Impact of Long-term Care Insurance on Setting and Use of Formal and Informal

Care

Christine Bishop, Ph.D.

Schneider Institute for Health Policy, Heller School for Social Policy and Management, Brandeis University

Boryana Dimitrova, Ph.D.

Deloitte & Touche

Marc Cohen, Ph.D.

LifePlans, Inc.

AcademyHealth Annual Research Meeting

Boston

June 27, 2005

2

Research Support

• Health Care Financing and Organization, an initiative of Robert Wood Johnson Foundation

• Data developed in previous projects supported by ASPE/ Office of the Assistant Secretary for Planning

and Evaluation, Department of Health and Human Services

Robert Wood Johnson Foundation/HCRI

3

The LTCI Market Has Experienced Steady Growth

8151,130

1,5501,930

2,4302,930

3,4173,837

4,351

4,9605,542

6,080

6,831

7,529

8,261

9,000

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

1987 1992 1997 2002

Pol

icie

s So

ld (

In T

hous

ands

)

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.

4

The Fastest Growing Segment of the LTCI Market is Employer-Sponsored

6%

22%

12%

18%

0

5

10

15

20

25

Total Individual Employer Life Riders

Per

cent

Average Annual Growth Rates in the LTC Insurance Marketplace (1991-2001)

Source: HIAA LTC Market Survey 2003: Lifeplans Computations

5

Estimated Market Penetration 2002

6%

4%

9%

0%1%2%3%4%5%6%7%8%9%

10%

Age 45+ Ages 45 to64

Age 65+

LifePlans Inc., 2003

6

Long-Term Care Insurance

A “contingent claim”

Provides holder with more resources when the insured “event” (disability) occurs

If the event occurs, resources have high value for consumption

7

Research Questions

• Does insurance affect choice of setting of care at home

vs. residential setting

• For community residents, does insurance affect Use of paid care Use of unpaid care (informal care)

8

Impact of insurance on choice of setting

• 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.

9

Choice of Setting by Income for Elders with Disabilities—NLTCS 1999

Income <$20K >$20K All

Care at Home 36.6% 17.2% 30.1%

Residential Care 63.4% 82.8% 69.9%

100.0% 100.0% 100.0%

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Modeling Selection Effect for Holding LTC Insurance

• LTC insurance market is new; age will differ

• Income: Medicaid programs, premium costs higher income for purchasers

• Education

• Marital status at time of purchase: more likely to be married

• Race: marketing to whites?

11

Unmeasured Effects

• Purchasers have a higher self-assessed

probability of needing LTC in next five years

• Purchasers are more risk averse than

nonpurchasers

See Finkelstein and McGarry (2004)

12

Data Sources

• All insured persons claiming benefits from 8 private LTC insurance companies in 1999 Disabilities in 2+ ADLs

OR Cognitive impairments

• 1999 National Long-term Care Survey comparison group – same functional level Disabilities in 2+ ADLs

OR Cognitive impairments

13

Comparing the two groups

• Insured group with physical disability is Younger More likely to be married Higher education Higher income More likely to be white

14

Not Insured with DisabilityInsured Age 85.723 79.843 ***Married 0.142 0.487 ***Male 0.216 0.346 ***Education HS, Not College 0.350 0.531 *** College Graduate 0.074 0.349 ***Income $20K+ 0.327 0.715 ***Proportion White 0.898 0.974 ***

Elders with disabilities: Insured elders differ from general population

15

34.8%

62.0%

65.2%

38.0%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Not Insured with Disability Insured with Disability

Nursing Home

Receiving Care at Home

Proportion in nursing home

16

Bivariate Probit for Insured State and Setting of Care

• Sample: restrict to nonpoor (couples or singles)

• Insured status Insurance as the endogenous variable of interest Education and never married as instruments: affect insured

state

• Setting of care Insurance Level of disability Income

17

Bivariate Probit Results

Variable Coefficient se t Pr > |t|Intercept -2.287 0.542 -4.22 <.0001Never married -0.659 0.253 -2.60 0.0092HS graduate 0.558 0.132 4.23 <.0001Technical school 1.682 0.235 7.17 <.0001Some college 1.213 0.158 7.68 <.0001College graduate 1.470 0.168 8.77 <.0001Graduate school 2.167 0.261 8.30 <.0001White 1.443 0.215 6.70 <.0001Age:Years 65-59 0.227 0.116 1.96 0.0497Age: Years 70-79 -0.052 0.022 -2.35 0.0185Age: Years 80+ -0.096 0.012 -8.14 <.0001

Estimates for Insured Status Insured = 1

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Bivariate Probit Results (2)

Variable Coefficient se t Pr > |t|Intercept 3.023 0.621 4.87 <.0001Insured 1.427 0.220 6.49 <.0001Married 0.212 0.129 1.64 0.1008Never married -0.394 0.270 -1.46 0.1443Male -0.205 0.116 -1.77 0.0761Log of Income (000) -0.113 0.074 -1.53 0.1249White -1.819 0.190 -9.56 <.0001Age:Years 65-59 0.115 0.114 1.01 0.3112Age: Years 70-79 -0.036 0.022 -1.65 0.0996Age: Years 80+ -0.032 0.013 -2.42 0.0156Disabled 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 <.0001Cognitive impairment -0.647 0.118 -5.49 <.0001

Estimates for Setting of Care: Community = 1

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Marginal Effects on Probability of Community Residence

VariableMean Marginal

Effect for Sample

Insured 0.390Married 0.058Never married -0.108Male -0.056Log of Income (000) -0.031White -0.497Age:Years 65-59 0.032Age: Years 70-79 -0.010Age: Years 80+ -0.009Disabled in 1 ADL -0.364 - 2 ADLs -0.329 - 3 ADLs -0.390 - 4 ADLs -0.460 - 5 ADLs -0.490 - 6 ADLs -0.598Cognitive impairment -0.177

20

Insurance is Associated with Higher Probability of Care at Home

• Care at home is not associated with higher 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?

21

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

22

Bivariate Probit for Joint Distribution of ANY Paid and ANY Unpaid Help

Variable Coefficient Sig t Coefficient Sig tIntercept -1.398 0.298 -0.748 nsInsurance 2.659 <.0001 0.090 nsLog of income (000) 0.166 ns -0.092 nsMale 0.284 0.260 0.168 nsYears 65 to 69 0.079 ns 0.087 nsYears 70 to 79 -0.066 0.131 -0.004 nsYears Over 80 0.010 ns 0.055 0.0193 ADLs 0.415 0.202 0.508 0.0354 ADLs 0.159 ns 0.726 0.0025 ADLs 0.917 0.002 0.595 0.0046 ADLs 1.098 0.001 0.430 0.107Cognitive Impairment -0.425 0.059 0.547 0.002Child within 25 miles 0.088 ns 0.497 0.001Married -0.554 0.044 0.893 <.0001Rho 0.108 ns

Any Paid Care = 1 Any Unpaid Care = 1

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If assume unpaid hours given --

Variable Coefficient Sig tIntercept -37.087 0.0328Insured 56.282 <.0001Log of Income (000) 3.405 0.1739Male 2.115 nsAge:Years 65-59 2.355 nsAge: Years 70-79 -0.946 0.1129Age: Years 80+ -0.300 ns - 3 ADLs 12.113 0.0191 - 4 ADLs 19.405 <.0001 - 5 ADLs 25.537 <.0001 - 6 ADLs 46.469 <.0001Cognitive impairment -3.863 0.2509Child within 25 mi -5.146 0.1052Married -18.489 <.0001Informal Care Hours -0.211 <.0001

Hours of Paid Care

24

Tobit Analysis Paid and Informal Hours

Variable Coefficient Sig t Coefficient Sig tIntercept -40.750 0.025 -27.074 0.185Insured 59.843 <.0001 -11.338 0.022Log of Income (000) 3.982 0.124 -3.248 0.296Male 1.096 ns 5.980 0.162Age:Years 65-59 2.045 ns 4.737 0.241Age: Years 70-79 -0.856 0.166 -0.090 nsAge: Years 80+ -0.492 ns 0.999 0.071 - 3 ADLs 10.046 0.059 21.834 0.000 - 4 ADLs 15.996 0.001 27.174 <.0001 - 5 ADLs 21.361 <.0001 29.646 <.0001 - 6 ADLs 41.828 <.0001 32.861 <.0001Cognitive impairment -5.375 0.121 12.469 0.002Child within 25 mi -6.485 0.047 10.448 0.006Married -23.536 <.0001 30.554 <.0001

Hours of Paid Care Hours of Informal Care

25

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

• Tobit shows large effect – 60 hours

26

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)

27

Compute Inverse Mills Analog Based on Bivariate Probit Results

),,(

)1(

)(2

12

YXF

XYX

commres

28

Paid Hours (2SLS)

Variable Parameter Estimate

Standard Error t Value Pr > |t|

Intercept -5.263 7.465 -0.71 0.4812Insurance 20.717 3.866 5.36 <.0001Hours of Unpaid Help -0.702 0.138 -5.09 <.0001ln Income (est) 1.401 2.279 0.61 0.539Number ADL Disabilities 8.779 1.312 6.69 <.0001Cognitive Impairment 4.695 3.227 1.45 0.1465

R-squared =.2439N=414

29

Unpaid Hours (2SLS)

Variable Parameter Estimate

Standard Error t Value Pr > |t|

Intercept 1.326 4.272 0.31 0.7564Hours of Paid Help -0.451 0.114 -3.96 <.0001Child within 25 miles 3.089 2.926 1.06 0.2917Married 15.510 3.171 4.89 <.0001Number ADL Disabilities 8.285 1.027 8.07 <.0001Cognitive Impairment 7.627 3.156 2.42 0.0161

R-squared =.25684N=414