SETTING ON SPOUSAL HEALTH OUTCOMES Jing Dong, IMPAQ International - - PowerPoint PPT Presentation

EFFECTS OF LONG-TERM CARE SETTING ON SPOUSAL HEALTH OUTCOMES

Jing Dong, IMPAQ International Harold Pollack, University of Chicago

• R. Tamara Konetzka, University of Chicago

BACKGROUND

EXPANSION IN NONINSTITUTIONAL LTC

• LTC and LTC setting
• A large expansion in noninstitutional care. Public financing of LTC has

been shifting away from nursing home to home and community-based services (HCBS).

• Elderly people generally prefer HCBS to institutional care
• Less expensive for users with less intensive care needs
• It is hoped that the shift to HCBS will help individuals to get high-quality

services at lower costs

BACKGROUND

KNOWLEDGE GAP AND RESEARCH QUESTIONS

• Family members usually participate in LTC decisions and are inevitably

affected by the decision to use different care

• Prior studies have mainly focused on the preferences and well-being of

LTC users in different care settings

• Little is known about whether and how HCBS (versus nursing home) use

may affect health outcomes for family members of care recipients

• Spouses play an important role in providing informal care and making

LTC decisions– important to understand the impact of different care settings on their health

BACKGROUND

KNOWLEDGE GAP AND RESEARCH QUESTIONS

• Hypotheses:
• HCBS may inevitably place greater informal caregiving burden on the spouses,

and informal care leads to worse physical and mental health outcomes for caregivers

• An altruistic spouse may gain internal satisfaction and have better mental

health outcomes from providing more care, from supporting the care recipients to stay in their preferred LTC setting, and from living with the care recipients

• We would expect HCBS to have negative impact on physical health but

unclear impact on mental health for spouses of care recipients

BACKGROUND

SIGNIFICANCE AND CONTRIBUTION

• To inform policy makers about the potential costs and benefits of HCBS

expansion for spouses of HCBS recipients and help them to design programs to better support spouses:

• Describe the characteristics of HCBS and nursing home users and their

spouses

• Examine the causal impact of HCBS (versus nursing home) on physical and

mental health outcomes for spouses of care recipients

METHODS

DATA

• Health and Retirement Study (HRS) (1996-2012)
• Longitudinal study that surveys a nationally representative sample of adults 50+

and their spouses every 2 years since 1992

• Information on SES, health, insurance, and medical expenditures
• Cross-Wave Geographic Information file (restricted)
• State, county and zip code information
• Area Health Resource File and Census Data
• County-level nursing home bed supply (IV)

METHODS

SAMPLE

HRS (207,816 observations/ 37,319 individuals/ 23,373 households) 175,522 observations/ 35,044 individuals/ 22,163 households Keep only 1996-2012 Keep if care recipients use only HCBS or only nursing home in the 2nd wave. Drop if spouses lived in a different county in the 1st wave Keep if spouses are in 2 consecutive waves and have a partner 88,672 observations/ 22,065 individuals/ 11,345 households 8,789 observations/ 6,031 individuals/ 4,757 households

METHODS

VARIABLES

• Spousal health outcomes
• Physical health: (1) good self-rated health; (2) need help with Activities of Daily

Living (ADL); (3) need help with Instrumental Activities of Daily Living (IADL); (4) onset of five common chronic conditions

• Mental health: (1) onset of diagnosed psychiatric problems; (2) CESD >=3
• Treatment
• HCBS (versus nursing home) use by care recipient
• Covariates
• Spouse SES, household wealth, family, spouse health insurance, spouse

health at previous wave, care recipient health, and year and state FEs

METHODS

CONCERNS WITH NAÏVE IDENTIFICATION STRATEGY

• Selection bias
• In many cases, the care setting is chosen by care recipients and/or their

spouses and may, therefore, be correlated with factors that also affect spousal health.

• Failure to control for all confounders may result in selection bias
• Reverse causality
• Spousal health may reversely affect LTC decisions

METHODS

SOLUTION: INSTRUMENTAL VARIABLE (IV)

IV Assumptions Strengths Potential threats to IV exogeneity and solutions County-level number of nursing home beds per 1,000 people 65+ (1) IV should predict HCBS use (2) IV should not directly affect spousal health or

• ther unobserved

confounders County-level, less likely to be correlated with individual-level unobserved confounders (1) People move for desired LTC settings– drop spouses who moved 2 years before LTC use (2) Nursing home demand induced supply– average 0.8% annual change in IV (3) IV is correlated with county-level variables– balance check:

• bservables are

balanced

METHODS

TWO-STAGE RESIDUAL INCLUSION MODEL (2SRI)

• First stage model

𝑚𝑝𝑕𝑗𝑢 𝑄 𝐼𝐷𝐶𝑇𝑠,𝑢 = 1 = 𝛽0 + 𝛽1𝐽𝑊

𝑠,𝑢 + 𝛽2𝐼𝑡,𝑢−1 + 𝛽3𝑌𝑡,𝑢 + 𝛽4𝑌𝑠,𝑢 + 𝑍𝑓𝑏𝑠𝑢 + 𝑇𝑢𝑏𝑢𝑓𝑡,𝑢

• Second stage model

𝑚𝑝𝑕𝑗𝑢 𝑄 𝐼𝑡,𝑢 = 1 = 𝛾0 + 𝛾1𝐼𝐷𝐶𝑇𝑠,𝑢 + 𝛾2𝐼𝑡,𝑢−1 + 𝛾3𝑌𝑡,𝑢 + 𝛾4𝑌𝑠,𝑢 + 𝑍𝑓𝑏𝑠𝑢 + 𝑇𝑢𝑏𝑢𝑓𝑡,𝑢 + 𝑠

𝑡,𝑢

• HCBS= whether care recipient used HCBS
• IV= county-level number of skilled nursing home beds per 1000 people 65+
• Hs,t-1= a set of previous health variables for spouse
• X= a set of control variables
• Yeart and State= year and state fixed effects
• 𝑠

𝑗𝑢= response residuals from the first stage model

• Standard errors are clustered at individual level
• Bootstrap procedure for both stages with 500 iterations

RESULTS

SAMPLE CHARACTERISTICS

Independent variables Nursing Home (N=781) HCBS (N=3,553) P value Spouse SES Age (Mean) 75.7(10.3) 68.1(10.0) <0.001 Female (%) 54.2 49.4 0.029 Race (%) 0.049 White 81.8 85.6 Black 13.2 10.7 Other races 5.0 3.7 Hispanic (%) 9.9 7.6 0.045 Education (%) <0.001 Less than HS 34.6 18.4 GED 3.9 4.3 High school 30.9 30.1 Some college 17.1 22.2 College and above 13.6 25.1 Retired (%) 66.2 52.6 <0.001 Household wealth Log total financial assets ($) 7.3(5.0) 8.3(4.9) <0.001 Log total income ($) 10.4(1.1) 10.9(1.0) <0.001 Family Number of children (%) <0.001 6.3 3.4 1 11.2 8.2 2 23.3 26.5 3+ 59.2 62.0

RESULTS

SAMPLE CHARACTERISTICS

Independent variables Nursing Home (N=781) HCBS (N=3,553) P value Spouse health insurance Uninsured (%) 2.9 4.3 0.125 Has LTCI (%) 13.8 14.4 0.694 Spouse health at t-1 Lagged # diagnosed disorder (Mean) 2.2(1.5) 1.9(1.4) <0.001 Lagged # mobility tasks cannot do (Mean) 1.5(1.6) 1.0(1.4) <0.001 Lagged any psychiatric problems (%) 21.7 15.6 <0.001 Lagged any pain problems (%) 38.4 32.7 0.006 LTC user health # diagnosed disorder (Mean) 3.1(1.5) 2.6(1.5) <0.001 # mobility tasks cannot do (Mean) 3.0(1.9) 1.7(1.7) <0.001 Any psychiatric problems (%) 31.1 22.6 <0.001 Any pain problems (%) 40.3 49.2 <0.001

The comparisons between the two treatment arms are calculated based on simple two-sample t-tests or chi-squared test. Standard deviations in parentheses.

RESULTS

MARGINAL EFFECTS OF HCBS ON SPOUSE PHYSICAL HEALTH (BASE MODELS)

(1) (2) (3) (4) Model Good Health Any ADLs Any IADLs 5 Common Conditions IV models Marginal effect

• 0.073**

0.014 0.015 0.008 Bootstrap S.E. (0.031) (0.027) (0.025) (0.031) First-stage F statistics 11.6 11.6 11.6 11.6 Mean of dependent var 0.724 0.171 0.164 0.157 Observations 8,775 8,777 8,777 8,758

p<0.1; ** p<0.05; *** p<0.01. Standard errors in parentheses

RESULTS

MARGINAL EFFECTS OF HCBS ON SPOUSE PHYSICAL HEALTH (T+1 MODELS)

(1) (2) (3) (4) Model Good Health Any ADLs Any IADLs 5 Common Conditions IV models Marginal effect

• 0.082*

0.040 0.058* 0.081** Bootstrap S.E. (0.043) (0.032) (0.031) (0.040) First-stage F statistics 8.8 8.5 8.5 13.1 Mean of dependent var 0.716 0.176 0.167 0.124 Observations 6,422 6,425 6,424 6,456

p<0.1; ** p<0.05; *** p<0.01. Standard errors in parentheses

RESULTS

MARGINAL EFFECTS OF HCBS ON SPOUSE MENTAL HEALTH (BASE MODELS)

(5) (6) Model Psychiatric Problems CESD>=3 IV models Marginal effect

• 0.019
• 0.154***

Bootstrap S.E. (0.023) (0.038) First-stage F statistics 11.8 8.9 Mean of dependent var 0.024 0.210 Observations 8,651 7,954

p<0.1; ** p<0.05; *** p<0.01. Standard errors in parentheses

RESULTS

MARGINAL EFFECTS OF HCBS ON SPOUSE PHYSICAL HEALTH (T+1 MODELS)

(5) (6) Model Psychiatric Problems CESD>=3 IV models Marginal effect 0.013

• 0.027

Bootstrap S.E. (0.014) (0.043) First-stage F statistics 8.7 7.3 Mean of dependent var 0.024 0.217 Observations 6,311 5,851

p<0.1; ** p<0.05; *** p<0.01. Standard errors in parentheses

CONCLUSIONS

CONCLUSIONS

• HCBS use leads to consistently harmful effects on spousal physical health,

especially in the long-term, which may potentially be caused by increased informal care responsibilities.

• HCBS use also leads to improved spousal mental health outcomes,

especially improved depression symptoms, which may potentially be caused by increased satisfaction

• Policies aimed at expanding HCBS to reduce nursing home use should

consider these effects on spousal health, and include complementary policies that assist and support families, as the shift to HCBS inevitably shifts greater responsibility to them.

THANK YOU!

Jing Dong, IMPAQ International jdong@impaqint.com