model to analyze the data. We conducted two
additional regression analyses of facility margins in which we
controlled for case mix (the average acuity of the residents in a
nursing home) and other sources of revenue (such as home health or
hospice care). We do not report these analyses because each variable
was correlated with payer mix and controlling for them did not
increase the amount of variability that was accounted for by our
models.
Results of Aggregate Analyses Adjusting for Control Variables:
Table 6 shows the statistical results of our comparisons of
deficiencies, nurse staffing, and financial performance for the key
groups included in our analyses, controlling for chain affiliation,
payer mix, facility size, occupancy rate, market competition, and
state.
Table 6: Differences in Deficiencies, Nurse Staffing Ratios, and
Financial Performance Identified in Comparisons of Adjusted Data:
Comparison: In 2003, (a) PI-acquired versus (b) other for-profit homes;
Total deficiencies (a - b)[A]: [Empty];
Any serious deficiency (a - b)[B]: [Empty];
Total nurse staffing ratio (a - b): -;
RN ratio (a - b): [Empty];
LPN ratio (a - b): -;
CNA ratio (a - b): -;
Facility costs per resident day (a - b): [Empty];
Capital-related costs per resident day (a - b): -;
Facility margins (a - b): +.
Comparison: In 2003, (a) PI-acquired versus (b) nonprofit homes;
Total deficiencies (a - b)[A]: +;
Any serious deficiency (a - b)[B]: +;
Total nurse staffing ratio (a - b): -;
RN ratio (a - b): -;
LPN ratio (a - b): -;
CNA ratio (a - b): -;
Facility costs per resident day (a - b): -;
Capital-related costs per resident day (a - b): -;
Facility margins (a - b): +.
Comparison: In 2003, (a) other for-profit versus (b) nonprofit homes;
Total deficiencies (a - b)[A]: +;
Any serious deficiency (a - b)[B]: +;
Total nurse staffing ratio (a - b): -;
RN ratio (a - b): -;
LPN ratio (a - b): -;
CNA ratio (a - b): -;
Facility costs per resident day (a - b): -;
Capital-related costs per resident day (a - b): +;
Facility margins (a - b): +.
Comparison: For PI-acquired homes, (a) 2009 or 2008[C] versus (b) 2003;
Total deficiencies (a - b)[A]: +;
Any serious deficiency (a - b)[B]: -;
Total nurse staffing ratio (a - b): +;
RN ratio (a - b): +;
LPN ratio (a - b): +;
CNA ratio (a - b): [Empty];
Facility costs per resident day (a - b): +;
Capital-related costs per resident day (a - b): +;
Facility margins (a - b): +.
Comparison: The difference between 2003 and 2009 or 2008[C] in (a) PI-
acquired versus (b) other for-profit homes;
Total deficiencies (a - b)[A]: [Empty];
Any serious deficiency (a - b)[B]: [Empty];
Total nurse staffing ratio (a - b): [Empty];
RN ratio (a - b): +;
LPN ratio (a - b): [Empty];
CNA ratio (a - b): -;
Facility costs per resident day (a - b): +;
Capital-related costs per resident day (a - b): +;
Facility margins (a - b): [Empty].
Comparison: The difference between 2003 and 2009 or 2008[C] in (a) PI-
acquired versus (b) nonprofit homes;
Total deficiencies (a - b)[A]: [Empty];
Any serious deficiency (a - b)[B]: [Empty];
Total nurse staffing ratio (a - b): [Empty];
RN ratio (a - b): +;
LPN ratio (a - b): [Empty];
CNA ratio (a - b): -;
Facility costs per resident day (a - b): +;
Capital-related costs per resident day (a - b): +;
Facility margins (a - b): +.
Comparison: The difference between 2003 and 2009 or 2008[C] in (a)
other for-profit versus (b) nonprofit homes;
Total deficiencies (a - b)[A]: -;
Any serious deficiency (a - b)[B]: [Empty];
Total nurse staffing ratio (a - b): [Empty];
RN ratio (a - b): [Empty];
LPN ratio (a - b): [Empty];
CNA ratio (a - b): [Empty];
Facility costs per resident day (a - b): [Empty];
Capital-related costs per resident day (a - b): +;
Facility margins (a - b): +.
Comparison: In 2009 or 2008,[C] (a) PI-acquired versus (b) other for-
profit homes;
Total deficiencies (a - b)[A]: [Empty];
Any serious deficiency (a - b)[B]: [Empty];
Total nurse staffing ratio (a - b): -;
RN ratio (a - b): +;
LPN ratio (a - b): -;
CNA ratio (a - b): -;
Facility costs per resident day (a - b): +;
Capital-related costs per resident day (a - b): +;
Facility margins (a - b): +.
Comparison: In 2009 or 2008,[C] (a) PI-acquired versus (b) nonprofit
homes;
Total deficiencies (a - b)[A]: +;
Any serious deficiency (a - b)[B]: [Empty];
Total nurse staffing ratio (a - b): -;
RN ratio (a - b): +;
LPN ratio (a - b): -;
CNA ratio (a - b): -;
Facility costs per resident day (a - b): -;
Capital-related costs per resident day (a - b): +;
Facility margins (a - b): +.
Comparison: In 2009 or 2008,[C] (a) other for-profit versus (b)
nonprofit homes;
Total deficiencies (a - b)[A]: +;
Any serious deficiency (a - b)[B]: +;
Total nurse staffing ratio (a - b): -;
RN ratio (a - b): -;
LPN ratio (a - b): -;
CNA ratio (a - b): -;
Facility costs per resident day (a - b): -;
Capital-related costs per resident day (a - b): +;
Facility margins (a - b): +.
Comparison: In 2003 and among PI-acquired homes, (a) homes for which
the same PI firm acquired both operations and real estate versus (b)
homes for which the same PI firm did not acquire both operations and
real estate;
Total deficiencies (a - b)[A]: [Empty];
Any serious deficiency (a - b)[B]: -;
Total nurse staffing ratio (a - b): [Empty];
RN ratio (a - b): [Empty];
LPN ratio (a - b): [Empty];
CNA ratio (a - b): [Empty];
Facility costs per resident day (a - b): +;
Capital- related costs per resident day (a - b): -;
Facility margins (a - b): +.
Comparison: For homes for which the same PI firm acquired both
operations and real estate, (a) 2009 or 2008[C] versus (b) 2003;
Total deficiencies (a - b)[A]: +;
Any serious deficiency (a - b)[B]: [Empty];
Total nurse staffing ratio (a - b): +;
RN ratio (a - b): +;
LPN ratio (a - b): +;
CNA ratio (a - b): [Empty];
Facility costs per resident day (a - b): +;
Capital-related costs per resident day (a - b): +;
Facility margins (a - b): +.
Comparison: The difference between 2003 and 2009 or 2008[C] in (a)
homes for which the same PI firm acquired both operations and real
estate versus (b) homes for which the same PI firm did not acquire
both operations and real estate;
Total deficiencies (a - b)[A]: [Empty];
Any serious deficiency (a - b)[B]: [Empty];
Total nurse staffing ratio (a - b): [Empty];
RN ratio (a - b): +;
LPN ratio (a - b): [Empty];
CNA ratio (a - b): [Empty];
Facility costs per resident day (a - b): -;
Capital- related costs per resident day (a - b): -;
Facility margins (a - b): [Empty].
Comparison: In 2009 or 2008[C] and among PI-acquired homes, (a) homes
for which the same PI firm acquired both operations and real estate
versus (b) homes for which the same PI firm did not acquire both
operations and real estate;
Total deficiencies (a - b)[A]: [Empty];
Any serious deficiency (a - b)[B]: [Empty];
Total nurse staffing ratio (a - b): [Empty];
RN ratio (a - b): +;
LPN ratio (a - b): [Empty];
CNA ratio (a - b): [Empty];
Facility costs per resident day (a - b): [Empty];
Capital-related costs per resident day (a - b): -;
Facility margins (a - b): +.
Source: GAO analysis of OSCAR and Medicare SNF cost reports.
Notes. Data were adjusted to control for the influence of chain
affiliation, payer mix, facility size, occupancy rate, market
competition, and state so that one can make comparisons holding these
other variables constant.
Cell entries indicate the relationship between two values, labeled (a)
and (b) in first column. There were three possible relationships
between the two values: If (a) was significantly higher than (b), the
cell contains a +; if (a) did not differ significantly from (b), the
cell is empty; and if (a) was significantly lower than (b), the cell
contains a -. Our standard for statistical significance was p < .05.
[A] We analyzed how much more or less the expected incidence rate for
total deficiencies is for one type of home when compared to another.
In this report, we used the term total deficiencies rather than
incidence rates.
[B] We analyzed odds ratios, that is, we analyzed how much more or
less likely the odds are for one or more serious deficiencies to have
been cited for one type of home when compared to another. In this
report, we used the term likelihood of a serious deficiency rather
than odds ratios.
[C] Data regarding deficiencies and nurse staffing were from 2009;
data regarding financial performance were from 2008.
[End of table]
Firm-Level Data Analyses:
In addition, to determine whether there were systematic differences
among nursing homes owned by PI firms in outcomes we studied, we
conducted a series of analyses in which we separately compared each of
five PI firms' homes to all other PI-acquired nursing homes in our
study. We restricted our analyses to those homes for which we could
identify both the PI owner of operations and real estate and those PI
firms for which we determined we had data from a sufficient number of
homes.[Footnote 87]
* For three PI firms' homes, the same PI firm acquired both operations
and real estate.
* For two PI firms that acquired the nursing home operations, a
different PI firm acquired the real estate.
In each of five separate analyses, we compared the homes owned by a PI
firm to all other PI homes in our larger aggregate analysis, including
homes owned by the other firms we studied and any other homes owned by
that PI firm (e.g., those for which we could not identify the real
estate owner). Again, we statistically controlled for other variables
that may influence deficiencies, staffing, and financial performance.
Unless otherwise specified, all results that we present were
statistically significant at the 0.05 level in analyses of adjusted
data. To better understand differences among the nursing homes owned
by these PI firms, we also interviewed representatives of PI firms
that acquired nursing home operations, real estate, or both, and
representatives of companies that operate PI-owned homes and, if their
homes were part of our firm-level analyses, we discussed the results
for their homes.
Data Reliability and Limitations:
There are several important limitations to our findings: The results
of our analyses can not be generalized beyond the PI-acquired nursing
homes in our review. In addition, the differences between PI-acquired
and other nursing homes that we observed cannot necessarily be
attributed to PI ownership because they may have been caused by other
uncontrolled and unquantified variables, such as specific
characteristics of the particular sets of homes or particular PI firms
in our review or the fact that these homes changed ownership, rather
than the effect of PI ownership per se. Moreover, although our data
for homes that were acquired by PI firms came from before and after
the PI firm acquired them, we cannot assume that any difference we
observed between the data from 2003 and the data from 2008 or 2009
were due to acquisition by the PI firm because other things could have
occurred between those years. For example, changes we observed could
have occurred after 2003, but before acquisition by the PI firm.
In addition, each of our measures has limitations:
PI ownership. Our sample of PI-acquired homes did not include all PI-
owned homes. Specifically, to compare data from before and after
acquisition by a PI firm, we excluded PI-owned homes that were
acquired before or after our target acquisition interval. Moreover,
the 10 PI firms in our sample acquired about 94 percent of the nursing
homes that were acquired by PI firms from 2004 through 2007; we could
not identify the other approximately 6 percent of PI-acquired nursing
homes, and as a result, some homes that we classified as other for-
profit or nonprofit homes may have been PI-owned.
Deficiency data. We have previously documented inconsistencies in
states' citation of deficiencies.[Footnote 88] Our analyses controlled
for variation across states, but may not have captured all variation
associated with state surveys.[Footnote 89] In addition, deficiency
data provide incomplete information about quality of care. Although
cited deficiencies indicate problems with the quality of care that
were identified during a survey, the absence of cited deficiencies
does not necessarily indicate that the quality of care was good
because surveyors may have failed to identify and cite actual quality
problems.
Staffing data. Although OSCAR was the most suitable data source
available for our analyses, OSCAR staffing data have several
limitations. First, OSCAR provides a 2-week snapshot of staffing and a
1-day snapshot of residents at the time of the survey, so it may not
have accurately depicted a facility's staffing or number of residents
over a longer period. Second, staffing is reported across the entire
facility, while the number of residents is reported only for Medicare-
and Medicaid-certified beds; as a result, our calculations may have
overstated staffing ratios for homes with noncertified beds.[Footnote
90] Third, neither CMS nor the states regularly attempt to verify the
accuracy of the OSCAR staffing data, and at least some studies
question these data. For example, research in one state suggested
systematic inaccuracies, with larger and for-profit homes being more
likely to report higher levels of RN staffing in OSCAR than in their
audited state Medicaid cost reports.[Footnote 91]
Financial data. Although Medicare cost reports provided the most
suitable data for our analyses, they are not routinely audited and are
subject to minimal verification, so they may contain inaccuracies.
Since the implementation of the Medicare prospective payment system
(in 1998 for SNFs), providers are no longer reimbursed directly on the
basis of costs, and some have raised concerns that the quality and
level of effort providers put into accurately completing Medicare cost
reports may have eroded. In addition, the Medicare program limits the
amount of capital-related costs that may be reported--for example, by
limiting the reporting of certain financing costs associated with
acquisition of a facility. If a provider's financing costs exceed
these limits, the provider's full financing costs cannot be reported.
As a result, a portion of the providers' reported margins may be
needed to offset these unreported financing costs. Also, for about one-
third of PI homes, our 2008 financial performance data are from less
than 1 year after acquisition. Thus, our postacquisition time period
may not fully capture any impact of PI ownership on the home's
financial performance.
Despite these limitations, our analyses do provide a reasonable basis
for comparing deficiencies, nurse staffing, and financial performance
of the PI-owned homes we studied to each other and to other types of
nursing homes at two points in time. We reviewed all data for
soundness and consistency and determined that they were sufficiently
reliable for our purposes. We performed data reliability checks on the
list of PI homes we compiled, OSCAR, Medicare's Provider of Services,
and Medicare SNF cost report data we used, reviewed relevant
documentation, and discussed these data sources with knowledgeable
officials and industry experts. We also reviewed published research on
the quality and costs of nursing home care, our prior work on nursing
homes, and other relevant documentation. We interviewed officials from
CMS; representatives of PI firms that acquired nursing home
operations, real estate, or both; representatives of companies that
operate PI-owned nursing homes; and experts on nursing home quality
and costs.
[End of section]
Appendix II: Comments from the Department of Health and Human Services:
Department Of Health & Human Services:
Office Of The Secretary:
Assistant Secretary for Legislation:
Washington, DC 20201:
June 21, 2011:
John Dicken:
Director, Health Care:
U.S. Government Accountability Office:
441 G Street N.W.
Washington, DC 20548:
Dear Mr. Dicken:
Attached are comments on the U.S. Government Accountability Office's
(GAO) draft report entitled: "Nursing Homes: Private Investment Homes
Sometimes Differed from Others in Deficiencies, Staffing, and
Financial Performance" (GAO-11-571).
The Department appreciates the opportunity to review this report
before its publication.
Sincerely,
Signed by:
Jim R. Esquea:
Assistant Secretary for Legislation:
Attachment:
[End of letter]
General Comments Of The Department Of Health And Human Services (HHS)
On The Government Accountability Office's (GAO) Draft Report Entitled,
"Nursing Homes: Private Investment Homes Sometimes Differed From
Others In Deficiencies, Staffing, And Financial Performance" (GA0-11-
571):
The Department appreciates the opportunity to review and comment on
this draft report.
The Centers for Medicare & Medicaid Services (CMS) appreciates the
effort of GAO to determine the effect of Private Investment (PI)
Firms' acquisition of nursing homes on the quality of care provided in
these homes. GAO undertook this analysis in response to concerns that
the acquisition of large nursing home chains by private investment
firms would lead to decreased quality of care provided in the acquired
facilities. The effect that nursing home ownership structure has on
the quality of care for residents in nursing homes is of critical
importance to CMS and the public.
In these comments, we provide several observations that we hope will
assist GAO to better quantify the effect that PI firm acquisition of
nursing homes may have on the quality of care provided in these
facilities. (For the most part, our concerns are acknowledged by GAO
in the limitations section of the proposed report.)
First, and perhaps most importantly, the particular pre-/post-
methodology employed makes it difficult to determine the extent to
which PI ownership is associated with differences in quality of care.
Although some potentially confounding variables were controlled for in
the regression models, the time points chosen are somewhat arbitrary ”
that is, the pre-acquisition period was 2003 and the post-acquisition
period was 2009 for essentially all nursing homes included in the
analyses. This approach treats all the units of analysis similarly and
fails to compare the PI homes that were acquired at different times in
the period of heaviest PI acquisition (2004-2007).
Additionally, this analysis could potentially lead to bias if PI-
acquired firms that received many deficiencies or were poor performing
on other metrics were sold before 2009. In this instance, the
arbitrary time cutoffs would skew the results toward more positive
results of PI-acquired firms compared to other ownership categories.
Further, since comparison within PI firms indicated "some differences"
on almost all metrics analyzed, we would conclude that the variability
within the PI-acquired category is sufficient to require a pre-/post-
test strategy that more closely approximates the changes occurring
around the time of acquisition. To more accurately examine any
association between PI-acquisition and nursing home quality, a
methodological approach that considered the year prior to individual
nursing home acquisition and a time point after acquisition
(determined a priori based on the literature) may be more effective.
The Online Survey Certification and Reporting System and CMS Skilled
Nursing Facility Cost Reports datasets would be appropriate for this
analytic approach. This would allow a more precise tailoring of the
pre- and post-acquisition time period to the actual ownership change
of each nursing home in question, rather than the one-size-fits-all
timeframe (2003-2009) imposed on all nursing homes in the study.
A number of alternative analyses may be possible to help explore the
relationship between private investment and quality of care. For
instance, an analysis based on the methodology now employed in CMS'
Five-Star Quality Rating System may add particular value, applied
retrospectively to the period in question. The Five-Star rating system
uses a robust methodology to assess nursing home quality and has been
used since 2009 on the Nursing Home Compare Web site [hyperlink,
http://www.medicare.Rov/NHCompare]. The overall Five-Star rating takes
into account health inspection scores, staffing, and quality measures,
and a separate Five-Star rating is provided for each of these
constructs.
In addition, an approach that took into account repeated citations
with a scope/severity score of G or higher may add further insight
into the quality of care. We have found, and a number of GAO reports
(GAO/HEHS-99-46 and GAO-09-689) have indicated, that some poorly-
performing nursing homes (especially chain-affiliated and for-profit
homes) tend to be cited repeatedly for deficiencies on numerous,
successive surveys. Therefore, an analytic approach that examines
repeat deficiencies might capture more variability in nursing home
performance based on ownership. Additionally, GAO might include
analyses on the number of complaints and enforcement actions against
each nursing home.
With regard to costs and staffing levels, GAO compared the costs
incurred by PI-acquired homes versus other ownership types in response
to the concern that PI firms would cut costs for improved profits.
These analyses suggest that the facility costs and the capital-related
costs actually rose more dramatically between 2003 and 2008 in PI-
acquired homes. However, as the report and interviews with owners
suggests, these costs are related largely to improving the
attractiveness of facilities for higher paying residents. The
association between these types of costs (e.g., improving facility
attractiveness) and the quality of care is not clear. We would suggest
an analysis that focused specifically on any association between
aggregate staffing payroll and quality of care.
The staffing data in the draft report do suggest that costs associated
with the direct provision of care went down in PI firms due to
decreased Certified Nurse Assistant and total nursing staff hours per
resident. However, these costs were not broken down to determine if
the increase in Registered Nurse hours in PI-acquired homes offset any
potential cost decreases in the other nursing categories. Some homes
that had reduced or flat total staffing hours reported that they
focused on training and retention of staff. While these activities
should theoretically improve quality of care (and at least one home
that reported a focus on training and retention had lower deficiencies
cited), neither the costs associated with training nor the rate of
turnover were accounted for in these analyses.
We appreciate the efforts that went into this report and look forward
to working with GAO on this and other issues. The report is an
important step toward better understanding the effect of nursing home
ownership, specifically PI acquisition, on the quality of care
received in nursing homes.
[End of section]
Appendix III: GAO Contact and Staff Acknowledgments:
GAO Contact:
John E. Dicken (202) 512-7114 or dickenj@gao.gov:
Acknowledgments:
In addition to the contact name above, Walter Ochinko, Assistant
Director; Dae Park, Assistant Director; Kristen Joan Anderson; Jennie
Apter; Ramsey Asaly; Leslie V. Gordon; Dan Lee; Jessica Smith; and
Sonya L. Vartivarian made key contributions to this report.
[End of section]
Related GAO Products:
Nursing Homes: More Reliable Data and Consistent Guidance Would
Improve CMS Oversight of State Complaint Investigations. [hyperlink,
http://www.gao.gov/products/GAO-11-280]. Washington, D.C.: April 7,
2011.
Nursing Homes: Complexity of Private Investment Purchases Demonstrates
Need for CMS to Improve the Usability and Completeness of Ownership
Data. [hyperlink, http://www.gao.gov/products/GAO-10-710]. Washington,
D.C.: September 30, 2010.
Poorly Performing Nursing Homes: Special Focus Facilities Are Often
Improving, but CMS's Program Could Be Strengthened. [hyperlink,
http://www.gao.gov/products/GAO-10-197]. Washington, D.C.: March 19,
2010.
Nursing Homes: Addressing the Factors Underlying Understatement of
Serious Care Problems Requires Sustained CMS and State Commitment.
[hyperlink, http://www.gao.gov/products/GAO-10-70]. Washington, D.C.:
November 24, 2009.
Nursing Homes: Opportunities Exist to Facilitate the Use of the
Temporary Management Sanction. [hyperlink,
http://www.gao.gov/products/GAO-10-37R]. Washington, D.C.: November
20, 2009.
Nursing Homes: CMS's Special Focus Facility Methodology Should Better
Target the Most Poorly Performing Homes, Which Tended to Be Chain
Affiliated and For-Profit. [hyperlink,
http://www.gao.gov/products/GAO-09-689]. Washington, D.C.: August 28,
2009.
Nursing Homes: Federal Monitoring Surveys Demonstrate Continued
Understatement of Serious Care Problems and CMS Oversight Weaknesses.
[hyperlink, http://www.gao.gov/products/GAO-08-517]. Washington, D.C.:
May 9, 2008.
Nursing Home Reform: Continued Attention Is Needed to Improve Quality
of Care in Small but Significant Share of Homes. [hyperlink,
http://www.gao.gov/products/GAO-07-794T]. Washington, D.C.: May 2,
2007.
Nursing Homes: Efforts to Strengthen Federal Enforcement Have Not
Deterred Some Homes from Repeatedly Harming Residents. [hyperlink,
http://www.gao.gov/products/GAO-07-241]. Washington, D.C.: March 26,
2007.
Nursing Homes: Despite Increased Oversight, Challenges Remain in
Ensuring High-Quality Care and Resident Safety. [hyperlink,
http://www.gao.gov/products/GAO-06-117]. Washington, D.C.: December
28, 2005.
Nursing Home Quality: Prevalence of Serious Problems, While Declining,
Reinforces Importance of Enhanced Oversight. [hyperlink,
http://www.gao.gov/products/GAO-03-561]. Washington, D.C.: July 15,
2003.
Skilled Nursing Facilities: Medicare Payments Exceed Costs for Most
but Not All Facilities. [hyperlink,
http://www.gao.gov/products/GAO-03-183]. Washington, D.C.: December
31, 2002.
Skilled Nursing Facilities: Available Data Show Average Nursing Staff
Time Changed Little after Medicare Payment Increase. [hyperlink,
http://www.gao.gov/products/GAO-03-176]. Washington, D.C.: November
13, 2002.
Skilled Nursing Facilities: Providers Have Responded to Medicare
Payment System by Changing Practices. [hyperlink,
http://www.gao.gov/products/GAO-02-841]. Washington, D.C.: August 23,
2002.
Nursing Homes: Quality of Care More Related to Staffing than Spending.
[hyperlink, http://www.gao.gov/products/GAO-02-431R]. Washington,
D.C.: June 13, 2002.
Nursing Homes: Sustained Efforts Are Essential to Realize Potential of
the Quality Initiatives. [hyperlink,
http://www.gao.gov/products/GAO/HEHS-00-197]. Washington, D.C.:
September 28, 2000.
Nursing Homes: Aggregate Medicare Payments Are Adequate Despite
Bankruptcies. [hyperlink,
http://www.gao.gov/products/GAO/T-HEHS-00-192]. Washington, D.C.:
September 5, 2000.
Skilled Nursing Facilities: Medicare Payment Changes Require Provider
Adjustments but Maintain Access. [hyperlink,
http://www.gao.gov/products/GAO/HEHS-00-23]. Washington, D.C.:
December 14, 1999.
Nursing Home Care: Enhanced HCFA Oversight of State Programs Would
Better Ensure Quality. [hyperlink,
http://www.gao.gov/products/GAO/HEHS-00-6]. Washington, D.C.: November
4, 1999.
Nursing Home Oversight: Industry Examples Do Not Demonstrate That
Regulatory Actions Were Unreasonable. [hyperlink,
http://www.gao.gov/products/GAO/HEHS-99-154R]. Washington, D.C.:
August 13, 1999.
Nursing Homes: Proposal to Enhance Oversight of Poorly Performing
Homes Has Merit. [hyperlink,
http://www.gao.gov/products/GAO/HEHS-99-157]. Washington, D.C.: June
30, 1999.
Nursing Homes: Complaint Investigation Processes Often Inadequate to
Protect Residents. [hyperlink,
http://www.gao.gov/products/GAO/HEHS-99-80]. Washington, D.C.: March
22, 1999.
Nursing Homes: Additional Steps Needed to Strengthen Enforcement of
Federal Quality Standards. [hyperlink,
http://www.gao.gov/products/GAO/HEHS-99-46]. Washington, D.C.:
March 18, 1999.
California Nursing Homes: Care Problems Persist Despite Federal and
State Oversight. [hyperlink,
http://www.gao.gov/products/GAO/HEHS-98-202]. Washington, D.C.: July
27, 1998.
[End of section]
Footnotes:
[1] See, for example, Nursing Home Transparency and Improvement,
Hearing Before the Special Committee on Aging, U.S. Senate, Nov. 15,
2007, Serial No. 110-17, U.S. Government Printing Office (Washington,
D.C.: 2008). In the Hands of Strangers: Are Nursing Home Safeguards
Working?, Hearing Before the Subcommittee on Oversight and
Investigations, Committee on Energy and Commerce, U.S. House of
Representatives, May 15, 2008, Serial No. 110-116, U.S. Government
Printing Office (Washington, D.C.: 2008).
[2] See C. Duhigg, "At Many Homes, More Profit and Less Nursing," The
New York Times (Sept. 23, 2007). Conversely, a subsequent study found
little evidence to suggest that nursing home quality worsens
significantly following PI acquisition. See D. Stevenson and D.
Grabowski, "Private Equity Investment and Nursing Home Care: Is it a
Big Deal?" Health Affairs, vol. 27, no. 5 (2008).
[3] The Securities and Exchange Commission requires publicly traded
companies to disclose financial and other information to the public to
inform investment decisions.
[4] Medicare is the federal health care financing program for the
elderly and disabled individuals and individuals with end stage renal
disease. Medicaid is the joint federal-state health care financing
program for certain categories of low income individuals.
[5] The Medicare program covers skilled care or rehabilitation in a
nursing home for up to 100 days following a medically necessary
hospital stay of at least 3 days. While about 3 million individuals
received care in a nursing home at some point during 2008, there were
approximately 1.5 million nursing home residents on any given day.
[6] Because deficiencies and nurse staffing are linked with quality of
care, CMS uses both measures in its Five-Star Quality Rating System
for nursing homes. CMS's Five-Star System provides an overall quality
rating of nursing homes in which every nursing home in the United
States is rated from one (much below average) to five (much above
average) stars. See GAO, Nursing Homes: CMS's Special Focus Facility
Methodology Should Better Target the Most Poorly Performing Homes,
Which Tended to Be Chain Affiliated and For-Profit, [hyperlink,
http://www.gao.gov/products/GAO-09-689] (Washington, D.C.: Aug. 28,
2009).
[7] See GAO, Nursing Homes: Complexity of Private Investment Purchases
Demonstrates Need for CMS to Improve the Usability and Completeness of
Ownership Data, [hyperlink, http://www.gao.gov/products/GAO-10-710]
(Washington, D.C.: Sept. 30, 2010).
[8] These PI acquisitions represented about 12 percent of the
approximately 16,000 nursing homes that participated in the Medicare
and Medicaid programs as of December 2008.
[9] We chose 2004 through 2007 because these were the years when the
greatest number (more than 1,800) of nursing homes was acquired by PI
firms. Specifically, 595 nursing homes were acquired by PI firms in
2004, 39 in 2005, 682 in 2006, and 525 in 2007. See [hyperlink,
http://www.gao.gov/products/GAO-10-710]. We excluded (1) nursing homes
that were hospital-based or government owned in 2009 because they
differed from other homes in important ways, including resident needs
and financial performance; (2) homes that were not certified by
Medicare in 2009 because almost all homes owned by the PI firms were
Medicare-certified; (3) homes for which we did not have data from both
before and after our target acquisition period (2004 through 2007);
and (4) homes for which extreme values suggested data entry or other
reporting errors.
[10] See [hyperlink, http://www.gao.gov/products/GAO-10-710]. This
report determined the top 10 PI acquirers of nursing homes based on
the number of homes purchased by firms from 1998 through 2008. These
top 10 PI acquirers accounted for almost 90 percent of nursing homes
acquired by PI firms during these 11 years.
[11] A skilled nursing facility (SNF) provides skilled nursing care
and participates in the Medicare program. SNFs are required to submit
annual cost reports to CMS.
[12] State surveys evaluate both the quality of care provided to
residents--the health portion of the survey--and compliance with
federal fire safety standards. Our analysis excluded deficiencies
cited during the fire safety portion of surveys.
[13] See GAO, Nursing Homes: Some Improvement Seen in Understatement
of Serious Deficiencies, but Implications for the Longer-Term Trend
Are Unclear, [hyperlink, http://www.gao.gov/products/GAO-10-434R]
(Washington, D.C.: Apr. 28, 2010); Nursing Homes: Addressing the
Factors Underlying Understatement of Serious Care Problems Requires
Sustained CMS and State Commitment, [hyperlink,
http://www.gao.gov/products/GAO-10-70] (Washington, D.C.: Nov. 24,
2009); and Nursing Homes: Federal Monitoring Surveys Demonstrate
Continued Understatement of Serious Care Problems and CMS Oversight
Weaknesses, [hyperlink, http://www.gao.gov/products/GAO-08-517]
(Washington, D.C.: May 9, 2008).
[14] Facility and capital-related costs were adjusted for inflation.
Capital-related costs included mortgage payments, rents, depreciation,
taxes, and insurance, as well as land and building improvements,
including upgrades to equipment.
[15] Deficiency and staffing data were from the calendar year, whereas
financial performance data reflect the provider's fiscal year. We used
financial data from 2008 rather than 2009 because Medicare SNF Cost
Report data from 2009 were not available at the time we collected our
data.
[16] Chain affiliation is indicated in OSCAR by a nursing home's self-
reported multi-nursing home (chain) ownership. Multi-nursing home
chains are defined as having two or more homes under one owner or
operator.
[17] For several PI firms, these restrictions led us to analyze a
subset of all homes owned by the PI firm. As a result, information
about homes included in these analyses may not be representative of
other homes owned by the PI firm.
[18] D. Stevenson, D. Grabowski, and L. Coots, Nursing Home
Divestiture and Corporate Restructuring: Final Report, a special
report prepared at the request of the Department of Health and Human
Services (HHS), Assistant Secretary for Planning and Evaluation
(December 2006).
[19] See [hyperlink, http://www.gao.gov/products/GAO-10-710].
[20] However, their lease arrangements with nursing home operators may
have the potential to influence the operations of the homes. See GAO-
10-70. For example, officials at a PI firm that acquired a nursing
home chain commented that leasing arrangements have minimal risk for
real estate owners, but when revenues decline, nursing home operators
are more likely to cut staff to pay the base rent and to maintain a
level of profitability. PI firms we studied that acquired only real
estate acknowledged the risk to their investment should the quality of
care in the homes decline or one of their operators lose its state
license to operate a nursing home. Two of these firms told us that
their leases require the operators to maintain certain standards of
care and that this requirement is routine in the industry.
[21] See [hyperlink, http://www.gao.gov/products/GAO-10-710]. In 2011,
two of the PI firms we studied sold the real estate for the chains
they had purchased in 2007.
[22] Although the average percentage of residents whose care was
reimbursed by Medicare increased from 2003 to 2009 regardless of type
of ownership, this increase was less for PI homes than for other
homes. Our analyses of payer mix did not include control variables.
[23] Our analyses of occupancy rates did not include control variables.
[24] Social Security Act §§ 1819 (g) (codified at 42. U.S.C. § 1395i-
3(g)), 1919(g) (codified at 42 U.S.C. § 1396r(g)).
[25] Social Security Act § 1124 (codified at 42 U.S.C. §1320a-3). The
enactment of the Patient Protection and Affordable Care Act in March
2010 expanded the ownership and control reporting requirements to
improve the transparency of the ownership for Medicare and Medicaid
nursing homes. Pub. L. No. 111-148, § 6101, 124 Stat. 119, 699.
[26] In addition to health standards, the standard survey also
includes an assessment of federal fire safety standards.
[27] See GAO, Nursing Homes: More Reliable Data and Consistent
Guidance Would Improve CMS Oversight of State Complaint
Investigations, [hyperlink, http://www.gao.gov/products/GAO-11-280]
(Washington, D.C.: Apr. 7, 2011).
[28] See GAO, Nursing Homes: Despite Increased Oversight, Challenges
Remain in Ensuring High-Quality Care and Resident Safety, [hyperlink,
http://www.gao.gov/products/GAO-06-117] (Washington, D.C.: Dec. 28,
2005).
[29] See [hyperlink, http://www.gao.gov/products/GAO-10-434R],
[hyperlink, http://www.gao.gov/products/GAO-10-70], and [hyperlink,
http://www.gao.gov/products/GAO-08-517].
[30] For example, see M. P. Hillmer, W. P. Wodchis, S. S. Gill, G. M.
Anderson, and P. A. Rochon, "Nursing Home Profit Status and Quality of
Care: Is There Any Evidence of an Association?" Medical Care Research
and Review, vol. 62, no. 2 (April 2005).
[31] For example, see C. O'Neill, C. Harrington, M. Kitchener, and D.
Saliba, "Quality of Care in Nursing Homes: An Analysis of
Relationships among Profit, Quality, and Ownership," Medical Care,
vol. 41, no. 12 (2003) and S. Chesteen, B. Helgheim, T. Randall, and
D. Wardell, "Comparing Quality of Care in Non-Profit and For-Profit
Nursing Homes: A Process Perspective," Journal of Operations
Management, vol. 23, no. 2 (2005).
[32] D. Stevenson and D. Grabowski.
[33] D. Stevenson, D. Grabowski, and J. Bramson, Nursing Home
Ownership Trends and Their Impact on Quality of Care. HHS, Office of
Disability, Aging and Long-Term Care Policy (August 2009).
[34] In some states, licensed practical nurses (LPN) are known as
licensed vocational nurses. We use the term LPN to refer to both LPNs
and licensed vocational nurses. In addition to nursing staff, nursing
homes employ a variety of other healthcare professionals, including
physicians, social workers, physical therapists, and other types of
therapists.
[35] See for example, GAO, Nursing Homes: Quality of Care More Related
to Staffing than Spending, [hyperlink,
http://www.gao.gov/products/GAO-02-431R] (Washington, D.C.: June 13,
2002); C. Harrington, "Quality of Care in Nursing Home Organizations:
Establishing a Health Services Research Agenda," Nursing Outlook, vol.
53, no. 6 (2005); Institute of Medicine, Committee on the Work
Environment for Nurses and Patient Safety, Keeping Patients Safe:
Transforming the Work Environment of Nurses (Washington D.C.: The
National Academies Press, 2004); and Institute of Medicine, Committee
on Improving Quality in Long-Term Care, Improving the Quality of Long-
term Care (Washington D.C.: The National Academies Press, 2001).
[36] 42 U.S.C. § 1395i-3(b).
[37] C. Harrington, Nursing Home Staffing Standards in State Statutes
and Regulations (December 2010).
[38] Health Care Financing Administration, Appropriateness of Minimum
Nurse Staffing Ratios in Nursing Homes, Report to Congress (2000).
Prior to July 2001, CMS was known as the Health Care Financing
Administration.
[39] See V. Mor, C. Caswell, S. Littlehale, J. Niemi, and B. Fogel,
Changes in the Quality of Nursing Homes in the US: A Review and Data
Update (Aug. 15, 2009) and C. Harrington, H. Carrillo, and B. W.
Blank, Nursing Facilities, Staffing, Residents and Facility
Deficiencies, 2003 Through 2008 (San Francisco, Calif.: Department of
Social & Behavioral Sciences, University of California San Francisco,
2009).
[40] For example, see C. Donoghue, "The Percentage of Beds Designated
for Medicaid in American Nursing Homes and Nurse Staffing Ratios,"
Journal of Health and Social Policy, vol. 22, no. 1 (2006).
[41] D. Stevenson and D. Grabowski.
[42] D. Stevenson, D. Grabowski, and J. Bramson.
[43] The Medicare prospective payment system also adjusts payments for
geographic differences in labor costs.
[44] See GAO, Skilled Nursing Facilities: Medicare Payments Exceeded
Costs for Most but Not All Facilities, [hyperlink,
http://www.gao.gov/products/GAO-03-183] (Washington, D.C.: Dec. 31,
2002), and Medicare Payment Advisory Commission, Report to the
Congress: Medicare Payment Policy (Washington, D.C.: March 2011).
[45] We analyzed how much more or less the expected incidence rate for
total deficiencies is for one type of home when compared to another.
In this report, we used the term total deficiencies rather than
incidence rates. For more information, see appendix I.
[46] We analyzed odds ratios, that is, we analyzed how much more or
less likely the odds are for one or more serious deficiencies to have
been cited for one type of home when compared to another. In this
report, we used the term likelihood of a serious deficiency rather
than odds ratios. For more information, see appendix I.
[47] Nursing homes also had a significantly more total deficiencies
(1) in chain-affiliated homes than in individually owned homes, (2)
the lower the percentage of residents whose stay was paid by Medicare,
(3) the lower the percentage of residents whose stay was paid by a
source other than Medicare or Medicaid, (4) the greater the number of
beds, and (5) the greater the degree of competition in the county.
[48] Other explanatory factors included chain affiliation, payer mix,
facility size, occupancy rate, market competition, and state. Nursing
homes were also significantly more likely to have had a serious
deficiency (1) if chain-affiliated rather than individually owned, (2)
the lower the percentage of residents whose stay was paid by Medicare,
(3) the lower the percentage of residents whose stay was paid by a
source other than Medicare or Medicaid, and (4) the greater the number
of beds.
[49] Average reported total nurse staffing ratios were also
significantly higher (1) for individually owned homes than chain-
affiliated homes, (2) the greater the percentage of residents whose
stay was paid by Medicare, (3) the greater the percentage of residents
whose stay was paid by a source other than Medicare or Medicaid, (4)
the fewer the beds, (5) the lower the occupancy rate, and (6) the
greater the degree of competition in the county.
[50] See CMS Report to Congress (2000). The average acuity of nursing
home residents has increased since that report was issued.
[51] We controlled for chain affiliation, payer mix, facility size,
occupancy rate, market competition, and state. Average reported RN
staffing ratios were significantly higher (1) for individually owned
homes than chain-affiliated homes, (2) the greater the percentage of
residents whose stay was paid by Medicare, (3) the greater the
percentage of residents whose stay was paid by a source other than
Medicare or Medicaid, (4) the fewer the beds, (5) the lower the
occupancy rate, and (6) the greater the degree of competition in the
county.
[52] See CMS Report to Congress (2000). The average acuity of nursing
home residents has increased since that report was issued.
[53] We controlled for chain affiliation, payer mix, facility size,
occupancy rate, market competition, and state. Unadjusted average
reported LPN ratios for PI homes did not differ significantly from
other homes in 2003 or 2009. Average reported LPN ratios were
significantly higher (1) in individually owned homes than in chain-
affiliated homes, (2) the greater the percentage of residents whose
stay was paid by Medicare, (3) the greater the percentage of residents
whose stay was paid by a source other than Medicare or Medicaid, (4)
the lower the occupancy rate, and (5) the greater the degree of
competition in the county.
[54] We controlled for chain affiliation, payer mix, facility size,
occupancy rate, market competition, and state. Average reported CNA
ratios were significantly higher (1) in individually owned homes than
in chain-affiliated homes, (2) the greater the percentage of residents
whose stay was paid by Medicare, (3) the greater the percentage of
residents whose stay was paid by a source other than Medicare or
Medicaid, and (4) the lower the occupancy rate.
[55] We controlled for chain affiliation, payer mix, facility size,
occupancy rate, market competition, and state. On average, reported
facility costs per resident day were also higher (1) the greater the
percentage of residents whose stay was paid by Medicare, (2) the
greater the percentage of residents whose stay was paid by a source
other than Medicare or Medicaid, (3) the greater the number of beds,
and (4) the greater the degree of competition in the county.
[56] Medicare regulations place certain limits on the calculation of
nursing home providers' capital-related costs. If a provider's
financing costs exceed these limits, the provider's full financing
costs cannot be included in Medicare cost reports. Several of the PI
firms in our study made use of financing to acquire their homes. The
largest transaction among our firms was a $6.3 billion deal in 2007 of
which about $5 billion was financed. In 2011, this PI firm sold its
nursing homes' real estate to a real estate investment trust through a
$6.1 billion transaction as well as about 10 percent of the
facilities' operations for about $95 million.
[57] We controlled for chain affiliation, payer mix, facility size,
occupancy rate, market competition, and state. On average, capital-
related costs per resident day were also higher (1) in chain
affiliated homes than in individually-owned homes, (2) the greater the
percentage of residents whose stay was paid by Medicare, (3) the
greater the percentage of residents whose stay was paid by a source
other than Medicare or Medicaid, (4) the greater the number of beds,
(5) the lower the occupancy rate, and (6) the greater the degree of
competition in the county.
[58] Facility margins are the amount of total facility revenues
exceeding total facility costs, divided by total facility revenues.
Medicare regulations place certain limits on the calculation of
nursing home providers' capital-related costs. If a provider's
financing costs exceed these limits the provider's full financing
costs cannot be reported. As a result, a portion of the provider's
reported margins may be needed to offset the financing costs that are
not included in Medicare cost reports.
[59] On average, facility margins were also higher (1) the greater the
percentage of residents whose stay was paid by Medicare, (2) the
greater the number of beds, (3) the greater the occupancy rate, and
(4) the lesser the degree of competition in the county.
[60] In two cases, companies that operate homes owned by PI firms
reviewed the draft. We refer to all reviewers as representatives of
the PI firms--eight firms in total.
[61] See D. Stevenson and D. Grabowski.
[62] We used the latest available data--2008 for financial performance
and 2009 for deficiency and staffing--in order to give any changes
associated with PI acquisition time to take effect.
[63] See GAO, Nursing Homes: Complexity of Private Investment
Purchases Demonstrates Need for CMS to Improve the Usability and
Completeness of Ownership Data, [hyperlink,
http://www.gao.gov/products/GAO-10-710] (Washington, D.C.: Sept. 30,
2010). This report determined the top 10 PI acquirers of nursing homes
based on the number of homes purchased and retained by firms from 1998
through 2008. To identify acquisitions, this report used merger and
acquisition data compiled by Dealogic, a company that offers financial
analysis products to the investment banking industry. We supplemented
the Dealogic data with information from other sources, such as company
Web sites, nursing home industry publications, and company filings
with the Securities and Exchange Commission. Nine of these PI firms
provided us with information about their acquisitions; the other did
not respond to any of our requests for data.
[64] Specifically, 595 nursing homes were acquired by PI firms in
2004, 39 in 2005, 682 in 2006, and 525 in 2007. See [hyperlink,
http://www.gao.gov/products/GAO-10-710]. We defined the date of
acquisition in terms of the most recent PI acquisition of operations,
real estate, or both.
[65] See [hyperlink, http://www.gao.gov/products/GAO-10-710].
[66] We did not differentiate among PI-acquired homes based on prior
ownership, which could have been PI, other for-profit, or nonprofit.
[67] We could not determine whether the same PI firm acquired both the
operations and the real estate or not for about 9 percent of the PI
homes we identified. Although other for-profit and nonprofit homes may
also have separate owners of operations and real estate, CMS did not
capture relevant information in national databases.
[68] Nursing homes enrolled in the Medicaid program alone (and not
jointly enrolled in the Medicare and Medicaid programs) accounted for
approximately 4 percent of nursing homes participating in either
program during 2009.
[69] Chain affiliation is indicated in OSCAR by a nursing home's self-
reported multi-nursing home (chain) ownership, where multi-nursing
home chains are defined as having two or more homes under one
ownership or operation.
[70] Payers other than Medicare and Medicaid include private
insurance, religious organizations, the Department of Veterans
Affairs, residents who pay for their own care, and others.
[71] If there were two or more surveys in 2009, we used the first
survey. If there were two or more surveys in 2003, we used the last
survey.
[72] Some states use the term licensed vocational nurse rather than
LPN. Throughout this report we use LPN to refer to both.
[73] Facilities are instructed to report only residents in certified
beds. If a nursing home had residents in noncertified beds, actual
nursing hours per resident per day would be lower than our
calculations indicate. We considered several criteria for excluding
homes based on the percentage of noncertified beds and concluded that
excluding homes with more than 10 percent of noncertified beds results
in data of sufficient reliability for our purposes.
[74] Facility costs were taken from the Medicare SNF cost report's G-2
and G-3 worksheets. Facility costs were adjusted for inflation. Less
than 25 percent of nursing homes' margins we analyzed included costs
and revenues for other lines of business conducted within the same
nursing home, such as other long-term care, home health, outpatient
rehabilitation services, and hospice.
[75] Capital-related costs are those that were allocated to nursing
home resident care on the Medicare SNF cost report's worksheet B, part
II. These costs include mortgage payments, rents, improvements to
land, buildings and equipment, depreciation, taxes, and property
insurance. We adjusted capital-related costs for inflation.
[76] Facility revenues include net patient and other income from the
Medicare SNF cost report's worksheet G-3. These revenues include
Medicare payments, which are based on a per diem amount for each
Medicare beneficiary. The per diem is adjusted for geographic
differences in labor costs and for differences in the resource needs
of the Medicare resident. Facility costs are the same as described
above. Margins calculated in this way are interpreted as the percent
profit or loss that the nursing home experiences for the year. Less
than 25 percent of nursing homes' margins we analyzed included costs
and revenues for other lines of business conducted within the same
nursing home, such as other long-term care, home health, outpatient
rehabilitation services, and hospice.
[77] Generally, a provider's fiscal year is a 12-month period, but
under certain circumstances, a provider may prepare a cost report for
a period that is less than or greater than 12 months.
[78] About 38 percent of PI homes we studied were acquired less than 1
year before the time period reflected by their 2008 Medicare cost
report.
[79] We used a similar procedure to the one described for the
deficiency data, with the constraint that the OSCAR data for PI-
acquired homes had to be from before the acquisition and after
acquisition.
[80] The differences between the numbers of nursing homes included in
these datasets and those used to analyze deficiencies and nurse
staffing were primarily due to the restrictions on the time period
covered by the cost report and the requirement for data from both
years.
[81] Because our outcome measures had different distributions, our
criteria for identifying outliers differed. There were fewer nursing
homes retained in our examination of facility margins than either
facility costs or capital-related costs because there more nursing
homes with extreme values for margins than for facility or capital-
related costs.
[82] Panel regression models can be used when data come from a cross-
section of entities--in this case, nursing homes--and are collected at
two or more points in time. Such models allow comparisons of data from
the different points in time. We also conducted panel regression
analyses on some key covariates (a) the percentage of residents for
whom the payer was Medicare, (b) the percentage of residents for whom
the payer was neither Medicare nor Medicaid, and (c) occupancy rate.
In these analyses, we examined the effects of type of ownership and
year; we did not include any control variables in these analyses.
[83] We defined market competition in terms of the number of beds in a
nursing home's county using a Herfindahl index. This index can range
from 0, indicating perfect competition, to 1, indicating monopoly.
[84] Categorical variables classify units of study into categories.
For example, the categorical variable ownership type classifies
nursing homes into three categories: PI, other for-profit, and
nonprofit. In statistical models that include a categorical
independent variable, where there are k categories, only k-1 dummy
indicator variables are necessary to represent k categories in the
regression model. The excluded category is the reference category.
Year has two categories (2003 and 2009) and is represented by a term
for 2009, with 2003 as the reference category for the variable year.
Ownership type has three categories and is represented by two terms in
our model: other for-profit homes and nonprofit homes, with PI homes
as the reference category.Because our model has main effects for year
and ownership type as well as their interactions, the reference
category in our model is PI homes in 2003.
[85] We applied Stata xt series commands to analyze our panel data.
Specifically, to analyze nurse staffing ratios, we used the xtreg
command. We used the xi command along with the xt series command to
specify the two interaction terms. These commands generated the
information presented in table 4.
[86] Regression analyses test the significance of some comparisons
directly; the significance of other comparisons is tested using chi-
square tests to analyze the appropriate linear combination of
regression parameters that had been calculated by the panel analysis.
We conducted chi-square tests after our panel analyses of
deficiencies, nurse staffing, and financial performance data.
[87] For several PI firms, these restrictions led us to analyze a
subset of all homes owned by the firm. As a result, information about
the homes included in these analyses may not be representative of
other homes owned by the PI firm.
[88] See GAO, Nursing Homes: Some Improvement Seen in Understatement
of Serious Deficiencies, but Implications for the Longer-Term Trend
Are Unclear, [hyperlink, http://www.gao.gov/products/GAO-10-434R]
(Washington, D.C.: Apr. 28, 2010); Nursing Homes: Addressing the
Factors Underlying Understatement of Serious Care Problems Requires
Sustained CMS and State Commitment, [hyperlink,
http://www.gao.gov/products/GAO-10-70] (Washington, D.C.: Nov. 24,
2009); and Nursing Homes: Federal Monitoring Surveys Demonstrate
Continued Understatement of Serious Care Problems and CMS Oversight
Weaknesses, [hyperlink, http://www.gao.gov/products/GAO-08-517]
(Washington, D.C.: May 9, 2008).
[89] Variation in citation of deficiencies could be linked to
differences in the district offices that are responsible for the
surveys. We considered controlling for district office rather than
state when analyzing deficiency data, but found that we could not
reliably associate district offices with the nursing homes they were
responsible for surveying.
[90] We excluded nursing homes that reported that more than 10 percent
of beds were not certified for Medicare or Medicaid.
[91] A comparison of OSCAR to Texas Medicaid Cost Reports--which
summarize a year's payroll data and are subject to auditing processes
not used with OSCAR--indicated that OSCAR was more likely to suggest
higher average RN levels than the Texas Medicaid Cost Reports when the
facilities were larger or for-profit than when they were smaller or
nonprofit. See B. A. Kash, C. Hawes, and C. D. Phillips, "Comparing
Staffing Levels in the Online Survey Certification and Reporting
(OSCAR) System With the Medicaid Cost Report Data: Are Differences
Systematic?" The Gerontologist, vol. 47, no. 4 (2007).
[End of section]
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