Impact of Long-term Care Insurance on
Setting and Use of Formal and Informal
Care
Research Support
• Health Care Financing and Organization, an
Christine Bishop, Ph.D.
Schneider Institute for Health Policy, Heller School for Social
Policy and Management, Brandeis University
initiative of Robert Wood Johnson Foundation
• Data developed in previous projects supported
Boryana Dimitrova, Ph.D.
Deloitte & Touche
by
♦ ASPE/ Office of the Assistant Secretary for
Planning and Evaluation, Department of Health and
Human Services
♦ Robert Wood Johnson Foundation/HCRI
Marc Cohen, Ph.D.
LifePlans, Inc.
AcademyHealth Annual Research Meeting
Boston
June 27, 2005
2
The Fastest Growing Segment of the
LTCI Market is Employer-Sponsored
The LTCI Market Has Experienced
Steady Growth
Average Annual Growth Rates in the LTC Insurance Marketplace
(1991-2001)
10000
9000
22%
7,529
6,831
7000
20
6,080
6000
18%
5,542
4,960
5000
4,351
3,837
4000
3,417
2,930
3000
2,430
2000
1000
25
8,261
8000
Percent
Policies Sold (In Thousands)
9,000
1,550
815
12%
10
6%
1,930
1,130
5
0
1987
15
1992
1997
Source: LifePlans computations; Number of Long-Term Care Insurance Policies Sold, Cumulatively
1987-2002 estimates AAHP-HIAA LTC Market Survey 2003. Includes preliminary numbers for 2002.
0
2002
3
Total
Individual
Source: HIAA LTC Market Survey 2003: Lifeplans Computations
Employer
Life Riders
4
Estimated Market Penetration 2002
Long-Term Care Insurance
10%
9%
8%
7%
6%
5%
4%
3%
2%
1%
0%
9%
6%
ƒ A “contingent claim”
ƒ Provides holder with more resources when the
insured “event” (disability) occurs
4%
ƒ If the event occurs, resources have high value
for consumption
Age 45+
Ages 45 to
64
Age 65+
LifePlans Inc., 2003
5
6
Impact of insurance on choice of
setting
Research Questions
•
Does insurance affect choice of setting of care
♦
♦
•
Higher income is associated in cross-section with
greater use of residential care given disability, perhaps
because of living arrangement and caregiver patterns
by socioeconomic status
•
“Extra” resources contingent on disability could
support earlier entry into residential care
OR
Could support care at home, other things (marital
status, age, disability, living arrangement, caregivers)
constant.
at home
vs.
residential setting
• For community residents, does insurance affect
♦
♦
Use of paid care
Use of unpaid care (informal care)
•
7
8
Choice of Setting by Income for Elders
with Disabilities—NLTCS 1999
Modeling Selection Effect for Holding
LTC Insurance
Income <$20K
>$20K
All
Care at Home
36.6%
17.2%
30.1%
Residential Care
63.4%
82.8%
69.9%
• LTC insurance market is new; age will differ
• Income: Medicaid programs, premium costs Î
higher income for purchasers
• Education
• Marital status at time of purchase: more likely
to be married
100.0%
100.0% 100.0%
9
• Race: marketing to whites?
10
Data Sources
Unmeasured Effects
• All insured persons claiming benefits from 8
private LTC insurance companies in 1999
♦ Disabilities in 2+ ADLs
• Purchasers have a higher self-assessed
OR
probability of needing LTC in next five years
• Purchasers are more risk averse than
♦ Cognitive impairments
• 1999 National Long-term Care Survey
nonpurchasers
comparison group – same functional level
♦ Disabilities in 2+ ADLs
♦ See Finkelstein and McGarry (2004)
OR
♦ Cognitive impairments
11
12
Comparing the two groups
Elders with disabilities: Insured elders
differ from general population
• Insured group with physical disability is
♦ Younger
♦ More likely to be married
♦ Higher education
♦ Higher income
♦ More likely to be white
Age
Married
Male
Education
HS, Not College
College Graduate
Income $20K+
Proportion White
13
Proportion in nursing home
90%
65.2%
***
***
***
***
Sample: restrict to nonpoor (couples or singles)
Insured status
♦ Insurance as the endogenous variable of interest
60%
♦ Education and never married as instruments: affect insured
50%
state
•
40%
Setting of care
♦ Insurance
62.0%
30%
♦ Level of disability
34.8%
♦ Income
10%
Nursing Home
Receiving Care at Home
0%
Not Insured with Disability
Insured with Disability
15
16
Bivariate Probit Results (2)
Bivariate Probit Results
Estimates for Setting of Care: Community = 1
Variable
Coefficient
se
t
Pr > |t|
Intercept
3.023
0.621
4.87 <.0001
Insured
1.427
0.220
6.49 <.0001
Married
0.212
0.129
1.64 0.1008
Never married
-0.394
0.270
-1.46 0.1443
Male
-0.205
0.116
-1.77 0.0761
Log of Income (000)
-0.113
0.074
-1.53 0.1249
White
-1.819
0.190
-9.56 <.0001
Age:Years 65-59
0.115
0.114
1.01 0.3112
Age: Years 70-79
-0.036
0.022
-1.65 0.0996
Age: Years 80+
-0.032
0.013
-2.42 0.0156
Disabled in 1 ADL
-1.331
0.344
-3.87 0.0001
- 2 ADLs
-1.203
0.313
-3.84 0.0001
- 3 ADLs
-1.426
0.308
-4.64 <.0001
- 4 ADLs
-1.685
0.304
-5.54 <.0001
- 5 ADLs
-1.793
0.295
-6.07 <.0001
- 6 ADLs
-2.187
0.302
-7.24 <.0001
Cognitive impairment
-0.647
0.118
-5.49 <.0001
Estimates for Insured Status Insured = 1
Variable
Coefficient
se
t
Pr > |t|
Intercept
-2.287
0.542
-4.22 <.0001
Never married
-0.659
0.253
-2.60 0.0092
HS graduate
0.558
0.132
4.23 <.0001
Technical school
1.682
0.235
7.17 <.0001
Some college
1.213
0.158
7.68 <.0001
College graduate
1.470
0.168
8.77 <.0001
Graduate school
2.167
0.261
8.30 <.0001
White
1.443
0.215
6.70 <.0001
Age:Years 65-59
0.227
0.116
1.96 0.0497
Age: Years 70-79
-0.052
0.022
-2.35 0.0185
Age: Years 80+
-0.096
0.012
-8.14 <.0001
17
0.531
0.349
0.715
0.974
Bivariate Probit for Insured State and
Setting of Care
•
•
38.0%
80%
20%
0.350
0.074
0.327
0.898
14
100%
70%
Not Insured w Insured
85.723
79.843 ***
0.142
0.487 ***
0.216
0.346 ***
18
Marginal Effects on Probability of Community
Residence
Variable
Insured
Married
Never married
Male
Log of Income (000)
White
Age:Years 65-59
Age: Years 70-79
Age: Years 80+
Disabled in 1 ADL
- 2 ADLs
- 3 ADLs
- 4 ADLs
- 5 ADLs
- 6 ADLs
Cognitive impairment
Mean Marginal
Effect for Sample
0.390
0.058
-0.108
-0.056
-0.031
-0.497
0.032
-0.010
-0.009
-0.364
-0.329
-0.390
-0.460
-0.490
-0.598
-0.177
19
Insurance is Associated with Higher
Probability of Care at Home
• Care at home is not associated with higher
•
•
20
For Community Residents: Effect of
Insurance on Paid Care and/or
Unpaid Care?
• Conditional on community residence: selection
effect
♦ Because insurance affects who remains at home, we
are observing a different group than would occur
otherwise
• Should be modeled as simultaneous with choice
of setting (choose based on care available)
• Paid and unpaid care: substitutes or
complements?
• Zeros
21
Bivariate Probit for Joint Distribution of ANY
Paid and ANY Unpaid Help
Any Paid Care = 1 Any Unpaid Care = 1
Variable
Coefficient
Sig t Coefficient
Sig t
Intercept
-1.398
0.298
-0.748 ns
Insurance
2.659 <.0001
0.090 ns
Log of income (000)
0.166 ns
-0.092 ns
Male
0.284
0.260
0.168 ns
Years 65 to 69
0.079 ns
0.087 ns
Years 70 to 79
-0.066
0.131
-0.004 ns
Years Over 80
0.010 ns
0.055
0.019
3 ADLs
0.415
0.202
0.508
0.035
4 ADLs
0.159 ns
0.726
0.002
5 ADLs
0.917
0.002
0.595
0.004
6 ADLs
1.098
0.001
0.430
0.107
Cognitive Impairment
-0.425
0.059
0.547
0.002
Child within 25 miles
0.088 ns
0.497
0.001
Married
-0.554
0.044
0.893 <.0001
Rho
0.108 ns
22
If assume unpaid hours given -Variable
Intercept
Insured
Log of Income (000)
Male
Age:Years 65-59
Age: Years 70-79
Age: Years 80+
- 3 ADLs
- 4 ADLs
- 5 ADLs
- 6 ADLs
Cognitive impairment
Child within 25 mi
Married
Informal Care Hours
23
income -- does not appear to be a “superior
good”
But perhaps additional resources contingent on
disability are used differently from ordinary
income?
Or people preferring care at home are more
likely to purchase insurance?
Hours of Paid Care
Coefficient
Sig t
-37.087
0.0328
56.282 <.0001
3.405
0.1739
2.115 ns
2.355 ns
-0.946
0.1129
-0.300 ns
12.113
0.0191
19.405 <.0001
25.537 <.0001
46.469 <.0001
-3.863
0.2509
-5.146
0.1052
-18.489 <.0001
-0.211 <.0001
Tobit Analysis Paid and Informal Hours
Variable
Intercept
Insured
Log of Income (000)
Male
Age:Years 65-59
Age: Years 70-79
Age: Years 80+
- 3 ADLs
- 4 ADLs
- 5 ADLs
- 6 ADLs
Cognitive impairment
Child within 25 mi
Married
24
Hours of Paid Care
Hours of Informal Care
Coefficient
Sig t
Coefficient
Sig t
-40.750
0.025
-27.074
0.185
59.843 <.0001
-11.338
0.022
3.982
0.124
-3.248
0.296
1.096 ns
5.980
0.162
2.045 ns
4.737
0.241
-0.856
0.166
-0.090 ns
-0.492 ns
0.999
0.071
10.046
0.059
21.834
0.000
15.996
0.001
27.174 <.0001
21.361 <.0001
29.646 <.0001
41.828 <.0001
32.861 <.0001
-5.375
0.121
12.469
0.002
-6.485
0.047
10.448
0.006
-23.536 <.0001
30.554 <.0001
Insurance has a strong effect on paid
care for community-resident elders
• Bivariate probit shows large significant effect
•
on any paid (of course)
Estimate given paid hours are nonzero implies
56 hours a week more for insured; paid hours
are reduced by about 12 minutes for every
hour of informal care
Insurance affects informal care
through effect on amount of paid care
•
•
•
No significant effect on the probability of any informal
care
Tobit shows reduction of about 11 hours for insured
(Of course) insured must be buying more care for
themselves than they would with an equal income
increase – (about an hour a week for a $10000 income
increase)
• Tobit shows large effect – 60 hours
25
26
Compute Inverse Mills Analog Based
on Bivariate Probit Results
λcommres
⎡
⎤
Yγ − ρXβ ⎥
⎢
φ ( Xβ ) Φ
1
⎢
⎥
2 2
⎢ (1 − ρ ) ⎦⎥
⎣
=
F ( Xβ , Yγ , ρ )
Paid Hours (2SLS)
Variable
Intercept
Insurance
Hours of Unpaid Help
ln Income (est)
Number ADL Disabilities
Cognitive Impairment
R-squared =.2439
N=414
27
28
Unpaid Hours (2SLS)
Variable
Intercept
Hours of Paid Help
Child within 25 miles
Married
Number ADL Disabilities
Cognitive Impairment
R-squared =.25684
N=414
29
Parameter Standard
Estimate
Error
1.326
-0.451
3.089
15.510
8.285
7.627
4.272
0.114
2.926
3.171
1.027
3.156
t Value
Pr > |t|
0.31
0.7564
-3.96 <.0001
1.06
0.2917
4.89 <.0001
8.07 <.0001
2.42
0.0161
Parameter Standard
Estimate
Error
-5.263
20.717
-0.702
1.401
8.779
4.695
7.465
3.866
0.138
2.279
1.312
3.227
t Value
Pr > |t|
-0.71
0.4812
5.36 <.0001
-5.09 <.0001
0.61
0.539
6.69 <.0001
1.45
0.1465