Demand for Medical ServicesDemand for Medical ServicesPart 2Part 2

Health EconomicsProfessor Vivian Ho

Fall 2007

These notes draw from material in Santerre & Neun, Health Economics, Theories, Insights and Industry Studies. Thomson 2004

OutlineOutline

Empirical estimates of demand from the literature

Practice problems The RAND Health Insurance

Experiment Example: Interpreting results from a

regression on abortion demand

Estimating Demand for Medical CareEstimating Demand for Medical Care

Quantity demanded = f( … )out-of-pocket pricereal incometime costsprices of substitutes and complementstastes and preferencesprofilestate of healthquality of care

Empirical Evidence Empirical Evidence

Demand for primary care services (prevention, early detection, & treatment of disease) has been found to be price inelasticEstimates tend to be in the -.1 to -.7 rangeA 10% in the out-of-pocket price of

hospital or physician services leads to a 1 to 7% decrease in quantity demanded

Ceteris paribus, total expenditures on hospital and physician services increase with a greater out-of-pocket price

Empirical Evidence (cont.)Empirical Evidence (cont.)

Demand for other types of medical care is slightly more price elastic than demand for primary care

Consumers should be more price sensitive as the portion of the bill paid out of pocket increases

Out-of-Pocket Payments in the U.S.

Hypothesis: Consumers are more price sensitive if they pay a larger % of the health care bill

The fall in the % of out-of-pocket payments may explain the rapid rise in health care costs

1960 1980 2000 2004National health expenditures ($b) $23.4 $214.6 $1,130.4 $1,560.2% out of pocket 55.2% 27.1% 17.2% 15.1%

Total Expenditures and % Paid Out-of-Pocket, 2004

Out-of-Pocket Payments in the U.S.

$bHospital care $570.8 3.3%Physician Services 399.9 10.0%Prescription Drugs 188.5 24.9%Nursing Home Care 115.2 27.7%Other 285.9 34.4%

Hypothesis: Consumers are more price sensitive if they pay a larger % of the health care bill

Higher hospital and physician expenditures may be due to the low % paid out-of-pocket

Out-of-Pocket Payments in the U.S. Out-of-Pocket Payments in the U.S. (cont.)(cont.)

The previous 2 slides argue that: insurance coverage expenditures

But it may be the opposite: expenditures insurance coverage.

We cannot identify a causal effect using just this data

Empirical Evidence (cont.)Empirical Evidence (cont.)

Studies which have examined price and quantity variation within service types have found that:The price elasticity of demand for dental

services for females is -.5 to -.7 The own-price elasticity of demand for

nursing home services is between -.73 and -2.4

Empirical Evidence (cont.)Empirical Evidence (cont.) At the individual level, the income

elasticity of demand for medical services is below +1.0

The travel time elasticity of demand is almost as large as the own-price elasticity of demand

Little consensus on whether hospital care and ambulatory physician services are substitutes or complements

International Estimates of Income International Estimates of Income ElasticityElasticity

Are health care expenditures destined to consume a larger portion of GDP as GDP grows?

Regression Analysis Sample - developed countries

Ln(Real per capita Ln(Real per = + + health expenditures) capita income)

Estimates of range between 1.13 and 1.31

Applying Demand Theory to Real Applying Demand Theory to Real DataData

• Demand analyses in health care must take Demand analyses in health care must take insurance into accountinsurance into account

• Demand analyses are critical in shaping Demand analyses are critical in shaping managerial and public policy decisionsmanagerial and public policy decisions

The Rand Health Insurance The Rand Health Insurance ExperimentExperiment

A large, social science experiment to study individuals’ medical care under insurance

A large sample of families were provided differing levels of health insurance coverageResearchers then studied their subsequent

health care use

The Sample The Sample

• 5,809 individuals, under 65

• 6 sites (Dayton OH, Seattle WA, Fitchburg MA, Charlston SC, Georgetown County SC, Franklin County MA)

• 1974 – 1977

• Cost : $80 million

Insurance Plans in the Insurance Plans in the Experiment Experiment

1. Free fee-for-service (FFS).1. Free fee-for-service (FFS). - i.e., no coinsurance- i.e., no coinsurance

2. 25% copayment per physician visit2. 25% copayment per physician visit

3. 50% copayment per physician visit3. 50% copayment per physician visit

4. 95% copayment per physician visit4. 95% copayment per physician visit

1. Free fee-for-service (FFS).1. Free fee-for-service (FFS). - i.e., no coinsurance- i.e., no coinsurance

2. 25% copayment per physician visit2. 25% copayment per physician visit

3. 50% copayment per physician visit3. 50% copayment per physician visit

4. 95% copayment per physician visit4. 95% copayment per physician visit

Insurance Plans in the Insurance Plans in the Experiment Experiment

5. Individual deductible5. Individual deductible - $150 deductible for physician visits; all - $150 deductible for physician visits; all

subsequent visits freesubsequent visits free

6. HMO6. HMO - Not the same as free fee-for-service- Not the same as free fee-for-service - Since HMO receives a fixed annual fee, it seeks - Since HMO receives a fixed annual fee, it seeks

to limit physician visitsto limit physician visits

5. Individual deductible5. Individual deductible - $150 deductible for physician visits; all - $150 deductible for physician visits; all

subsequent visits freesubsequent visits free

6. HMO6. HMO - Not the same as free fee-for-service- Not the same as free fee-for-service - Since HMO receives a fixed annual fee, it seeks - Since HMO receives a fixed annual fee, it seeks

to limit physician visitsto limit physician visits

Plans* Face-to- Outpatient Inpatient Total Probability Face Visits Expenses Dollars Expenses Using Any (1984 $) (1984 $) (1984 $) Medical Service

Free 4.55 340 409 749 86.825% 3.33 260 373 634

78.850% 3.03 224 450 674

77.295% 2.73 203 315 518

67.7Individualdeductible 3.02 235 373 608 72.3

Plans* Face-to- Outpatient Inpatient Total Probability Face Visits Expenses Dollars Expenses Using Any (1984 $) (1984 $) (1984 $) Medical Service

Free 4.55 340 409 749 86.825% 3.33 260 373 634

78.850% 3.03 224 450 674

77.295% 2.73 203 315 518

67.7Individualdeductible 3.02 235 373 608 72.3

Table 3.3. Sample Means for Annual Use of Table 3.3. Sample Means for Annual Use of Medical Services per CapitaMedical Services per Capita

* The chi-square test was used to test the null hypothesis of no difference among the five plan means. In each instance, the chi-square statistic was significant to at least 5 percent level. The only exception was for inpatient dollarsSource : Willard G. Manning et al. “Health Insurance and the Demand for Medical Care : Evidence from a Randomized Experiment,” American Economic Review 77 (June 1987), Table 2

No statistically significant difference in inpatient (hospital) expenses by insurance typeDoes NOT necessarily imply inelastic demand

for hospital servicesExperiment included $1,000 cap on out-of-

pocket medical expenses; 70% of hospital admissions costs $1,000 +

Results (cont.)Results (cont.)

O As coinsurance ‘s, probability of ANY use ‘sAs coinsurance ‘s, probability of ANY use ‘s

Results (cont.) Results (cont.)

• As consumers’ copayments drop, demand for As consumers’ copayments drop, demand for medical care becomes more price inelasticmedical care becomes more price inelastic

The data confirms the theoryThe data confirms the theory

Own Price Elasticity of DemandOwn Price Elasticity of Demand

All Care Outpatient CareAll Care Outpatient Care

Copay 0-25%Copay 0-25% - 0.10 - 0.13 - 0.10 - 0.13Copay 25-95%Copay 25-95% - 0.14 - 0.21 - 0.14 - 0.21

Results (cont.) Results (cont.)

• HMO patients cost 30% less than FFS patients HMO patients cost 30% less than FFS patients on averageon average

• HMO’s do save money relative to FFSHMO’s do save money relative to FFS

Free fee-for-service (FFS) versus HMO coverage No difference in physician visits found But only 7.1% of HMO patients admitted

to hospital, versus 11.2% of FFS patients

Free fee-for-service (FFS) versus HMO coverage No difference in physician visits found But only 7.1% of HMO patients admitted

to hospital, versus 11.2% of FFS patients

Health Implications Health Implications

What are the implications for health outcomes? i.e restraining medical care expenditures is not

the only objective we care about, especially for the poor

What are the implications for health outcomes? i.e restraining medical care expenditures is not

the only objective we care about, especially for the poor

The experiment verifies that coinsurance demand for medical care

The experiment verifies that coinsurance demand for medical care

Health Implications (cont.)Health Implications (cont.)

Poor adults (lowest 20% of income distribution) Poor adults (lowest 20% of income distribution) with high blood pressure experienced clinically with high blood pressure experienced clinically significant improvement under free FFS plan, significant improvement under free FFS plan, but but notnot in cost sharing plan in cost sharing plan

Similar findings for myopia, dental healthSimilar findings for myopia, dental health

Free FFS only improves health outcomes in 3 Free FFS only improves health outcomes in 3 specific cases versus cost-sharingspecific cases versus cost-sharing

If want to restrain costs and maintain health, If want to restrain costs and maintain health, targeted programs at these 3 health problems is targeted programs at these 3 health problems is more cost-effective than free care for all more cost-effective than free care for all servicesservices

Was it worth it?Was it worth it?

Rand Health Insurance Experiment cost $80 Rand Health Insurance Experiment cost $80 millionmillion

Initial results published in 1981Initial results published in 1981

Government sponsored studies often yield important Government sponsored studies often yield important knowledge for businessknowledge for business

In the next 2 years, # of insurance companies with In the next 2 years, # of insurance companies with first-dollar coinsurance for hospital care first-dollar coinsurance for hospital care increased from 30% to 63%increased from 30% to 63%

# of insurance companies w/ annual deductible of # of insurance companies w/ annual deductible of $200 + per person ‘d from 4% to 21%$200 + per person ‘d from 4% to 21%

Estimated cost saving from ‘d demand for Estimated cost saving from ‘d demand for medical care = $7 billionmedical care = $7 billion

Economically Objective Data on Economically Objective Data on AbortionAbortion

Is the choice of abortion responsive to Is the choice of abortion responsive to economic factors?economic factors?

Medoff ( 1988)Medoff ( 1988) Sample : state-level data from 1980Sample : state-level data from 1980

Model the demand for abortion as a function of Model the demand for abortion as a function of price and other relevant factorsprice and other relevant factors

A = - 207.780 - 0.924P + 0.031Y + 4.194SNGL + 4.456LFPA = - 207.780 - 0.924P + 0.031Y + 4.194SNGL + 4.456LFP (1.41) (3.22) (3.31) (1.74) (2.57)(1.41) (3.22) (3.31) (1.74) (2.57) + 18.287W + 1.207CATH + 43.775M+ 18.287W + 1.207CATH + 43.775M (1.74) (1.50) (2.12)(1.74) (1.50) (2.12)RR2 2 = .77= .77N = 50N = 50

Where : A = Number of abortion per 1,000 pregnancies of women of A = Number of abortion per 1,000 pregnancies of women of childbearing age (15-45)childbearing age (15-45)

P = Price of an abortionP = Price of an abortion Y = Average incomeY = Average income SNGL = Percentage of woman who are singleSNGL = Percentage of woman who are single LFP = Labor force participant rateLFP = Labor force participant rate W = Dummy variable to control for women in western statesW = Dummy variable to control for women in western states CATH = Percentage of Catholic population in each stateCATH = Percentage of Catholic population in each state M = Dummy variable to control for states that provide Medicaid M = Dummy variable to control for states that provide Medicaid

funding of abortionsfunding of abortions

An Economic Analysis of the Demand for An Economic Analysis of the Demand for Abortion (Medoff, 1988)Abortion (Medoff, 1988)

Economically Objective Data on Economically Objective Data on AbortionAbortion

Price effect is negative and statistically Price effect is negative and statistically significantsignificant Implied price of elasticity of demand = - 0.81Implied price of elasticity of demand = - 0.81

If abortion price ‘s 50%, demand for abortions If abortion price ‘s 50%, demand for abortions would 40.5%would 40.5%

Income variable positive and statistically Income variable positive and statistically significantsignificant

Implied income elasticity of demand = 0.79Implied income elasticity of demand = 0.79

Economically Objective Data on Economically Objective Data on Abortion (cont.)Abortion (cont.)

SNGL and LFP positive and statistically SNGL and LFP positive and statistically significantsignificant

Single and working women have higher Single and working women have higher opportunity cost of time from raising childrenopportunity cost of time from raising children

Medicaid funding strongly ‘s demand for Medicaid funding strongly ‘s demand for abortionsabortions

ConclusionsConclusions

Our economic model of demand provides hypotheses that we can test with real data

Although it is difficult to measure the quantity of medical services demanded and economic variables, both price and income effects are important determinants of the demand for medical care