Demand for Medical Services Part 2 Health Economics Professor Vivian Ho Fall 2007 These notes draw from material in Santerre & Neun, Health Economics, Theories, Insights and Industry Studies. Thomson 2004

Outline l Empirical estimates of demand from the literature l Practice problems l The RAND Health Insurance Experiment l Example: Interpreting results from a regression on abortion demand

Estimating Demand for Medical Care l Quantity demanded = f( … )  out-of-pocket price  real income  time costs  prices of substitutes and complements  tastes and preferences  profile  state of health  quality of care

Empirical Evidence l Demand for primary care services (prevention, early detection, & treatment of disease) has been found to be price inelastic  Estimates tend to be in the -.1 to -.7 range  A 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.) l Demand for other types of medical care is slightly more price elastic than demand for primary care l 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. lHypothesis: Consumers are more price sensitive if they pay a larger % of the health care bill èThe fall in the % of out-of-pocket payments may explain the rapid rise in health care costs

Total Expenditures and % Paid Out-of-Pocket, 2004 Out-of-Pocket Payments in the U.S. lHypothesis: Consumers are more price sensitive if they pay a larger % of the health care bill èHigher hospital and physician expenditures may be due to the low % paid out-of-pocket

Out-of-Pocket Payments in the U.S. (cont.) l The previous 2 slides argue that:  insurance coverage   expenditures l But it may be the opposite:  expenditures   insurance coverage. l We cannot identify a causal effect using just this data

Empirical Evidence (cont.) l 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.) l At the individual level, the income elasticity of demand for medical services is below +1.0 l The travel time elasticity of demand is almost as large as the own-price elasticity of demand l Little consensus on whether hospital care and ambulatory physician services are substitutes or complements

International Estimates of Income Elasticity l Are health care expenditures destined to consume a larger portion of GDP as GDP grows? l 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 Data Applying Demand Theory to Real Data Demand analyses in health care must take insurance into account Demand analyses in health care must take insurance into account Demand analyses are critical in shaping managerial and public policy decisions Demand analyses are critical in shaping managerial and public policy decisions

The Rand Health Insurance Experiment The Rand Health Insurance Experiment l A large, social science experiment to study individuals’ medical care under insurance l A large sample of families were provided differing levels of health insurance coverage  Researchers 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 Experiment Insurance Plans in the Experiment 1. Free fee-for-service (FFS). - i.e., no coinsurance 2. 25% copayment per physician visit 3. 50% copayment per physician visit 4. 95% copayment per physician visit 1. Free fee-for-service (FFS). - i.e., no coinsurance 2. 25% copayment per physician visit 3. 50% copayment per physician visit 4. 95% copayment per physician visit

Insurance Plans in the Experiment Insurance Plans in the Experiment 5. Individual deductible - $150 deductible for physician visits; all subsequent visits free 6. HMO - Not the same as free fee-for-service - Since HMO receives a fixed annual fee, it seeks to limit physician visits - Since HMO receives a fixed annual fee, it seeks to limit physician visits 5. Individual deductible - $150 deductible for physician visits; all subsequent visits free 6. HMO - Not the same as free fee-for-service - Since HMO receives a fixed annual fee, it seeks to limit physician visits - Since HMO receives a fixed annual fee, it seeks to limit physician visits

Plans* Face-to- Outpatient Inpatient Total Probability Face Visits Expenses Dollars Expenses Using Any (1984 $) (1984 $) (1984 $) Medical Service Free % % % Individual deductible Plans* Face-to- Outpatient Inpatient Total Probability Face Visits Expenses Dollars Expenses Using Any (1984 $) (1984 $) (1984 $) Medical Service Free % % % Individual deductible Table 3.3. Sample Means for Annual Use of Medical Services per Capita Table 3.3. Sample Means for Annual Use of Medical 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 dollars Source : 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

l No statistically significant difference in inpatient (hospital) expenses by insurance type  Does NOT necessarily imply inelastic demand for hospital services  Experiment included $1,000 cap on out-of- pocket medical expenses; 70% of hospital admissions costs $1,000 + Results (cont.) Results (cont.) As coinsurance ‘s, probability of ANY use ‘s O As coinsurance ‘s, probability of ANY use ‘s

Results (cont.) Results (cont.) As consumers’ copayments drop, demand for medical care becomes more price inelastic As consumers’ copayments drop, demand for medical care becomes more price inelastic wThe data confirms the theory Own Price Elasticity of Demand All Care Outpatient Care All Care Outpatient Care Copay 0-25% Copay 25-95%

Results (cont.) Results (cont.) HMO patients cost 30% less than FFS patients on average HMO patients cost 30% less than FFS patients on average HMO’s do save money relative to FFS HMO’s do save money relative to FFS lFree fee-for-service (FFS) versus HMO coverage wNo difference in physician visits found wBut only 7.1% of HMO patients admitted to hospital, versus 11.2% of FFS patients lFree fee-for-service (FFS) versus HMO coverage wNo difference in physician visits found wBut only 7.1% of HMO patients admitted to hospital, versus 11.2% of FFS patients

Health Implications Health Implications lWhat are the implications for health outcomes? w i.e restraining medical care expenditures is not the only objective we care about, especially for the poor lWhat are the implications for health outcomes? w i.e restraining medical care expenditures is not the only objective we care about, especially for the poor l The experiment verifies that coinsurance demand for medical care l The experiment verifies that coinsurance demand for medical care

Health Implications (cont.) Health Implications (cont.) lPoor adults (lowest 20% of income distribution) with high blood pressure experienced clinically significant improvement under free FFS plan, but not in cost sharing plan w Similar findings for myopia, dental health w Free FFS only improves health outcomes in 3 specific cases versus cost-sharing If want to restrain costs and maintain health, targeted programs at these 3 health problems is more cost-effective than free care for all services  If want to restrain costs and maintain health, targeted programs at these 3 health problems is more cost-effective than free care for all services

Was it worth it? Was it worth it? lRand Health Insurance Experiment cost $80 million lInitial results published in 1981  Government sponsored studies often yield important knowledge for business w In the next 2 years, # of insurance companies with first-dollar coinsurance for hospital care increased from 30% to 63% w # of insurance companies w/ annual deductible of $200 + per person ‘d from 4% to 21% w Estimated cost saving from ‘d demand for medical care = $7 billion

Economically Objective Data on Abortion Economically Objective Data on Abortion lIs the choice of abortion responsive to economic factors? lMedoff ( 1988) w Sample : state-level data from 1980  Model the demand for abortion as a function of price and other relevant factors

A = P Y SNGL LFP (1.41) (3.22) (3.31) (1.74) (2.57) (1.41) (3.22) (3.31) (1.74) (2.57) W CATH M W CATH M (1.74) (1.50) (2.12) (1.74) (1.50) (2.12) R 2 =.77 N = 50 A = Number of abortion per 1,000 pregnancies of women of childbearing age (15-45) Where : A = Number of abortion per 1,000 pregnancies of women of childbearing age (15-45) P = Price of an abortion P = Price of an abortion Y = Average income Y = Average income SNGL = Percentage of woman who are single SNGL = Percentage of woman who are single LFP = Labor force participant rate LFP = Labor force participant rate W = Dummy variable to control for women in western states W = Dummy variable to control for women in western states CATH = Percentage of Catholic population in each state CATH = Percentage of Catholic population in each state M = Dummy variable to control for states that provide Medicaid funding of abortions M = Dummy variable to control for states that provide Medicaid funding of abortions An Economic Analysis of the Demand for Abortion (Medoff, 1988) An Economic Analysis of the Demand for Abortion (Medoff, 1988)

Economically Objective Data on Abortion Economically Objective Data on Abortion lPrice effect is negative and statistically significant w Implied price of elasticity of demand = w If abortion price ‘s 50%, demand for abortions would 40.5% lIncome variable positive and statistically significant w Implied income elasticity of demand = 0.79

Economically Objective Data on Abortion (cont.) Economically Objective Data on Abortion (cont.) lSNGL and LFP positive and statistically significant w Single and working women have higher opportunity cost of time from raising children lMedicaid funding strongly ‘s demand for abortions

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