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INQUIRY: The Journal of Health Care
Organization, Provision, and Financing

Volume 55: 1 –12
© The Author(s) 2018

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DOI: 10.1177/0046958018793285

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The Role of Assisted Living Capacity on
Nursing Home Financial Performance

Justin Lord, MBA, CMA, FHFMA1 , Ganisher Davlyatov, MPH2,
Kali S. Thomas, PhD3, Kathryn Hyer, PhD, MPP4,
and Robert Weech-Maldonado, PhD2

Abstract
The rapid growth of the assisted living industry has coincided with decreased levels of nursing home occupancy and financial
performance. The purpose of this article is to examine the relationships among assisted living capacity, nursing home
occupancy, and nursing home financial performance. In addition, we explore whether the relationship between assisted living
capacity and nursing home financial performance is mediated by nursing home occupancy. This research utilized publicly
available secondary data, for the state of Florida from 2003 through 2015. General descriptive statistics were used to assess
the relationships among financial performance, assisted living capacity, and occupancy. To explore the relationships among
financial performance, assisted living capacity and occupancy, and test potential mediation of occupancy, we followed Baron
and Kenny’s approach and estimated 3 models examining the relationships between (1) assisted living capacity and nursing
home financial performance, (2) assisted living capacity and nursing home occupancy, and (3) nursing home occupancy and
financial performance after assisted living capacity is included in the model. We used generalized estimating equations, to
adjust for repeated measures and to model the above relationships. Year fixed effects control for time trend. The independent
variable, assisted living beds, was lagged for 1 year to account for the potential influence on financial performance. The final
analytic sample consisted of 7688 nursing home-year observations from 657 unique nursing homes. Our findings suggest
that assisted living capacity does have a negative impact on nursing homes’ financial performance. Even though, assisted living
capacity seems not to significantly decrease nursing home occupancy. The relationship between assisted living capacity and
financial performance was not mediated through occupancy. These findings suggest that assisted living communities may not
be able to significantly reduce nursing home occupancy; however, the presence of assisted living communities may create
additional financial/competitive pressures that result in decreased nursing home financial performance.

Keywords
assisted living, financial performance, nursing homes, competition

Original Research

What do we already know about this topic?
The rapid growth of the assisted living industry has coin-
cided with decreased levels of nursing home occupancy
and financial performance, yet relatively few studies have
examined the impact of assisted living competition on
nursing home performance, especially as it relates to
occupancy.
How does your research contribute to the field?
This study contributes to the literature by exploring the
relationships among assisted living capacity, nursing
home occupancy, and nursing home financial perfor-
mance in the state of Florida from 2003 to 2015.
What are your research’s implications toward theory,
practice, or policy?
Assisted living communities may not be able to significantly
reduce nursing home occupancy; however, the presence of

assisted living communities may create additional financial/
competitive pressures that result in decreased nursing home
financial performance.

793285 INQXXX10.1177/0046958018793285INQUIRY: The Journal of Health Care Organization, Provision, and FinancingLord et al
research-article2018

1Louisiana State University Shreveport, USA
2The University of Alabama at Birmingham, USA
3Brown University, Providence, RI, USA
4University of South Florida, Tampa, USA

Received 3 January 2018; revised July 5 2018; revised manuscript
accepted 6 July 2018

Corresponding Author:
Justin Lord, Doctoral Candidate, James K. Elrod Health Administration
Department, Louisiana State University Shreveport, One University Place,
Room 301B, Shreveport, LA 71115, USA.
Email: Justin.Lord@lsus.edu

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mailto:Justin.Lord@lsus.edu

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2 INQUIRY

Introduction

The assisted living/residential care industry has experienced
significant growth since its introduction in 1981.1 Growth in
the assisted living industry has coincided with falling levels
of nursing home occupancy.2,3 In 1981, nursing home occu-
pancy was around 93% but has declined to around 82% in
2014.4,5 During the same period, the number of assisted liv-
ing/residential care communities grew to around 30 200 with
an estimated 1 million beds.6 The growth of nursing home
substitutes, such as assisted living and home- and commu-
nity-based services (HCBS), has provided more alternatives
for individuals seeking long-term care but has also increased
the levels of indirect competition within the nursing home
industry. The increased levels of competition within the
long-term care industry have the potential to impact nursing
homes’ bottom line.3

On average, nursing homes operate on low margins.7
Nursing homes must balance the many challenges that can
negatively impact their financial position, such as staffing
requirements,8 falling occupancy rates,9 high liability insur-
ance costs,3 and state Medicaid reforms.10 As such, increased
competition from substitute providers may exacerbate a
nursing home’s weak financial position. The financial per-
formance of a nursing home can have a direct impact on the
residents of the nursing home and the community. Nursing
homes with poor financial performance have been found to
have worse resident quality11,12 and be at increased risk of
closure and consolidation.3

Relatively few studies have examined the impact from
assisted living competition on nursing home performance.13
These studies have focused on the impact from assisted liv-
ing competition on nursing home utilization,3 nursing home
quality,14 private-pay prices,13 nursing home strategic posi-
tioning,15 and nursing home case mix.16,3 This article contrib-
utes to the literature by exploring the relationships among
assisted living capacity, nursing home occupancy, and nurs-
ing home financial performance in the state of Florida. In
addition, we explore whether the relationship between
assisted living capacity and nursing home financial perfor-
mance is mediated by nursing home occupancy. It is impor-
tant for policy makers and health care leaders to understand
the relationship between assisted living supply and nursing
homes profitability as this may impact the equitable delivery
of long-term care.

The state of Florida was chosen for this study for the fol-
lowing reasons. First, due to its large population of aging indi-
viduals. As of 2010, the population estimates of individuals 65
and older in Florida was around 17.3% as compared with the
national average of 13.0%.17 Second, Florida is 1 of 3 states,
the others being California and Pennsylvania, that account for
33% of all assisted living units nationwide.18,19 Third, Florida
had been very progressive and innovative in funding for long-
term care. Florida had introduced its own waiver program, The
ALE, that allows low-income individuals to use state Medicaid

program dollars to pay for assisted living.20 Fourth, there is
limited national data on assisted living homes and Florida is
one state that actually collects that information.

The Growth of Assisted Living and Nursing Home
Care

Assisted living communities, also called residential care
communities, have emerged as a popular housing and long-
term care option for older Americans.3,21 Although there is
no national definition for assisted living communities, they
are typically described as organizations that provide 24 hours
of supervised care in a residential /homelike setting, yet pro-
vide the residents with more independence and autonomy as
compared with a nursing home.14 Depending on the market
and assisted living community, there can be a wide range of
diverseness in scope and breadth of services, as well as the
populations served by assisted living communities.3,22 On
average, assisted living communities differentiate them-
selves from nursing homes by providing care to residents
who have a lower level of need as compared with average
nursing home residents.14 However, over time, some assisted
living communities have evolved by providing more inten-
sive care and services for increasingly sick and disabled indi-
viduals who have more complex chronic health conditions
and less independence.3,23,24

Several factors explain the growth in the popularity of
assisted living communities. First, there have been increasing
federal and state efforts to move individuals from institutional
(ie, nursing homes) to noninstitutional or community-based
settings.25,26 Second, advances in medical technology have
altered both demand and need for institutional care.15 Third,
there has been a consumer preference shift for more indepen-
dent living.27,28 Individuals want to retain their autonomy and
independence for as long as possible. The result has been a
demand for long-term care services that provide limited assis-
tance for individuals who can no longer live independently
but who do not require institutionalized care.2,15 Fourth,
assisted living communities are generally perceived in a more
positive (functional) light relative to nursing homes. A major-
ity of Americans have a negative public perception regarding
the quality of care in a nursing home.29 Even with increased
public reporting of nursing home quality, this has done little
to sway consumers.30,31,32 Finally, on average, assisted living
communities are less costly as compared with nursing
homes.33,34 According to the Genworth 2010 Cost of Care
Survey, the median annual cost of nursing home care in the
United States for a semiprivate room in 2010 was $67 525 but
for assisted living care, it was $38 200.34 As most assisted liv-
ing communities are private-pay, consumers who are price-
sensitive may choose the option that provides the best value
for their dollar.35,3

Given the negative public opinion, the high cost,34 institu-
tional bias,27 and cost associated with nursing home care, it is

Lord et al 3

little wonder why alternative long-term care providers, such
as assisted living communities, have become a popular resi-
dential care option for older adults.36,3,15

Conceptual Framework

An organization’s ability to accomplish its goals is dependent
on the availability of necessary resources.37,38 Organizations
actively try to obtain critical resources from the environment
to ensure continued existence.39 Resources that are critical for
organizations to function are often scarce and not equally dis-
tributed.40 The ability to acquire critical resources can be
challenging because some critical resources are controlled by
other entities/organizations.41,42 Resource dependency theory
(RDT) states that “the key to organizational survival is the
ability to acquire and maintain resources.”42 Uncertainty
regarding the availability of resources may explain changes in
organizational behavior and performance.42,43 Managers must
effectively manage their resources and relationships in an
ever-changing environment to succeed.44 If the environment
changes, it is contingent on the organization to stabilize or
find new flows of resources.42

For many years, nursing homes were the primary source
of institutional long-term care; however, over the past sev-
eral years, there has been increasing levels of direct and indi-
rect competition from within and outside of the nursing home
industry.45 Assisted living communities and nursing homes
both provide long-term care services. In the past, the distinc-
tion between nursing home residents and assisted living resi-
dents was rather clear-cut. Nursing homes typically had
residents with worse acuity and who required more intensive
assistance and supervision as compared with assisted living
residents.13 However, over the past several years, the scope
of assisted living care has been expanding. Many assisted
living communities are admitting persons with greater levels
of physical need and allowing residents to “age in place” lon-
ger before discharge to a nursing home.13,24 Another big dif-
ferentiator between assisted living communities and nursing
homes has revolved around the payer-mix. Historically,
assisted living communities were private-pay,3 yet this has
started to change with increased funding from Medicaid.

Most states have initiated transfer programs or Medicaid
1915(c) waivers to shift the delivery of long-term care from
institutional providers (nursing homes) to residential/commu-
nity-based long-term care providers.19 These programs are
responding to the public’s consumer desire to receive care in
the least restrictive setting possible46 and also have been driven
by the increasing large percentage that Medicaid long-term
spending has on state’s budgets.47,19 States using the 1915(c)
waivers have more flexibility to pay for services traditionally
not covered under Medicaid. These waiver programs vary
state by state and usually have enrollment caps, waiting lists,
or specific state coverages.48 Under most 1915(c) waivers,
Medicaid funds cannot be used to pay for basic housing
expenses or food in an assisted living community but can be

used to reimburse an assisted living community for any
service(s) deemed medically necessary.18,19 The state of
Florida had 2 1915(c) waivers, the assisted living for the
elderly (ALE) waiver and the nursing home diversion waiver,
that funneled Medicaid dollars to assisted living communities.
These waivers were available for assisted living facilities
that provided extended congregate care or limited nursing
services.49 In 2014, Florida discontinued all Medicaid waivers
and transformed the program to a Statewide Medicaid
Managed Care Long-Term Care (SMMC LTC); however, the
assisted living component remained.50

Assisted Living as a Potential Substitute of
Nursing Home Care

Competition occurs not only between organizations that
offer identical types of products or services but also from
organizations that produce similar but different products or
services.51,52 Dissimilar organizations that are indirect com-
petitors of each other can eventually impact the behavior of
each other.13 In most cases, assisted living and nursing homes
cannot be viewed as pure substitutes for each other,13 but, as
in the case in Florida, they can provide some overlapping
services for individuals seeking long-term care. As assisted
living communities increase their breadth and depth of ser-
vices into long-term care, they can be indirect competitors to
nursing homes. Assisted living facilities typically attract
healthier, private-pay individuals as compared with nursing
homes.3 This can implications for nursing homes in regard to
“cream skimming.”53 As assisted living communities attract
healthier and private-pay individuals, nursing homes could
see a decrease in their private-pay census and a worsening of
the average patient acuity.3 The loss of private-pay residents
and worsening resident acuity could increase costs and
reduce the profitability for nursing homes. The threat of
increased competition can drive down profitability of an
industry.54 It is therefore hypothesized that

Hypothesis 1: Increased assisted living capacity will
be associated with lower nursing home financial
performance.

Assisted living capacity has been found to be negatively
associated with nursing home occupancy.3 This is due to sev-
eral factors that were explored earlier in the article, such as
increasing federal and state efforts to move individuals from
institutional to noninstitutional or community-based set-
tings,25,26 shift in consumer preferences for more indepen-
dent living,27,28 perception,29 and cost.33,34 Previous research
has found that increasing assisted living capacity has been
associated with declining nursing home occupancy.3 The
proliferation of long-term care alternatives, such as assisted
living providers, can impact the demand for nursing homes,
as a market can only support a finite number of organiza-
tions.13,55 It is therefore hypothesized that

4 INQUIRY

Hypothesis 2: Increased assisted living capacity will be
associated with lower nursing home occupancy rate.

Assisted Living Capacity and Nursing Home
Financial Performance: The Mediation Effect of
Nursing Home Occupancy

Prior research has found lower occupancy to be associated
with worse nursing home financial performance.9 Occupancy
is an important metric to examine within nursing homes
because of its revenue implications.56 Organizations that are
producing at their optimal levels, or at full capacity, are bet-
ter able to cover their fixed costs, which can impact financial
performance. Nursing homes with low levels of occupancy
will have generated less revenue, which will negatively
impact the bottom line. Given the expected relationships
between increased assisted living capacity and nursing home
occupancy, and the association between occupancy and
financial performance, we expect occupancy rate to be a
potential mediator between the relationship between assisted
living capacity and financial performance. Therefore, we
hypothesize that

Hypothesis 3: Increased assisted living capacity will be
associated with decreased occupancy rate, and this will in
turn result in lower financial performance

These hypothesized relationships are summarized in
Figure 1.

Methods

Data

This research utilizes data from 4 different sources: Brown
University’s LTCFocus, Medicare Cost Reports, Area
Resource File (ARF), and the State of Florida’s list of
licensed assisted living communities from 2003-2015.

Brown University’s LTCFocus data provide nursing home
organizational, demographic, quality, and market informa-
tion. This dataset is the amalgamation of multiple sources of
data, including the Minimum Data Set, CMS’s Nursing
Home Compare, ARF, Bureau of Labor Statistics, Residential
History File, OSCAR/CASPER, and state policy surveys.
The Medicare Cost Reports provide financial data for nurs-
ing homes that participate in the Medicare program. The
ARF dataset contains county-level information on socioeco-
nomic status, population demographics, and environmental
characteristics.57 The Florida assisted living data are the
annual licensed provider lists housed by the Agency for
Health Care Administration,58 which provided insights into
the number and type of assisted living beds operated in the
state of Florida for the study period.

Sample

The sample consisted of all the nursing homes in the state of
Florida from 2003 through 2015. There were 8889 nursing
home-year observations in Florida from 2003-2015. First,
we excluded hospital-based nursing homes observations (n
= 211). Second, we excluded all nursing homes observa-
tions that reported no Medicare payments (n = 123), and
other nursing homes observations that had incomplete or
skewed financial data (n = 867). Because this study was
focused on examining all nursing homes in counties with
assisted living capacity, we excluded counties without a
licensed assisted living (roughly 7 counties and 76 nursing
home observations). This resulted in an analytic sample
comprised of 7688 unique nursing home-year observations
across the 13 years, with approximately 657 nursing homes
in a given year.

Measures

The dependent variable for hypothesis 1 and 3, financial per-
formance, was operationalized as the operating margin,59,60

Figure 1. Conceptual model.

Lord et al 5

which focuses on core business functions and excludes the
influence of nonoperating income like endowments and non-
operating expenses such as interest payments. As such, it
measures the percentage profitability as a result of resident
revenues and costs. It is calculated as follows:

Operating margin

operating revenue

operating expenses
=

−









operating revenue
.

The dependent variable for hypothesis 2 consists of the occu-
pancy rate, a facility-level variable that represents the num-
ber of occupied beds as divided by the total number of beds
within a nursing home.

The independent variables included total assisted living
beds (hypothesis 1-3) and occupancy rate (mediator in
hypothesis 3). We specified assisted living beds as the num-
ber of beds per 1000 individuals 65 years and older. This
variable was lagged for 1 year to account for the potential
lagged influence on financial performance. Occupancy rate
was calculated as discussed above.

Control variables included organizational and environ-
mental factors that may impact nursing home financial per-
formance. The organizational control variables consisted of
chain affiliation, ownership, racial/ethnic resident composi-
tion, percentage of residents covered by a Health Maintenance
Organization (HMO), and average acuity of residents. Chain
affiliation reflects whether the nursing home is part of a
chain. Ownership is a dichotomous variable that identifies
whether a nursing home is for-profit (0 = not for-profit; 1=
for-profit). Race/ethnicity shows the percentage of nursing
home residents who are Black and Hispanic. Percent of resi-
dents covered by a HMO identifies the percentage of nursing
home residents who are covered by a Medicare HMO in a

given year. Acuity index is an average measure of the resi-
dent’s level of care needed. This measure is based on the
number of residents needing various levels of assistance with
mobility, activities of daily living (ADL), special treatments,
as well as the proportion of residents who are bedfast, exhibit
dementia, and who require assistance with ambulation or
transfers.

Market control variables included competition, the num-
ber of home health agencies, the number of short-term hos-
pital beds, Medicare Advantage penetration rate, and
percentage of lower education population at the county
level. Competition is measured using the Herfindahl index,
which is the squared total number of nursing home beds as
divided by the sum of all county beds squared. This is a
continuous variable that ranges from 0 to 1. The closer to 1,
the less competitive the market for nursing homes. The num-
ber of home health agencies describes the number of home
health agencies in the county for every 1000 persons age 65
or older. Home health care agencies are one mechanism of
delivering home and community-based care. Home health
care provides less intensive care as compared with nursing
homes. The number of short-term hospital beds is the num-
ber of short-term general hospital beds in the county for
every 1000 persons age 65 or older. Hospitals represent a
supplier of residents for nursing homes, particularly for
post-acute care. Medicare managed care penetration rate is
calculated as the proportion of all Medicare beneficiaries in
the county who are enrolled in a Medicare managed care
organization (MCO). These organizations attempt to control
costs and limit utilization by steering patients to preferred
providers.61,62 Lower educational attainment is a socioeco-
nomic factor that examines the percentage of the population
with less than a high-school education. Table 1 provides a
summary of these variables.

Table 1. List of Variables With Datasets.

Dependent variable
Nursing home’s operating margin Medicare Cost Reports
Independent variables
Assisted living beds per 1000 over the age of 65 State of Florida & Area Resource File
Occupancy rate Brown University’s LTCFocus
Organizational control variables
Chain affiliation (multifacility) Brown University’s LTCFocus
Ownership (for-profit) Brown University’s LTCFocus
Percent Black Brown University’s LTCFocus
Percent Hispanic Brown University’s LTCFocus
Percentage of residents covered by health maintenance organization Brown University’s LTCFocus
Acuity index Brown University’s LTCFocus
Market control variables
Herfindahl index Brown University’s LTCFocus
Number of home health agencies per 1000 adults Brown University’s LTCFocus
Number of short-term hospital beds per 1000 adults Brown University’s LTCFocus
Medicare managed care penetration rate Brown University’s LTCFocus
Educational attainment (less than high-school) Area Resource File

6 INQUIRY

Analysis

Descriptive statistics were examined for all variables
included in the analysis. To explore the relationships among
financial performance, assisted living capacity and occu-
pancy, and test potential mediation of occupancy, we fol-
lowed Baron and Kenny’s approach and estimated 3 models
examining the relationships between (1) assisted living
capacity and nursing home financial performance, (2)
assisted living capacity and nursing home occupancy, and (3)
nursing home occupancy and financial performance after
assisted living capacity is included in the model.63 We used
generalized estimating equations, to adjust for repeated mea-
sures at the nursing home facility level and to model the
above relationships. Year fixed effects control for time trend.
The level of statistical significance was set at α = 0.05. Stata
13 was used to perform the analysis.

Results

Table 2 reports the means and standard deviations for all the
dependent, independent, and control variables. Nursing
homes, in the state of Florida, had a mean operating margin of
11.7% and an occupancy rate of 88.9%. There was an average
of 25.7 assisted living beds per 1000 individuals 65 and older.
Sixty percent of the nursing homes were chain affiliated and
78% of the facilities were classified as for-profit. The percent-
age of Blacks in a nursing home was around 23.3%, while the
percentage of Hispanics was around 15.7%. Around 15% of
all nursing home residents were covered by a Medicare HMO.
The average acuity of a nursing home resident was around

12.1. The Herfindahl index, a proxy measure for competition,
was around 0.10, suggesting a highly competitive market.
There was an average of 28 home health agencies per 1000
individuals 65 and older and around 18.3 short-term hospital
beds for the same population. The Medicare managed care
penetration rate was around 28.4%.

Assisted Living Capacity and Nursing Home
Financial Performance (model 1)

Table 3 shows the results of the generalized estimating equa-
tions for the 3 models. Hypothesis 1 was supported. Assisted
living capacity was found to have a statistically significant
negative association with nursing homes’ financial perfor-
mance (P < .05) (model 1). For each additional 10 assisted living beds (per 1000 over the age of 65 in the county), nurs- ing homes’ operating margin decreased by 1.1%. For-profit (P < .05) and chain affiliated (P < .01) nursing homes were associated with higher financial performance. However, nursing homes with a higher percentage of Black residents (P < .001) had worse financial performance. Nursing homes in less competitive markets (P < .001) exhibited higher financial performance. In markets with a higher percentage of Medicare managed care (P < .001) and a greater number of hospital beds (P < .001), the nursing homes exhibited higher financial performance. The other variables, such as percent Hispanic, percent HMO, resident acuity, number of home health agencies, and lower educational attainment were not significantly associated with nursing home finan- cial performance.

Table 2. Descriptive Statistics for Variables in the Study (N = 7688 nursing home-year observations).

Mean SD

Dependent variable
Nursing home’s operating margin 11.67% 8.04
Independent variables
Assisted living beds per 1000 over the age of 65 25.67 9.78
Occupancy rate 88.88% 9.40
Organizational control variables
Chain affiliation (multifacility) 60%
Ownership (for-profit) 78%
Percent Black 23.30% 18.58%
Percent Hispanic 15.67% 25.75%
Percentage of residents covered by HMO 14.66% 16.61%
Acuity index 12.14 1.22
Market control variables
Herfindahl index 0.10 0.17
Number of home health agencies per 1000 adults 27.91 29.18
Number of short-term hospital beds per 1000 adults 18.27 11.07
Medicare managed care penetration rate 28.41% 16.01%
Educational attainment (less than high-school) 9.88% 2.95%

Note. HMO = health maintenance organization.

Lord et al 7

Assisted Living Capacity and Nursing Home
Occupancy (model 2)

Hypothesis 2 was not supported. Assisted living capacity was
not found to have a statistically significant negative associa-
tion with nursing occupancy (model 2). In this model, it was
the racial/ethnicity variables that had a statistically significant
impact on occupancy rate. As the percentage of Black nursing
home residents (P < .05) increased, this was negatively asso- ciated with nursing home occupancy; however, an increase in the percentage of Hispanic nursing home residents was posi- tively associated with nursing home occupancy (P < .001). The increased acuity of the residents was negatively associ- ated with nursing home occupancy (P < .01). The only mar- ket-level factors that positively influenced occupancy was the number of hospital beds (P < .05). The other variables, such as chain affiliation, ownership, percent HMO, competition, number of home health agencies, Medicare managed care penetration rate, and lower educational attainment were not significantly associated with nursing home occupancy.

Assisted Living Capacity, Nursing Home
Occupancy and Financial Performance (model 3)

Hypothesis 3 was not supported. After controlling for occu-
pancy, assisted living capacity still exhibited a statistically

significant negative relationship with nursing homes finan-
cial performance (β = −0.1123, P < .05) (model 3). Even though the hypothesized relationship was not mediated by occupancy rate, it was noted that the significance of the rela- tionship between assisted living and nursing home financial performance decreased after controlling for occupancy rate. Occupancy (P < .001) was found to have a positive associa- tion with nursing home financial performance. The organiza- tional variables from the first model kept the same directional relationship with chain affiliation (P < .01) and ownership (P < .05) being positively associated with nursing home financial performance. A higher percentage of Black nursing home residents (P < .001) negatively associated with finan- cial performance. Market-level factors like Medicare man- aged care (P < .001), number of hospital beds (P < .01), and less competition (P < .001) were found to be positively asso- ciated with nursing home financial performance. The other variables, such as percent Hispanic, percent HMO, resident acuity, number of home health agencies, and lower educa- tional attainment were not significantly associated with nurs- ing home financial performance.

Discussion

The goal of this study was to examine the relationships
among assisted living capacity, nursing home occupancy,

Table 3. Generalized Estimating Equation Linear Regression: Assisted Living Capacity, Nursing Home Occupancy and Financial
Performance.

Model 1: Assisted living (IV)
and financial performance

(DV)a

Model 2: Assisted
living (IV) and occupancy

(DV)b

Model 3: Assisted living,
occupancy (DV) and

financial performance (IV)c

Coefficient (SE) P values Coefficient (SE) P values Coefficient (SE) P values

Assisted living capacity
(per 1000 over the age of 65)

−0.11 (0.05) .018* −0.02 (0.05) .678 −0.11 (0.05) .02*

Organizational variables
Chain affiliation (multifacility) 1.93 (0.75) .010** −0.06 (0.79) .936 1.94 (0.75) .010**
Ownership (for-profit) 2.22 (0.95) .019* −1.50 (0.99) .129 2.40 (0.94) .011*
Percent Black −0.07 (0.02) .001*** −0.05 (0.02) .033* −0.07 (0.02) .001***
Percent Hispanic −0.02 (0.03) 0.443 0.11 (0.03) .001*** −0.03 (0.02) .197
Percent HMO −0.02 (0.03) 0.437 0.04 (0.03) .125 −0.03 (0.03) .331
Acuity index −0.31 (0.34) .365 −0.99 (0.35) .005** −0.19 (0.33) .578
Market variables
Competition 16.52 (4.28) .001*** 6.59 (4.46) .139 15.73 (4.25) .001***
Home health agencies 2.84 (1.52) .063 0.33 (1.59) .837 2.80 (1.51) .064
Hospital beds 0.14 (0.41) .001*** 0.11 (0.04) .008** 0.12 (0.04) .003**
Medicare MCO 0.14 (0.04) .001*** −0.08 (0.04) .074 0.14 (0.05) .001***
Educational attainment −0.35 (0.20) .075 −0.26 (0.21) .210 −0.32 (0.20) .102
Occupancy 0.12 (0.04) .001***
Constant 11.36 (4.92) 103.75 (5.13) –1.02 (6.21)

Note.Year fixed effects control for time trend. IV = independent variable; DV = dependent variable; HMO = health maintenance organization;
MCO = managed care organization.
aModel 1: Operating margin = f (assisted living capacity, control variables).
bModel 2: Nursing home occupancy = f (assisted living capacity, control variables).
cModel 3: Operating margin = f (assisted living capacity, nursing home occupancy, control variables).
*P < .05. **P < .01. ***P < .001.

8 INQUIRY

and the financial performance of nursing homes in the state
of Florida from 2003-2015. We hypothesized that increased
levels of assisted living capacity would be associated with
both lower nursing home occupancy and worse nursing
home financial performance, and that occupancy may be a
mediator between assisted living capacity and financial per-
formance. Our findings suggest that assisted living capacity
does have a negative impact on nursing homes’ financial per-
formance, and that the relationship between assisted living
capacity and financial performance was not mediated through
occupancy. However, the increased assisted living supply
may create additional financial/competitive pressures, such
as more acute residents that can result in decreased nursing
home financial performance. In addition, the increase of
assisted living supply result in higher operating costs as nurs-
ing homes potentially have to increase spending on market-
ing and other amenities to remain competitive in the market.
These findings suggest assisted living is not a “true” substi-
tute service for nursing home care, as it does not impact nurs-
ing home occupancy. Yet, assisted living communities could
be viewed as another indirect competitor in the long-term
care industry, thus potentially dampening the profitability of
the existing nursing homes.

Assisted living capacity was not found to significantly
lower nursing home occupancy. This may have been a result
of nursing homes reacting and adjusting to their environ-
ment. It is possible that when nursing homes were facing
decreasing occupancy, they evolved and focused more of
their business to skilled nursing, as to reduce the potential
impact of having fewer long-term care residents. According
to the National Health Expenditure Survey, the percent nurs-
ing homes’ total revenue coming from Medicare has almost
doubled from 13% in 2000 to 24% in 2015.64 The potential
loss of long-term care residents may have been tempered
with an increase in skilled nursing residents.

It is important to note the relationship between the organi-
zational variables in the selected models. In the first (assisted
living and financial performance) and the third model
(assisted living, occupancy, and financial performance),
chain affiliation and for-profit ownership were both posi-
tively and statistically associated with financial performance.
Chain-affiliated nursing homes may have greater access to
resources and thus better financial performance. For-profit
organizations have a responsibility to maximize shareholder
wealth, so these organizations may focus on decreasing costs
and increasing profitability. Neither of these organizational
factors had any impact on occupancy, indicating that finan-
cial performance may be under management discretion,
while occupancy may be driven by market factors, such as
more demand for post-acute care services (ie, higher supply
of hospital beds).

In this study, nursing homes that had a higher percentage of
Black residents had worse financial performance and occu-
pancy. The financial performance finding was concerning but
not surprising given the documented racial disparities in

long-term care.65 Nursing homes located in areas with large
minority populations have been found to have worse financial
and operational performance.66,67,68,69 In addition, nursing
homes with a higher percentage of Black residents had lower
occupancy rate. This may be a result of socioeconomic and
segregation factors. Blacks are more likely to be placed in
nursing homes that have greater financial vulnerability, lower
levels of staffing and worse quality, as compared with
Whites.69 Nursing home quality has been shown to vary with
socioeconomic70,71 and geographic differences.72,73,74 Nursing
homes that are located in communities with higher rates of
poverty and minorities are likely to have worse quality.75
Nursing homes that have worse quality could be less attractive
to potential residents and thus have the lower occupancy. This
has implications for quality in the delivery of long-term care.

On the contrary, occupancy rate was positively associated
with a higher percentage of Hispanic residents. This may be
attributed to the growth of the Hispanic population in Florida.
The Hispanic population in Florida (24.9%) is much higher
relative to the rest of the United States (17.8%).76 In Florida,
Hispanics are the largest minority in Florida77; they also have
tremendous purchasing power and are the fastest growing
consumer segment in Florida. With the recent disasters of
Hurricane Irma and Maria, it is forecasted that the migration
of Puerto Ricans and others moving to Florida permanently
will lead to a permanent net increase of over 53 134
Hispanics.78 This may explain the increase in occupancy and
the percentage of Hispanic residents.

Nursing homes with greater resident acuity were associ-
ated with lower occupancy rate. This may be symptomatic of
a larger national trend of falling nursing home occupancy
and worsening resident acuity.79 This may also be reflective
of the perceived quality of the nursing home. Individuals
make subjective assessments about the quality of nursing
home care service through various determining factors.80
Worsening resident acuity may be interpreted, by potential
residents, as an indicator of resident quality. Individuals may
choose to avoid nursing homes that they perceive as having
worse care.

The market-level variable, Medicare managed care was
positively associated with nursing home financial perfor-
mance. Although this may seem counterintuitive, it is impor-
tant to recognize that Medicare post-acute spending has
doubled from 2001 to 2013 and now accounts for 10% of all
long-term care spending.81,82,83 In 2015, Medicare reimburse-
ments for skilled nursing, post-acute care, on average,
accounted for 24% of a nursing homes revenue.64 These dol-
lars represent an increasingly crucial revenue stream for most
nursing homes.84 As of 2016, over 30% of Medicare benefi-
ciaries had their coverage administered through a Medicare
MCO.85 Although Medicare MCOs may attempt to control
costs and limit utilization62 by restricting provider networks
and adjusting post-acute cost-sharing arrangements,85,82 their
ability to steer Medicare skilled nursing patients may still be
financially beneficial for the nursing home. This may help

Lord et al 9

explain why their presence has had a positive association with
nursing home financial performance.

The Herfindahl index, a proxy for competition was posi-
tively associated with financial performance. As the market
became more monopolistic, the higher the financial perfor-
mance of the nursing home. These findings suggest that nurs-
ing homes in these markets faced less competition relative to
other markets and thus have higher levels of profitability.

An increase in hospital beds was associated with higher
financial performance and occupancy within a nursing home.
This finding is understandable, given the supply and demand
relationship that has developed between freestanding nursing
homes and hospitals. Thinking of the supply–demand rela-
tionship, nursing homes in markets with a higher number of
hospital beds should expect to see more patients who need
skilled nursing care after discharge. The influx of patients
into nursing homes can have a positive impact on nursing
homes occupancy and ultimately financial performance.
Nursing homes with a higher Medicare resident census typi-
cally have better financial and operating performance.56
Nursing homes, that provide skilled nursing care, will want
to have favorable relationships with hospitals as to maximize
the number of Medicare referrals. Nursing homes will pros-
per and or suffer based on their ability to gain those resources.

There are several limitations of this study. The observed
relationship between assisted living capacity and financial
performance may be endogenous. Assisted living communi-
ties are located in markets with disproportionally higher edu-
cational attainment, income, and wealth.14,86 Other factors of
competition, supply, demand, or other unobservable variables
may be linked to both higher occupancy and better financial
performance. Second, our study was limited to respondents in
the state of Florida. This state is unique as it relates to the high
proportion of aging individuals and the large presence of
assisted living communities.18,19 Also Florida is unique in that
it has recently moved away from the waiver programs and has
deployed a SMMC LTC.48 These unique factors dealing with
the state of Florida may limit the generalizability of these
findings. Third, this study did not capture any data on the
impact of HCBS, which is an important supplier of long-term
care services. Future studies should examine the relationship
between assisted living capacity and financial performance
among more markets and states. Despite the limitations of
this research, this study makes an important contribution to
the literature on the examination of the competition through
assisted living capacity, nursing home occupancy, and finan-
cial performance. Future research needs to examine the future
effects of assisted living capacity and of quality care in the
nursing home industry.14

Conclusion

Nursing homes often provide long-term care services to
some of the nation’s sickest, frailest, financially and socially
vulnerable individuals in long-term care.87 For nursing

homes to remain operational, they must remain profitable
and financially solvent. In 2012, the average total facility
margin was only 2.1%, and with profit margins that low,
there is not a lot of room for error.16 As this research found,
assisted living capacity has the potential to further depress
nursing home financial performance.

Nursing home administrators must make decisions to pro-
tect the financial viability of nursing homes, while finding
ways to deliver high quality care. This is done through a
combination of increasing revenue and decreasing costs.
Increasing the occupancy rate has been one way to improve
a nursing homes financial performance.88 However, occu-
pancy rates can be impacted by market factors, such as
increased competition. Policy makers need to recognize the
potential negative effects that indirect competitors can have
on nursing homes. If nursing homes are not able to maintain
adequate profit margins, they may ultimately close, which
can have future access implications. Additional research is
needed to examine the other impacts that increased competi-
tion from assisted living can have on nursing home quality,
staffing, performance, and survival.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect
to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, author-
ship, and/or publication of this article.

ORCID iD

Justin Lord https://orcid.org/0000-0002-4557-955X
Robert Weech-Maldonado https://orcid.org/0000-0002-5005-0909

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Medicare Advantage 2015 Spotlight: Enrollment Market Update

Medicare Advantage 2015 Spotlight: Enrollment Market Update

Medicare Advantage 2015 Spotlight: Enrollment Market Update