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Fall related injuries among older adults in the Los Angeles region
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Fall related injuries among older adults in the Los Angeles region
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Content
FALL RELATED INJURIES AMONG OLDER ADULTS
IN THE LOS ANGELES REGION
by
Caroline Cicero
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(GERONTOLOGY)
December 2010
Copyright 2010 Caroline Cicero
ii
ACKNOWLEDGMENTS
“Live as if you were to die tomorrow. Learn as if you were to live forever.”
--Mahatma Gandhi
To my steadfast and loving partner and husband, Craig, with whom, at a tiny little
restaurant off Main Street, I started this California Dream more than 20 years ago. Thank
you for loving me, for encouraging me, and for making “having it all” possible.
To my amazing kids, Theo, and Zoe, who were just 3 and 6 when I started my PhD five
years ago and have kept me alive through it all, with hope, joy, and serious perspective!
To my parents Jan and Frank and sister Erica, whose ongoing love and support never fails.
To my grandmothers-Adelyn Anderson Pickett and Maria Magherita Balma Cicero-who
sparked my interest in ethnic populations, aging, senior housing, and end-of-life care.
To all those pilots whose flights made me wonder who lives in the neighborhoods below.
To the USC Student Health Center and USC Norris Cancer Center. To Dr. Lisa
Richardson, who told me not to blow off the lump in my neck. To Elizabeth and Dr.
Dennis Holmes for paying attention to that lump when others did not. To Dr. Anne
iii
Mohrbacher and the incredible day hospital nurses who got me through the worst six
months of my life, even when the sight of you made me sick. To my fellow PhD students,
Culver City community, long time friends, mother-in-law Jill, Aunt Nancy, and Elizabeth
and Lesley, who fed me and my family and played with my kids in those trying days. To
my church community, and Marianne and Chrissy, who held me up. To all those angels
across the country and world who knitted, called, prayed and sent cards, messages and
flowers. Truly, every day is a gift!
To Drs. Jon Pynoos, Dowell Myers, Susan Enguidanos, Phoebe Liebig, and Kate Wilber
for all their encouragement and guidance and for teaching me to say it once the right way,
peel an onion, speak truth to power, and capitalize on windows of opportunity.
To Maria Henke, Jim Devera, Linda Broder, and all the hardworking staff at the USC
Leonard Davis School of Gerontology.
To the Archstone Foundation for having the generous vision for reducing falls.
To my new communities in Malibu and Pepperdine, especially Dr. Priscilla MacRae, for
welcoming me with hospitality, greener pastures, and the ocean view from which I write.
iv
To my high school journalism teacher, John Reque, who taught me to investigate and
report, and who complimented me just once by calling me “tenacious.”
To God, for letting me see this day and opening doors for me tomorrow! Hallelujah!
v
TABLE OF CONTENTS
Acknowledgments ii
List of Tables vi
List of Figures ix
Abstract xii
Chapter 1: Introduction, Falls Among Older Adults: 1
A Growing Health Problem
Chapter 1 References 18
Chapter 2: Literature Review 20
Chapter 2 References 35
Chapter 3: Demography of the Los Angeles Region’s Older Population 41
Chapter 3 References 88
Chapter 4: The Los Angeles Region’s Community Dwelling 90
Hospitalized Fallers
Chapter 4 References 109
Chapter 5: Predictors of Costs 110
Chapter 5 References 119
Chapter 6: Source of Pay 120
Chapter 6 References 135
Chapter 7: Discharge Disposition 136
Chapter 7 References 157
Chapter 8: Conclusion: A Needs Assessment for Reducing Falls 158
in the Los Angeles Region
Chapter 8 References 175
Bibliography 178
vi
LIST OF TABLES
Table 1 Baby Boomers’ Ages Projected for Each Decade 8
Table 2 Demographic Characteristics for Older Adult Population 43
Comparison of Five Counties in Los Angeles Region, 2000
Table 3 Demographic Characteristics for Older Adult Population 45
Comparison of Five Counties in Los Angeles Region, 2006
Table 4 Institutionalized Older Population in Los Angeles Region, 2000 51
Table 5 Institutionalized Older Population in Los Angeles Region, 2006 51
Table 6 Non Institutionalized Older Adult Population, 53
Five County Los Angeles Region, 2000
Table 7 Non Institutionalized Older Adult Population, 54
Five County Los Angeles Region, 2006
Table 8 Disability Status of 65+ Non Institutionalized Population, 55
Five County Los Angeles Region, 2000
Table 9 Type of Disability of 65+ Non Institutionalized Population: 56
Physical, 2000
Table 10 Type of Disability of 65+ Non Institutionalized Population: 57
Sensory, 2000
Table 11 Type of Disability of 65+ Non Institutionalized Population: 58
Go Outside, 2000
Table 12 Type of Disability of 65+ Non Institutionalized Population: 59
Self-Care, 2000
Table 13 Type of Disability of 65+ Non Institutionalized Population: 60
Mental, 2000
Table 14 Disability Status for 65+ Non Institutionalized Population, 61
2000
Table 15 Type of Disability of 65+ Non Institutionalized Population: 63
Go Outside, 2006
vii
Table 16 Type of Disability of 65+ Non Institutionalized Population: 64
Self Care and Mental, 2006
Table 17 Type of Disability of 65+ Non Institutionalized Population: 65
Physical and Sensory, 2006
Table 18 Los Angeles Region Median Income of Non Family 80
Households, Householder 65+
Table 19 Type of Fall for Community Dwelling, 92
Hospitalized Fallers, 2000
Table 20 Type of Fall for Community Dwelling, 94
Hospitalized Fallers, 2006
Table 21 Demographic Characteristics for Community Dwelling 98
Hospitalized Fallers, 2000
Table 22 Demographic Characteristics for Community Dwelling 100
Hospitalized Fallers, 2006
Table 23 Rate of Hospitalized Falls Per 1,000 in Population, 105
by Age, 2000
Table 24 Rate of Hospitalized Falls Per 1,000 in Population, 106
by Age, 2006
Table 25 Dependent Variable: Billed Charges, Tests of Significance 114
for Independent Variables
Table 26 Regression Coefficients Predicting Total Billed Charges 116
for Hospitalized Fallers in the Los Angeles Region, 2006
Table 27 Expected Source of Pay, Tests of Significance for 123
Independent Variables
Table 28 Odds Ratios Representing Effects of Demographic 126
Characteristics, County of Residence, and Discharge
Disposition on Having Medicare as a Source of Pay
Table 29 Odds Ratios Representing Effects of Demographic 127
Characteristics, County of Residence, and Discharge
Disposition on Having Medical as a Source of Pay
viii
Table 30 Discharge Disposition, Tests of Significance for 145
Independent Variables
Table 31 Odds Ratios Representing Effects of Injury Type, 148
Demographic Characteristics, County, Length of Stay,
and Source of Pay on Being Discharged to a SNF
Table 32 Odds Ratios Representing Effects of Injury Type, 150
Demographic Characteristics, County, Length of Stay,
and Source of Pay on Being Discharged Home
Table 33 Odds Ratios Representing Effects of Injury Type, 152
Demographic Characteristics, County, Length of Stay,
and Source of Pay on Death in Hospital
Table 34 Three Levels of Policy and Programming Serving Older Adults 162
After They are Discharged Home Following a Fall
ix
LIST OF FIGURES
Figure 1 Five County Los Angeles Region Older Adult 10
Population Projections
Figure 2 Los Angeles Region Projected Hospitalized Fallers, 11
Ages 65+, 2000-2050
Figure 3 Five County Los Angeles Region Population Projections 12
by Race, 65+
Figure 4 Five County Los Angeles Region Population Projections 13
by Race, 85+
Figure 5 Los Angeles Region Projected Hospitalized Fallers 14
by Race, 65+
Figure 6 Los Angeles Region Age Distribution of Older Adult 46
Population, 2000
Figure 7 Los Angeles Region Age Distribution of Older Adult 48
Population, 2006
Figure 8 Los Angeles Region Older Adults Rates of Any 68
Disability, 2000
Figure 9 Los Angeles Region Older Adults Rates of Any 69
Disability, 2006
Figure 10 Los Angeles Region Older Adults Rates of Physical 71
Disabilities, 2000
Figure 11 Los Angeles Region Older Adults Rates of Physical 72
Disabilities, 2006
Figure 12 Los Angeles Region Older Adults Rates of Go Outside 73
Home Disabilities, 2000
Figure 13 Los Angeles Region Older Adults Rates of Go Outside 74
Home Disabilities, 2006
Figure 14 Los Angeles Region Older Adults Rates of Sensory 75
Disabilities, 2000
x
Figure 15 Los Angeles Region Older Adults Rates of Sensory 75
Disabilities, 2006
Figure 16 Los Angeles Region Older Adults Rates of Self-Care 76
Disabilities, 2000
Figure 17 Los Angeles Region Older Adults Rates of Self-Care 77
Disabilities, 2006
Figure 18 Los Angeles Region Older Adults Living Alone, 2006 78
Figure 19 Los Angeles Region Median Household Income, 79
Householder 65+, 2006
Figure 20 Percent of All Households in Los Angeles Region Counties 80
with Social Security Income
Figure 21 Percent of All Households in Los Angeles Region Counties 81
with Supplemental Security Income (SSI)
Figure 22 Los Angeles Region, 65+ Household Income 82
Figure 23 Hospitalized Falls Incidences of Older Adults 96
in the Los Angeles Region
Figure 24 Age Distribution of Hospitalized Fallers, 2000 101
Figure 25 Age Distribution of Older Adult Population, 2000 103
Figure 26 Age Distribution of Hospitalized Fallers, 2006 103
Figure 27 Age Distribution of Older Adult Population, 2006 104
Figure 28 Rate of Hospitalized Falls Per 1,000 in Population, 2000 105
Figure 29 Rate of Hospitalized Falls Per 1,000 in Population, 2006 107
Figure 30 Mean Billed Charges of Hospitalizations from Older Adult 111
Falls by Los Angeles Region County, 2006
Figure 31 Percent of All Households in Los Angeles Region Counties 131
With Social Security Income
xi
Figure 32 Percent of All Households in Los Angeles Region Counties 132
with Supplemental Security Income (SSI)
Figure 33 Discharge Model Following a Community Dwelling Older 137
Adult’s Hospitalization for a Fall Related Injury
Figure 34 Discharge Disposition of 65+ Hospitalized Fallers in the 138
Los Angeles Region
Figure 35 65+ Hospitalized Fallers Discharged to a Skilled Nursing 140
Facility
Figure 36 Percentage of Hospitalized Fallers in Each County Discharged 141
to a Skilled Nursing Facility
Figure 37 65+ Hospitalized Fallers Who Died in the Hospital 142
Figure 38 65+ Hospitalized Fallers Discharged Home 143
Figure 39 Percentage of Hospitalized Fallers in Each County 144
Discharged Home
xii
ABSTRACT
This study is a comparative analysis of community dwelling older adults who
were hospitalized after falling in five Los Angeles Region counties: Los Angeles, Orange,
Riverside, San Bernardino, and Ventura. It provides a current demographic assessment,
future public health projections, and a planning response for local governments. Nearly
30,000 of the Los Angeles Region’s 1.8 million older adults were hospitalized for falls in
2006. Aging Baby Boomers will cause the Region’s older population to swell to over 5
million by the year 2050. The Region’s hospitalizations for fall-induced injuries cost
Medicare and Medi-Cal over $1.3 billion in 2006. However, according to projections,
the costs will increase dramatically by 2020, when over 40,000 older adults will be
hospitalized for falls each year. By the year 2035, hospitalizations for falls will reach
60,000 per year, increasing through 2050. The older population of the Region is more
diverse than the national population of older adults. Analysis of fallers’ billed charges,
sources of pay, and discharge disposition in the Los Angeles Region found that White
fallers are most costly to the federal Medicare system and non-White fallers have lower
rates of Medicare utilization. Higher billed charges and high Medi-Cal utilization for
falls among Latino, Asian, African-American, and Other race fallers are costly to the
State of California. The majority of fallers are discharged to a Skilled Nursing Facility
(SNF), and those with SNF discharge were older, had longer lengths of stay, and higher
billed charges. They were more often White. Patients discharged to their homes were
younger, had shorter hospital stays, and had lower billed charges. Asian and Latino
fallers had high home discharge rates. While the primary public economic impact of falls
xiii
is on federal and state programs, it is in local jurisdictions where falls occur, where
rehabilitation and long term care after hospital discharge must be provided, and where
repeat falls and injuries can be prevented through targeted programming and urban
planning policy that supports aging in place. Fall prevention initiatives for local
governments are presented.
1
CHAPTER 1: INTRODUCTION
Falls Among Older Adults: A Growing Public Health Problem
Falls among older adults are a growing public health problem. They are the
leading cause of older adult injury and injury-related death. Each year, one out of three
adults ages 65+ and one half of all 85+ year olds fall. More than 16,000 older Americans
die as a result of their fall related injuries every year (CDC, 2005). In 2006, 2.1 million
older Americans were treated in emergency departments (ED) for non-fatal falls (Owens,
et al., 2009), up from 1.8 million in 2005 (CDC, 2005). Whereas 24 percent of those
treated in ED’s were hospitalized for their injuries in 2005 (CDC, 2005), nearly 30
percent were hospitalized in 2006 (Owens et al., 2009).
Falls are costly. The nation’s direct medical expenditures for nonfatal falls were
$19 billion in 2006. By 2020, the federal financial cost of fall-related injuries among
older adults is expected to reach $40 to 55 billion (Englander, et al. 1996; Stevens et al,
2006). As the nation’s Baby Boomers age over the next several decades, and health care
expenses rise, the costs of falls will increase dramatically.
After an older person’s fall, hospitalization and medical costs are usually billed to
Medicare, burdening the nation’s federal health insurance program for older people. In
California, when an older, low income, Medi-Cal recipient is hospitalized following a fall,
charges are billed to the Medi-Cal system, impacting both the federal government and the
State of California. The costs of falls are on the rise. In the five-county Los Angeles
2
Region, hospitalizations following older adult falls cost Medicare and Medi-Cal over
$1.3 billion in 2006, more than double the costs in 2000. The Region’s private insurance
companies paid another $65 million for billed hospitalization charges in 2000 and $102
million in 2006.
The public economic impact of falls affects the federal and state governments’
health expenditures. Therefore, falls among older adults are a growing concern in aging
policy and the public health fields. However, it is in local jurisdictions where falls occur
and where rehabilitation and long term care following hospital discharge must be
provided. Therefore, aging policy, public health policy and local policy require a
threefold symbiotic relationship. Utilizing federal Older Americans Act funding, some
local governments have set up fall prevention programs for older adults in their
communities.
The Centers for Disease Control and Prevention (CDC) offer demographic
profiles of older adults most at risk for falls (CDC, 2009) so that local governments can
target their programming to those most in need. However, CDC statistics are based on
the national population, and the older population of the Los Angeles metropolitan area
differs demographically from the national population of older adults. For example,
national studies that compare White fallers to African-American fallers omit two large
3
cultural groups living in Southern California. The proportion of Asians
1
and Latinos
2
in
the Los Angeles Region is much greater than in national samples, and the proportion of
African-Americans in the Los Angeles Region is much smaller than in other major
metropolitan areas. National directives for preventing falls that cite statistics comparing
outcomes of White and African-American falls do not provide Californians with adequate
information to address falls in their populations. Therefore, this study examines the
demographic profiles of older hospitalized fallers in the Los Angeles Region and their
representation within the Region’s older population.
This study is a comparative analysis of community dwelling older adults who
were hospitalized after falling in five Southern California counties. Collectively called
the Los Angeles Region, the five counties that comprise the metropolitan area include:
Los Angeles, Orange, Riverside, San Bernardino, and Ventura. Hospitalization data is
drawn from the State of California Office of Statewide Health Planning and Development
1
Asians, Asian-Americans, and Pacific Islanders together will be referred to as Asians.
Caucasians will be called Whites. Blacks will be called African-Americans. Because of
their limited numbers, Native Americans and Native Alaskans are included in Other races,
which also include Mixed Races and Unknown Races.
2
Latino is used throughout to describe older adults of Latin-American and Spanish
origins, culture, or ethnicity, regardless of race (Gassoumis et al. 2010; Office of
Management and Budge, 1997). Census data and OSHPD hospitalization data utilize the
word Hispanic for ethnicity that may apply to people of varying races. However,
Categorization of Latino throughout these chapters follows the California Department of
Finance and Myers’ (2007) method of treating Hispanics as a racial category, and
removing them from other racial groups both in Census data and OSHPD hospitalization
data. The professional choice used herein is to use the word Latino in place of Hispanic
and to treat Latinos as a race. This is consistent with the Los Angeles County
Department of Public Health’s methodology (Sternfeld & Culross, 2008).
4
(OSHPD) Hospital Patient Discharge Database. OSHPD is a department within the
California Health and Human Services Agency. Discharge data from 2006 is the most
current information set available, and 2000 data will provide a comparison of changes in
hospitalizations over a six year period.
In order to understand the scope of the public health problem of older adult falls
in the area and the potential impact of falls in the Region’s future, this study also
comparatively analyzes the hospitalized fallers within the context of the Region’s present
and future older adult population (ages 65+). Population data used includes 2000
Decennial Census data (SF 3), 2006 American Community Survey data, and California
Department of Finance Population projections. At the time of this writing, Census 2010
has been recently administered, and data is not yet available.
A Regional Perspective: Addressing Falls Through the Comparison of Five Counties
This five county comparative analysis is intended to promote collaboration among
local governments, their planners, and private citizens towards mitigating the growing
public health problem of falls among older adults in Southern California. The resident
populations of neighboring cities and counties are dynamic. Individuals and families
migrate between municipalities, and as consumers of most resources, they are not bound
by city or county lines. Broad policy issues such as air pollution, homelessness,
transportation, housing, immunizations, and economic development are regional issues
5
where the health of one entity affects the other and where what happens in the Region
impacts State and federal budgets and environmental health.
Falls among older adults have a similar position, because individuals in the
population intersect with different geographical locales and no one public or private
agency is responsible for falls. The state and county health departments track falls
injuries through OSHPD discharge data. However, the problem of falls among older
adults is a multifaceted crisis that addresses issues that are larger than municipal or
county boundaries, such as mortality and morbidity, environmental design, long term care,
health care provision, and health insurance utilization. Local governments working
together to address problems, such as falls, both recognize the need to prevent injury
among the Region’s increasing older population and affirm the impact that the Region’s
falls have on the nation’s and state’s health care expenditures.
Although the older adult population may not confine itself within distinct local
boundaries, hospital discharge data categorizes patients by counties for public health
purposes. Furthermore, analyzing falls in the geographical context of each county’s
population is vital for federal and state mandates and funding which fall within
jurisdictional lines. Area Agencies on Aging, public health departments, social service
agencies, and some housing and transportation authorities operate within counties and
serve their respective publics. Furthermore, cities also operate housing, transportation,
public works, parks and recreation, and risk management departments that can address
the problem of falls. While elected officials in each jurisdiction have powerful authority
6
over how federal and state funding is spent, they must protect the interests of their
constituents. However, recognition that the problem of falls will hinder our collective
future can motivate an intergovernmental collaboration, leading to coordinated action and
a more prudent use of resources.
Population and Geography
The population dynamics of older adults in the Los Angeles Region are
compelling. Together, the five counties that comprise the Region include more than 170
cities and numerous unincorporated areas (Wolch, Pastor, Dreier, 2004). More than 16
million people live in the Region, which spans 35,000 square miles (with 14,000 of them
being inhabited), and 1.8 million of them are older adults (2006 ACS, Table B18001).
The US Census Bureau labels the five county Los Angeles Region as a Los
Angeles-Long Beach-Riverside Combined Statistical Area (CSA). As the second largest
CSA in the nation behind New York, the CSA combines three former Metropolitan
Statistical Areas that cover the five area counties (Rosenberg, 2003). The older adult
population (ages 65+) in the five county Los Angeles Region is comparable to the entire
populations of Nebraska or West Virginia. There are more older adults living in the Los
Angeles Region than the entire populations of each of the 12 following states: Alaska,
Delaware, Hawaii, Idaho, Maine, Montana, New Hampshire, North Dakota, Rhode Island,
South Dakota, Vermont, and Wyoming (2000 Decennial Census SF-1, Table P1).
7
A side by side comparison of the Region’s five counties paints a portrait of the
area’s diversity. Los Angeles County, whose broad boundaries contain the City of Los
Angeles and 87 other incorporated cities, has a very diverse population itself.
Incorporated in 1850, the City of Los Angeles is no longer a central business district with
concentric circles of residential communities radiating out. Instead, it is at the center of
the county and a metropolitan Region, of nearly 4 million residents. The County’s second
largest city, Long Beach, has a population of nearly half a million.
By 2040, it is estimated that the Region’s four surrounding counties will equal
Los Angeles County’s in population (Wolch, Pastor, & Dreir, 2004). To the south,
Orange County, was developed as post-World War II single-family home communities.
Two of them now house more than 300,000 each—Santa Ana and Anaheim--and their
racial/ethnic profiles have changed dramatically in recent years. Inland, San Bernardino
and Riverside Counties have exploded in population in recent decades with planned
commuter-based exurbs and large scale retail. To the north, Ventura County remains the
least populated and most undeveloped part of the Region, with smaller bedroom
communities and an enduring agricultural industry.
Regional Projections
This comparative analysis of five neighboring counties provides urban planners,
social service providers, and public health professionals with the opportunity to compare
the prevalence of falls in their own population to that of their neighbors’. The four
8
smaller counties, whose populations will grow more diverse in coming years, can observe
how Los Angeles County’s falls incidences reflect its unique population profile. In the
future, lessons learned from targeting fall prevention towards specific segments of the
population can be shared towards the common goal of reducing falls everywhere.
Addressing the problem of falls within the context of the older adult population
and its impending growth presents an opportunity to reconnect urban planning and public
health (Abbott, 2009; Corburn, 2004; Frumkin et al, 2004; Kochtitzky, et al., 2006). The
Region’s population is undergoing a demographic transition over the next four decades
(Myers, 2007). In 1990, older adults in the Region totaled 1.4 million (Census, 1990,
Table P011). Ten years later in 2000, 1.6 million older adults lived in the Region
(Census, 2000, Table P 12), and in 2006, two hundred thousand more older adults (1.8
million) resided in the Region (ACS, 2006, Table B18001). The projected transition
between 2010 and 2050, however, is unprecedented.
As in most states across America, the aging of the Baby Boomer cohorts will
dramatically increase the size of the Region’s older adult population. Baby Boomers
consist of two cohorts. Early baby boomers were born 1946 – 1954. Late baby boomers
were who born 1955 to 1964 (Myers, 2007). Table 1 shows how the Baby Boomer
cohorts will age over the next 40 years.
Table 1
Baby Boomers’ Ages Projected for Each Decade
2000 2010 2020 2030 2040 2050
Early Boomers 45-54 55-64 65-74 75-84 85-94 95-104
Late Boomers 35-44 45-54 55-64 65-74 75-84 85-94
9
In the Los Angeles Region, vast communities of Baby Boomers will be aging; the
majority of them live in suburbs and exurbs across the five counties. From a labor
market perspective, the dramatic demographic shift is over the next 20 years, between
now and 2030, when all the Baby Boomers turn 65 (Myers, 2007). Indeed, by 2030,
over 4 million adults ages 65+ will live in the Los Angeles Region, as shown in Figure 1
below, and half a million of them will be ages 85+.
However, from a public health perspective concerned about those older adults
most vulnerable to falls, the demographic transition over the two decades between 2030
and 2050 is most compelling. In 2050, the youngest baby boomers will have reached age
85. The entire older population will swell to over 5 million by 2050, with over one
million 85+ year old Baby Boomers. Based on these population figures, it is estimated
that every year, over 60,000 older adults in the Region will be hospitalized for falls
beginning in the year 2035 and continuing beyond 2050. Figures 1 and 2 below depict
the transition and increase in hospitalized fallers.
10
11
Race
The aging of the Baby Boomer population is one component of the demographic
transition facing the Region and the nation at large. California and the Los Angeles
Region are at the forefront of the racial and ethnic demographic transitions also facing the
nation (Myers, 2007). The most dramatic change is in the Latino population, which is
growing in all corners of the Region. Latino Baby Boomers will have a large impact on
the Region (Gassoumis, Wilber, & Torres-Gil, 2008). Figure 3 shows that the 65+
White population will peak in 2030 and then decline, while the 65+ Latino population
12
will swell to over 2 million in 2040. The Asian older adult population will continue to
rise as well, to a million in 2050.
Comparing Figure 3 to Figure 4 indicates that the size of the 85+ Latino
population will surpass the 85+ White population approximately a decade after the size of
the 65+ Latino population outgrows the 65+ White population. By 2050, over half a
million Latino 85+ year olds are projected in the Los Angeles Region. For all racial
groups, the 85+ population will continue to rise through 2050. White 85+ year olds will
13
total more than 450,000, and Asian 85+ year olds will total more than 250,000 in 2050.
These 85+ year olds will be at high risk for falls. Chapters 4-7 will discuss the
relationship between age and race in the Region’s hospitalized fallers.
With a Regional population that has aged and changed in racial and ethnic
composition, the demographics of projected hospitalized fallers’ will change over the
next four decades. Figure 5 shows that the aging of White Baby Boomers will lead to
over 30,000 hospitalized falls across the Region in 2030. However, as the proportional
population of White older people declines in 2040 and 2050, so will the White
hospitalized fallers. On the other hand, as shown in Figures 3, 4, and 5 , the rising Latino
14
older population suggests that over 25,000 Latino older adults will be hospitalized for
falling per year by 2050. Hospitalized fallers among older Asians in the Los Angeles
Region will rise at a steady rate also, to just under 10,000.
With the number of older people hospitalized for fall related injuries rising
dramatically in the coming decades, hospitalization bills and direct medical costs will rise
exponentially. Billions of dollars in Medicare and Medi-Cal dollars will be spent by the
United States and California governments to pay for these hospitalizations.
Acknowledging this fiscal impact, the federal government has been encouraging states
and local governments to implement fall prevention programs, funded through the Older
15
Americans Act, in senior centers and community centers. While local governments in the
five Los Angeles Regional counties are beginning to recognize the problem of falls and
consider implementing fall prevention programs, it is important that they target their
programs towards those elders in their populations who are most at risk. Therefore, this
study analyzes the demographic characteristics of hospitalized fallers, ages 65+, in the
five counties of the Los Angeles Region--Los Angeles, Orange, Riverside, San
Bernardino, and Ventura—in relation to their populations within each county and the
Region. By analyzing the characteristics of older adults hospitalized for falls in each
county in relation to the broader older adult population, it will be determined which
demographic groups are most appropriate targets of fall prevention funding and
programming.
Research Questions
Research has shown that the problem of falls among older adults is a key public
health issue of the future. Taking a long term view, the federal CDC and Administration
on Aging encourage states and local governments to address the problem. Furthermore,
in California, the Department of Aging (CDA) and CDPH have highlighted the problem
of falls in recent years. Because of their collective population size proportional to both
the State and the nation and because of the potential state and federal fiscal impacts of
falls, this study analyzes the five Los Angeles Regional counties side by side so that local
16
policy makers can examine their fallers’ profiles in comparison with their neighbors’. To
this end, the comparative analysis will address the following broad research questions:
1. Based on what we know about the national demographics of older adult falls, how
do the five counties in the Los Angeles Region--Los Angeles, Orange, Riverside,
San Bernardino, and Ventura--compare? What are the demographic
characteristics of the hospitalized fallers in each county?
2. How do the each county’s fallers compare to their older adult populations at
large?
3. How will demographic transition impact the public health problem of falls in the
coming decades? What will be the profile of Region’s fallers over the next 40
years?
4. How do the outcomes of hospitalizations for falls compare across counties? What
are the costs? Who pays for hospitalization? Where are patients discharged?
Chapter 2 provides a literature review of relevant previous research. Chapters 3
and 4 provide descriptive statistics of the Los Angeles Region older adult population and
its hospitalized fallers. Chapters 5, 6, and 7 will address specific research questions
pertinent to hospitalization-related and population variables. Data analyzed comes from
the following sources: OSHPD Hospital Patient Discharge Data, 2000 Decennial Census,
2006 American Community Survey, and Department of Finance Projections.
17
Chapter Outline
Chapter 2 Literature Review
Chapter 3 Demography of the Los Angeles Region’s Older Population
What are the demographic profiles of the Region’s older adults, in terms of age, race,
gender, income level, and disability status? How do they compare across the five
Regional Counties?
Chapter 4 Demography of the Los Angeles Region’s Hospitalized Fallers
What are the demographic profiles of the Region’s hospitalized fallers in terms of age,
race, gender, and fall rates? How do they compare across the Region’s five
counties?
Chapter 5 Costs of Los Angeles Region’s Falls
What demographic variables, if any, predict billed cost-related hospitalization
outcomes in Los Angeles Region’s fallers? Are age, race, source of pay, county, and
discharge disposition predictors of billed charges of hospitalized fallers?
Chapter 6 Source of Pay for Hospitalizations from Falls
What are the mean differences in fallers’ age, length of stay and hospitalization
charges depending upon their insurance coverage? What demographic characteristics,
if any, are associated with utilization of Medicare and Medi-Cal as payment for the
hospitalizations of the Los Angeles Region’s fallers?
Chapter 7 Discharge Disposition of Los Angeles Region’s Fallers
What are the hospitalization costs associated with different discharge disposition?
How do discharge dispositions differ by County within the Los Angeles Region and
between Medicare and Medi-Cal patients? What are the demographic differences
related to fallers’ discharge disposition?
Chapter 8 Conclusions and the Role of the Local Government in Fall Prevention
How can risks, costs, and repercussions of falls be minimized? What policies,
programs, and practices could mitigate risks, falls, and costs of falls in the Los
Angeles Region’s five counties?
18
CHAPTER 1 REFERENCES
Abbott, P. (2009). Public Health and the Built Environment. In P.S. Abbott, N. Carman,
J. Carman, & B. Scarfo (Eds.), Re-Creating Neighborhoods for Successful Aging
(pp. 23-32). Baltimore: Health Professions Press.
American Community Survey, 2006, Table B18001.
CDC, 2005. Centers for Disease Control and Prevention, National Center for Injury
Prevention and Control. Web–based Injury Statistics Query and Reporting System
(WISQARS) [online]. Retrieved on January 23, 2010 from
www.cdc.gov/ncipc/wisqars.
CDC, 2009. Falls Among Older Adults: An Overview. Retrieved Jan. 4, 2010 from
http://www.cdc.gov/HomeandRecreationalSafety/Falls/adultfalls.html#.
Census (1990) Decennial Census, Summary Tape File Table P011.
Census (2000) Decennial Census, Summary File SF-1 Table P 12.
Corburn, J. (2004). Confronting the Challenges in Reconnecting Urban Planning and
Public Health. American Journal of Public Health, 94, 4, 541-547.
Englander, F., Hodson, T.J., Terregrossa, R.A. (1996). Economic dimensions of slip and
fall injuries. Journal of Forensic Science, 41(5), 733–46.
Frumkin, H., Frank, L., Jackson, R., (2004). Urban Sprawl and Public Health.
Washington: Island Press.
Gassoumis, Z., Wilber, K., Torres-Gil, F., (2008). Latino Baby Boomers A Hidden
Population. Latinos & Social Security Policy Brief, No. 3. UCLA Center for
Policy Research on Aging, USC Ethel Percy Andrus Gerontology Center, UCLA
Chicano Studies Research Center.
Kochitzky, C., Frumkin, H., Rodriguez, R., Dannenberg, A.L., Rayman, J., Rose, K.,
Gillig, R., Kanter, T., (2006). Urban Planning and Public Health at CDC.
MMWR, Dec. 22, 2006/ 55(SUP02); 34-38.
Owens, P.L., Russo, C.A., Spector, W. and Mutter, R.. (2009). Emergency Department
Visits for Injurious Falls among the Elderly, 2006. HCUP Statistical Brief #80.
October 2009. Agency for Healthcare Research and Quality, Rockville, MD.
Retrieved from http://www.hcupus.ahrq.gov/reports/statbriefs/sb80.pdf. on
February 3, 2010.
19
Sternfeld I. and Culross P.L., (2008). Los Angeles County Injury Hospitalization Report
2008. Los Angeles County Department of Public Health. August.
Stevens J.A., (2005). Falls among older adults—risk factors and prevention strategies. In:
Falls free: promoting a national falls prevention action plan. Washington, DC:
The National Council on the Aging.
Stevens, J.A., Corso, P.S., Finkelstein, E.A., Miller, T.R. (2006). The costs of fatal and
nonfatal falls among older adults. Injury Prevention; 12, 290–5.
Wolch, J., Pastor, M., Dreier, P. (Eds.), (2004). Up Against The Sprawl. Minneapolis:
University of Minnesota Press.
20
CHAPTER 2: LITERATURE REVIEW
The problem of falls among older adults is a multifaceted one that has gained
increased attention from both researchers and practitioners in recent years. For a few
decades, academic and medical researchers have been conducting research trials both on
the causes of falls and on reducing fall-risk. However, only in recent years have clinical,
policy, and service professionals begun to translate knowledge about falls into evidence-
based community practice and programming (Tinetti et al, 2008). Research literature
addressing the problem of falls previously was found solely in academic journals on
gerontology, medical, health, and injury prevention. More recently, scholars,
practitioners, policy analysts, and advocates have attempted to broaden the translation of
fall related research to broader aging, public health and policy literature (Li et al. 2006;
NCOA, 2009; Wallace et al. 2010).
Further public dissemination of fall related injuries’ impacts on federal and state
budget and policy, in addition to discussion of implications for local policy, planning, and
programming, is required. The following review will address research and policy
literature pertinent to the components of this study. Topics include previous findings on
the demographic characteristics of falls among older adults; assessments of the financial
impacts and discharge disposition of hospitalizations for falls; evidence-based
interventions to prevent falls within community dwelling local populations; and policy
studies on the five counties of the Los Angeles Region and its population dynamics.
21
The Problem of Falls Among Older Adults
One out of three adults ages 65+ and one half of all 85+ year olds fall each year
(CDC, 2005; Hausdorff et al., 2001; Hornbrook et al., 1994; O’Loughlin et al., 1993,
Kelsey et al., 1992; Tinetti et al., 1995). A few data sets have been used to study falls in
California. Ellis and Trent (2001a and 2001b) and Sternfeld & Culross (2008) previously
analyzed OSHPD Hospitalization Discharge Data. Falls were the leading cause of
hospitalization for older adults in the state (Ellis & Trent, 2001a) and in Los Angeles
County, where falls are the number one cause of injury related hospitalizations for adults
ages 35+ (Sternfeld & Culross, 2008). In addition, an extrapolation of the National
Hospital Ambulatory Medical Care Survey, concluded that in 2000, there were 168,000
older adult falls leading to emergency room visits in California (Kochera, 2002).
Fall related hospitalization rates increase with advancing age. For 65-74 year olds
in California, hospitalization rates were 683 hospitalized fall injuries per 100,000 in 1995.
The rate for 75-84 year olds was 2,089 out of 100,000, and for 85+ year olds, it was
5,532 out of 100,000 (Ellis and Trent, 2001a). Nationwide, nearly two-thirds of falls
among older adults that resulted in internal injuries required hospitalization, and half of
all falls resulting in fractures required hospitalization (Owens et al., 2009).
22
Known Demographic Risk Profile of Fallers
Race
In addition to the known risk that grows with advancing age, previous research
paints a more descriptive demographic profile of fallers and their resulting injuries. The
highest risk fallers have been described as White females over age 75, with risk
increasing for those over 85 (CDC, 2005; Donald & Bulpitt, 1999; Stevens et al., 2006;
Stevens & Sogolow, 2005; Wallace, et al., 2010). For older adults over age 75, White
men have the have the highest fatality rates from falls. Nationwide data indicates that
White women, African-American men, and African-American women follow with
respective decreasing fatality rates. Furthermore, among women who fall, Whites are
more likely to sustain hip fractures than African-Americans (Stevens, 2005). In general,
women sustain more non-fatal fractures, such as in the hip or pelvis, in addition to other
problems, such as traumatic brain injury (CDC, 2005; Stevens et al., 2006).
Both national and international entities portray that White older adults fall at a
higher rate than their peers (CDC, 2005; WHO, 2007). However, most studies that
address falls have done so in homogenous settings. Furthermore, few studies have
examined the effects of race on falls and differences among racial and cultural groups.
Furthermore, the findings are inconsistent (Davis et al., 1997; Ellis and Trent, 2001;
Grisso et al., 1992; Hanlon et al., 2002; Means et al., 2000; Nevitt et. al., 1989; Reyes-
Ortiz et al., 2005; Schwartz, et. al., 1999; Studenski, et. al., 1994; Tinetti et al., 1988).
Other Regions in the United States compare the two predominant segments of their older
23
populations--Whites and African-Americans. For example, differences between African-
American and White fallers were studied in the Duke Established Populations for
Epidemiologic Studies of the Elderly (EPESE) because of the black/white composition of
the population (Hanlon et al., 2002).
Some research has utilized race and/or ethnicity as a lens through which to
comparatively study falls among distinctive geographical populations (Reyes-Ortiz et al.,
2005), including another five county area (Hanlon et al., 2002). However, the Los
Angeles Region, as home to thousands of older adults hailing from the world’s diverse
cultural groups, has four primary racial groups: Whites, African-Americans, Asians, and
Latinos, with the population of the latter increasing at exponential rates. In addition,
there are a substantial number of older adults identifying themselves as mixed race or
other races.
One study of Japanese Hawaiians found that Japanese women fell half as often as
their White peers (Davis, et al, 1999). However, there is a dearth of research on Asian
American fallers in relation to other racial/ethnic groups. Major national longitudinal
studies of aging have not included Asians in their surveys because of their small
representation within the entire country’s older population.
While some studies report that Latinos fall less often than their peers (Schiller et
al., 2007), others found that Mexican-American women have the same fall rates as White
women (Reyes-Ortiz et al., 2004; Schwartz et al, 1999). The nationwide finding that one
out of three older Americans fall each year applies to the Latino community. The H-
24
EPESE study found that Mexican-Americans in the Southwestern United States,
including California fall at a rate of 32% (Reyes-Ortiz et al., 2004).
Working for the California Department of Public Health (CDPH), Ellis and Trent
(2001a and 2001b) previously analyzed OSHPD Hospital Discharge Data to examine the
problem of falls in the state’s 58 counties. Ellis and Trent (2001b) compared 1995-1997
injury and hospitalization data for the four major racial groups in California. They found
that the hospitalization rate for White fallers in California were 2-4 times higher than
Latinos and Asians and 20% higher than African-Americans (Ellis and Trent, 2001b).
The Los Angeles County Department of Public Health used OSHPD data to analyze race
differences among hospitalized fallers in all age groups. Across all age groups, the
average ages were: 72 for White fallers; 67 years for Asians/Other races; 58 for African-
Americans; and 50 for Latinos (Sternfeld & Culross, 2008).
Disability
Physical disability is major risk factor for falls. Older adults with chronic
diseases and vision impairments, as well as those with general mobility impairments,
including difficulty walking ¼ mile outside the home, have higher injury rates when they
fall (Lord, 2006; Schiller, et al., 2007). Physical limitations increase with age, and
subsequently, fall injuries among the 85+ population are up to five times more common
than among younger older adults, ages 65 to 74 (Stevens & Sogolow, 2005). Among
Spanish speaking elders in the Southwestern US, risk factors for fallers include being
25
female, plus numerous physical problems: reduced cognitive functioning, depression,
urinary incontinence, hypertension, arthritis, diabetes, and sensory deficits in hearing and
vision (Reyes-Ortiz et al., 2005). Difficulties performing Activities of Daily Living
(ADLs) render an older adult at risk for falls as well (AGS 2001; Komara, 2005; Reyes-
Ortiz et al., 2005). Having a disability that limits basic physical activities and having
chronic medical conditions such as diabetes have been found to lead to multiple falls in
Californians (Wallace et al., 2010).
Income
There is a dearth of research on the socioeconomic factors related to falls in the
United States. In its categorization of the public health problem, the CDC does not list
socioeconomic factors as contributors to fall risk among older adults. However, WHO
categorizes socioeconomic risk factors as one of the four main risk factors for falls in
addition to biological, behavioral, and environmental risk factors (WHO, 2007).
Low-income older people, especially females, those who live alone, and in rural
areas are at higher risk of falls than others (Reyes et al., 2004; WHO, 2007). Factors
related to an increased fall risk among low income older adults are the poor residential
environment, poor diet, lack of access to primary health care, which exacerbate acute and
chronic illnesses, and reduced community resources (WHO, 2007). Having a low
income has been found to contribute to multiple falls in California (Wallace et al., 2010).
26
Older people who live alone sustain more fall-related injuries than their
cohabitating peers (Schiller et al., 2007; WHO, 2007). Being alone at the time of the
fall has been found to put fallers at risk of a poorer recovery (Grisso et al., 1992). Older
adults who live alone have much lower household incomes than those living with a
spouse or other family members (2006 American Community Survey Table B19215).
Females who live alone comprise 20 percent of all older adults in the United States (US
Census, 2000 Table P30).
Financial Costs
Nationwide, direct medical expenses from non-fatal falls cost $19 billion in 2000,
and fatal falls cost another $179 million (Stevens et al. 2006). This study will analyze
hospitalization charges for acute care resulting from fall-induced injuries. However the
economic burden of falls is much greater than hospitalization costs. Other direct costs
include pre-hospitalization costs, skilled nursing care, physicians fees, post discharge
care by doctors, rehabilitation, long term care, home health care, prescription medications,
and medical equipment (Ellis and Trent, 2001b; Englander, et al., 1996; Stevens, et al.,
2006). Other indirect costs include supportive modifications to make a faller’s house
safer when they return home, insurance processing, and lost work and wages of patients
themselves but also caregivers (Englander, et al., 1996, Stevens et al., 2006).
Roudsari et al. (2005) discuss researchers’ differing methods in calculating the
cost of falls. Whereas Englander et al. (1996), Rizzo et al. (1998) and Stevens, et al.
27
(2006) include post acute care in their direct costs of falls, Roudsari et al. (2005) examine
Medicare reimbursed hospitalization costs only. Although they point out the exclusion of
home care and rehabilitation costs as a limitation of their study (Roudsari et al., 2005).
Roudsari et al. (2005) found that Medicare patients’ mean cost for hospitalization after a
fall was $17,483 in 1998, with no significant differences between costs males and
females. These findings are similar to other studies (Barrett-Connor, 1995).
While the primary burden of financial costs encumbers the federal and state health
care systems, local governments also assume responsibility for the cost of falls. The most
frequent cost is in emergency responder calls. According to the Los Angeles Fire
Department, 20 percent of their emergency calls are in response to older adult falls. It
has been reported that 40 percent of ambulance call outs in the United Kingdom are
responses to falls (Martin, 2009). However, other expenses from falls impact cities too.
For example, between 2001 and 2005, the City of Los Angeles paid out more than $20
million in 907 “trip, slip, and fall” claims made by people who were injured in public
spaces (City of Los Angeles, 2006). The Region’s smaller jurisdictions pay out millions
for fall claims each year as well; West Hollywood had over 80 trip and fall claims
between 2000 and 2005 (City of West Hollywood, 2006). While the public pays for
these claims against local jurisdictions, these lawsuits raise the additional policy
consideration of the opportunity cost of spending resources on fall related injuries that
could otherwise be utilized in a productive way (Skelton & Todd, 2005).
28
Source of Pay
Public insurance systems bear the burden for falls (Stevens, 2005). After
hospitalization, where costs are most often paid by Medicare, some older adults return
home, with home health care prescribed by their physicians. For low income patients
whose hospitalization is paid by California’s Medi-Cal program, In Home Supportive
Services pays for assistance at home, although recent budget cuts have reduced this
benefit. CHIS found that 1/5 of older Californians who fall have Medicare and Medi-Cal
health insurance coverage, impacting both state and federal programs (Wallace et al.,
2010).
However, many patients are discharged to a skilled nursing facility (SNF).
Medicare and Medi-Cal pay for a limited number of days of rehabilitative care. Fallers
who require unlimited long term care can apply for California’s Long Term Medi-Cal
program if their income and assets are low enough. Medicare and Medi-Cal pay billions
of dollars each year for the loss of independence that result from fall related injuries
(Guralnik et al., 2002).
Roudsari et al. (2005) estimated that 2003 Medicare-reimbursed costs for acute
care for the nation’s older adult falls were $8 billion, with another $316 million expended
for Emergency Department visits. Due to increasing health care costs and a growing
aged population, the national cost of fall-related injuries is expected to approximate
$40 to 55 billion by 2020 (Englander et al. 1996; Stevens et al., 2006). The youngest of
the Baby Boomers will all turn 65 by the time the year 2030 begins (Myers, 2007). With
29
increasing life expectancies, millions of Baby Boomers will still be at risk of falls in the
year 2050, when they will be 86-104 years old.
Discharge Disposition
Falls that require hospitalization due to fractures, traumatic brain injury, and
wounds can require long term care placement that may last up to a year or more
following hospital discharge (Donald et al. 1999; Stevens, 2005). Older adults with
fractures required long term care placement at a higher rate than those with internal organ
injuries (41 percent compared to 33 percent). Up to 13 percent of all other injuries
required long term placement as well (Owens et al., 2009).
Discharge disposition varies by age, gender, and race of hospitalized faller (Ellis
& Trent, 2001a and 2001b), although few studies have examined discharge disposition
according to race. The likelihood of discharge to long-term care increases with age.
Fallers 75+ are four to five times more likely to be admitted to a long-term care facility
for a year or longer than their younger peers (Donald et al. 1999). White fallers were
discharged to a SNF at higher rates than other groups in California in 1995-1997, and
females, both White and Latino, were discharged to a SNF more often than males (Ellis
& Trent, 2001b). Asians are discharged home at a higher rate than other racial groups
(Ellis & Trent, 2001b).
Long term care costs differ depending on the geographical location within a state
and whether the location is urban, rural, or suburban (MetLife, 2009). Data for data
30
estimates that SNF placement costs $165 – $291 per day in the Los Angeles Region,
depending on location and whether the patient has a private or semi-private room
(MetLife, 2009). The private pay base rate for assisted living is $1,300 to $3,500 per
month in the Los Angeles Region (MetLife, 2009). Fallers discharged home who require
assistive care services pay on an average of $18 per hour for a home health aide or
homemaker (MetLife, 2009), with nursing visits to the home costing Medicare and Medi-
Cal much more. In 1995, 688 older Californians died after a fall, and more than 53,000
were hospitalized (Ellis & Trent, 2001a).
Reducing Fall Risk and Preventing Falls
Local Programming
The economic burden of fall injuries require that cost effective strategies must be
implemented (Stevens, et al, 2006). The benefits of effective evidence-based fall
prevention programs have been found to be worth the costs (Davis et al., 2010; Rizzo et
al, 1998; Rizzo et al., 1996). However, programs developed in research settings and for
hospital rehabilitation programs may not be applicable in the community, and therefore,
new approaches to falls prevention and management are warranted and require policy-
maker support (Davis et al., 2010; Ganz et al., 2008; Skelton & Todd, 2005).
The federal Administration on Aging, and state public health departments have
been promoting local interest in fall risk reduction in recent years, although programs are
often offered in isolation from other aspects. Physicians, senior centers, parks and
31
recreation programs, and home health could complement each other’s resources a through
a community based chronic care approach to fall prevention (Ganz et al., 2008).
An important comparative analysis of two geographical locations by Tinetti and
colleagues (2008) studied the effects of disseminating fall prevention evidence in
reducing injuries. They compared two regions each comprised of 50+ zip code tabulation
areas, where one received fall prevention interventions and one maintained its usual care.
Their important findings highlight that fall prevention efforts can reduce fall related
injuries. However, the generalizability of such results to other geographical locations,
especially Southern California may not be comparable, because the populations of the
two areas in Connecticut were 93% white, less than 6% African-American, less than
2.5% Other, and 2% Latino. Asian older adults were not mentioned in the study and may
have been counted as Other (Tinetti, et al., 2008).
A population based approach to fall prevention considers the faller’s social and
cultural context, access to services, options available, and financial resources (Skelton &
Todd, 2005). Established evidence-based cooperative community fall prevention
programs are prevalent in Europe, Canada, and Australia and can be supported by local
entities (Clemson et al., 1999; Davis et al., 2010; Ganz et al., 2008; Martin, 2009). A
Norwegian research study compared two municipalities, with one as a control, and the
other implementing a fall prevention intervention. Community residents in the city
which performed the intervention reduced falls and decreased hospital admissions for fall
related fractures over the 8 year study (Ytterstad, 1996).
32
The most effective fall prevention programs may intervene on multiple risk
factors (Tinetti & Kumar, 2010). Multifactorial fall prevention programs include
exercise, medical risk assessment, medication monitoring, home modification, vision
assessments, and behavior modification. Appropriate physical activity programs have
been shown to reduce falls and fall risk as well (Rose, et al. 2008) and are the most
effective single factor program. However, recent findings have accentuated that in order
for potential fallers to incorporate prevention programs into their lifestyles, fall
prevention programs must accentuate positive aspects of improving over all health,
strength, and balance rather than reducing fall risk (Stevens et al., 2010; Yardley & Todd,
2004). The integration of fall prevention programs into wider community health
programs make them effective (Ganz et al., 2008; Skelton & Todd, 2004, 2005).
Enhancing policy makers’ understanding of the costs of falls and their local
populations’ fall risk will contribute to their investment in addressing the growing public
health problem. To that end, the National Council on Aging Center for Healthy Aging
has developed the national Falls Free Coalition which is a group of national and state
organizations working to gain awareness about falls and reduce fall related injuries. The
coalition has published a number of manuals and guides that are resources for states
trying to build fall prevention agendas (NCOA, 2009).
33
Connecting Local Policy to Falls
NCOA (2009) and UCLA Center for Health Policy Research (Wallace, 2010)
address policy initiatives that local governments can take to help reduce falls in their
communities. For example, NCOA’s (2009) publication describes the State of
California’s health and safety code regulation that requires the Department of Health to
develop fall prevention and introduce protocols into community implementation. UCLA
Health Policy Research Center (Wallace et al., 2010) offers local policy
recommendations such as training Emergency responders to encourage seniors in seeking
medical attention after a fall whether or not they are injured or not, based on the
assumption that a fall prevention evaluation can help reduce future falls.
Wolch, Pastor, and Dreier (2004) and their contributors do not write about aging
or falls among older adults. However, they make a case for the impact of local and
regional policies on Southern California’s interdependent five county Los Angeles
Region. They contend that innovative policy making in the Region can offer lessons for
progressive policy reform. Innovative policy suggestions must apply to the aging Baby
Boomers in the numerous Los Angeles Region municipalities. Myers (2007) and
Gassoumis et al. (2008) both address policies towards aging Baby Boomers. While
Myers (2007) suggests that policy must provide for immigrants, such as Latinos, to have
enough education to fill in Baby Boomers’ jobs and eventually buy Baby Boomers’
homes, Gassoumis et al. (2008) take an innovative look at Baby Boomers--Latino Baby
Boomers—who will have their own needs in the Los Angeles Region.
34
Frey (2001 and 2003) addresses policy issues concerning Baby Boomers aging in
America’s suburbs. Across the country, 31 percent of total suburban populations were
Baby Boomers, and suburbs are aging more rapidly than nation as a whole (Frey, 2003).
Furthermore, Los Angeles County, with its fast growing Latino population, has one of the
highest suburban minority populations in the nation (Frey, 2001). Frey suggests (2003)
that Los Angeles’ local entities will face new challenges and opportunities with the aging
of the suburban population and that required adjustments in local demand will include
housing, health care, transportation, recreation, the provision of services.
The growing public health problem of falls presents new challenges that require
new local policy innovations and programming opportunities. The following study will
provide a needs assessment for the problem of falls in the Los Angeles Region. Results
of the statistical analysis and conclusions will be used to suggest, in the final chapter,
specific evidence based fall prevention methodologies and innovations, in anticipation of
the Region’s aging Baby Boomer population.
35
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41
CHAPTER 3: DEMOGRAPHY OF THE LOS ANGELES REGION’S OLDER
ADULT POPULATION
Because it is one of the largest metropolitan areas in the United States, the
importance of studying the population dynamics of older adults in the Los Angeles
Region are undeniable. Furthermore, for purposes of understanding the current and
future public health problem of older adult falls in the Region, a comparative analysis of
each county’s population dynamics is imperative. With population-based variables
including age, sex, race, and disability status and with household-based variables such as
income and whether one lives alone, Census data portrays segments of each county’s
population that are most at risk for falls, most likely to sustain injuries or die after falling,
and most costly to the health care systems.
As shown in Table 2, 1,627,000 adult ages 65+ lived in the five county Los
Angeles Region in 2000. Of these older adults, 11.6 percent, or 189,000, were the oldest
old, ages 85+. By 2006, the Region’s older adult population grew to over 1,812,000, a 13
percent increase over six years, with the share of the 85+ population increasing 1.5
percentage points to nearly 237,000, as shown in Table 3.
The Region’s five counties will be compared in their population’s descending
order, which expediently is also their alphabetical order. Los Angeles County, the
center of the Region, is the most populated county in the United States, with nearly 9.9
million residents in 2008 (Census, 2009). In 2000, Los Angeles County’s share of the
42
Region’s older adult population was 57 percent, with 927,000 older residents. By 2006,
Los Angeles’ share of the older population declined by one percent to 56 percent, while
the number of older people grew 8.6 percent to over 1,013,000.
While the Region’s other four counties have much smaller populations than Los
Angeles County, their populations are growing. Orange County is the fifth most
populated county in the United States with more than 3 million residents (Census, 2009).
Its older population in 2000 was nearly 281,000, representing 17.26 percent of the
Region’s older population. Orange County’s older population grew 13 percent to
323,300 in 2006, with a half percent increase in Regional share. Riverside County’s is
the 11
th
most populated county in the nation with more than 2 million residents (Census,
2009). Its older adult population in 2000 was 196,000 representing 12.05 of the Regional
share, and it grew 13.8 percent to 227,500 by 2006, with a half percent increase in
Regional share as well.
San Bernardino County is the 12
th
most populated county in the United States
with 2 million residents (Census, 2009). With 146,500 older residents, it had nine
percent of the Regional share in 2000. The older population grew 9.6 percent to 162,000
in 2006, which made its Regional share decline slightly, to 8.94 percent. Ventura County
has the smallest population of the Region, with less than 800,000 residents (ACS, 2006-
2008). It had only 76,800 older residents in 2000, representing 4.72 percent of the
Regional share, and its older population grew by nearly 10,000 older residents with over
86,000 and a nearly identical Regional share of 4.
43
Table 2
Demographic Characteristics for Older Adult Population
Comparison of Five Counties in Los Angeles Region, 2000
Los Angeles Orange Riverside San Bern. Ventura Region Total
Total 65+ 926,673 280,763 195,964 146,459 76,804 1,626,663
% of Region 56.97 17.26 12.05 9.00 4.72 100
Age Freq. % Freq. % Freq. % Freq. % Freq. % Freq. %
65-69 258,176
27.9 79,157
28.19 52,309
26.7 43,250
29.5 21,437 27.9 454,329 27.9
70-74 234,657
25.3 69,545
24.8 50,845
25.9 37,994
25.9 18,807 24.5 411,848 25.3
75-79 198,147
21.4 59,578
21.2 44,184
22.5 30,968
21.1 16,308 21.2 349,185 21.5
80-84 126,546
13.7 38,389
13.7 27,542
14.1 18,997
13.0 10,963 14.3 222,437 13.7
85+ 109,147
11.8 34,094
12.1 21,084
10.8 15,250
10.4 9,289 12.1 188,864 11.6
Gender
Male 383,240
41.4 115,886
41.3 86,140
44.0 61,954
42.3 32,416 42.2 679,636 41.8
Female 543,433
58.6 164,877
58.7 109,824
56.0 84,505
57.7 44,388 57.8 947,027 58.2
44
Table 2, Continued
Race
White 513,602
55.4 216,732
77.2 159,504
81.4 103,490
70.7 59,500 77.5 1,052,828 64.7
African-Amer 87,228
9.4 1,878 0.7 6,361
3.2 7,720
5.3 964 1.3 104,151 6.4
Latino 187,447
20.2 28,175
10.0 22,878
11.7 26,621
18.2 11,494 15.0 276,615 17.0
Asian/Pac. Is. 120,811
13.0 30,181
10.7 4,554
2.3 5,777
3.9 3,930 5.1 165,253 10.2
Other 17,585
1.9 3,797 1.4 2,667
1.4 2,851
1.9 916 1.2 27,816 1.7
Source: Census 2000 Summary File SF-1 Table P 12.
45
Table 3
Demographic Characteristics for Older Adult Population
Comparison of Five Counties in Los Angeles Region, 2006
Los Angeles Orange Riverside San Bernardino Ventura Region Total
Total 65+ 1,013,339 323,279 227,420 161,980 86,243 1,812,261
% of Region 55.92 17.84 12.55 8.94 4.76 100.0
Age Freq. % Freq. % Freq. % Freq. % Freq. % Freq. %
65-69 289,634 28.6 93,890 29.0 57,552 25.3 47,450 29.3 25,520 29.6 514,046 28.4
70-74 234,150 23.1 75,396 23.3 51,730 22.7 40,335 24.9 19,874 23.0 421,485 23.3
75-79 195,467 19.3 60,992 18.9 51,338 22.6 31,424 19.4 17,076 19.8 356,297 19.7
80-84 159,270 15.7 50,053 15.5 35,186 15.5 25,366 15.7 13,632 15.8 283,507 15.6
85+ 134,818 13.3 42,948 13.3 31,614 13.9 17,405 10.7 10,141 11.8 236,926 13.1
Gender
Male 423,878 41.8 138,204 42.8 98,771 43.4 69,421 42.9 37,548 43.5 767,822 42.4
Female 589,461 58.2 185,075 57.2 128,649 56.6 92,559 57.1 48,695 56.5 1,044,439 57.6
Race
White 501,160 49.5 228,909 70.8 166,121 73.0 98,654 60.9 62,495 72.5 1,057,339 58.3
African-Amer. 93,705 9.2 2,657 0.8 8,694 3.8 9,696 6.0 1,299 1.5 116,051 6.4
Latino 248,655 24.5 39,736 12.3 39,335 17.3 40,801 25.2 15,973 18.5 384,500 21.2
Asian/Pac. Is. 159,343 15.7 48,247 14.9 9,057 4.0 10,159 6.3 6,031 7.0 232,837 12.8
Other 10,476 1.0 3,730 1.2 4,213 1.9 2,670 1.6 445 0.5 21,534 1.2
Source: 2006 American Community Survey Tables B01001A-I
46
Age Distribution of Older Population in Region’s Five Counties
Figures 6 and 7 compare the percentage shares of each county’s older age groups
in 2000 and 2006. As shown in Table 2, more than 450,000 people ages 65-69 lived in
the Region in 2000, representing nearly 28 percent of all older residents. Most of these
older adults lived in Los Angeles County (258,176); however, within each county, 65-69
year olds represent the majority of the older population, over 26 percent. One quarter of
the Region’s older residents were 70-74 years old, with similar shares of 70-74 year olds
within each county. Again, more than half of this group lived in Los Angeles County.
Twenty-one percent of the Region’s older residents were 75-79, and another quarter of
the Region’s residents were 80+ (411,301). Nearly 190,000 older adults in the Region
were 85+ in 2000.
47
San Bernardino County had the youngest older population in 2000, with the
highest percentage of 65-69 and the lowest percentage of 85+. Orange and Ventura
Counties had the highest percentages of very old, 85+year olds. However, as shown in
Figure 6, Riverside had the lowest percentage of 65-70 year olds and the second highest
percentage of 80-84 year olds behind Ventura.
In 2006, the Region had more 65-69, 80-84, and 85+ year olds than in 2000, with
the 80-84 year old group growing by the largest percentage share over six years (1.93).
However, percentage shares of 70-74 and 75-79 year olds declined. More than 236,000
85+ year olds lived in the Region in 2006, and over half of them lived in Los Angeles
County. As in 2000, more than half of each age group lived in Los Angeles County in
2006. Ventura Counties had the highest percentages of 65-69 year olds—30 percent,
and Los Angeles, Orange, and San Bernardino Counties all had 29 percent. Los Angeles
and Orange Counties both had over 13 percent of their older population consisting of 85+
year olds, but Riverside County had the highest percentage of 85+ year olds at 14 percent.
More than 31,000 of Riverside County’s older adults were 85+. However, over 134,000
85+ year olds lived in Los Angeles County in 2006.
48
Advanced age is a known risk factor for falls (Tinetti et al., 1995, O’Loughlin et
al., 1993, Kelsey et al., 1992). While one-third of all adults 65+ fall each year, one-half
of all 85+ year olds fall (CDC, 2005). However, gender and racial characteristics are
also risk factors for falls (CDC, 2005, Tinetti et al., 1995, Nevitt et al., 1991) and must be
considered in assessing the Regional population’s fall risk. Tables 2 and 3 above
display each county’s population by age, race, and gender.
Distribution of Region’s Population by Gender
Regionwide, 58.22 percent of older residents were female in 2000, with the
proportion of females dropping slightly by 2006 to 57.6 percent. The percentage of
49
females in the older population rises with advancing age. Across the Region, the older
female population is generally twice as large as the male population, which is not
unexpected. The gender characteristics of the Region’s older population are pertinent
because gender is a key determinant of fall related injuries and fatal falls. The CDC
reports that women are much more likely than men to sustain injuries following a non-
fatal fall, but men are more likely to die from a fall (CDC, 2009).
Older Population’s Race
The Los Angeles Region is a multicultural landscape, with a population
increasing in racial and ethnic diversity as well as age. In 2000, 64.7 percent of the
Region’s older population was White (1,052,828), but this percentage dropped by 6.4%
to 58.3 percent in 2006 (1,057,339) even though the number of White older adults in the
Region grew slightly between 2000 and 2006. At the same time, Asians increased in
population size, by more than 67,000 and in their share of the older adult population
(+2.6%). Black elders maintained steady proportions of the older adult populations
between 2000 and 2006. Latino older adults grew by more than 100,000 (4.2%) over six
years, and comprised more than 21 percent of all older adults in the Region by 2006.
Within each county, racial composition differs. In 2000, Whites comprised 55.4
percent of Los Angeles County’s older adult population, but this percentage declined to
49.5 percent in 2006. While most of the Region’s older White residents lived in Los
Angeles County, Whites comprised the smallest share of the population in Los Angeles
50
County compared to the other four counties, and this percentage decreased by six percent
between 2000 and 2006. While the White population declined proportionately between
2000 and 2006 in Los Angeles County, percentages of Asians and Latinos grew.
Percentage shares of White older adults declined in the other four counties as well, by
more than 8 percent in Riverside and nearly 10 percent in San Bernardino County
Furthermore, Orange, Riverside, San Bernardino, and Ventura Counties saw increases in
percentage shares of Asians and Latinos as well, with Asians increasing more than 4
percent in Orange and Latinos increasing more than 7 percent in San Bernardino County.
With Asian and Latino older populations increasing in all counties of the Region, the
older population is growing more diverse and will continue on its path through 2050, as
shown in Figures 3 and 4 in Chapter 1.
51
Institutionalized Population
Tables 4 and 5 below show the institutionalized older adults in each county in
2000 and 2006. While 57,000 were counted in 2000, the figure declined in 2006 to
51,000. The Census counts institutions including skilled nursing facilities, prisons, or
other residential treatment centers. As shown in Tables 6 and 7, the 2000 Decennial
Census counted 1,570,000 non-institutionalized older adults ages 65+ living in the Los
Angeles Region in 2000, and the 2006 American Community Survey estimated 1,761,000
non-institutionalized older adults in the Region six years later.
Table 4
Institutionalized Older Population in Los Angeles Region, 2000
Los
Angeles Orange Riverside
San
Bernardino Ventura Total
Percent 3.61 3.62 2.77 3.40 4.32 3.50
People 33,461 10,162 5,424 4,984 3,317 57,348
Table 5
Institutionalized Older Population in Los Angeles Region, 2006
Los Angeles Orange Riverside San Bernardino Ventura Total
Percent 3.72 2.30 1.86 0.05 2.48 2.85
People 37,727 7,427 4,241 81 2,137 51,613
52
Disability Status
Physical limitations, including lower body weakness, balance and gait problems,
in addition to visual impairments, are risk factors for falls (AGS, 2001). In addition to
other known risk factors such as age, gender, and race, the Census counts disabilities in a
local population which may contribute to falls among older adults. The disabilities
include: physical; self-care; sensory; and “go outside the home.” Tables 8 through 17
show the disability status of older adults in the Los Angeles Region in 2000 and 2006.
53
Table 6
Non Institutionalized Older Adult Population
Five County Los Angeles Region, 2000
San
Los Angeles Orange Riverside Bernardino Ventura Region Total
Total 65+ 893,212 270,601 190,540 141,475 73,487 1,569,715
% of
Region 56.90 17.24 12.14 9.01 4.68 100.00
Age Frequency % Frequency % Frequency % Frequency % Frequency % Frequency %
65-74 491,486 55.0 146,930 54.3 102,433 53.8 80,842 57.1 39,368 53.6 861,279 54.9
% of
Region 31.3 9.4 6.5 5.2 2.5 54.9
75+ 401,726 45.0 123,671 45.7 88,107 46.2 60,633 42.9 34,119 46.4 708,436 45.1
% of
Region 25.6 7.9 5.6 3.9 2.2 45.1
Gender
Male 371,687 41.6 112,763 41.7 84,017 44.1 59,708 42.2 31,201 42.5 659,546 42.0
Female 521,525 58.4 157,838 58.3 106,523 55.9 81,767 57.8 42,286 57.5 910,169 58.0
Source: Census 2000 Summary File (SF 3) Tables PCT26 & 30
54
Table 7
Non Institutionalized Older Adult Population
Five County Los Angeles Region, 2006
San
Los Angeles Orange Riverside Bernardino Ventura Region Total
Total
65+ 975,612
315,852 223,179 161,899 84,106 1,760,648
% of
Region 55.4 17.9 12.7 9.2 4.8 100.0
Age Frequency % Frequency % Frequency % Frequency % Frequency % Frequency %
65-74 516,778 53.0
167,265
53.0
108,256 48.5 86,719
53.6 44,994 53.5 924,012 52.5
% of
Region 55.93 18.10 11.72 9.39 4.87 100.00
75+ 458,834 47.0
148,587
47.0
114,923 51.5 75,180
46.4 39,112 46.5 836,636 47.5
% of
Region 54.84 17.76 13.74 8.99 4.67 100.00
Gender
Male 412,285 42.3
136,405
43.2 97,203 43.6 67,765
41.9 37,096 44.1 750,754 42.6
Female 563,327 57.7
179,447
56.8
125,976 56.4 94,134
58.1 47,010
55.9 1,009,894
57.4
Source: 2006 American Community Survey Table B18001
55
Table 8
Disability Status of 65+ Non Institutionalized Population
Five County Southern California Region
2000
Los
Angeles % Orange % Riverside %
San
Bern. % Ventura % Total %
Total
Population 893,212 100.0 270,601 100.0 190,540 100.0 141,475 100.0 73,487 100.0 1,569,715 100.0
Male 371,687 41.6 112,763 41.7 84,017 44.1 59,708 42.2 31,201 42.5 659,546 42.0
65 – 74 216,395 24.2 66,407 24.5 46,940 24.6 36,439 25.8 17,923 24.4 384,203 24.5
75+ 155,292 17.4 46,356 17.1 37,077 19.5 23,269 16.4 13,278 18.1 275,342 17.5
Female 521,525 58.4 157,838 58.3 106,523 55.9 81,767 57.8 42,286 57.5 910,169 58.0
65 – 74 275,091 30.8 80,523 29.8 55,493 29.1 44,403 31.4 21,445 29.2 477,076 30.4
75+ 246,434 27.6 77,315 28.6 51,030 26.8 37,364 26.4 20,841 28.4 433,093 27.6
With Any
Disability 399,903 44.8 103,532 38.3 78,243 41.1 65,233 46.1 29,164 39.7 676,245 43.1
Male 155,376 17.4 39,631 14.6 33,632 17.7 26,731 18.9 11,504 15.7 266,943 17.0
Female 244,527 27.4 63,901 23.6 44,611 23.4 38,502 27.2 17,660 24.0 409,303 26.1
No
Disability 493,309 55.2 167,069 61.7 112,297 58.9 76,242 53.9 44,323 60.3 893,470 56.9
Male 216,311 24.2 73,132 27.0 50,385 26.4 32,977 23.3 19,697 26.8 392,603 25.0
Female 276,998 31.0 93,937 34.7 61,912 32.5 43,265 30.6 24,626 33.5 500,867 31.9
Source: Census 2000 Summary File (SF 3) Tables PCT26 &
30
56
Table 9
Type of Disability of 65+ Non Institutionalized Population: Physical, 2000
Los
Angeles % Orange % Riverside %
San
Bern. % Ventura % Total %
With Physical
Disability 264,710 29.64 68,865 25.45 52,768 27.69 45,138 31.91 19,647 26.74 451,243 28.75
65 - 74 years 110,334 12.35 26,116 9.65 21,747 11.41 20,126 14.23 7,333 9.98 185,704 11.83
Male 44,246 4.95 10,417 3.85 9,579 5.03 8,832 6.24 3,094 4.21 76,188 4.85
Female 66,088 7.40 15,699 5.80 12,168 6.39 11,294 7.98 4,239 5.77 109,516 6.98
75+ 154,376 17.28 42,749 15.80 31,021 16.28 25,012 17.68 12,314 16.76 265,539 16.92
Male 50,035 5.60 13,552 5.01 11,279 5.92 8,312 5.88 4,284 5.83 87,484 5.57
Female 104,341 11.68 29,197 10.79 19,742 10.36 16,700 11.80 8,030 10.93 178,055 11.34
No Physical
Disability 628,502 70.36 201,736 74.55 137,772 72.31 96,337 68.09 53,840 73.26 1,118,472 71.25
65 - 74 years 381,152 42.67 120,814 44.65 80,686 42.35 60,716 42.92 32,035 43.59 675,576 43.04
Male 172,149 19.27 55,990 20.69 37,361 19.61 27,607 19.51 14,829 20.18 308,015 19.62
Female 209,003 23.40 64,824 23.96 43,325 22.74 33,109 23.40 17,206 23.41 367,560 23.42
75+ 247,350 27.69 80,922 29.90 57,086 29.96 35,621 25.18 21,805 29.67 442,897 28.22
Male 105,257 11.78 32,804 12.12 25,798 13.54 14,957 10.57 8,994 12.24 187,858 11.97
Female 142,093 15.91 48,118 17.78 31,288 16.42 20,664 14.61 12,811 17.43 255,039 16.25
57
Table 10
Type of Disability of 65+ Non Institutionalized Population: Sensory, 2000
Los
Angeles % Orange % Riverside %
San
Bern. % Ventura % Total %
With Sensory
Disability
129,795
14.53
35,227
13.02
27,479
14.42
23,116
16.34
10,268
13.97 225,943
14.39
65 - 74 years
43,280 4.85
10,708 3.96
8,731 4.58
8,231 5.82
3,178 4.32 74,147 4.72
Male 21,323 2.39 5,606 2.07 4,892 2.57 4,791 3.39 1,634 2.22 38,256 2.44
Female 21,957 2.46 5,102 1.89 3,839 2.01 3,440 2.43 1,544 2.10 35,891 2.29
75+
86,515 9.69
24,519 9.06
18,748 9.84
14,885 10.52
7,090 9.65 151,796 9.67
Male 33,993 3.81 9,220 3.41 8,576 4.50 6,041 4.27 2,986 4.06 60,832 3.88
Female 52,522 5.88 15,299 5.65 10,172 5.34 8,844 6.25 4,104 5.58 90,964 5.79
No Sensory
Disability
763,417
85.47
235,374
86.98 163,061
85.58
118,359
83.66
63,219
86.03 1,343,772
85.61
65 - 74 years
448,206 50.18
136,222 50.34
93,702 49.18
72,611 51.32
36,190 49.25 787,132 50.14
Male 195,072 21.84 60,801 22.47 42,048 22.07 31,648 22.37 16,289 22.17 345,947 22.04
Female 253,134 28.34 75,421 27.87 51,654 27.11 40,963 28.95 19,901 27.08 441,185 28.11
75+
315,211 35.29
99,152 36.64
69,359 36.40
45,748 32.34
27,029 36.78 556,640 35.46
Male 121,299 13.58 37,136 13.72 28,501 14.96 17,228 12.18 10,292 14.01 214,510 13.67
Female 193,912 21.71 62,016 22.92 40,858 21.44 28,520 20.16 16,737 22.78 342,129 21.80
Source: Census 2000 Summary File (SF 3) Tables PCT26-31
58
Table 11
Type of Disability of 65+ Non Institutionalized Population: Go Outside, 2000
Los
Angeles % Orange % Riverside %
San
Bern. % Ventura % Total %
With Go Outside
Disab.
212,452
23.79
51,280
18.95
35,593
18.68
30,968
21.89
13,576
18.47
343,952
21.91
65 - 74 years
87,196 9.76
17,354 6.41
13,396 7.03
11,976 8.47
4,707 6.41
134,661 8.58
Male 34,733 3.89 6,995 2.58 5,955 3.13 4,840 3.42 1,942 2.64
54,478 3.47
Female 52,463 5.87 10,359 3.83 7,441 3.91 7,136 5.04 2,765 3.76
80,183 5.11
75+
125,256 14.02
33,926 12.54
22,197 11.65
18,992 13.42
8,869 12.07
209,292 13.33
Male 39,775 4.45 9,847 3.64 7,422 3.90 5,945 4.20 2,664 3.63
65,669 4.18
Female 85,481 9.57 24,079 8.90 14,775 7.75 13,047 9.22 6,205 8.44
143,622 9.15
No Go Outside
Disab.
510,595
57.16
159,516
58.95 114,336
60.01
80,376
56.81
43,996
59.87
909,052
57.91
65 - 74 years
234,125 26.21
69,771 25.78
48,426 25.42
38,735 27.38
18,746 25.51
409,908 26.11
Male 181,662 20.34 59,412 21.96 40,985 21.51 31,599 22.34 15,981 21.75
329,725 21.01
Female 52,463 5.87 10,359 3.83 7,441 3.91 7,136 5.04 2,765 3.76
80,183 5.11
75+
276,470 30.95
89,745 33.17
65,910 34.59
41,641 29.43
25,250 34.36
499,144 31.80
Male 115,517 12.93 36,509 13.49 29,655 15.56 17,324 12.25 10,614 14.44
209,673 13.36
Female 160,953 18.02 53,236 19.67 36,255 19.03 24,317 17.19 14,636 19.92
289,471 18.44
59
Table 12
Type of Disability of 65+ Non Institutionalized Population: Self- Care, 2000
Los
Angeles % Orange % Riverside %
San
Bern. % Ventura % Total %
With Self Care
Disability
103,987
11.64
23,292
8.61
16,139
8.47
14,742
10.42
6,217
8.46
164,416
10.47
65 - 74 years
34,882 3.91
5,895 2.18
4,960 2.60
4,753 3.36
1,731 2.36
52,233 3.33
Male 12,970 1.45 2,288 0.85 2,033 1.07 1,826 1.29 693 0.94
19,815 1.26
Female 21,912 2.45 3,607 1.33 2,927 1.54 2,927 2.07 1,038 1.41 32,418 2.07
75+
69,105 7.74
17,397 6.43
11,179 5.87
9,989 7.06
4,486 6.10
112,183 7.15
Male 20,472 2.29 4,840 1.79 3,420 1.79 2,827 2.00 1,308 1.78
32,875 2.09
Female 48,633 5.44 12,557 4.64 7,759 4.07 7,162 5.06 3,178 4.32
79,308 5.05
No Self Care
Disability
789,225
88.36
247,309
91.39 174,401
91.53
126,733
89.58
67,270
91.54
1,405,299
89.53
65 - 74 years
338,245 37.87
105,635 39.04
78,564 41.23
55,055 38.92
29,200 39.73
606,856 38.66
Male 203,425 22.77 64,119 23.70 44,907 23.57 34,613 24.47 17,230 23.45
364,389 23.21
Female 134,820 15.09 41,516 15.34 33,657 17.66 20,442 14.45 11,970 16.29
242,468 15.45
75+
450,980 50.49
141,674 52.36
95,837 50.30
71,678 50.66
38,070 51.81
798,443 50.87
Male 253,179 28.34 76,916 28.42 52,566 27.59 41,476 29.32 20,407 27.77 444,658 28.33
Female 197,801 22.14 64,758 23.93 43,271 22.71 30,202 21.35 17,663 24.04 353,785 22.54
Source: Census 2000 Summary File (SF 3) Tables PCT26-31
60
Table 13
Type of Disability of 65+ Non Institutionalized Population: Mental
2000
Los
Angeles % Orange % Riverside %
San
Bern. % Ventura % Total %
With Mental Disability 125,839 14.09 30,489 11.27 20,045 10.52 17,413 12.31 7,986 10.87 201,820 12.86
65 - 74 years 46,146 5.17 9,222 3.41 6,655 3.49 6,123 4.33 2,335 3.18 70,497 4.49
Male 19,175 2.15 4,023 1.49 2,921 1.53 2,547 1.80 1,021 1.39 29,694 1.89
Female 26,971 3.02 5,199 1.92 3,734 1.96 3,576 2.53 1,314 1.79 40,803 2.60
75+ 79,693 8.92 21,267 7.86 13,390 7.03 11,290 7.98 5,651 7.69 131,323 8.37
Male 27,413 3.07 6,797 2.51 5,110 2.68 3,859 2.73 1,979 2.69 45,169 2.88
Female 52,280 5.85 14,470 5.35 8,280 4.35 7,431 5.25 3,672 5.00 86,154 5.49
No Mental Disability 767,373 85.91 240,112 88.73 170,495 89.48 124,062 87.69 65,501 89.13 1,367,895 87.14
65 - 74 years 445,340 49.86 137,708 50.89 95,778 50.27 74,719 52.81 37,033 50.39 790,782 50.38
Male 197,220 22.08 62,384 23.05 44,019 23.10 33,892 23.96 16,902 23.00 354,509 22.58
Female 248,120 27.78 75,324 27.84 51,759 27.16 40,827 28.86 20,131 27.39 436,273 27.79
75+ 322,033 36.05 102,404 37.84 74,717 39.21 49,343 34.88 28,468 38.74 577,113 36.77
Male 127,879 14.32 39,559 14.62 31,967 16.78 19,410 13.72 11,299 15.38 230,173 14.66
Female 194,154 21.74 62,845 23.22 42,750 22.44 29,933 21.16 17,169 23.36 346,940 22.10
Source: Census 2000 SF 3 Tables PCT26-31
61
Table 14
Disability Status for 65+ Non Institutionalized Population, 2000
Los Angeles Orange Riverside
San
Bernardino Ventura
Total 65+ 893,212 270,601 190,540 141,475 73,487
Male:
65 years and over: 371,687 41.6 112,763 41.7 84,017 44.1 59,708 42.2 31,201 42.5
With one type of
disability: 77,935 8.7 21,571 8.0 18,392 9.7 14,071 9.9 6,013 8.2
Sensory disability 17,141 1.9 5,783 2.1 5,044 2.6 3,692 2.6 1,674 2.3
Physical disability 30,167 3.4 9,113 3.4 8,086 4.2 6,217 4.4 2,610 3.6
Mental disability 5,584 0.6 1,447 0.5 1,031 0.5 655 0.5 386 0.5
Self-care disability 753 0.1 101 0.0 84 0.0 92 0.1 24 0.0
Go-outside-home
disability 24,290 2.7 5,127 1.9 4,147 2.2 3,415 2.4 1,319 1.8
With two or more types
of disability: 77,441 8.7 18,060 6.7 15,240 8.0 12,660 8.9 5,491 7.5
Includes self-care
disability 32,689 3.7 7,027 2.6 5,369 2.8 4,561 3.2 1,977 2.7
Does not include self-
care disability: 44,752 5.0 11,033 4.1 9,871 5.2 8,099 5.7 3,514 4.8
No disability 216,311 24.2 73,132 27.0 50,385 26.4 32,977 23.3 19,697 26.8
Female:
65 years and over: 521,525 58.4 157,838 58.3 106,523 55.9 81,767 57.8 42,286 57.5
With one type of
disability: 102,208 11.4 28,706 10.6 20,878 11.0 16,912 12.0 8,117 11.0
Sensory disability 14,209 1.6 4,515 1.7 3,430 1.8 2,388 1.7 1,532 2.1
Physical disability 46,424 5.2 14,433 5.3 11,035 5.8 9,013 6.4 3,997 5.4
Mental disability 7,189 0.8 1,748 0.6 1,241 0.7 1,049 0.7 570 0.8
Self-care disability 1,039 0.1 245 0.1 121 0.1 158 0.1 72 0.1
Go-outside-home
disability 33,347 3.7 7,765 2.9 5,051 2.7 4,304 3.0 1,946 2.6
62
Table 14, Continued
With two or more types
of disability: 142,319 15.9 35,195 13.0 23,733 12.5 21,590 15.3 9,543 13.0
Includes self-care
disability 69,506 7.8 15,919 5.9 10,565 5.5 9,931 7.0 4,144 5.6
Does not include self-
care disability: 72,813 8.2 19,276 7.1 13,168 6.9 11,659 8.2 5,399 7.3
No disability 276,998 31.0 93,937 34.7 61,912 32.5 43,265 30.6 24,626 33.5
Source: Census 2000 SF 3 Table
PCT26
63
Table 15
Type of Disability of 65+ Non Institutionalized Population: Go Outside, 2006
Five County Southern California Region
County
Los
Angeles % Orange % Riverside %
San
Bern. % Ventura % Total %
Total Non
Institional.
Pop.
975,612
100
315,852
100 223,179
100
157,164
100 84,106
100
1,755,913 100
With Any
Disability
427,608
43.8
109,213
34.6 88,257
39.5 73,774
46.9 29,869
35.5
728,721 41.5
Male
156,308
16.0
40,953
13.0 36,010
16.1 29,507
18.8 12,390
14.7
275,168 15.7
Female
271,300
27.8
68,260
21.6 52,247
23.4 44,267
28.2 17,479
20.8
453,553 25.8
No Disability
548,004
56.2
206,639
65.4 134,922
60.5 83,390
53.1 54,237
64.5
1,027,192 58.5
Male
255,977
26.2
95,452
30.2 61,193
27.4 38,258
24.3 24,706
29.4
475,586 27.1
Female
292,027
29.9
111,187
35.2 73,729
33.0 45,132
28.7 29,531
35.1
551,606 31.4
With Go
Outside
Home Dis.
226,757
23.2
51,544
16.3 37,333
16.7 33,403
21.3 12,644
15.0
361,681 20.6
Male
67,814
7.0
16,849
5.3 12,400
5.6 10,413
6.6 3,734
4.4
111,210 6.3
Female
158,943
16.3
34,695
11.0 24,933
11.2 22,990
14.6 8,910
10.6
250,471 14.3
No Go
Outside
Home Dis.
748,855
76.8
264,308
83.7 185,846
83.3
123,761
78.7 71,462
85.0
1,394,232 79.4
Male
344,471
35.3
119,556
37.9 84,803
38.0 57,352
36.5 33,362
39.7
639,544 36.4
Female
404,384
41.4
144,752
45.8 101,043
45.3 66,409
42.3 38,100
45.3
754,688 43.0
64
Table 16
Type of Disability of 65+ Non Institutionalized Population: Self Care and Mental, 2006
Five County Southern California Region
County
Los
Angeles % Orange % Riverside %
San
Bern. % Ventura % Total %
With Self
Care
Disability
148,868
15.3
29,481
9.3 22,624
10.1 22,995
14.6 7,220
8.6
231,188 13.2
Male
47,550
4.9
10,359
3.3 6,930
3.1 7,464
4.7 2,262
2.7
74,565 4.2
Female
101,318
10.4
19,122
6.1 15,694
7.0 15,531
9.9 4,958
5.9
156,623 8.9
No Self Care
Disability
826,744
84.7
286,371
90.7 200,555
89.9
134,169
85.4 76,886
91.4
1,524,725 86.8
Male
364,735
37.4
126,046
39.9 90,273
40.4 60,301
38.4 34,834
41.4
676,189 38.5
Female
462,009
47.4
160,325
50.8 110,282
49.4 73,868
47.0 42,052
50.0
848,536 48.3
With Mental
Disability
165,951
17.0
37,299
11.8 26,513
11.9 27,512
17.5 8,680
10.3
265,955 15.1
Male
59,691
6.1
14,102
4.5 10,762
4.8 11,358
7.2 3,737
4.4
99,650 5.7
Female
106,260
10.9
23,197
7.3 15,751
7.1 16,154
10.3 4,943
5.9
166,305 9.5
No Mental
Disability
809,661
83.0
278,553
88.2 196,666
88.1
129,652
82.5 75,426
89.7
1,489,958 84.9
Male
352,594
36.1
122,303
38.7 86,441
38.7 56,407
35.9 33,359
39.7
651,104 37.1
Female
457,067
46.8
156,250
49.5 110,225
49.4 73,245
46.6 42,067
50.0
838,854 47.8
65
Table 17
Type of Disability of 65+ Non Institutionalized Population: Physical and Sensory, 2006
Five County Southern California Region
2006
County
Los
Angeles % Orange % Riverside %
San
Bern. % Ventura % Total %
With Physical
Disability 329,630
33.8
78,365
24.8 69,915
31.3
57,773
36.8
22,101
26.3
557,784 31.8
Male 112,907
11.6
29,057
9.2 27,048
12.1
21,823
13.9
8,717
10.4
199,552 11.4
Female 216,723
22.2
49,308
15.6 42,867
19.2
35,950
22.9
13,384
15.9
358,232 20.4
- - - - -
No Physical Disability 645,982
66.2
237,487
75.2 153,264
68.7
99,391
63.2
62,005
73.7
1,198,129 68.2
Male 299,378
30.7
107,348
34.0 70,155
31.4
45,942
29.2
28,379
33.7
551,202 31.4
Female 346,604
35.5
130,139
41.2 83,109
37.2
53,449
34.0
33,626
40.0
646,927 36.8
With Sensory
Disability 164,274
16.8
42,004
13.3 34,618
15.5
29,954
19.1
10,693
12.7
281,543 16.0
Male 70,951
7.3
17,147
5.4 15,962
7.2
13,555
8.6
4,796
5.7
122,411 7.0
Female 93,323
9.6
24,857
7.9 18,656
8.4
16,399
10.4
5,897
7.0
159,132 9.1
66
Table 17, Continued
No Sensory Disability 811,338
83.2
273,848
86.7 188,561
84.5
127,210
80.9
73,413
87.3
1,474,370 84.0
Male 341,334
35.0
119,258
37.8 81,241
36.4
54,210
34.5
32,300
38.4
628,343 35.8
Female 470,004
48.2
154,590
48.9 107,320
48.1
73,000
46.4
41,113
48.9
846,027 48.2
Source: 2006 American Community Survey Tables B18030-B18035
67
As shown in Table 12, 43 percent of the Region’s older adults had a disability in
2000, and the majority of those disabled were female. The type of disability thataffected
the Region’s older population the most was physical (28.75%), followed by “Go Outside
the Home Disability” (21.91%), sensory (14.39%), mental (12.86%), and self care
(10.47%). In 2006, the American Community Survey estimated 41.5 percent of the
Region’s older population had at least one disability. Physical disabilities were still the
most prevalent at 31.77 percent, followed again by “Go Outside the Home Disability”
(20.6%), mental (15.15%), self care (13.17%), and sensory (6.97%).
Across the Region, females have higher disability rates than males. The
exception is in 2000 among 65-74 year olds in Orange, Riverside San Bernardino, and
Ventura Counties, where females do not have substantially higher disability rates than
males. It is not unexpected that older adults ages 75+ have higher disability rates than
their younger peers. Figures 8-17, below, compare disability rates across Regional
counties. Figures 8 and 9 show the rates of any disabilities in each county’s older
population and by gender in 2000 and 2006. Females over 65 in the Los Angeles Region
have higher rates of disability than males.
68
In 2000, San Bernardino had the highest rates of any disability in its total older
population (.46) and among its older males (.19), as shown in Figure 8. San Bernardino
County’s older females shared the highest rate of any disability with Los Angeles
County’s older females (.27). Los Angeles County was just below San Bernardino with
the second highest rates of any disabilities among its total older population (.45) in 2000.
However, it was Riverside County that had the second highest rate of any disability
among older males (.18) after San Bernardino’s. Riverside County had the lowest rate of
disabilities among its female population (.23). Orange and Ventura Counties had the
lowest rates of any disabilities among males and in the total older population.
69
70
Between 2000 and 2006, rates of any disability in San Bernardino County did not
change considerably, and it remained the highest among total older population (.46) as
well as males (.18) and females (.27). However, the rate of any disabilities in Los
Angeles County’s total older population declined significantly from .45 in 2000 to .39 in
2006. Figure 9 shows that in 2006, Riverside County shared Los Angeles County’s
position of the second highest rate of any disabilities among their total older populations
(.39). Los Angeles County had the second highest rates of any disabilities among
females (.25) and Riverside County had the second highest rate of any disabilities among
males (.16). Orange and Ventura Counties had the lowest rates of any disabilities among
each gender and in the total older population.
Examining specific types of disabilities provides more insight into differences in
the older populations across the Region’s counties. Figures 10 and 11 show physical
disability rates for 2000 and 2006. As with any disabilities, older females across the Los
Angeles Region have substantially higher rates of physical disability their male peers.
Physical disabilities among older people pose a fall risk factor.
71
San Bernardino had the highest rates of physical disability in the older population
in 2000, with a rate of .31, and it rose to .36 in 2006. In 2000 and 2006, San Bernardino
also had the highest physical disability rates among males and females. Los Angeles
County had the second highest rates of physical disability among the total older
population in 2000 (.29) and its rate of rose to .30 in 2006. However, Riverside County’s
rate rose substantially to .31 in 2006, and it had then second highest rates among the total
older population. Males in Riverside have higher rates of physical disabilities in both
2000 and 2006 (.11 and .12 respectively) in both years than males in Los Angeles County.
However, females have higher rates of physical disability in Los Angeles County (.18
and .20) than in Riverside.
72
73
“Go outside the home” disabilities could put older people at risk of falls and fear
of falling as well (Schiller, et al., 2007). The prevalence of “go outside the home
disabilities” in the Los Angeles Region are lower than physical disabilities. Females
throughout the Region have higher rate of “go outside the home” disabilities than males.
With “go outside the home” disabilities, Los Angeles County (.23) leads San Bernardino
County (.21) in 2000, but they have equal rates (.21) in 2006 for total older population.
Los Angeles County’s females and males have slightly higher rates of “go outside the
home” disabilities than San Bernardino County’s in 2000 as do females in 2006. Among
males in 2006, the rates are equal in the two counties (.06).
74
A less prevalent disability among the Region’s older population is sensory
disability. However, sensory disabilities, especially visual disabilities, pose a fall risk
(Lord, 2006; Abdelhafiz & Austin, 2003). Although females have had considerably
higher rates of other disabilities than males throughout the Region, the differences
between their sensory disability rates (.08) and males (.07) is negligible in 2000, as seen
in Figure 14. However, Figure 15 shows that in 2006, females have higher sensory
disability rates than males in all counties of the Los Angeles Region. Both in 2000 and in
2006, as with other types of disability, San Bernardino County had the highest rate of
sensory disabilities in the Region, .16 and .18 respectively. Similar to other disabilities,
Los Angeles and Riverside Counties have equal sensory disability rates for their total
populations (.15), but males in Riverside County have slightly more sensory disabilities
than males in Los Angeles County. The reverse is true for females.
75
Older people who have difficulties performing Activities of Daily Living (ADLs)
such as eating, bathing, toileting, dressing, and grooming, are at risk for falls (Komara,
76
2005, AGS 2001). Census data offers a picture of the rate of self-care disability within
the Los Angeles Region’s older population. Figures 16 and 17 show self-care disability
rates.
Throughout the Los Angeles Region, females have double the rate of self-care
disability compared to males. In 2000, Los Angeles County had the highest rates of self-
care disability among the total older population (.11) as well as males (.04) and females
(.08). In 2006, Los Angeles County’s self care disability rate rose to .14, and it was
matched by San Bernardino County. San Bernardino County’s males and females had
slightly higher rates of self-care disabilities than their peers in Los Angeles County, as
shown in Figure 17.
77
Throughout the Region, females have substantially higher rates of disability than
males, with the exception of sensory disabilities in 2000, when female disability rate are
only marginally higher than males. In general, San Bernardino, Riverside, and Los
Angeles Counties have disability rates that are higher than Orange and Ventura Counties.
Compared to the other counties in the Region, Orange and Ventura Counties have high
proportions of 85+ year olds. Therefore, based on age, it is unexpected that their
disability rates are lower. In addition, it is unexpected that San Bernardino’s population
had some of the highest rates of disability because, as shown in Figure 6 above, its older
population was the youngest in the Region compared to other counties in 2000. In 2006,
San Bernardino maintained its position of having the lowest percentage of 85+ year olds.
78
However, it shared its position in percentage of 65-69 year olds with Los Angeles and
Orange Counties and Ventura had a higher percentage of the youngest old.
Living Alone
Research shows that older people who live alone sustain more injuries when they
fall than their cohabitating peers (Schiller, et al., 2007, WHO, 2007). Figure 18 shows
the distribution of the Region’s older adults living alone by county. In the five county
Los Angeles Region in 2006, there were 144,004 males over 65+ living alone, and more
than twice as many females, a total of 317,654 (ACS, 2006 Table B17017). Over
170,000 older women live alone in Los Angeles County, descending numbers in the other
four counties, shown in Figure 18.
79
Household Income
Figure 19 shows that the median household income for 65+ households in the
Region varies by greatly by county. In 2006, Orange and Ventura Counties had the
highest median household incomes of the five counties in the Region, $41,850 and
$40,023 respectively. Los Angeles ($32,668) and Riverside ($32,694) Counties’ median
household income for older adults were nearly identical. San Bernardino County had the
lowest median household income for older adults in the Region in 2006: $31,250.
Median Household income of each county changes when one considers whether
the older adult lives alone or with others. Table 18 below shows the differences between
males and females and older adults living alone or with others. Orange and Ventura
Counties again have the highest median household incomes, and San Bernardino County
has the lowest.
80
Table 18
Los Angeles Region Median Income Of Non Family Households, Householder 65+
Los Angeles Orange Riverside
San
Bernardino Ventura
Males Living Alone 21,767 30,285 24,409 18,244 24,745
Males Not Alone 54,773 80,691 44,721 41,530 93,806
Females Living Alone 16,358 22,172 19,117 15,448 21,128
Females Not Alone 45,269 57,718 41,279 51,691 63,036
Source: 2006 American Community Survey Table B19215
In considering the socioeconomic status (SES) of older people in the Region, it is
helpful to consider older adults’ income source. Figures 20 and 21 show Social Security
and Supplemental Security Income (SSI) in the five Regional Counties. The majority of
Social Security recipients are 65+. Furthermore, the majority of Social Security
recipients also have Medicare coverage. However, not all Medicare recipients have
Medicare Part A, which covers hospitalizations such as the ones which will be discussed
in the following chapters. SSI on the other hand, is a good proxy for Medi-Cal coverage.
Although not all SSI recipients are older adults, most SSI recipients also have Medi-Cal
coverage.
81
Figure 22 shows the household income within each county and the Region. In all
counties the majority of 65+ households had an income of less than $25,000 in 2006. Of
the million older adult households in the Region, one quarter of them, nearly 225,000,
were low income households of less than $25,000 in Los Angeles County. While older
adults’ household income varies according to their household composition, an
examination of racial differences in household income will also help in an understanding
of older adults SES across the Region.
82
Los Angeles County generally has high percentages of lower income households
across racial groups. For Whites, 40 percent of 65+ households in San Bernardino
County had household incomes below $25,000 in 2006, and nearly 40 percent in Los
Angeles County did as well. Orange and Ventura Counties did not have large enough
African-American older populations for the 2006 American Community Survey to
calculate. However, half of all older African-American households in Los Angeles and
San Bernardino Counties had an income of $25,000 or less.
Among 65+ Asian households, nearly half of them in Los Angeles and San
Bernardino Counties had incomes less than $25,000 per year. For Latino 65+ households,
at least half of them in Los Angeles County had an income of $25,000 or less in 2006.
Riverside and Ventura have the next highest percentages of Latinos with the lowest
83
household income. In San Bernardino County, White, African-American, and Asian
households had been poorer than their peers in other counties, but this is not the case with
Latinos in the inland county.
Discussion
The literature review in the previous chapter spelled out known risk factors for
falls and related injuries. The results of the comparative analysis of each county’s fall
risk in their population’s age distribution, gender and racial composition, disability status,
prevalence of individuals living alone, and household income provides a demographic
based needs assessment and allows each jurisdiction to consider their needs in relation to
their neighbors. Local government plans for housing, transportation, school districts,
water, parks and recreation, and waste disposal use Census data similarly to assess
demographic needs.
Advanced age is a risk factor for falls, with fall injuries among the 85+ population
up to five times more common than among younger older adults, ages 65 to 74 (Stevens
& Sogolow, 2005). As of 2006, there were more than 1.8 million 65+ year olds and
236,000 85+ year olds in the Region. Therefore, previous research would suggest that
600,000 older adults 65+ fall each year, with more than 115,000 85+ year olds falling
each year. Compared to the other counties, San Bernardino County is the youngest, with
the highest percentage of 65-69 and the lowest percentage of 85+. Los Angeles and
Orange Counties had the highest percentages of very old, 85+year olds. Chapter 4 will
84
assess how many of these possible fallers were in fact hospitalized for fall related injuries
in 2000 and 2006.
Previous research found that being female is a risk factor for falls and related non-
fatal injuries (CDC, 2005; Stevens et al., 2005) and that males are more likely to die from
a fall (CDC, 2005) . As the population ages after 65, females increasingly outnumber
males. Females constitute 58 percent of the Los Angeles Region’s older adult population.
However, with men over 85 at high risk of dying after a fall, it is important to note that
there were more than 70,000 very old men in the Region in 2000 and more than 85,000 in
2006.
In addition, being White is a risk factor for falls (CDC, 2005; Nevitt et al., 1991;
Tinetti et al., 1995), although some studies have found that non-White older adults fall at
the same rates as Whites. Of the 1.2 million White older adults in the Region, half of
them live in Los Angeles County. However, Los Angeles County had the smallest
percentage of White older people in the Region. Considering that advanced age and
being White puts elders at risk of falls, that being female deems them more likely to
sustain serious injury, and that being male makes them more likely to die from falling,
the Region’s older White population, totaling over 1 million, is compelling regardless of
whether or not its percentages will be declining in coming decades.
Older adults with chronic diseases and vision impairments, as well as those with
general mobility impairments, including difficulty walking ¼ mile outside the home,
have higher injury rates when they fall (Schiller, et al., 2007). In 2000, there were more
than 675,000 older adults in the Region with a disability that could make them
85
susceptible to falls. Fifty-three percent (361,272) of them had two or more disabilities,
and 314,803 had one disability. The majority of men with disabilities had one type of
impairment (137,982 compared to 128,892), and for disabled women, the majority had at
least two disabilities (232,380 compared to 176,821).
Physical disabilities are the most prevalent type in the older population. More
than 450,000 of the Region’s older adults were physically disabled in 2000. More than
265,000 were 75+ and had a physical disability, and two-thirds of those 75+ year olds
were female. Table 17 shows that the Region’s older physically disabled population
grew by 100,000 in 2006, to more than 550,000 older adults (65+); sixty five percent of
them were female.
Sensory disabilities, which could include vision or hearing impairments, affected
more than 225,000 of the Region’s older adults in 2000, and the majority of them were
75+. Six years later, the Region had 281,000 older adults with sensory disabilities
which could make them susceptible to falling. More than 343,000 of the Region’s older
adults reported a “Go Outside the Home” disability, which would make walking ¼ mile
outside the home difficult. Of these, 42 percent were females 75+, 19 percent were males
75+, and 23 percent were females 65-74. The Region’s older population with “Go
Outside the Home” disabilities grew to 361,681 in 2006, and 69 percent were females.
Older adults who have difficulties performing ADLs, have self-care disabilities,
and they are at risk for falls (AGS 2001; Reyes-Ortiz et. al., 2004). Nearly 165,000
older adults in the Region had self- care disabilities in 2000, and nearly one half of them
86
were females ages 75+. The number with self-care disabilities rose to 231,188 in 2006,
with 68 percent of them being females.
Older people who live alone sustain more injuries than their cohabitating peers
(Schiller, et al., 2007). More than 460,000 older people in the Los Angeles Region lived
alone in 2006. Twice as many were females as males. With females and people living
alone sustaining more injuries than males and people who do not live alone, the 317,654
females who live alone are at risk of being hospitalized for fall related injuries.
Tinetti et al. (1988) found that multiple risk factors increase an older person’s
likelihood of falling by up to 78% for four or more risk factors. Therefore, the risk factor
profiles outlined above show that the Region has a large population of older people at
risk of falling and at risk of requiring hospitalization for their injuries. According to the
research literature, each county’s residents who are most likely to fall and sustain injuries
are 85+ White females who have physical, sensory, self-care, and/or “Go outside the
home” disabilities. In addition, if they live alone, they are at risk of sustaining more
injuries than their peers who do not live alone and have diminished likelihood of a
successful recovery. Furthermore, the Region’s males who are White, 85+ and have the
same disabilities are more at risk of death following a fall than their female counterparts.
The following section, Chapter 4, will analyze OSHPD Hospital Patient
Discharge data to provide a comparative analysis of hospitalized fallers in the five Los
Angeles Region counties and to determine whether their hospitalized fallers reflect the
population discussed above who are most at risk. Population income data presented in
this chapter will provide a demographic frame of reference for source of pay discussed in
87
the following chapters. That is, Chapter 3’s portrayal of Social Security and SSI
recipients as well as the older population’s income (with racial differences) will assist in
the comparative analysis of the prevalence of Medicare, Medi-Cal patients in each
county’s population.
88
CHAPTER 3 REFERENCES
Abdelhafiz, A.H., & Austin, C.A. (2003). Visual factors should be assessed in older
people presenting with falls or hip fracture. Age and Ageing, 32, 26–30.
ACS, 2006-2008 American Community Survey Retrieved from
http://factfinder.census.gov/servlet/ACSSAFFFacts?_event=Search&geo_id=&_g
eoContext=&_street=&_county=ventura+county&_cityTown=ventura+county&_
state=04000US06&_zip=&_lang=en&_sse=on&pctxt=fph&pgsl=010 on
February 3, 2010.
AGS Panel on Falls Prevention. (2001). Guideline for the prevention of falls in older
persons. Journal of the American Geriatrics Society, 49(5), 664–72.
CDC, 2009. Falls Among Older Adults: An Overview. Retrieved February 9, 2010 from
http://www.cdc.gov/HomeandRecreationalSafety/Falls/adultfalls.html#.
Census, 2009, Table 7: Resident Population Estimates for the 100 Largest U.S. Counties
Based on July 1, 2008 Population Estimates: April 1, 2000 to July 1, 2008 (CO-
EST2008-07), Population Division, U.S. Census Bureau. Retrieved from
http://www.census.gov/popest/counties/tables/CO-EST2008-07.xls on February 4,
2010.
CDC (2005). Centers for Disease Control and Prevention, National Center for Injury
Prevention and Control. Web–based Injury Statistics Query and Reporting System
(WISQARS) [online]. (2005) [cited 2007 Jan 15]. Available from URL:
www.cdc.gov/ncipc/wisqars.
Kelsey, J.L., Browner, W.S., & Seeley D.G., et al. (1992). Risk factors for fractures of
the distal forearm and proximal humerus. American Journal of Epidemiology, 135,
477-489.
Lord, S. R., (2006). Visual risk factors for falls in older people. Age and Ageing. 35-S2,
ii42–ii45.
Myers, D. (2007). Immigrants and Boomers. New York: Sage Publications.
Nevitt, M.C., Cummings, Sr., Hudes, E.S. (1991). Risk factors for injurious falls: A
prospective study. Journals of Gerontology, 46, M164-170.
89
O'Loughlin, J.L., Robitaille, Y., Boivin, J.F., & Suissa, S. (1993). Incidence of and risk
factors for falls and injurious falls among the community-dwelling elderly.
American Journal of Epidemiology, 137, 342-354.
Reyes-Ortiz, C.A., Al Snih, S., Loera, J., Ray, L.A., & Markides, K.S. (2004). Risk
factors for falling in older Mexican Americans. Ethnicity
&
Disease, 14, 417-422.
Schiller, J.S., Kramarow, E.A., Dey, A.N. (2007). Fall injury episodes among
noninstitutionalized older adults: United States, 2001–2003. Advance data from
vital and health statistics; no 392. Hyattsville, MD: National Center for Health
Statistics.
Stevens J.A., & Sogolow E.D., (2005). Gender differences for non-fatal unintentional fall
related injuries among older adults. Injury Prevention, 11, 115–9.
Tinetti, M.E., Speechley, M., & Ginter S.F., (1988). Risk factors for falls among elderly
persons living in the community. New England Journal of Medicine, 319 (26),
1701–7.
Tinetti, M.E., Doucette, J., Claus, E., et al. (1995). Risk factors for serious injury during
falls by older persons in the community. Journal of the American Geriatric
Society, 43(11), 1214–21.
90
CHAPTER 4: THE LOS ANGELES REGION’S COMMUNITY DWELLING
HOSPITALIZED FALLERS
Hospitalized fallers in this study are community dwelling older adults whose
source of admission was “Home” rather than a residential care, skilled nursing facility,
other designated institution providing supportive care, or another acute hospital. The
locations of their falls that precipitated hospitalization were not necessarily in their home,
however. Tables 19 and 20 show the location of falls according to E Code. Because
these are community dwelling older adults, the sample can therefore be examined in
relation to the community dwelling population of the Region’s counties.
This chapter presents descriptive statistics on fallers in the Region and is intended
to provide an illustrative demographic comparison of hospitalized fallers within and
among each of the five Regional Counties: Los Angeles, Orange, Riverside, San
Bernardino, and Ventura. Descriptive data is differentiated by county for the additional
purpose of comparison within the context of each county’s older populations that were
described in Chapter 3. Subsequent chapters, Chapters 5-7, will use multiple and logistic
regression to analyze dependent variables of billed charges, source of pay, and discharge
disposition and to control for and examine independent variables such as gender, age,
race, injury type, length of stay, and county. Therefore, subsequent chapters will be able
to make conclusions about predictors and outcomes of hospitalizations for fall related
injuries and to explain descriptive demographic differences portrayed herein.
91
California Hospital Patient Discharge Data
The California Office of Statewide Health Planning and Development (OSHPD)
Patient Discharge Database collects public administrative data from hospitals throughout
the state. Patients are deidentified to protect patient confidentiality and privacy. In order
to find a temporal match between the hospitalization data and population data from the
most recent Decennial Census, discussed in Chapter 3, this study uses discharge data
from the year 2000. Moreover, in order to examine the Los Angeles Region’s change in
falls incidence over time, this study also analyzes discharge data from 2006, the most
recent year for which this administrative data is available. Therefore, 2006 American
Community Survey data analyzed in the previous chapter provides a temporal match and
allows for an analysis of the Region’s changing population over a six-year period.
92
Table 19
Type of Fall for Community Dwelling, Hospitalized Fallers
Five County Los Angeles Region
2000
Los
Angeles Orange Riverside San Bern. Ventura Region Total
N 16,403 4,839 2,785 2,206 1,177 27,410
Description
E
Code # % # % # % # % # % # %
8800 6 0 1 0 1 0 1 0.1 9 0
Fall on or from sidewalk curb 8801 84 0.5 30 0.6 15 0.5 7 0.3 5 0.4 141 0.5
Fall on or from other stairs of steps 8809 506 3.1 142 2.9 45 1.6 50 2.3 39 3.3 782 2.9
Fall from ladder 8810 167 1 46 1 41 1.5 32 1.5 5 0.4 291 1.1
8811 20 0.1 20 0.1
Fall from or out of building or other structure 8820 1 0 4 0.1 2 0.1 1 0.1 1 0.1 9 0
8830 8 0 1 0 9 0
8839 1 0 2 0.1 3 0.1 6 0
8841 3 0 1 0.1 4 0
Fall from chair 8842 270 1.6 67 1.4 54 1.9 34 1.5 30 2.5 455 1.7
Fall from wheelchair 8843 225 1.4 67 1.4 37 1.3 38 1.7 13 1.1 380 1.4
Fall from bed 8844 652 4 177 3.7 109 3.9 101 4.6 41 3.5 1,080 3.9
Fall from other furniture 8845 33 0.2 13 0.3 3 0.1 5 0.2 4 0.3 58 0.2
Fall from commode 8846 94 0.6 37 0.8 20 0.7 22 1.0 8 0.7 181 0.7
Other fall from one level to another 8849 148 0.9 61 1.3 27 1 21 1.0 14 1.2 271 1
8850 5058 30.8 1393 28.8 803 28.8 757 34.3 360 30.6 8,371 30.5
93
Table 19, Continued
Fall from other slipping**, 8859 1671 10.2 473 9.8 271 9.7 222 10.1 115 9.8 2,752 10
8860 1 0 1 0
8869 59 0.4 11 0.2 7 0.3 9 0.4 5 0.4 91 0.3
Fall resulting in striking against sharp object (use
additional e code to identify object (E920) 8880 7391 45.1 2315 47.8 1348 48.4 904 41.0 535 45.5 12,493 45.6
**tripping, or stumbling (including fall from moving sidewalk, fall from or in stationary motor vehicle, tripping or falling over an animal, stumbling over
object)) Source: California Patient Discharge Data, 2000, State of California Office of Statewide Health Planning and Development
94
Table 20
Type of Fall for Community Dwelling, Hospitalized Fallers
Five County Los Angeles Region, 2006
Los
Angeles Orange Riverside San Bern Ventura Region Total
N 17,703 5,046 3,301 2,371 1,436 29,857
Description
E
Code # % # % # % # % # % # %
8800 11 0.1 0 0 0 0 2 0.1 1 0.1 14 0
Fall on or from sidewalk curb 8801 58 0.3 47 0.9 20 0.6 9 0.4 10 0.7 144 0.5
Fall on or from other stairs of steps 8809 571 3.2 163 3.2 57 1.7 54 2.3 45 3.1 890 3
Fall from ladder 8810 145 0.8 43 0.9 34 1 21 0.9 19 1.3 262 0.9
8811 1 0 0 0 0 0 0 0 0 0 1 0
Fall from or out of building or other structure 882 14 0.1 5 0.1 4 0.1 4 0.2 2 0.1 29 0.1
8839 1 0 2 0 3 0.1 1 0 0 0 7 0
8841 3 0 0 0 0 0 0 0 0 0 3 0
Fall from chair 8842 278 1.6 82 1.6 50 1.5 34 1.4 22 1.5 466 1.6
Fall from wheelchair 8843 232 1.3 64 1.3 37 1.1 32 1.3 21 1.5 386 1.3
Fall from bed 8844 785 4.4 215 4.3 130 3.9 122 5.1 66 4.6 1,318 4.4
Fall from other furniture 8845 31 0.2 11 0.2 7 0.2 5 0.2 2 0.1 56 0.2
Fall from commode 8846 115 0.6 37 0.7 22 0.7 19 0.8 20 1.4 213 0.7
Other fall from one level to another 8849 170 1 66 1.3 20 0.6 22 0.9 11 0.8 289 1
8850 7 0 0 0 1 0 0 0 0 0 8 0
Fall from other slipping** 8859 7,056 39.9 1,854 36.7 1327 40.2 1028 43.4 550 38.3 11,815 39.6
8860 2 0 1 0 0 0 0 0 0 0 3 0
8869 33 0.2 5 0.1 1 0 4 0.2 0 0 43 0.1
95
Table 20, Continued
Fall resulting in striking against sharp object
(use additional e code to identify object
(E920) 8880 14 0.1 3 0.1 1 0 1 0 1 0.1 20 0.1
Fall resulting in striking against other object 8881 275 1.6 98 1.9 58 1.8 40 1.7 20 1.4 491 1.6
Other fall 8888 1,001 5.7 207 4.1 214 6.5 120 5.1 108 7.5 1,650 5.5
Unspecified fall (Fall NOS) 8889 6,896 39 2,142 42.4 1313 39.8 849 35.8 538 37.5 11,738 39.3
Source: California Patient Discharge Data, 2006, State of California Office of Statewide Health Planning and Development
96
Variables of interest from Hospital Patient Discharge Data include: year of
admission; age; sex; race; county; principal external cause of injury (E-code); total billed
charges; source of payment; length of stay; disposition of patient (e.g. died, home,
assisted living, nursing facility). Hospitalized fallers analyzed include patients ages 65+
whose cases show E-codes for falls, as shown in Tables 19 and 20 above. In OSHPD
discharge data, only first admissions for an injury have E Codes. Therefore, readmitted
or transferred patients are not selected (Ellis & Trent, 2001b).
Demographic Description of Fallers
In 2000, 27,410 community-dwelling older adults residing in the five-county Los
Angeles Region were hospitalized after falling. Figure 23 below shows hospitalized fall
incidences in the Region by county for 2000 and 2006.
97
As shown in Table 21, below, 59.8 percent of the Region’s fallers (16,403) lived
in Los Angeles County and 17.7 (4,839) lived in Orange County in 2000. Another 10.2
percent lived in Riverside (2,785), 8.0 percent lived in San Bernardino (2,206).
Furthermore, 4.3 percent (1,177) lived in Ventura County.
In 2006, there were 29,857 fallers, up 8.2 percent from 2000. Each county’s
share of the Region’s fallers changed only slightly. As shown in Table 22 below, 59.3
percent of the 2006 fallers (17,703) lived in Los Angeles County, and 16.9 percent
(5,046) in Orange County. Across the Region, another 11.1 percent of fallers (3,301)
lived in Riverside, 7.9 percent lived in San Bernardino (2,371), and 4.8 percent (1,436)
lived in Ventura County.
Based on this California hospital discharge data and Census data presented in the
previous chapter, 1.75 percent of the Los Angeles Region’s community dwelling older
adult population was hospitalized after falling in 2000. In addition, 1.70 percent of the
Los Angeles Region’s community dwelling older adult population was hospitalized after
falling in 2006.
98
Table 21
Demographic Characteristics for Community Dwelling Hospitalized Fallers
Five County Los Angles Region, 2000
Los Angeles Orange Riverside San Bernardino Ventura Region Total
Total
Fallers 16,403 4,839 2,785 2,206 1,177 27,410
% of
Region 59.8 17.7 10.2 8.0 4.3 100.0
Age
Frequency Percent
Frequency Percent
Frequency Percent
Frequency Percent
Frequency Percent Frequency Percent
65-69 1,438 8.8 345 7.1 207 7.4 207 9.4 96 8.2 2,293 8.4
70-74 2,082 12.7 580 12.0 386 13.9 320 14.5 146 12.4 3,514 12.8
75-79 3,334 20.3 904 18.7 506 18.2 455 20.6 212 18.0 5,411 19.7
80-84 3,638 22.2 1,130 23.4 682 24.5 477 21.6 268 22.8 6,195 22.6
85+ 5,911 36.0 1,880 38.9 1,004 36.1 747 33.9 455 38.7 9,997 36.5
% 85+
of Reg. 59.1 18.81 10.04 7.47 4.55
85-89 3,334 20.3 1,070 22.1 564 20.3 429 19.4 243 20.6 5,640 20.6
90-94 1,913 11.7 628 13.0 339 12.2 245 11.1 164 13.9 3,289 12.0
95-99 578 3.5 172 3.6 85 3.1 61 2.8 42 3.6 938 3.4
100-
104 83 0.5 9 0.2 16 0.6 11 0.5 6 0.5 125 0.5
105+ 3 0.0 1 0.0 - 0.0 1 0.0 - 0.0 5 0.0
Gender
Male 4,837 29.5 1,366 28.2 850 30.5 645 29.2 320 27.2 8,018 29.3
Female 11,566 70.5 3,473 71.8 1,935 69.5 1,561 70.8 857 72.8 19,392 70.7
Race
White 11,430 69.68 4,236 87.54 2,489 89.37 1,817 82.37 990 84.11 20,962 76.48
African-
Ame 1,007 6.14 12 0.25 44 1.58 53 2.40 3 0.25 1,119 4.08
99
Table 21, Continued
Latino 2,539 15.48 228 4.71 188 6.75 265 12.01 152 12.91 3,372 12.30
Asian 1,129 6.88 215 4.44 13 0.47 39 1.77 21 1.78 1,417 5.17
Other 298 1.82 148 3.06 51 1.83 32 1.45 11 0.93 540 1.97
Source: California Patient Discharge Data, 2000, State of California Office of Statewide Health Planning and Development
100
Table 22
Demographic Characteristics for Community Dwelling Hospitalized Fallers
Five County Los Angeles Region, 2006
Los Angeles Orange Riverside San Bern. Ventura Region Total
Total Fallers 17,703 5,046 3,301 2,371 1,436 29,857
% of Region 59.3 16.9 11.1 7.9 4.8 100.0
Age # % # % # % # % # % # %
65-69 1,542 8.7 414 8.2 291 8.8 239 10.1 94 6.5 2,580 8.6
70-74 2,128 12.0 542 10.7 399 12.1 287 12.1 171 11.9 3,527 11.8
75-79 3,034 17.1 810 16.1 568 17.2 443 18.7 223 15.5 5,078 17.0
80-84 4,204 23.7 1,301 25.8 787 23.8 585 24.7 356 24.8 7,233 24.2
85+ 6,795 38.4 1,979 39.2 1256 38.0 817 34.5 592 41.2 11,439 38.3
% 85+ of Reg. 59.4 17.3 11.0 7.1 5.2 100
85-89 3,851 21.8 1,162 23.0 740 22.4 470 19.8 333 23.2 6,556 22.0
90-94 2,186 12.3 618 12.2 412 12.5 258 10.9 194 13.5 3,668 12.3
95-99 669 3.8 171 3.4 83 2.5 83 3.5 58 4.0 1,064 3.6
100-104 82 0.5 26 0.5 19 0.6 6 0.3 7 0.5 140 0.5
105+ 7 0.0 2 0.0 2 0.1 0 0.0 11 0.0
Gender
Male 5,685 32.1 1,496 29.6 1,119 33.9 763 32.2 467 32.5 9,530 31.9
Female 12,018 67.9 3,550 70.4 2,182 66.1 1,607 67.8 969 67.5 20,326 68.1
101
Table 22, Continued
Race
White 11,301
63.8
4,163
82.5
2,776
84.1
1,804
76.1 1243 86.6 21,287
71.3
African-Amer 995
5.6
23
0.5
65
2.0 80
3.4 9 0.6 1,172
3.9
Latino 3,197
18.1
336
6.7
353
10.7 385
16.2 117 8.1 4,388
14.7
Asian 1,696
9.6
360
7.1
40
1.2 50
2.1 24 1.7 2,170
7.3
Other 514
2.9
164
3.3
67
2.0 52
2.2 43 3.0 840
2.8
Source: California Patient Discharge Data, 2006, State of California Office of Statewide Health Planning and Development
102
102
Age
Figures 24 and 26 show the age distribution of the Region’s fallers. In both 2000
and 2006, the largest percentage of fallers were in the 85+ category, with these oldest
patients representing approximately 35 to 40 percent of the Region’s fallers in each
county. These figures are a sharp contrast to Figures 25 and 27, shown in Chapter 3 and
repeated below, which show that 10-15 percent of each county’s population is 85+. On
the other end, the four figures show that while 65-69 years old represent approximately
one quarter of more of the older population, they have only 5 to 10 percent of
hospitalized falls. The rates of fallers in each age group per their representation within
the population will be discussed below.
103
103
104
104
Fallers in Proportion to Population: Fall Rates
When comparing the Los Angeles Region’s counties, the percentages of fallers in
each county appear generally proportional to the county populations overall in both 2000
and 2006. It is notable, however, that while Los Angeles County has 56.9 percent of the
Region’s older adult population in 2000, it had 59.8 percent of the fallers. In 2006, the
pattern is similar: 55.4 percent of the Region’s older adult population lived in Los
Angeles County, but it had 59.3 percent of the fallers.
For 2000, Riverside, and San Bernardino, Ventura Counties’ older adults
respectively comprised 10.2, 8.0, and 4.3 percents of the Region’s fallers, which were all
smaller than their share of the Regional population. However, Orange County had 17.7
105
105
percent of the Region’s fallers and 17.2 percent of the population. Figures 28 and 29
show the rates of hospitalized fallers for all age groups, per 1,000 in population.
Table 23
Rate of Hospitalized Falls Per 1,000 in Population, by Age, 2000
Los
Angeles Orange Riverside
San
Bernardino Ventura Region
65-69 5.6 4.4 4.0 4.8 4.5 5.0
70-74 8.9 8.3 7.6 8.4 7.8 8.5
75-79 16.8 15.2 11.5 14.7 13.0 15.5
80-84 28.7 29.4 24.8 25.1 24.4 27.9
85+ 54.2 55.1 47.6 49.0 49.0 52.9
Figure 28 and Table 23, above, show that the hospitalized fall rate increases
greatly with advancing age. In 2000, the Regionwide rate for 65-69 year olds was 5
hospitalizations for falls per 1,000 in the population, with Riverside County having the
lowest rate of 4.0 and Los Angeles County having the highest rate among 65-69 year olds
106
106
of 5.6 per 1,000. Riverside maintained the lowest rate for each age group. Among 80-84
year olds and 85+ year olds, Orange County the highest hospitalized fall rates (29.4 and
55.1 per 1,000, respectively), surpassing Los Angeles County.
For 2006, Orange, Riverside, and San Bernardino Counties’ older adults
respectively comprised 17.9, 12.7, and 9.2 percents of the Region’s population, and these
figures indicate that their Regional share of fallers were smaller than their Regional share
of the older adult population. Regionwide, Ventura County had the same proportion of
fallers and older adult population, 4.8 percent.
Table 24 and Figure 29 below show the rate of falls for each county in 2006.
Ventura County had the lowest rate for 65-69 year olds—3.7 hospitalized fallers per
1,000 in the population. Meanwhile, Los Angeles again had the highest rate among the
youngest seniors. However, Ventura also had the highest rate of hospitalized falls among
the oldest old with 58.4 per 1,000 85+ year olds being hospitalized for falls.
Table 24
Rate of Hospitalized Falls Per 1,000 in Population, by Age, 2006
Los
Angeles Orange Riverside
San
Bernardino
Ventura Region
65-69 5.3 4.4 5.1 5.0 3.7 5.0
70-74 9.1 7.2 7.7 7.1 8.6 8.4
75-79 15.5 13.3 11.1 14.1 13.1 14.3
80-84 26.4 26.0 22.4 23.1 26.1 25.5
85+ 50.4 46.1 39.7 46.9 58.4 48.3
Source: Author’s Calculations Based on 2006 American Community Survey and OSHPD data
These rates are comparable to the rates found by Ellis and Trent (2001a) in 1995-
1997. However, they reported the rate of hospitalized fall injuries in California per
107
107
100,000 in population and use larger age groups. They calculate 683/100,000 for 65-74
year olds, 2,089/100,000 for 75-84 year olds, and 5,532/100,000 for 85+.
Further Research
An issue to be considered for future research concerns the County of Los
Angeles’ proportion of fallers within the Region. That is, why is it that Los Angeles
County had 56.9 percent of the Region’s older adult population in 2000, but it had 59.8
percent of the fallers? Six years later, why did Los Angeles County have 55.4 percent of
the Region’s older adult population but 59.3 percent of the fallers? Los Angeles has
smaller proportions of White females in its population than the four other counties.
Therefore, further research should address whether there are environmental differences in
Los Angeles County which may add to fall risk among specific demographic groups. For
108
108
example, the age, quality, or condition of the housing stock in certain areas or outdoor
infrastructure such as sidewalks, curbs and streets could affect older people’s fall risk.
109
CHAPTER 4 REFERENCES
Ellis, A., and Trent, R. (2001a). Do the Risks and Consequences of Hospitalized Fall
Injuries Among Older Adults in California Vary by Type of Fall? Journal of
Gerontology: Medical Sciences, Vol. 56A, No. 11, M686–M692.
Ellis, A.A., & Trent, R.B. (2001b). Hospitalized fall injuries and race in California. Injury
Prevention, 7, 316-320.
110
CHAPTER 5: PREDICTORS OF COSTS
The Costs of Falls
The OSHPD hospitalization data used in this study measures costs with total
billed charges incurred by patients and billed to private insurance companies, Medicare,
and Medi-Cal. Less than one percent of fallers have charges billed to other sources, have
no insurance, and/or self pay. Costs analyzed in this study include only billed charges for
the first admission to the hospital following an injury. Any subsequent hospitalizations
for the same injury are not included in the data. Billed charges do not include
professional fees, which physicians bill separately for their time.
As described in the literature review, hospitalization data does not portray what
portion of total billed charges is reimbursed through the insurance systems. For policy
analysis purposes, however, it paints a comparative portrait of the demographic profiles
of the most costly fallers as well as the fiscal impact on the health care systems. While
this chapter will examine the dollar amounts of billed charges, Chapter 6 will address the
relationship between demographic characteristics and charges billed to different sources
of pay: Medicare and Medi-Cal.
Discharge data does not include the costs of post acute care following
hospitalization for fall-related injuries. Chapter 7 will address the discharge dispositions
of hospitalized fallers with implications for long term care costs. However, the Los
Angeles Region’s hospitalization costs/billed charges are compelling on their own.
Figure 30 compares mean billed charges for each county in 2006.
111
Ventura County, the smallest county in the Region, had the lowest total billed
charges: $72,350,000. However, it had the highest mean billed charges in the Region at
$50,383 per hospitalization. Los Angeles County followed with the second highest
mean cost per hospitalization in the Region: $48,187. With the largest number of fallers,
it had the highest total cost of hospitalizations, more than $853 million. San Bernardino
had the lowest mean cost at $32,977, up from $20,497 in 2000.
112
Research Questions
In light of the variation in total billed charges and mean billed charges of each of
the Region’s five counties, the following research questions were formulated in order to
analyze the predictors of costs. What demographic variables, if any, predict billed cost-
related hospitalization outcomes in the Region’s fallers? Are age, race, source of pay,
and discharge disposition predictors of billed charges of hospitalized fallers? How do the
predictors compare in each of the five regional counties? In order to answer research
questions, the following hypotheses will be tested:
H1 There will be significant differences in billed charges between different age groups.
H2 There will be significant differences in billed charges between different racial groups.
H3 There will be significant differences in billed charges between different sources of
pay.
H4 There will be significant differences in billed charges between different discharge
dispositions.
H5 There will be significant differences between counties.
Method
The dependent variable in this chapter’s multiple regression analysis is total billed
charges. Bivariate analysis was performed to test the associations between billed
charges and independent variables of gender, race/ethnicity, insurance coverage, and
discharge disposition. Analysis of variance found significant relationships between billed
charges and source of pay discharge disposition, injury type, and county of residence.
113
Independent samples T tests found a significant relationship between age and billed
charges. The significance of independent variables are displayed in Table 25. SPSS used
stepwise analysis to determine the model in which the independent variables are the best
predictor of billed charges.
Length of Stay is measured in days. ICD 9 Injury Diagnosis codes were
categorized into the following for comparison of major injuries: head injury, lower limb
fracture (including hip fracture), upper limb fracture, internal injuries, spinal and spinal
cord injuries, and other injuries. Other injuries is the referent group. Fallers were
divided into four age groups for comparison: 65-74; 75-84; 85-94, and 95+, with 65-74 as
the referent. Source of Pay includes Medicare and Medi-Cal with Private Insurance as a
referent. Discharge Disposition includes discharge Home, to a SNF, to Assisted Living,
and Died, with Other Acute as a referent.
While insurance coverage is not typically a demographic measure, it is the closest
variable to income available in the California Hospital Patient Discharge Data and
provides a way of categorizing patients for policy analysis purposes. Including county of
residence as an independent variable provides for a geographic comparison of the costs of
falls across the Los Angeles Region, with Los Angeles County as a referent. N=29,857
for all five counties in the analysis.
114
Results
Table 25 shows the mean values for independent variables. T tests and analysis
of variance found significant relationships at the p<.001 level between the billed charges
and the independent variables, except race.
Table 25
Dependent Variable: Billed Charges
Tests of Significance for Independent Variables
N=29,857
Mean SD
Injury ** Head $ 64,428 $ 95,480
Upper $ 34,668 $ 41,856
Lower Limb $ 53,656 $ 48,037
Internal $ 72,126
$
133,964
Spinal $ 35,672 $ 56,874
Other Injury $ 39,410 $ 63,081
Age ** 65-74 $ 48,177 $ 76,892
75-84 $ 46,033 $ 60,921
85-94 $ 44,306 $ 50,023
95+ $ 41,837 $ 45,639
Gender ** Male $ 50,484 $ 74,661
Female $ 45,709 $ 60,686
Race White $ 45,174 $ 58,357
African-American $ 45,314 $ 59,216
Latino $ 45,308 $ 62,159
Asian $ 49,979 $ 71,713
Other $ 50,958 $ 78,673
County ** Los Angeles $ 48,187 $ 60,686
Orange $ 45,428 $ 59,739
Riverside $ 39,967 $ 4,648
San Bernardino $ 32,977 $ 47,648
Ventura $ 50,382 $ 54,291
Source of Pay ** Medicare $ 45,437 $ 60,148
Medi-Cal $ 59,943 $ 80,175
Private Insurance $ 40,949 $ 53,417
Discharge ** Home $ 31,945 $ 39,536
SNF $ 48,769 $ 56,662
Assisted Living $ 29,070 $ 28,388
Died
$
103,776
$
130,619
Different Acute $ 43,680 $ 84,146
**p<.001
115
Table 26 below shows the predictors of billed charges for hospitalized falls in the
Los Angeles Region. After Length of stay (t=62.4; p<.001), controlling for injury type,
the strongest predictors of billed charges are the fallers’ disposition to Home (t=-21.8;
p<.001), with an average of $23,000 fewer billed charges than fallers discharged to a
different acute setting, and discharge disposition in Death (t=16.6; p<.001), with more
than $33,000 higher in billed charges. After fatal fallers, patients discharged to a SNF
incurred the highest billed charges, approximately, $15,000 higher billed charges on
average than those discharged Home or to Assisted Living.
Compared to other injuries, fallers with lower limb fractures (including hip),
incurred an average of nearly $10,000 more in billed charges (t=31.2; p<.001), and head
injured patients incurred nearly $17,000 more on average (t=12.7; p<.001), while patients
with internal injuries incurred an average of $27,000 more in billed charges (t=7.1;
p<.001). Fallers above age 75 had lower billed charges than their younger peers in the
65-74 year old age group. The charges were nearly $4,000 lower on average for 75-84
year olds (t=-4.5); more than $7,000 lower on average for 85-94 year olds (t=-7.9); and
an average of nearly $10,000 lower for 95+ year olds (t=-5.71). In addition, compared to
males, females had $5,400 lower billed charges on average (t=-7.8).
Having Medicare did not have a significant result. However, compared to fallers
utilizing private insurance, Medi-Cal patients incurred an average of $10,000 more in
billed charges (t=5.4), controlling for length of stay. County was a predictor of billed
charges as well. The two significant findings among counties were San Bernardino
County (t=-10.8), where fallers incurred an average of nearly $13,000 less than Los
116
Angeles County patients and Riverside County (t=-7.0), where fallers incurred an average
of $7,000 less.
Table 26
Regression Coefficients Predicting Total Billed Charges for Hospitalized Fallers
in the Los Angeles Region, 2006
B t Sig.
(Constant) $ 52,376.78 32.16 0.000 **
Length of Stay Length of stay $ 1,535.18 62.39 0.000 **
ICD 9 Dx Head $ 16,689.11 12.70 0.000 **
(Ref. Other Injury) Lower Limb $ 9,901.28 13.21 0.000 **
Internal $ 27,040.35 7.06 0.000 **
Spinal $ (3,515.12) -3.10 0.002 *
Age 75-84 $ (3,924.14) -4.54 0.000 **
(Referent 65-74) 85-94 $ (7,192.39) -7.95 0.000 **
95+ $ (9,901.52) -5.71 0.000 **
Sex (Ref. Male) Female $ (5,368.03) -7.78 0.000 **
County Orange $ (1,614.83) -1.86 0.063
(Ref. Los Angeles) Riverside $ (7,326.80) -7.04 0.000 **
San Bernardino $(12,906.42) -10.80 0.000 **
Source of Pay Medicare $ 2,165.98 1.90 0.058
(Ref. Priv. Insur.) Medi-Cal $ 10,107.82 5.41 0.000 **
Discharge Home $(23,141.80) -21.81 0.000 **
(Ref. Diff. Acute) SNF $ (8,988.07) -8.94 0.000 **
Assisted Living $(24,955.31) -8.84 0.000 **
Died $ 33,061.00 16.58 0.000 **
N=29,857
R Squared 0.189
F 386.87
**p<.001
117
Discussion
It is not unexpected that length of stay is the strongest predictor of billed charges.
It was unexpected that younger fallers would have higher billed charges than older fallers.
Further research could examine the relationship between location of fall and age of faller,
to see if younger fallers have more expensive injuries, such as head and internal injuries,
from falling off ladders or other incidences not generally included in frail elderly’s
activities of daily living. Ellis and Trent (2001a) suggested more in depth study of
location of falls as well.
In addition to age, source of pay predicts costs. Fallers on Medi-Cal had higher
billed charges than private pay or Medicare fallers. Chapter 6 will analyze source of pay
as a dependent variable to examine the suggestion from these results that fallers on Medi-
Cal are younger. It will also allow for an analysis of the relationship between race and
source of pay; however, race was not significant in this analysis.
This data does not explain why Medi-Cal incurs higher billed charges for fall
related injuries than other fallers. One possible explanation is health disparities among
patients with Medi-Cal. While the injuries resulting from falls may not be more costly
for Medi-Cal patients, it is possible that Medi-Cal beneficiaries who fall have other
chronic health conditions that predispose them to spending longer stays in the hospital
and incurring more billed charges for their care. Further research could examine the
secondary diagnosis of Medi-Cal patients to determine if they play a role in the costs
incurred. It is a limitation of this data that it is unknown how much reimbursement Medi-
Cal pays hospitals.
118
There were significant differences in predictors of billed charges across the five
counties, which was not unexpected given the mean billed charges for each county.
Income and the costs of living in Riverside and San Bernardino Counties are lower than
in the Los Angeles, Orange, and San Bernardino Counties. Further research could
compare counties and examine whether billed charges are lower simply because medical
costs are lower in those two counties, or because of variables related to the populations’
demographics and health.
There were significant differences in billed charges between those discharged to
another acute and those discharged home, to AL, to a SNF, and in death. Patients
discharged home had significantly lower billed charges than those sent to a different
hospital or a SNF. Fallers who suffered fatal injuries incurred significantly higher billed
charges than non fatal fallers. These results are consistent with previous research
(Stevens et al., 2006). Another limitation of this study and data is that it does not
include post acute costs. How much is spent on patients after they are discharged to
different locations and whether Medi-Cal patients or younger patients cost more after
hospital discharge is beyond the scope of this analysis.
In addition to the analysis of source of pay in Chapter 6, predictors of discharge
disposition will be analyzed in Chapter 7. These two subsequent chapters will offer
insight on the outcomes of hospitalized fall injuries in the Los Angeles region beyond
billed charges. Medicare, Medi-Cal and private insurance pay hospital costs as well as
post-acute costs following discharge.
119
CHAPTER 5 REFERENCES
Ellis, A.A., & Trent, R.B., (2001a) Do the Risks and Consequences of Hospitalized Fall
Injuries Among Older Adults in California Vary by Type of Fall? The Journals of
Gerontology Series A: Biological and Medical Sciences, M686-M692.
Stevens, J.A., Corso, P.S., Finkelstein, E.A., & Miller, T.R. (2006). The costs of fatal and
nonfatal falls among older adults. Injury Prevention; 12, 290–5.
120
CHAPTER 6: SOURCE OF PAY
Expected Source of Pay for Hospitalization Charges
Hospitalization charges for the Region’s fallers are paid primarily by the
government-- through Medicare and Medi-Cal. Medicare as source of pay includes the
federally administered third party reimbursement program, whose coverage is known as
Medicare Part A and B, plus Health Maintenance Organization Medicare Risk. Medicare
payments include those crossovers to secondary payers. Individuals’ Medicare benefits
vary depending on factors including lifetime number of employment years, wage rates,
and marital status.
Medi-Cal as source of pay includes the State of California administered third
party reimbursement programs known as Medi-Cal and Medi-Cal Managed Care Plan.
Qualification for Medi-Cal benefits require that older adults have very low income and
minimal assets, and other states administer similar programs under the name Medicaid.
While insurance coverage itself is not typically a demographic measure, it is the closest
variable to income available in the California Hospital Patient Discharge Data and
provides a way of categorizing patients for policy analysis purposes.
A portion of the total billed charges for hospitalized fall injuries, however, are
paid by private sources, rather than the public. Private Pay includes payment covered by
private, non-profit, or commercial health plans, such as Preferred Provider Organizations
(PPO), Point of Service (POS), Exclusive Provider Organizations (EPO) provided by
Blue Cross/Blue Shield, and other Commercial Insurance Companies (OSHPD, 2007).
121
Because public payment sources are the major payer for fall related injuries, it is
important to compare the variables predicting Medicare and Medi-Cal payment in the
five Los Angeles Region’s counties. The previous chapter concluded that Medi-Cal
coverage was a predictor of higher billed charges in the Los Angeles Region, and the
highest billed charges were incurred by younger patients.
In 2006, total costs of hospitalizations for the Region’s fallers were more than
$1.45 billion. Medicare billing was $1.26 billion, and Medi-Cal charges were $84
million. In addition, private insurers paid $102 million for older adults’ fall related
hospitalizations.
In order to further examine the relationship between age, billed charges, and
insurance coverage, this chapter will address the following research questions: What
demographic characteristics, if any, are associated with utilization of Medicare and Medi-
Cal as payment for the hospitalizations of the Los Angeles Region’s fallers? How do
billing for Medicare and Medi-Cal differ in each county? In order to address these
questions, the following hypotheses were formed:
H1: Age, gender, and race will be associated with having Medicare as a source of pay.
H2: Age, gender, and race will be determinants of having Medi-Cal as a source of pay.
METHOD
SPSS software for Windows was utilized to assess bivariate relationships between
the independent variables and dependent variables. Chi square tests found significant
relationships between source of pay and sex, race, county, and discharge disposition.
122
Results are shown in Table 27. In addition, analysis of variance found significant results
between source of pay and age, length of stay, and billed charges, with the exception of
the relationship between billed charges and Medicare utilization.
Binary logistic regressions tested Hypotheses 1 and 2. Having Medicare as the
source of pay is the dependent variable for Hypothesis 1, with independent variables
including age, gender, race, and discharge disposition. Length of stay, total charges, and
injury diagnosis are included as controls. The logistic regression assessed the odds of
ratios of the independent variables compared to referent groups of 65-74 year olds for age,
males, White fallers for race, and those moved to another acute hospital for discharge
disposition. Hypothesis 2 tested the same independent variables with Medi-Cal as the
dependent variable. SPSS software for windows conducted the logistic regressions with
a backwards likelihood ratio to determine which independent variables were the best
predictors of source of pay.
123
Table 27
Expected Source of Pay
Tests of Significance for Independent Variables
Hospitalized Fallers in the Los Angeles Region, N=29,857
Dependent Variable
Medicare Medi-Cal Private
N 25,972 1,337 2,335
Independent Variable % % %
Sex ** ** **
Male 31.83 25.13 35.67
Female 68.16 74.87 64.33
Race ** ** **
White 73.60 21.54 76.19
African-American 3.85 3.29 5.05
Latino 13.23 46.22 11.48
Asian 6.76 22.06 4.37
Other 2.55 6.88 2.91
County ** ** **
Los Angeles 58.61 83.99 51.56
Orange 17.29 7.26 18.84
Riverside 11.23 3.81 13.40
San Bernardino 7.60 4.41 13.70
Ventura
Discharge Disposition ** ** **
SNF 46.57 33.21 48.27
Home 35.16 54.90 38.54
AL 1.46 1.42 1.03
Death 3.19 3.96 2.96
Other Acute 2.87 2.62 0.05
Mean (SD) Mean (SD) Mean (SD)
Age 81.9 (7.8) ** 79.8 (8.3) ** 80.0 (8.2) **
Length of Stay 5.4 (5.4) ** 10.7 (56.0) ** 4.3 (4.6) **
Billed Charges
$45,437
(60,149)
$59,943
(80,175) **
$40,950
(53,417) **
**p<.001
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Results
Across the Region in 2000, 86.5 percent of patients’ hospitalizations were paid by
Medicare, with Riverside County having the highest percentage of fallers billing
Medicare (91.1). Orange County (87.5%), Los Angeles County (86.2%), and Ventura
County (84.0%) followed. San Bernardino had the lowest percentage of Medicare
billings at (82.5%)
Similar to 2000, 87 percent of the hospitalizations were paid by Medicare across
the Region in 2006. However, by 2006, individual counties’ patients’ billing sources
changed. For example, in 2006, Ventura County had the highest percentage of cases
billing Medicare in the Region, at 95.3 percent, compared to 84 percent in 2000. Orange
County’s Medicare billings grew to 89 percent in 2006. Riverside County dropped its
percentage of Medicare billing between 2000 and 2006.
The vast majority of Medi-Cal patients live in Los Angeles County. In 2000,
hospitals billed Medi-Cal for 852 patients, 5.2 percent of the fallers in Los Angeles
County, and number and percentage grew to 1,123 and 6.3 percent of the cases in 2006.
San Bernardino County had the second highest Medi-Cal billing rate, 2.5 percent, in both
2000 and 2006, but this represented only 55 and 59 patients, respectively. Ventura had
the lowest percentage billing Medi-Cal (.5%), less than 20 patients total in the two years.
Fallers whose charges were paid with private insurance may include those who do
not have Medicare and Medi-Cal. In 2000, 8.9 percent of patients’ billed charges were
paid by private insurance, while the figure dropped to 7.8 percent in 2006. In 2000, 14.6
percent of fallers in San Bernardino County and 14.1 percent of fallers in Ventura County
125
utilized private insurance to pay for their charges. Los Angeles County’s 1,248 patients
who utilized private pay comprised only 7.6 percent of its patients in 2000.
In 2006, Riverside County had an increase in percentage of private pay patients,
9.6 percent up from 6.7 percent in 2000, but the remaining 4 counties had a decline in
private pay patients. Santa Barbara County’s private pay patients declined to 13.5
percent. However, Ventura County’s private pay patients declined dramatically to 4
percent in 2006.
Two logistic regressions were performed to determine the odds of specific
demographic characteristics being associated with Medicare and Medi-Cal utilization in
the Region’s hospitalized fallers in 2006 (N=29,857). Table 28 shows the results for
Medicare. Table 29 shows the results for Medi-Cal.
Among the Region’s older adults, advancing age is a determinant of Medicare
utilization. Table 28 shows that the oldest hospitalized fallers have the greatest odds of
having their billed charges paid by Medicare. Compared to 65-74 year olds and
controlling for race, county, length of stay, billed charges, and discharge, 75-84 year olds.
126
Table 28
Odds Ratios (OR) Representing Effects of Demographic Characteristics, County of Residence, and
Discharge Disposition on Having Medicare as a Source of Pay, Controlling for Length of Stay and Billed Charges:
Los Angeles Region
OSHPD Hospital Patient Discharge Data, 2006
B S.E. Wald df Sig. Exp(B)
Constant 2.291 0.068 1136.737 1.000 0.000 9.883 **
Controls Length of Stay -0.004 0.001 8.915 1.000 0.003 0.996 *
Total Charges 0.000 0.000 3.871 1.000 0.049 1.000
Age 75-84 0.407 0.044 85.599 1.000 0.000 1.502 **
(Ref. 65-74) 85-94 0.458 0.048 93.058 1.000 0.000 1.582 **
95+ 0.635 0.105 36.263 1.000 0.000 1.887 **
Race Latino -0.775 0.044 307.042 1.000 0.000 0.461 **
(Ref. White) African-Amer. -0.255 0.087 8.534 1.000 0.003 0.775 *
Asian -0.705 0.060 137.372 1.000 0.000 0.494 **
Other -0.799 0.089 80.173 1.000 0.000 0.450 **
County Orange 0.132 0.051 6.865 1.000 0.009 1.142 *
(Ref. Los Angeles) San Bern. -0.305 0.060 25.836 1.000 0.000 0.737 **
Ventura 1.006 0.127 63.102 1.000 0.000 2.735 **
Discharge Home -0.642 0.061 109.822 1.000 0.000 0.526 **
(Ref. Diff. Acute) SNF -0.416 0.061 46.557 1.000 0.000 0.659 **
Died -0.492 0.111 19.811 1.000 0.000 0.611 **
N=29,857
*p<.01, **p<.001
127
Table 29
Odds Ratios (OR) Representing Effects of Demographic Characteristics, County of Residence, and
Discharge Disposition on Having Medi-Cal as a Source of Pay, Controlling for Length of Stay and Billed Charges:
Los Angeles Region
OSHPD Hospital Patient Discharge Data, 2006
B S.E. Wald df Sig. Exp(B)
Constant -5.290 0.149 1256.486 1.000 0.000 0.005 **
Controls Length of Stay 0.025 0.005 24.103 1.000 0.000 1.025 **
Total Charges 0.000 0.000 8.519 1.000 0.004 1.000 *
Age 75-84 -0.148 0.071 4.421 1.000 0.036 0.862
(Ref. 65-74) 85-94 -0.196 0.079 6.133 1.000 0.013 0.822 *
Sex Female 0.467 0.068 47.270 1.000 0.000 1.596 **
Race Latino 2.271 0.076 892.475 1.000 0.000 9.690 **
(Ref. White) African-Amer. 0.712 0.167 18.113 1.000 0.000 2.039 **
Asian 2.253 0.089 642.458 1.000 0.000 9.516 **
Other 2.136 0.129 274.098 1.000 0.000 8.464 **
County Orange -0.867 0.111 60.720 1.000 0.000 0.420 **
(Ref. Los Angeles) Riverside -0.986 0.149 44.032 1.000 0.000 0.373 **
San Bernard. -0.766 0.141 29.560 1.000 0.000 0.465 **
Ventura -2.053 0.380 29.170 1.000 0.000 0.128 **
Discharge Home 1.290 0.122 112.401 1.000 0.000 3.632 **
(Ref. Diff. Acute) SNF 0.725 0.125 33.885 1.000 0.000 2.064 **
AL 1.104 0.272 16.460 1.000 0.000 3.018 **
Died 0.920 0.195 22.331 1.000 0.000 2.509 **
N=29,857
*p<.01, **p<.001
128
have 1.5 times greater odds, 85-94 year olds have 1.6 greater odds, and 95+ year olds
have 1.9 times greater odds of using Medicare to pay for their billed charges (p<.001).
Race is a predictor of Medicare utilization as well. As shown in Table 29, non-
White patients had 1.3 to 2.2 (1/.775=1.3) times greater odds of not having Medicare
(p<.01-.001), compared to White fallers. Therefore, White fallers in the Region are more
likely to utilize Medicare than their peers. The county in which one lives and was
hospitalized predicts Medicare utilization also. Compared to Los Angeles County,
Ventura County residents were 2.7 times more likely to use Medicare to pay for their
hospitalization bills (p<.01), Orange County residents were 1.14 times more likely
(p<.01), and San Bernardino County residents were .7 times as likely (p<.001).
Table 29 shows that unlike with Medicare, gender is a predictor of Medi-Cal
utilization. Females were 1.6 times more likely to utilize Medi-Cal to pay for hospital
bills than males (p<.001). Race is a strong predictor of Medi-Cal utilization. Latinos
were 9.7 times more likely, Asians were 9.6 times more likely, Other races were 8.5
times more likely, and African-Americans were 2 times more likely to utilize Medi-Cal
(p<.001). Compared to their younger peers 85-94 year olds were 1.2 (1/.82=1.2) times
more likely not to have Medi-Cal (p<.01).
In addition, discharge disposition was a predictor of Medi-Cal usage. Compared
to those discharged to a different acute setting, those discharged Home were 3.6 times
more likely to utilize Medi-Cal, Assisted Living discharges were 3 time more likely, fatal
fallers were 2.5 times more likely, and SNF discharges were 2.1 times more likely to
utilize Med-Cal to pay for their hospitalization bills (p<.001). Table 29 shows also that
129
the fallers’ county predicts Medi-Cal use, as patients in the four smaller counties were
less likely than Los Angeles County’s to have Medi-Cal pay for their hospital charges
(p<.001).
Discussion
For falls in the Los Angeles Region, the $1.26 billion bill to Medicare and $84
million bill to Medi-Cal in 2006 made a considerable impact on the coffers of the federal
and state-administrated health insurance systems. With Baby Boomers’ increasing the
numbers of the Region’s aging population in the coming decades, it is expected that total
costs of fall related injuries will increase dramatically. OSHPD data does not provide
information on medical, rehabilitation, and long term care costs billed to Medicare and
Medi-Cal following discharge; however the association between patients’ discharge
dispositions’ and insurance coverage are noteworthy. It was unexpected that Medi-Cal
patients had the highest likelihood of being discharged Home, followed by AL, because
Medi-Cal covers post acute rehabilitation costs in SNF. The demographic
characteristics of Medi-Cal patients, however, may have an impact on discharge
disposition. Discharge will be analyzed as a dependent variable in the next chapter.
However, this chapter’s analysis offers insight into demographic and place-based
characteristics of Medicare and Medi-Cal-covered fallers. The most notable
demographic results are the high odds of Medi-Cal patients being non-White and female
and the odds of Medicare patients being White. Cumulative disadvantage theory
(Dannefer, 1987) supports the notion that low income non-White older adults are likely to
130
be on Medi-Cal, with health disparities making them more prone to poor health outcomes
(Gassoumis et al. 2010; Shuey & Willson, 2008). Older adults with a greater number of
chronic health problems could have longer stays in the hospital and higher billed charges
after injurious falls. The higher Medi-Cal utilization for falls among Latino, Asian,
African-American, and Others are costly to the State of California. Non-White fallers
have low Medicare utilization. White fallers in the Region are more costly to the federal
Medicare system.
In order to understand more about the impact of socioeconomic status on a
population’s fall profile, it is useful to examine Source of Pay hospitalization discharge
data in comparison with Census Data presented in Chapter 3 and repeated below. It is
not unexpected that the County, Los Angeles, with highest percentages of low income
older adult households would have a higher percentages of patients whose source of pay
is Medi-Cal. Conversely, counties with lower percentages of lower income older adult
households have higher percentages of patients whose source of pay is Medicare and/or
private pay.
131
Figure 31, above, shows that Ventura has a higher percentage of residents with
Social Security than three other counties, except Riverside. Receiving Social Security
benefits is generally a prerequisite to having Medicare health coverage. Regression
analysis showed that fallers in Ventura County were 2.7 times more likely and Orange
County were 1.1 times more likely than Los Angeles County fallers to have their
hospitalization paid by Medicare. These results are consistent with the Census analysis
that showed that Orange and Ventura Counties have the highest median incomes in the
Region and the largest percentages of older adults with high incomes. Furthermore, as
shown was shown in Figure 22 in Chapter 3, both Orange and Ventura Counties have the
lowest percentage of 65+ households with an income below $25,000. Women and racial
minority older adults in the Los Angeles Region who may have had fewer years of
consistent salary pay than their White male counter parts are less likely to have high
132
Social Security benefits and adequate Medicare coverage and are more likely to require
Medi-Cal to meet their health care needs, as reflected in the regression results in Table 29.
As shown in Figure 31, Los Angeles and San Bernardino had the lowest
percentages of households receiving Social Security income, which is why those not
receiving Social Security would need to apply for SSI and Medi-Cal. Some older people
receive low Social Security benefits and therefore also apply for SSI and Medi-Cal. Los
Angeles and San Bernardino have the highest percentages of households receiving SSI.
However, these households are not necessarily older adult households. Figure 22 also
showed that Los Angeles and San Bernardino Counties have the highest percentages of
65+ households living with low incomes under $25,000.
133
Limitations
While this chapter analyzes charges that the Region’s hospitals billed to Medicare
and Medi-Cal, it is unknown from this California Hospital Patient Discharge data set
whether the insurer reimbursed the total amount billed. In calculating the costs of falls,
Roudsari et al. (2005) analyzed costs by Medicare rather than charges billed by the
hospitals. They argue that other studies calculated costs based on billed charges but that
reimbursed costs give a more accurate representation of the true cost. However, broad
estimations of the direct costs of falls typically include long term care and follow up
services as well as non-Medicare payments. In this study of OSHPD data, analysis
includes acute hospitalization care only and not Emergency Department, long term care,
or follow-up services. Nevertheless, because a high percentage are billed to Medicare
and Medi-Cal, these charges are costly to the American public.
Another limitation of this study of source of pay and the data available is that
patients who have Medicare, Medi-Cal, and private insurance are not mutually exclusive.
The OSHPD discharge data does not include more than one expected source of pay.
However, older people often carry two types of medical insurance. Medicare Part A
typically covers hospitalization benefits while Medicare Part B covers outpatient visits.
Some people have both coverages. Others do not. For those older adults who do not
carry Medicare Part A to cover hospitalization, if their income and assets are low enough,
they may qualify for Medi-Cal. Therefore, some patients have both Medicare and Medi-
Cal, but probably only Medicare Part B. In addition, patients without Medicare Part A
who do not qualify for Medi-Cal can utilize private insurance carriers. If a patient has
134
both Medicare and Medi-Cal, the hospital would list one carrier as the expected
reimbursement agent, and therefore, it is unknown not only how much of the billed
charges were reimbursed, but which insurance carrier made the payment. Administrative
policy changes that include more details about multiple expected sources of pay and
reimbursement rates would improve data on fall related injuries in the future.
Source of pay is important in examining the length of hospitalizations, treatment
received, billed charges, age, and race of the Region’s fallers. Health insurance coverage
is an important factor in fallers’ discharge disposition. Whether the patient has Medicare,
Medi-Cal, and/or private insurance is crucial to rehabilitative and/or long term care
implemented post-hospitalization. The next chapter, Chapter 7, will examine the
discharge disposition of the Region’s fallers.
135
CHAPTER 6 REFERENCES
Dannefer, D. (1987). Aging as intracohort differentiation: Accentuation, the Matthew
Effect, and the life course. Sociological Forum, 2(2), 211–236.
Gassoumis, Z., Wilber, K., Baker, L., Torres-Gil, F., (2010). Who Are the Latino Baby
Boomers? Demographic and Economic Characteristics of a Hidden Population.
Journal of Aging & Social Policy, 22:1–16.
OSHPD, (2007). Patient Discharge Data File Documentation January-December 2006.
NonPublic Version. State of California Office of Statewide Health Planning and
Development.
Roudsari B.S., Ebel, B.E,, Corso, P.S., Molinari, N.M., Koepsell, T.D., (2005). The
acute medical care costs of fall-related injuries among the U.S. older adults.
Injury, International Journal of Care for the Injured; 36: 1316-22.
Shuey, K. M., & Willson, A. E. (2008). Cumulative disadvantage and black-white
disparities in life-course health trajectories. Research on Aging, 30(2), 200–225.
136
CHAPTER 7: DISCHARGE DISPOSITION
Discharge Disposition of Fallers in the Los Angeles Region
While the hospitalization costs associated with fall-related injuries in the Los
Angeles Region encumbered the Medicare and Medi-Cal systems respectively with $1.26
billion and $84 million in 2006, the subsequent costs of post-acute care for nearly 30,000
fallers were longer term. The original model in Figure 33 shows the flow of community
dwelling older adults after a fall. Figure 34 shows the discharge disposition of the Los
Angeles Region’s hospitalized fallers. Most fallers in the Los Angeles Region are
discharged to a skilled nursing facility (SNF). In 2000, 49 percent of hospitalizations
resulted in a SNF discharge. While the number of discharges to a SNF grew in 2006, the
percentage share of patients going to SNFs was somewhat smaller (45.9%). Figure 34
shows that the percentage of discharges to SNFs, Assisted Living, and different Acute
Hospitals declined between 2000 and 2006, while the percentage of discharges to Home
and Other increased over six years across the Region. The percentage of patients dying
remained constant.
137
Home
Emergency
Room
Hospital
Admittance
Died
Community
Dwelling
Older Adult
Falls at Home
or Away
From Home
SNF
AL
Other Acute
No
Injury
Discharge
Injur
y
Figure 33
Discharge Model Following a Community Dwelling Older Adult’s
Hospitalization for a Fall Related Injury
138
138
Generally, Medicare pays for certain rehabilitation costs and skilled nursing for a
prescribed number of days following a three day hospital stay. Medi-Cal pays most
skilled nursing home costs as well, and those who have Medi-Cal and SSI can utilize it to
pay for certain types of assisted living, such as board and care homes. These costs,
though not calculated in this data, add ongoing expenses to the public health problem of
falls.
Previous chapters found that mean billed hospitalization charges of fallers differ
between counties in the Los Angeles Region. Long term care costs differ depending on
the geographical location within a state and whether the location is urban, rural, or
suburban (MetLife, 2009). Without being able to ascertain from the OSHPD data set
what the fiscal impacts were after the Los Angeles Region’s fallers were discharged, the
following research questions remain concerning discharge disposition: How do discharge
139
139
dispositions differ by County within the Los Angeles Region and between Medicare and
Medi-Cal patients? What are the demographic differences related to fallers’ discharge
disposition?
H1: Demographic differences will determine discharge disposition.
H2: Source of Pay will be a determinant of discharge disposition.
H3: County of residence will be a determinant of discharge disposition.
H4: Injury Type will be a predictor of discharge disposition.
METHOD
Three binary logistic regressions tested Hypotheses 1-4 for discharge disposition:
with dependent variables of SNF, Home, and Death. Rationale for omitting AL
discharges in a regression analysis include the small number, inconsistencies in
definitions of AL care, and limited number of significant findings. Independent
variables include age, gender, race, county, injury type, and source of pay. Length of
stay is included as a control. The logistic regressions assess the odds of ratios of the
independent variables compared to referent groups of: 65-74 year olds for age, males,
White fallers for race, other injuries, Los Angeles County, and those whose expected
source of pay was private insurance. Analyses utilized SPSS software for Windows.
Independent variables were tested for significance and are shown following the
descriptive statistics in Table 30 below. Variables with significant associations were
included in the regression model. SPSS employed a backwards likelihood ratio to
determine which variables were the best predictors of discharge disposition.
140
140
Results
Skilled Nursing Facility (SNF)
While Figure 34 above showed that the majority of fallers in the Region are
discharged to a SNF when the leave the hospital, Figures 35 and 36 compare SNF
discharges in each county. Orange County’s percentage of SNF discharges remained
constant and Home discharges increased half a percentage point between 2000 and 2006.
However, the other four counties experienced reduced SNF discharges: Los Angeles
(-3.29%), Riverside (-3.33%), San Bernardino (-10.06%), and Ventura (-3.02) and
increases in their percentage of Home discharges in the six year period. Riverside
County, had the highest percentage of SNF discharges in both years: 63.9 percent in 2000
and 60.6 percent in 2006. Los Angeles County had the lowest SNF discharge rate at in
2000 at 45.2 percent and again in 2006 at 41.9 percent.
141
141
142
Death
Fallers who died in the hospital as a result of their injuries accounted for 2.7 to 3.9
percent of discharges in 2000, for a total of 886 deaths. San Bernardino had the highest
rate of deaths from falls, which represented 87 fallers, but 510 Los Angelenos died as a
result of their fall in 2000. In 2006, the counties each had more similar rates, between 3
and 3.4 percent of hospitalized fallers in each county dying as a result of their injuries, a
total of 962 people across the Region. San Bernardino and Orange Counties had fewer
deaths from falls in 2006: 79 and 151 respectively. Los Angeles, Riverside, and Ventura
Counties had an increase in the number of fall related deaths: 585, 98, and 49
respectively.
143
Home
Regionwide, 34 percent of fallers were discharged home following hospitalization
in 2000, and 36.5 percent of fallers were discharged home in 2006. Los Angeles County
had the highest discharge rate to home in 2000, more than 35 percent, and Riverside
County had the lowest (27.3%).
144
In 2006, San Bernardino County’s home discharge rate was reduced significantly
to 40.1%, the highest percentage in the region to be sent home and a 7.8 percent change
from 6 years prior. Again in 2006, Riverside County (29.3%) had the lowest percentage
of home discharges, as shown in Figure 39. In Los Angeles County, 38.3 percent were
discharged to their homes in 2006, a 2.5% increase from 2000.
Logistic Regressions
Table 30 shows that the bivariate analyses of independent variables of age, sex,
race, county, source of pay, length of stay, and billed charges all had significant
relationships with discharge disposition. Therefore, they were all input into the
regression model.
145
Table 30
Discharge Disposition, Tests of Significance for Independent Variables
N=29,857
Dependent Variable
SNF Home AL Died
Other
Acute
13,702 10,897 421 962 909
Indep. Variable % % % % %
Sex**
Male 27.79 35.29
29.22 50.42 37.84
Female 72.21 64.71
70.78 49.58 62.16
Race**
White 76.35 65.27
77.43 71.10 66.89
African-American 3.18 4.90
3.56 2.91 5.39
Latino 12.41 18.42
8.31 14.97 17.38
Asian 5.46 8.39
8.08 8.00 6.49
Other 2.60 3.02
2.61 3.01 3.85
County**
Los Angeles 54.10 62.27
61.05 60.81 61.50
Orange 18.71 15.77
15.20 15.70 19.36
Riverside 14.60 8.88
9.74 10.19 7.81
San Bernardino 7.43 8.73
11.88 8.21 8.47
Ventura 5.16 4.35
2.14 5.09 2.86
Source of Pay**
Medicare 88.27 83.79
89.79 86.07 82.07
Medi-Cal 3.24 6.74
4.51 5.51 3.85
Private Pay 8.23 8.26
5.70 7.17 13.09
M (SD) M (SD) M (SD) M (SD) M (SD)
Age
83.0
(7.5)**
79.7
(8.0)** 84.1 (8.2) 83.1 (8.0) 81.6 (7.8)
Length of Stay 5.8 (5.6)** 4.3 (4.5)** 5.5 (6.0)
12.3
(54.9)** 6.3 (5.5)
Billed Charges $48,769* $31,945** $29,070** $103,776** $66,353**
*p<.01, **p<001
146
Discharge to a SNF
Table 31 shows that in the Los Angeles Region in 2006, age, gender, race, county,
and injury type and insurance coverage are all determinants of being discharged to a SNF
following hospitalization for falls. Compared to males, females are 1.2 times more likely
to be discharged to a SNF, holding constant the other independent variables (p<.001).
Compared to their younger peers, Los Angeles fallers were more likely to be discharged
to a SNF with advancing age, an effect of 1.7 greater odds for 75-84 year olds, 2.3 greater
odds for 85-94 year olds, and 2.5 times greater odds for 95+ year olds (p<.001).
A faller’s race impacted the likelihood of being discharged to a SNF as well, with
White fallers being most likely to be discharged to a SNF. Compared to Whites, Latinos
had 1.2 lower odds (1/.8=1.2), African-Americans had 1.2 lower odds, Asians had 1.5
lower odds, and Other races had 1.2 lower odds of being discharged to a SNF (p<.001).
In addition, compared to fallers whose hospital bills are paid by private insurance, fallers
on Medi-Cal had 1.6 lower odds (1/.68=1.5) of being discharged to a SNF (p<.001).
The faller’s county was a predictor of SNF discharge, with Riverside County
fallers having the highest likelihood of SNF discharge compared to Los Angeles County
fallers (2.1), followed by Orange County (1.4), and Ventura County (1.2) (p<.001). The
strongest predictor of SNF discharge, however, was lower limb fracture (including hip),
whose fallers were 3.3 times more likely have a SNF discharge than other injuries
(p<.001). Spinal cord injured patients were 1.7 times more likely and upper limb
fractures were 1.2 times more likely than other injuries to be discharged to a SNF as well
147
(p<.001). In addition, fallers with head injuries were 1.3 (1/.78=1.3) times more unlikely
to be discharged to a SNF than other injured fallers (p<001).
148
Table 31
Odds Ratios (OR) Representing Effects of Injury Type, Dem. Characteristics,
County,
Length of Stay, and Source of Pay on Being Discharged to a SNF:
Los Angeles Region
OSHPD Hospital Patient Discharge Data, 2006
N=29,857 B S.E. Wald df Sig. Exp(B)
Constant
-
1.415 0.041 1199.241 1 0.000 0.243
Length of
Stay 0.007 0.002 11.998 1 0.001 1.007 **
Injury Type Head
-
0.254 0.054 21.735 1 0.000 0.776 **
(Ref. Other
Injury) Spinal 0.580 0.043 180.325 1 0.000 1.786 **
Upper Limb 0.188 0.053 12.716 1 0.000 1.207 **
Lower Limb 1.179 0.028 1728.705 1 0.000 3.253 **
Age 75-84 0.543 0.035 245.592 1 0.000 1.721 **
(Ref. 65-74) 85-94 0.813 0.036 511.977 1 0.000 2.254 **
95+ 0.936 0.067 193.436 1 0.000 2.550 **
Sex (Ref. Male) Female 0.185 0.027 46.703 1 0.000 1.204 **
Race (Ref.
White) Latino
-
0.205 0.037 30.460 1 0.000 0.814 **
African-
Amer.
-
0.201 0.066 9.228 1 0.002 0.818 *
Asian
-
0.418 0.051 68.108 1 0.000 0.659 **
Other Race
-
0.148 0.076 3.820 1 0.051 0.862
County Orange 0.305 0.034 80.804 1 0.000 1.356 **
(Ref. Los
Angeles) Riverside 0.714 0.041 304.972 1 0.000 2.043 **
Ventura 0.195 0.058 11.305 1 0.001 1.215 **
Source of Pay Medi-Cal
-
0.373 0.065 32.919 1 0.000 0.688 **
Ref. (Private
Ins.)
*p<.01,** p<.001
149
Discharge Home
Table 32 shows that injury type, age, gender, race, county, and source of pay were
determinants of Los Angeles County fallers discharge to Home. Compared to 65-74
year olds, 75-84 year olds were 1.8 times less likely (1/.56=1.8), 85-94 year olds were 2.6
times less likely, and 95+ year olds were 3.4 times less likely to be discharged home
following hospitalization for fall-related injuries (p<.001). In addition, females were 1.1
times less likely to be discharged home (p<.01).
Los Angeles County’s non-White fallers, however, are more likely to be
discharged home following hospitalization. Latino, African-American, and Asian fallers
were 1.1-1.4 times more likely than Whites to be discharged home (p<.001).
Furthermore, results indicate that controlling for injury, length of stay, billed charges, and
demographic characteristics, Medi-Cal recipients were 2.1 times more likely to be
discharged home and Medicare recipients were 1.1 times more likely not to be discharged
home than those who had private insurance coverage (p<.001). County played a role in
determining Home discharges too. Fallers in Orange County were 1.1 times more likely
not to be discharged home (p<.01) and Riverside County were 1.4 times more likely not
to be discharged home (p<.001) than their peers in Los Angeles County.
Type of injury is the strongest predictor of discharge home, as it was with
discharge to a SNF. Fallers with lower limb fractures 5.4 times more likely not to be
discharged home than those with other injuries. Furthermore, those with spinal cord
injuries were 1.9 times more likely not to be discharged home, and head injuries were 1.3
times more likely not to be discharged home (p<.001).
150
Table 32
Odds Ratios (OR) Representing Effects of Injury Type, Dem. Char., County,
Length of Stay, and Source of Pay on Being Discharged to Home:
Los Angeles Region
OSHPD Hospital Patient Discharge Data, 2006
B S.E. Wald df Sig. Exp(B)
N=29,857 Constant 1.168 0.058 398.691 1 0.000 3.214
Length of
Stay
-
0.083 0.003 620.891 1 0.000 0.920 **
Injury Type Head
-
0.280 0.050 30.926 1 0.000 0.756 **
(Ref. Other
Injury) Spinal
-
0.667 0.044 225.043 1 0.000 0.513 **
Lower Limb
-
1.681 0.032 2715.577 1 0.000 0.186 **
Age 75-84
-
0.587 0.035 282.897 1 0.000 0.556 **
(Ref. 65-74) 85-94
-
0.965 0.037 670.318 1 0.000 0.381 **
95+
-
1.210 0.077 248.397 1 0.000 0.298 **
Sex (Ref.
Male) Female
-
0.074 0.028 6.807 1 0.009 0.928 *
Race (Ref.
White) Latino 0.331 0.038 74.284 1 0.000 1.393 **
African-
Amer. 0.317 0.067 22.195 1 0.000 1.373 **
Asian 0.233 0.051 20.597 1 0.000 1.263 **
Other Races 0.138 0.080 2.934 1 0.087 1.147
County Orange
-
0.101 0.037 7.469 1 0.006 0.904 *
(Ref. Los
Angeles) Riverside
-
0.355 0.045 61.669 1 0.000 0.701 **
San Bern. 0.095 0.049 3.710 1 0.054 1.100
Source of Pay Medicare
-
0.137 0.047 8.477 1 0.004 0.872 *
(Ref. Private
Ins.) Medi-Cal 0.735 0.079 86.653 1 0.000 2.085 **
*p<.01,**
p<.001
151
Death
The binary logistic regression analyzing odds ratios of demographic
characteristics on discharge in death found that fatal fallers were nearly 3 times more
likely to be ages 95+, compared to 65-74 year olds (p<.001). In addition, 75-84 year olds
were 1.3 times more likely to die in the hospital (p<.01), and 85-94 year olds were 1.7
times more likely (p<001). Injury type is a strong predictor of death. Head injured
fallers had the greatest odds of death: 3.3, followed by internal injuries: 2.4. Upper limb
injuries, spinal injuries, and lower limb injuries had 3.2, 1.8, and 1.3 greater odds
respectively of not dying in the hospital (p<.001). Los Angeles Region’s males die
more often from fall-related injuries than females; Females were half as likely to die in
the hospital from their fall related injuries (p<.001). County was not a determinant of
fatal falls.
152
Table 33
Odds Ratios (OR) Representing Effects of Injury Type, Dem. Char., County,
Length of Stay, and Source of Pay on Death in Hospital
Los Angeles Region
OSHPD Hospital Patient Discharge Data, 2006
N=29,857 B S.E. Wald df Sig. Exp(B)
Constant
-
3.518 0.099 1259.974 1 0.000 0.030
Length of
Stay 0.027 0.004 54.845 1 0.000 1.027 **
Injury Type Head 1.196 0.090 178.365 1 0.000 3.307 **
(Ref. Other
Injury) Spinal
-
0.601 0.153 15.349 1 0.000 0.548 **
Upper
-
1.160 0.257 20.368 1 0.000 0.314 **
Lower
-
0.263 0.082 10.353 1 0.001 0.769 **
Internal 0.861 0.263 10.725 1 0.001 2.366 **
Age 75-84 0.287 0.099 8.456 1 0.004 1.333 *
(Ref. 65-74) 85-94 0.530 0.100 28.156 1 0.000 1.699 **
95+ 1.097 0.152 52.276 1 0.000 2.997 **
Sex (Ref.
Male) Female
-
0.697 0.068 104.988 1 0.000 0.498 **
*p<.01,**
p<.001
Discussion
Throughout the Region, fallers discharged to a SNF were older, had longer
lengths of stay, and higher billed charges than those discharged elsewhere. Similarly,
those who died in the hospital also were older, with longer lengths of stay and higher
billed charges. On the other hand, fallers discharged Home were younger than their
peers with lower billed charges and shorter lengths of stay.
There were demographic differences in discharge disposition of hospitalized
fallers, based on age, gender, and race. Females were more likely than males to be
153
discharged to a SNF. Conversely, being female had a negative effect on being
discharged home. Males had greater odds of being discharged home. These results are
similar to Stevens and Sogolow’s (2005) findings that males die more often than females
but that females suffer more injuries, such as hip or pelvis fracture and traumatic brain
injury, that require females to undergo long term care and rehabilitation after discharge.
Injury diagnosis was a predictor of discharge disposition, and the findings were
supported by previous research (CDC, 2005; Stevens & Sogolow, 2005; Stevens et al.,
2006). Therefore, it is not unexpected that internal and head injuries were predictors of
death, that lower limb fractures (including hip), spinal injuries, and upper limb fractures
were predictors of SNF discharge, and that other injuries predicted discharge Home.
Advancing age, known to be a risk factor for hip fracture, increased chances of going to a
SNF following hospitalization. The oldest counties, Orange, Riverside, and Ventura, had
the higher likelihoods of SNF discharge than Los Angeles. These three counties have far
fewer minorities than Los Angeles County.
Race had an effect on SNF discharge, with White fallers being more likely to be
discharged to a SNF than their peers. White fallers, especially women, may require SNF
discharge more often than non-White fallers because more often, they live alone and are
less likely to have family members available to care for them. Asian fallers had the
greatest odds, compared to Whites, of not being discharged to a SNF. This finding is
consistent with the discharge data from 1995-1997 analyzed by Ellis and Trents (2001b).
At the same time that non-White fallers were more likely not to be discharged to a SNF,
they were more likely to be discharged home.
154
Sociological theories of filial obligation and cultural norms in caregiving among
minority groups support the findings that non-White fallers were more likely to be
discharged home and avoid placement in a SNF following hospital discharge. The
finding that Latinos, African-Americans, and Asians were the more likely to be
discharged home supports previous research that caregiving obligations are especially
pronounced in minority communities (Goodman, 1990; Jones, et al., 2001). An
important consideration is whether discharge home for these fallers was medically
indicated and whether discharge to homes that do not provide adequate supportive
features will lead to repeat falls. In addition, while families may have cultural
expectations that they will be able to care for their aging relative at home after a fall
related injury, practical aspects of providing that care may not be realistic. Further
research should address the relationship between race and injury diagnosis in the Region
and whether non-Whites do not have the injury outcomes related to SNF discharge.
Source of Pay was a determinant of discharge disposition, with Medi-Cal patients
were more likely to be discharged home. Chapter 6 concluded that being non-White was
a predictor of Medi-Cal utilization. Therefore, it is not unexpected that Medi-Cal
patients who are minorities would be more likely to be discharged home. A question for
further research, however, is whether the discharge disposition of Medi-Cal patients to
the home is a fiscal, medical, and/or cultural issue. Although the program has suffered
cuts in the recent California fiscal crisis, Medi-Cal patients are eligible for the In Home
Supportive Services program (IHSS), which can pay caregivers, including family
members, to help out older adults who need assistance at home. In addition, Medi-Cal
155
patients who are frail and at risk SNF placement are eligible for programs such as
Multipurpose Senior Services Program (MSSP) and Assisted Living and Medi-Cal
Waiver programs whose aim is to save long term care costs by providing supportive
services in the home.
There were lower rates of SNF discharges in 2006 than in 2000. In recent years,
California’s healthcare, aging and housing policies have aimed to reduce
institutionalization, patients’ lack of choice, and high costs of skilled nursing care
through programs such as MSSP and Waivers. However, current budget problems have
affected the funding for these programs and IHSS. Further research which analyzes the
discharge rates of hospitalized fallers to SNFs and Home during the state’s fiscal
rollbacks would provide further knowledge.
In addition to the state, local governments in California can play important roles
in the success of Home discharges through housing programs such as home repair, home
modification, and accessory dwelling unit (ADU) development which benefit
intergenerational families and those who need caregivers. Furthermore, local investment
in community services and assisted transportation can provide support for home-
discharged patients and their families. These programs, including physical activity
programs and adult education, can be implemented at the local level through federal
Older Americans Act funding, and can help mitigate risk of repeat falls.
Such coordination of federal, state, and local policies are critical for all older
adults, including the 40,000 to 65,000 Los Angeles Region older adults expected to fall
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each year between 2020 and 2050. Conclusions about the profiles of fallers and further
discussion of the local government’s role in fall risk reduction will follow in Chapter 8.
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CHAPTER 7 REFERENCES
CDC, 2005. Centers for Disease Control and Prevention, National Center for Injury
Prevention and Control. Web–based Injury Statistics Query and Reporting System
(WISQARS) [online]. (2005) Retrieved April 30, 2010 from
www.cdc.gov/ncipc/wisqars.
Ellis, A.A., & Trent, R.B. (2001b). Hospitalized fall injuries and race in California. Injury
Prevention, 7, 316-320.
Goodman, C.C. (1990). The Caregiving Roles of Asian American Women. Journal of
Women and Aging, 2, 1, 109-120. Retrieved on May 5, 2010 from
http://www.informaworld.com/smpp/content~db=all~content=a904730054.
Jones, P., Jaceldo, K., Lee, J., Zhang, X., Meleis, A.. (2001). Role integration and
perceived health in Asian American women caregivers. Research in Nursing and
Health, 24, 2: 133-144. Retrieved on July 8, 2010 from
http://www.3.interscience.wiley.com/journal/80502584.
MetLife (2009). The 2009 MetLife Market Survey of Nursing Home, Assisted Living,
Adult Day Services, and Home Care Costs. Westport, CT: The MetLife Mature
Market Institute. Retrieved on February 21, 2010 from
http://www.metlife.com/assets/cao/mmi/publications/studies/mmi-market-survey-
nursing-home-assisted-living.pdf.
Stevens J.A., & Sogolow E.D., (2005). Gender differences for non-fatal unintentional fall
related injuries among older adults. Injury Prevention, 11, 115–9.
Stevens JA, Corso PS, Finkelstein EA, Miller TR. (2006). The costs of fatal and nonfatal
falls among older adults. Injury Prevention, 12, 290–5.
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CHAPTER 8: A NEEDS ASSESSMENT FOR REDUCING FALLS
IN THE LOS ANGELES REGION
Within the Region, each county and its municipalities can target specific
population groups within their boundaries. Findings from this study can assist in
determining the greatest need for fall prevention, and encourage further, more detailed
analyses. The results of the studies on billed charges, source of pay, and discharge
disposition can aide in priority and goal setting to mitigate hospitalization outcomes.
Billed Charges
The Region’s hospital bills for falls totaled more than $1.45 billion in 2006:
$1.26 billion to Medicare and $84 million to Medi-Cal. Because of its large older adult
population, the Los Angeles Region’s fall related costs represent a large percentage of the
nation’s and state’s costs. The highest cost fallers are those who die, as a result of
internal and head injuries. Fallers who break their hips and other lower limbs and are
discharged to a SNF follow fatal fallers in incurring billed charges. Those who are
discharged home incur fewer billed charges. Surprisingly, fallers in the 65-74 year old
age range are more costly than their older peers, and Medi-Cal patients incur higher
billed charges than others. The least expensive hospital bills in the Region were in the
two inland counties: Riverside and San Bernardino. Both these counties have lower
median incomes among 65+ year olds, compared to Orange and Ventura Counties and
lower cost of living, including hospital costs.
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Source of Pay
Medicare paid for eighty-seven percent of the Region’s hospitalizations for falls
in 2006. Fallers for whom the hospital billed Medicare are older than other patients and
more likely to be White. Non-White fallers have lower Medicare utilization. White
fallers are more costly to the federal Medicare system. Orange and Ventura Counties
have the highest utilization of Medicare, which is not unexpected given the counties’
higher income levels and higher income from Social Security.
Fallers for whom the hospitals billed Medi-Cal are much more likely to be non-
Whites, especially Latinos, Asians, and Other races. Higher billed charges and high
Medi-Cal utilization for falls among non-White fallers are costly to the State of
California. Medi-Cal patients are younger than those whose bills were paid by Medicare
or private insurance. Fallers in Los Angeles County have the highest Medi-Cal
utilization; Ventura County has the lowest.
Discharge Disposition
In 2000, 886 fallers died in the hospital as a result of their injuries following a fall,
and 962 died in 2006. Males died more often from fall-related injuries than females.
Those who died in the hospital were older, with longer lengths of stay, and higher billed
charges. The majority of fallers are discharged to a Skilled Nursing Facility (SNF). The
percentage of discharges to SNFs declined between 2000 and 2006, from 49 to 46 percent.
Fallers discharged to a SNF were older, had longer lengths of stay, and higher billed
charges than the other non-fatal patients who were discharged elsewhere. They were
most likely to be White and live in Orange, Riverside, and Ventura Counties.
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The percentage of discharges Home increased over six years, from 34 to 36.5
percent. Patients discharged to their homes were younger, had shorter hospital stays, and
had lower billed charges. Patients discharged Home were more likely to be non-White
and live in Los Angeles County. Increasing age rendered fallers more likely to not be
discharged home across the Region. Advancing age increased chances of going to a
SNF following hospitalization, although some differences among counties exist in fallers
ages 85 and up. Fallers with lower limb injuries, including hips, were most likely to be
discharged to a SNF. On the other hand, those with other injuries were most likely to be
discharged Home.
Goals for Mitigating Hospitalization Outcomes
The outcomes presented above can be mitigated through targeted fall prevention
efforts. For example, if a community’s goal is to reduce fall related deaths, it should
focus prevention efforts on their population’s older White males. If the goal is to reduce
falls’ billion dollar fiscal impacts on the federal Medicare system, White older adults,
especially females, should be targeted, with the goal of keeping them out of the hospital
and SNFs after discharge. Reducing falls in non-White communities, especially among
Asians, Latinos, and Other races would save the state administered Medi-Cal program
millions of dollars each year. Targeting non-White older adults with fall prevention
efforts would reduce falls and diminish the prevalence of fallers discharged into local
jurisdictions’ homes after hospitalization. Younger fallers incur higher billed charges
are more often discharged back into their communities as well, and therefore, local
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coalitions can direct fall prevention efforts towards them. Targeted groups do not need
to be mutually exclusive. Efforts which reach diverse groups of older adults can mitigate
impacts across policy levels.
Local Government’s Role in Preventing Falls
Results of the previous chapters illustrate the severe personal and financial
impacts of falls in the Los Angeles Region’s five counties. The reduction and prevention
of falls among older adults is one step towards reducing the potential fiscal impact of the
aging Baby Boomer population. The scope of fall risk among 70 million Baby Boomers,
combined with growing health care costs, will increase the financial burden of falls over
the next 40 years. The response to the growing public health problem will become an
increasingly pertinent issue in aging policy. Fall-related injuries are a major concern for
the federal government because of the costs billed to Medicare. Medi-Cal costs,
including Long Term Medi-Cal, impact both federal and state budgets.
However, falls are not solely a federal aging policy problem or a state public
health problem. Local governments must address falls within their own boundaries to
mitigate cumulative impacts on state and federal budgets. A community approach to
reducing falls will impact local budgets too. Fire departments and risk management
agencies bear the local cost burden of falls, with emergency response services and
litigious claims. The Los Angeles Region’s local governments, including more than 170
county and city jurisdictions, can prioritize the problem and take a primary role in the
prevention of falls and reducing fall-risk and injuries. Public health and aging policy
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need the cooperation of local policy to reduce falls. A threefold symbiotic relationship
and collaboration are required. Table 34 shows that federal, state, and local policy and
programming all serve older adults after they are discharged home following a fall.
Local policies are especially important in the prevention of falls among community
dwelling older adults before they occur as well.
Table 34
Three Levels of Policy and Programming Serving Older Adults After They are
Discharged Home Following a Fall
Federal--Medicare State—Medi-Cal Local – City and County
Aging Policy Public Health Policy Urban Planning Policy
Home Health Care
In Home Supportive Services
(IHSS)
Home Modifications
Physical Therapy
Multipurpose Senior Services
Program (MSSP)
Fall Prevention /
Physical Activity Program
Medication Management Medi-Cal Waivers Transportation Assistance
Geriatric Specialist
Fall Prevention Assessment
Caregiver Resource Center
Support (CRC)
Street and Sidewalk
Maintenance
Case Management
Educational Programs
Beyond Aging Policy and Public Health: Falls as an Urban Planning Problem
Falls among older people are a growing local policy and urban planning problem,
which will peak over the next 40 years. Recent efforts to reconnect urban planning and
public health (Abbott, 2009; Corburn, 2004; Frumkin et al., 2004; Kochtitzky et al.,
2006) support the prevention of falls in the growing older adult population. The
changing demographics of the Los Angeles Region’s population, combined with the
potential hazards presented by the macro and micro built environments, create a
burgeoning planning issue. Preventing injurious and costly falls are an integral part of
the broader goal of providing safe housing and neighborhoods for the Region’s growing
older population to age in place within the communities that have supported them
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throughout their life spans. Garnering public interest in fall prevention requires that
messages to patients and city residents emphasize positive health and social benefits
(Stevens, Noonan, Rubenstein, 2010), as well as the ability to live independently in the
neighborhood of choice, enjoy elderhood, and age in place.
Collaboration Through Coalitions
Coalitions are important in building capacity in local communities and in
engaging stakeholders in seeking solutions to a common problem. Local officials can
create and support coalitions to promote fall prevention in their communities similar to
other local efforts that require behavior change for the common good, such as recycling,
energy and water conservation, child immunizations, smoking, pet nuisances, driving
under the influence of alcohol and while holding cell phones, and childhood obesity.
Coalitions of planning, public works, housing, code enforcement, parks and recreation,
libraries, and transportation departments can collaborate with senior services agencies,
public health departments, and adult education programs to reduce costly falls and their
injuries. Publicity windows of opportunities include incidences when the news media
reports that celebrities have fallen in their homes and on public streets and sidewalks.
A few coalitions have already begun creating a fall prevention agenda in the Los
Angeles Region. Three fall prevention coalitions have been working to educate the
public and policy makers about the problem of falls. The Ventura County Down with
Falls Coalition and the Down with Falls Coalition, Orange County are two of ten
coalition grantees that were initially funded by the Archstone Foundation to set fall
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prevention agendas across California. More recently, the Kaiser Foundation Health Plan
Inc. funded the Fall Prevention Coalition - Los Angeles, which is addressing the
disproportionately high rate of fall injury among older adults in the City of Los Angeles
and its culturally diverse communities which have been underserved.
The most established coalition, the Down with Falls Coalition of Orange County,
began in 2005 with a “Down with Falls Forum” where 58 agencies, organizations, and
professionals committed to developing the Coalition to educate the County about the
dangers of falls (Down with Falls Coalition, Orange County). Orange County’s coalition
wrote a comprehensive strategic plan for 2007 – 2009 which outlined the following
goals:
• increase in size and diversity, becoming a recognized entity and resource in the
provider community;
• become the “household brand” for fall prevention programs, services, and
resources;
• become a comprehensive clearinghouse for fall prevention knowledge and
community resources;
• increase awareness and knowledge about strategies to lower the risk of falls and
• advocate for changes to the built environment to lower the risk of falls in Orange
County.
The City of Los Angeles Coalition was developed by staff at the Fall Prevention
Center of Excellence, whose program office is at the University of Southern California.
The City of Los Angeles Coalition includes overlapping county-wide members such as
the County of Los Angeles Area Agency on Aging and the Fire Department. Established
in 2009, it is presently conducting a needs assessment to determine which potential
activities warrant the greatest need among the City’s older adults. Efforts are underway
to improve data collection efforts by emergency responders so that researchers and policy
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makers can understand more about the environmental contexts in which falls among older
adults who live in their own homes. Other local governments can join those efforts.
Fall Prevention Programs
Generally, fall prevention programs can be distinguished either as physical
activity programs which focus on improving strength, balance and stamina, or
multifactorial programs which may include the features named above in addition to
physical activity. Physical activity programs are either part of greater health promotion
campaigns and may help reduce fall risk, or they may be targeted specifically for fall
prevention. Policy makers interested in reducing falls and fall related injuries among the
Los Angeles Region’s older adults should promote healthy aging via physical activity
programs.
The federal government’s Administration on Aging (AoA) has a Health,
Prevention and Wellness Program concerned with reducing falls among older adults as
well as confronting other health problems. Similarly, the National Council on Aging,
(NCOA), a private non-profit organization concerned with the well-being of the nation’s
older adults, promotes model health programs for communities through its Center for
Healthy Aging. AoA and NCOA endorse “A Matter of Balance”, a health promotion
program aimed at reducing older adults fear of falling through increased physical activity
levels (AoA, 2009; NCOA, 2006). In addition, AoA and NCOA promote Enhance
Fitness, a physical activity program aimed at preventing functional decline in older adults
(AoA, 2009; NCOA, 2006).
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Physical activity programs that have been tested and have been shown to reduce
fall risk and/or prevent falls include: Enhance Fitness, FallProof!, Falls Management
Exercise (FaME), A Matter of Balance, OsteoFit, Otago, Strategies and Action for
Independent Living (SAIL), Stepping On, Tai Chi: Moving for Better Balance (Rose, et
al. 2008). Each evidence-based program highlights its goals and specifies the intended
benefaciaries of its regimen. For example, some programs are intended to reduce falls
among those at high risk of falls, and others are intended to reduce risk of falls among
older adults who are in good physical and cognitive health.
FallProof!, an evidence based fall prevention program, was developed in Orange
County. It is a physical activity program instituted at 29 senior centers in the County.
Down with Falls Coalition members include certified instructors of FallProof! and other
physical activity programs. Increased strength and balance are very important in
reducing falls. However, the advantage of a coalition working towards preventing falls in
the Region, is that other components of the problem can be addressed as well.
While exercise and physical activity programs are the most effective single part of
a fall risk reduction and fall prevention program, research has shown that multifactorial
approaches to fall prevention can reduce falls, fall risk, and subsequently, injuries and
their resultant costs. A comprehensive fall prevention assessment should include as
medication management, vision assessment, home environment survey, outdoor
neighborhood examination, and/or a footwear inventory. Of the above-mentioned fall
prevention programs, FallProof! and A Matter of Balance are physical activity programs
which encourage participants to assess the safety of their homes (Rose et al., 2008).
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However, SAIL, operated in Canada, and Stepping On, created in Australia, are
multifactorial fall prevention programs which include a trained professional’s assessment
of the participant’s home environment and subsequent home modifications (Clemson et
al., 2003; Clemson et al., 1999; Injury Research and Prevention Unit, Interior Health;
2006).
Because of the many factors that can contribute to an older person falling, a broad
approach that addresses public health, urban planning, medical care, housing, and social
services is ideally addressed through a community based coalition. In the past, programs
have been often offered in isolation from other agencies. New approaches to falls
prevention and management are warranted and require policy-maker support (Davis et al.,
2010; Ganz et al., 2008; Skelton & Todd, 2005). Physicians, senior centers, parks and
recreation programs, and home health could complement each other’s resources a through
a community based chronic care approach to fall prevention (Ganz et al., 2008).
Special Concerns for the Los Angeles Region
An important concern for policy makers interested in setting up fall prevention
programs in the Los Angeles Region is whether the above mentioned programs, or any
other programs in which they are interested in implementing, have been shown to
decrease falls and fall risk of older adults most represented in their local populations. For
example, in the Los Angeles Region, thousands of older adults are non-White. Most
evidence based fall prevention programs have not been tested on such populations.
Although many of the Region’s communities are multi-racial and programs in their local
community centers or senior centers cater to a diverse older adult demographic, there are
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pockets of Asian, Latino, and African-American older adult communities throughout the
Region where fall prevention programs should target their specific population, including
language and cultural preferences. Furthermore, the Region’s Latino and Asian older
adult populations will be growing, and the population of White older adults will decline
in coming decades.
Another concern characterized by the Los Angeles Region is sprawl (Wolch et al.,
2004). Older adults’ ability to live safely in its five counties is a product of issues of
sprawl. Alternative transportation for residents who can no longer drive and well-timed
crosswalks are rare in suburban areas with a majority residential land use (Frumkin, et al.,
2004). Across the sprawl of the Region’s city centers, suburban areas, and exurbs,
residential development has rarely provided housing that is universally designed and suits
people in different stages of mobility and ability across their life spans. Inadequate
housing can put older people at risk of falls, especially when they have intrinsic risk
factors, such as physical and visual disabilities.
The Region’s sprawling suburbs and exurbs, whose populations consist primarily
of Baby Boomers (Census, 2000; Frey, 2003), will see falls increase dramatically in the
coming decades. Los Angeles County alone has incorporated 88 cities within its county
boundaries. In Los Angeles County, the cities of Agoura Hills, Redondo Beach,
Calabasas, Sierra Madre, Walnut, Malibu, El Segundo, West Hollywood, Manhattan
Beach, Hidden Hills, Santa Monica, and Diamond Bar all have populations consisting of
35 percent or more Baby Boomers (Census, 2000). The Region’s four other counties,
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with their younger municipalities, are home to many other cities with high Baby Boomer
populations.
Location of Falls
The majority of the Region’s falls in 2000 and 2006 were listed as falls from one
level to another and falls that were trips and slips. Many were also falls on stairs and
from the bed or toilet. The OSHPD hospital patient discharge data does not allow for
conclusions about specific interior home characteristics that may contribute to falls
among older adults in the Region. However, home modifications can help reduce fall
risk among older adults whose physical limitations make them higher risks for falls
(Kochera, 2002). The Los Angeles Region’s housing agencies can help to reduce costly
falls among older adults by participating in fall prevention efforts. Broad policy changes
that could motivate private citizens would be proposed tax credits for adults who make
home modifications to support safe aging in place (Ganz, Alkema, & Wu, 2008).
Outside the home, OSHPD discharge data E-Codes counted 141 and 144 injurious
falls on the Region’s sidewalks and curbs in 2000 and 2006 respectively. The outdoor
built environment can be implicated in falls that can occur in exurban communities where
there are few sidewalks, residents are car dependent, and are forced to walk in streets.
On the other hand, center city dilapidation in communities where sidewalks are broken,
present risks to older residents or force them to walk on the streets as well. In the middle,
many suburban communities developed in the post war era have sidewalks whose
pavements are pushed up by mature trees.
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Targeting the Problem of Falls
The first work of a coalition is to conduct a needs assessment of falls within its
jurisdiction in order to prioritize goals and target populations of fall prevention initiatives.
Previous chapters of this study provide a comprehensive fall prevention needs assessment
for each of the Region’s counties. Chapter 3 provided a demographic analysis of the
older adult population in Los Angeles, Orange, Riverside, San Bernardino, and Ventura
Counties. Municipalities can conduct more specific analysis of the older populations in
their geographies. The Census variables of age, race, income, disability status, and living
arrangements are imperative to assessing fall risk, comparable to their use in assessing
the housing needs of local communities for Housing Elements, Consolidated Plans, and
Redevelopment Plans. Moreover, Census data on the age and features of local housing
stock in addition to variables on length of residence, housing type and tenure provide
useful information on the condition of older residents’ built environment and potential
lack of adequate structural features that support safe aging in place.
Chapter 4 utilized OSHPD hospital discharge data to provide detailed profiles of
each county’s hospitalized fallers. This study included patients whose place of residence
was in the same county as the hospital where they were treated. Within each of the
Region’s counties, however, there are cities and communities whose demographic
profiles do not reflect the entire county population. Municipalities can request more
detailed localized data from the OSHPD. The administrative discharge data includes the
faller’s home zip code, and therefore, cities can assess their fall rates of residents within
their boundaries.
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The costs of hospitalization and source of pay data analyzed in Chapters 5 and 6
provide counties with a picture of the fiscal impact falls in local communities are having
on federal and state health care programs. The costs of falls incurred by local
governments are not included in this study; however, each entity can conduct its own
analysis of emergency response resources spent on falls, claims issued to risk
management departments, and any other known impacts on local budgets. It is hoped
that collaboration between governmental agencies and private citizens can help reduce
the financial resources spent on the local level as well as the financial burden on the
nation and state’s collective future.
Discharge disposition data examined in Chapter 7 is of major concern to local
governments. Deaths resulting from falls are a major problem for their obvious personal
impact as well as their costs, and local governments need to educate their population
about the grave outcomes that can result from falls. In addition to costly hospitalizations
for fatal falls, patients discharged to Skilled Nursing Facilities (SNF) are very costly to
the public health care providers both before and after acute hospitalization. If local
governments could play a role in preventing falls that end in death and SNF placement,
billions of dollars in Medicare funds would be saved each year.
However, following hospitalization, patients discharged Home into the
community are a primary concern of local governments. Newly discharged residents
will likely require in home assistance from family members or professional health care
providers and home health aides. They may require home modifications or supportive
features in their homes that can mitigate repeat falls. Discharge Home following a
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hospital visit may require a change in living arrangements, such as relocation to a first
floor, residence in a second unit in order to be near family members, and accessibility to
kitchen and bathroom. To avoid repeat injuries, fallers discharged home would benefit
from localized, comprehensive multifactorial fall prevention programs which include
environmental modifications described above, in addition to strength and balance training,
medical and vision assessments, education and behavior change, medication monitoring,
and footwear reviews.
Fall Prevention Awareness
State and federal policy makers are beginning to understand the impact of falls
among the older population and to seek prevention strategies. Growing attention from
the CDC, AoA, and NCOA’s Falls Free Initiative are helping to build a national fall
prevention agenda and to encourage states’ participation through coalitions.
For example, in 2008, Congress passed the federal Safety of Seniors Act, which amends
the Public Health Service Act and calls for public education programs, research, and
demonstration projects in fall prevention. However, no appropriations were included.
In California, Fall Prevention Awareness Week (FPAW) legislation was passed in
2008. FPAW legislation urges state and local agencies to incorporate fall prevention
language into their housing, transportation, and parks and recreation planning documents
and master plans. Many local entities are already engaging in fall prevention methods
but have not identified them as such. For example, many parks and recreation
departments and senior centers offer physical activity programs aimed at fall prevention.
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In order to raise awareness of the issue, however, local governments need to identify
these practices as part of an overall health campaign to reduce falls. In addition, housing
departments already have home repair and home modification programs in place.
Listing these programs as part of an overall strategy for reducing fall risk would raise
awareness in the community.
In 2008 and 2009, several California counties and cities issued FPAW
declarations and conducted community based FPAW activities. A common activity is
publicizing the problem of falls at a health fair. Other activities include conducing
walkability audits in local neighborhoods to call attention to the problem of falls and
assess public sidewalks and streets for fall hazards. In the Los Angeles Region, the
Ventura County, Orange County, and the City of Los Angeles coalitions plan FPAW
activities each year.
Securing broader community and local government support and capitalizing on
windows of opportunity, such as FPAW, are imperative to raising awareness of the
growing public health problem of falls in local communities. Across the five counties of
the Los Angeles Region, sister governmental and professional agencies can share their
jurisdictions’ approaches for addressing the problem of falls. The successes of
implementing numerous exercise-based fall prevention programs in Orange County can
inspire the other four counties. The emerging experience of addressing the cultural
communities in the City of Los Angeles’ Coalition can educate its neighbors in
responding to their growing ethnic older populations. In all corners of the Region, large
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numbers of Baby Boomers will be aging over the coming decades, and the Latino
population will be increasing dramatically.
It has been suggested that “It takes a village to prevent falls” (Ganz, Alkema, Wu,
2008, p. 266). Therefore, innovative and alternate approaches to falls prevention and
management, are needed. They secure the support of local governments and blur the
lines between urban planning, public health, and aging policy. These coalition based
approaches, which coordinate resources, link community partners, and provide
complementary services, can reach beyond the isolated settings in which fall prevention
research protocols have operated in the past and impact local jurisdictions’ older
populations through their implementation and incorporation into local policy practices.
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Abstract (if available)
Abstract
This study is a comparative analysis of community dwelling older adults who were hospitalized after falling in five Los Angeles Region counties: Los Angeles, Orange, Riverside, San Bernardino, and Ventura. It provides a current demographic assessment, future public health projections, and a planning response for local governments. Nearly 30,000 of the Los Angeles Region’s 1.8 million older adults were hospitalized for falls in 2006. Aging Baby Boomers will cause the Region’s older population to swell to over 5 million by the year 2050. The Region’s hospitalizations for fall-induced injuries cost Medicare and Medi-Cal over $1.3 billion in 2006. However, according to projections, the costs will increase dramatically by 2020, when over 40,000 older adults will be hospitalized for falls each year. By the year 2035, hospitalizations for falls will reach 60,000 per year, increasing through 2050. The older population of the Region is more diverse than the national population of older adults. Analysis of fallers’ billed charges, sources of pay, and discharge disposition in the Los Angeles Region found that White fallers are most costly to the federal Medicare system and non-White fallers have lower rates of Medicare utilization. Higher billed charges and high Medi-Cal utilization for falls among Latino, Asian, African-American, and Other race fallers are costly to the State of California. The majority of fallers are discharged to a Skilled Nursing Facility (SNF), and those with SNF discharge were older, had longer lengths of stay, and higher billed charges. They were more often White. Patients discharged to their homes were younger, had shorter hospital stays, and had lower billed charges. Asian and Latino fallers had high home discharge rates.
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Cicero, Caroline
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Core Title
Fall related injuries among older adults in the Los Angeles region
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Leonard Davis School of Gerontology
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Doctor of Philosophy
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Gerontology
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09/07/2010
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baby boomers,fall injuries,fall prevention,Local government,Los Angeles region,OAI-PMH Harvest,older adults,Public Health,Urban Planning
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California
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Los Angeles
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Orange
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Riverside
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San Bernardino
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Ventura
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English
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Pynoos, Jon (
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), Enguidanos, Susan M. (
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baby boomers
fall injuries
fall prevention
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older adults