 The population aged ≥ 65 is projected to increase from
38.9 million in 2008 (13% of the U.S. population) to 72 million in 2030 (20%) (USDHHS, 2008) .
 “Oldest-old” aged ≥ 85 are the fastest growing segment of the U.S. older population (Himes, 2002) .
 Increased longevity is accompanied by higher prevalence of chronic diseases and conditions (USDHHS, 2006) .
 The impact of disability on society increases with the growth of the older population.
2

 Ensuring adequate health care access is critical for older people with disabilities.
 More prevalent secondary health conditions among those with disabilities.
 Great risk of developing additional health-related challenges.
 There is a paucity of research investigating disparities in access to health care for older adults with disabilities.
 Older Americans aged ≥ 65 are almost universally covered by
Medicare.
 Medicare covers only 45% of health care expenses for institutionalized and non-institutionalized beneficiaries.
 Lack of focus on finding the determinants of disparities in research on health access disparities for older adults.
3

(Andersen, 1995)
 Predisposing : sex, age, race, marital status, education
 Enabling : annual household income, social and emotional support
 Health need : general health status, physical health, mental health, chronic diseases (diabetes, asthma, heart attack, coronary heart disease, stroke)
4

 To examine whether there is a disparity in delaying seeing a doctor due to cost between older adults with and without disabilities, after controlling for predisposing, enabling, and health need factors.
 To determine to what extent such a disparity could be accounted for by predisposing, enabling, and health need factors.
5

 Data Source: 2006 Behavioral Risk Factor Surveillance
System (BRFSS)
 Collaborative project of the CDC and U.S. states and territories
 Health status, health conditions, preventive health practices, and access to health care
 A probability sample of all households with a telephone
 A cross-sectional telephone survey
 A disproportionate stratified sample design
 Random-digit telephone interview of non-institutionalized civilians aged ≥ 18
6

 Nationally representative sample of community-dwelling adults aged ≥ 65 who health insurance and a usual source of care (n=86,610).
 Over 97 percent of elderly people aged ≥ 65 are covered by
Medicare.
 Independent and protective effects of having health insurance and a usual source of care on accessing health care (Devoe et al. 2003; Phillips et al. 2004).
 Individuals that do not have these social protections will experience even greater difficulties.
7

 Delay in seeing a doctor due to cost
 “Was there a time in the past 12 months when you needed to see a doctor but could not because of cost?”
 Individuals with disabilities
 “Are you limited in any way in any activities because of physical, mental, or emotional problems?” or
 “Do you now have any health problem that requires you to use special equipment, such as a cane, a wheelchair, a special bed, or a special telephone?”
8

Contd.
 Perceived health
 “Would you say that in general your health is—”
 Excellent, Very Good, Good, Fair, Poor
 “Now thinking about your physical health, which includes physical illness and injury, for how many days during the past 30 days was your physical health not good ?”
 “Now thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good
?”
9

 Four consecutive models for multivariate logistic regression analyses
 Model 1: Disability status
 Model 2: Model 1 +
Predisposing
Factors (sex, age, race, marital status, education)
 Model 3: Model 2 +
Enabling
Factors (annual household income, social and emotional support)
 Model 4: Model 3 +
Health Need
Factors (general health status, physical health, mental health, five chronic diseases)
 Analysis Tools
 SAS-callable SUDAAN 10.0
 IVEware
10

 Missing data are prevalent in empirical research.
 Nature of missing data
 Non-response items
 Don’t know/Not Sure, and Refused
 0 to 22.5%
 Outcome and independent variables were used in MI.
 Missing values for each individual in the data set are imputed
“conditional on all values observed for that individual.”
 Five multiply imputed data sets through ten iterations for each data set.
11

Variables
Outcome   Variables
Independent
Variables
Predisposing
Factors
Enabling
Factors
Health   Need
Factors
Subcategories
Delay   in   Seeing   a   Doctor   due   to   Cost
Sex   (male;   female)
Age   (65   to   74;   75   to   99)
Race   (white;   AA;   HS;   other   race   or   multiracial)
Marital   Status   (married;   widowed;   never   married)
Education   ( ≥ college;   some   college;   HS;   <HS)
Income   ( ≥ $50,000;   $35,000   to   <   $50,000;   $25,000   to   <   $35,000;   $15,000   to   <   $25,000;   <   $15,000)
Social   and   Emotional   Support   (usually   or   always;   sometimes;   rarely   or   never)
General   Health   Status   (good   or   better;   fair   or   poor)
Health   (<14   days;   14   days   to   30   days)
Mental   Health   (<14   days;   14   days   to   30   days)
Five   Chronic   Diseases
12

Population
Characteristics
Predisposing Female
Married
Variables With   Disabilities
(n=33,385;    39%)
62%
Without   Disabilities
(n=53,225;    62%)
58%
52%
19%
20%
63%
14%
12% Enabling
Less   than   High   School
Less   than   $15,000
Social   &   Emotional   Support
(Usually   or   Always)
Health   Need General   Health   Status
(Fair   or   Poor)
Unhealthy   Days   for   Physical
Health    (14   days   to   30   days)
Unhealthy   Days   for   Mental
Health    (14   days   to   30   days)
Diabetes
Stroke
77%
49%
38%
73%
24%
14%
81%
16%
73%
86%
15%
5%
Differences   between   two   samples   were   statistically   significant   for   all variables   ( p <.001)

 Adjusted Odds Ratios (AORs) for Delay in Seeing a
Doctor Due To Cost
Model   1:   Disability   status
Model
Model   2:   Model   1   +   Predisposing   Factors
Model   3:   Model   2   +   Enabling Factors
Model   4:   Model   3   +   Health   Need   Factors
AORs   (95%   CI)
2.34
(2.02,   2.70)
2.23
(1.92,   2.58)
2.05
(1.75,   2.39)
1.54
(1.30,   1.81)
 Older adults with disabilities were more likely to delay seeing a doctor due to cost than those with disabilities, after controlling for predisposing, enabling, and health need factors.
14

Independent   Variables
Female    [Male]
Age:   75   to   99    [65   to   74]
Non ‐ Hispanic   African   American    [Non ‐ Hispanic   White]
Divorced/widowed/separated    [Married]
<   High   School    [ ≥ College]
<   $15,000    [ ≥ $50,000]
Social   &   Emotional   Support:   Rarely   or   Never    [Usually   or   Always]
General   Health   Status:   Fair   or   Poor    [Good   or   better]
Unhealthy   Days   for   Physical   Health:   14   to   30   days    [<14   days]
Unhealthy   Days   for   Mental   Health:   14   to   30   days    [<14   days]
Stroke   [No]
* p   <.01;   [      ]:   Referent
Adjusted   ORs    (95%   CI)
1.13
(0.97,   1.31)
0.79
*    (0.68,   0.93)
1.60
*    (1.29,   1.98)
0.90
(0.75,   1.09)
1.45
*    (1.12,   1.88)
2.76
*    (2.05,   3.72)
1.67
*    (1.33,   2.08)
1.33
*    (1.11,   1.60)
1.17
(0.96,   1.44)
1.98
*    (1.51,   2.58)
1.30
*    (1.06,   1.59)
15

 Limitations related to the participation of people with disabilities in national population surveys.
 Disability Questions: Activity limitation, Use of special equipment
 Potential factors that could affect health care access for older people with disabilities could not be examined.
 Access to public transportation
 Time since onset of disability
 Health care coordination
 Types and sources of health insurance
 Limited number of chronic illnesses were assessed.
 Association ≠ Causation.
16

 Older adults with disabilities who had health insurance and a usual source of care were more likely to report a delay in seeing a doctor due to cost compared to older adults without disabilities.
 Health need factors collectively accounted the most for the delay in doctor visits.
17

 Policy makers need to judiciously address the economic burden that older adults with disabilities face in maintaining timely doctor visits, especially within the context of the recent health care reform act.
 Efforts to improve the timeliness of physician visits may need to target those who have significant health needs.
18

 Impact of types and source of insurance on access disparities
 Supplemental health insurance
 The impact of healthcare reform legislation
 No preexisting condition restrictions
 Outpatient prescription drug benefit
 Annual wellness visit and personalized prevention plan
 Access disparities by a specific disability
 Disparities from a lifelong perspective
19

Collaborators:
Romana Hasnain-Wynia, PhD
Denys T. Lau, PhD
Funding:
Advanced Rehabilitation
Research Training grant from the US Department of
Education, NIDRR (grant no.
H133P080006).
The content of this presentation does not necessarily represent the policy of the Department of
Education, and you should not assume endorsement by the
Federal Government.
20