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Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North Carolina Edward C. Norton, Univ of Michigan June 23, 2008 ASHE

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Page 1: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Prescription Drugs, Medical Care, and Health Outcomes:

A Model of Elderly Health Dynamics

Zhou Yang, Emory University

Donna B. Gilleskie, Univ of North Carolina

Edward C. Norton, Univ of Michigan

June 23, 2008ASHE

Page 2: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

The Big Picture

Prescription Drugs

Physician Services, Hospitalization

Health: Morbidity, Mortality

Supplemental Insurance,

Rx Coverage

Page 3: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Age

HealthSudden death: “extreme” health shock but no functional decline

Terminal Illness: good functional health then health shock and certain decline in function

Frailty: no health shock(s) or serious chronic condition, but slow decline in function

Entry-re-entry: chronic condition(s) associated with multiple health shocks and expected decline in function

Typical Patterns of Health Decline among the Elderly

JAMA 289(18), 2003

Page 4: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

A Preview of our Main Findings

A change from Medicare with no drug coverageto a plan that covers prescription drugs reveals that:

• Drug expenditures over 5 years increase between 7 and 27%.

• Survival rates increase 1-2%. But the distribution of functional status among survivors shifts toward worse health.

• Marginal survivors spend significantly more than individuals who would have survived anyway.

• There is some contemporaneous reallocation of consumption (a cross-price effect), but changes in consumption are largely driven by changes in health and survival as people age.

Page 5: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Model of behavior of individuals age 65+

It , Jt St At, Bt, Dt Et+1, Ft+1

beginning of age t

beginning of age t+1

insurance and drug coverage

health shock

medical care demand

health production

Ωt= (Et, Ft,

At-1, Bt-1, Dt-1, Xt,

ZIt, ZH

t, ZMt )

Ωt+1= (Et+1, Ft+1,

At, Bt, Dt, Xt+1,

ZIt+1, ZH

t+1, ZMt+1 )

And we model the set of structural equations jointly, allowing unobserved components to be correlated

Page 6: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Empirical Model

It , Jt St At, Bt, Dt Et+1, Ft+1

beginning of t

beginning of t+1

insurance and drug coverage

health shock

medical care demand

health production

Multinomial logit:

Medicare only (parts A and B) ( 8%) Medicaid dual coverage (12%) Private plan supplement (64%) Medicare managed care plan (part C) (16%)

Logit: Rx coverage (63%)

(conditional on private or Part C plan)

Page 7: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Empirical Model

It , Jt Skt At, Bt, Dt Et+1, Ft+1

beginning of t

beginning of t+1

insurance and drug coverage

health shock(s)

medical care demand

health production

Separate logits:

Heart/stroke event (ICD-9 390-439) in period t (24.5 %)

Respiratory event (ICD-9 480-496) in period t ( 4.8 %)

Cancer event (ICD-9 140-209) in period t ( 5.7 %)

Page 8: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Empirical Model

It , Jt Skt At, Bt, Dt Et+1, Ft+1

beginning of t

beginning of t+1

insurance and drug coverage

health shock(s)

medical care demand

health production

Separate logit for any use and OLS log expenditures conditional on any:

Hospital use and expenditures in period t (20 % and $13,057)

Physician service use and expenditures in period t (84 % and $2,013)

Prescription drug use and expenditures in period t (90 % and $980)

Page 9: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Empirical Model

It , Jt Skt At, Bt, Dt Ek

t+1, Ft+1

beginning of t

beginning of t+1

insurance and drug coverage

health shock(s)

medical care demand

health:ever had chronic

condition k , functional status

Multinomial logit for functional status entering period t+1:

Not disabled (no ADL or IADLs) (58%) Moderately disabled (IADL or <3 ADLs) (28%) Severely disabled (3 or more ADLs) (10%) Dead ( 5%)

Indicator for having ever had a chronic condition entering period t+1:

Heart/stroke (47%) Respiratory (15%) Cancer (19%) Diabetes (20%)

Ekt+1 = Ek

t + Skt

Page 10: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Unobserved Heterogeneity Specification

• Permanent: risk aversion or attitude toward medical care use

• Time-varying: unmodeled health shocks or natural rate of deterioration

uet = ρe μ + ωe νt + εe

t

where uet is the unobserved component for equation e decomposed into

• permanent heterogeneity factor μ with factor loading ρe

• time-varying heterogeneity factor νt with factor loading ωe

• iid component εet

distributed N(0,σ2e) for continuous equations and

Extreme Value for dichotomous/polychotomous outcomes

Page 11: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Medicare Current Beneficiary Survey (MCBS) Sample

• Survey and Event files from 1992-2001

• Overlapping samples followed from 2 to 5 years

• Exclude individuals ever in a nursing home

• Attrition due to death and sample design

• Sample: 25,935 men and women; 76,321 person-year obs

Page 12: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Actual and Simulated Annual Mortality Rate, by Age

Page 13: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Actual and Simulated Prescription Drug Expenditures, by Age and Death

Page 14: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Actual and Simulated Physician Services Expenditures, by Age and Death

Page 15: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Actual and Simulated Hospital Expenditures, by Age and Death

Page 16: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Simulations• Start everyone off with a particular type of health insurance

– Medicare only– Dual coverage by Medicaid– Private supplement without Rx coverage– Private supplement with Rx coverage– Medicare managed care (part C) without Rx coverage– Medicare managed care (part C) with Rx coverage

• Simulate behavior for 5 years

• Examine expenditures and health outcomes over 5 years

• Examine expenditures of 5-year survivors

Page 17: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Five-year Simulations – with unobserved heterogeneity

Page 18: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Five-year Simulations – without unobserved heterogeneity

Page 19: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Five-year Simulations – with unobserved heterogeneity

22.5

10.6

4.8

10.7

Page 20: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Sole Survivors vs. Marginal Survivors

Rx expenditures triple or quadruple

} With increases here, too

Increases in expenditures are 3.5 to 5.5 times larger

Page 21: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Take home message• Methodologically, we have built and estimated a comprehensive

dynamic model of health behavior of the elderly as they age.

• Substantively, our model allows us to examine the effects of health insurance extensions not simply on prescription drug use but also on other types of care, as well as the impacts of this altered demand on health outcomes and subsequent behavior over time.

• Recently, the paper was accepted by JHR and is available from the authors if you are interested in our other results or the model details. (www.unc.edu/~dgill)

Page 22: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Five-year Simulations – with unobserved heterogeneity

Page 23: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Five-year Simulations – without unobserved heterogeneity

Page 24: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Unobserved Heterogeneity Distribution

Page 25: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Actual and Simulated Prescription Drug Use and Expenditures, by Age

Page 26: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Actual and Simulated Hospital Use and Expenditures, by Age

Page 27: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Actual and Simulated Physician Services Use and Expenditures, by Age

Page 28: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Features of our Empirical Model Suggested by Theory

• Supplemental insurance coverage is chosen at the beginning of the period before observing health shocks, but with knowledge of one’s functional status, chronic conditions, and, most importantly, unobserved individual characteristics entering the period.

Page 29: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Features of our Empirical Model Suggested by Theory

• Permanent and time-varying unobserved individual characteristics affect annual demand for all three types of medical care.

Adverse selection

Page 30: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Features of our Empirical Model Suggested by Theory

• Health transitions are a function of medical care input allocations and health shocks during the year. (Grossman)

Adverse selectionJointly estimated demand

Page 31: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Features of our Empirical Model Suggested by Theory

• Previous medical care use may alter the utility of medical care consumption today; hence, lagged use affects current expenditures directly as well as indirectly through health transitions.

Adverse selectionJointly estimated demandDynamic health production

Page 32: Prescription Drugs, Medical Care, and Health Outcomes: A Model of Elderly Health Dynamics Zhou Yang, Emory University Donna B. Gilleskie, Univ of North

Features of our Empirical Model Suggested by Theory

Adverse selectionJointly estimated demandDynamic health productionDynamic demand for medical care