Transcript 3 Basic Steps in Economic Evaluation

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
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 Care

Quantity demanded = f( … )
 out-of-pocket
 real
price
income
 time costs
 prices of substitutes and complements
 tastes and preferences
 profile
 state of health
 quality of care
Empirical Evidence

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.)

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.
1960 1980
2000
2004
National health expenditures ($b) $23.4 $214.6 $1,130.4 $1,560.2
% out of pocket
55.2% 27.1% 17.2%
15.1%
 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
Out-of-Pocket Payments in the U.S.
Total Expenditures and % Paid Out-of-Pocket, 2004
Hospital care
Physician Services
Prescription Drugs
Nursing Home Care
Other
$b
$570.8
399.9
188.5
115.2
285.9
3.3%
10.0%
24.9%
27.7%
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. (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.)

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.)

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
Elasticity

Are health care expenditures destined to
consume a larger portion of GDP as GDP
grows?

Regression Analysis
 Sample - developed countries
Ln(Real per capita
health expenditures)
 Estimates
= a+b
Ln(Real per
capita income)
of b range between 1.13 and 1.31
+e
Applying Demand Theory to Real
Data
• Demand analyses in health care must take
insurance into account
•
Demand analyses are critical in shaping
managerial and public policy decisions
The Rand Health Insurance
Experiment

A large, social science experiment to study
individuals’ medical care under insurance

A large sample of families were provided
differing levels of health insurance coverage
 Researchers
then studied their subsequent
health care use
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
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
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
Table 3.3. Sample Means for Annual Use of
Medical Services per Capita
Plans*
Face-to- Outpatient Inpatient Total
Face Visits Expenses Dollars Expenses
(1984 $)
Free
25%
50%
95%
Individual
deductible
(1984 $)
(1984 $)
Probability
Using Any
Medical Service
4.55
3.33
3.03
2.73
340
260
224
203
409
373
450
315
749
634
674
518
86.8
78.8
77.2
67.7
3.02
235
373
608
72.3
* 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
Results (cont.)

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-ofpocket medical expenses; 70% of hospital
admissions costs $1,000 +
O As coinsurance ‘s, probability of ANY use ‘s
Results (cont.)
Own Price Elasticity of Demand
All Care
Copay 0-25%
Copay 25-95%
•
- 0.10
- 0.14
Outpatient Care
- 0.13
- 0.21
As consumers’ copayments drop, demand for
medical care becomes more price inelastic
 The data confirms the theory
Results (cont.)
 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
• HMO patients cost 30% less than FFS patients
on average
• HMO’s do save money relative to FFS
Health Implications
 The experiment verifies that coinsurance
demand for medical care
 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
Health Implications (cont.)
 Poor adults (lowest 20% of income distribution)
with high blood pressure experienced clinically
significant improvement under free FFS plan,
but not in cost sharing plan
 Similar findings for myopia, dental health
 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
Was it worth it?
 Rand Health Insurance Experiment cost $80
million
 Initial results published in 1981
 In the next 2 years, # of insurance companies with
first-dollar coinsurance for hospital care
increased from 30% to 63%
 # of insurance companies w/ annual deductible of
$200 + per person ‘d from 4% to 21%
 Estimated cost saving from ‘d demand for
medical care = $7 billion
 Government sponsored studies often yield important
knowledge for business
Economically Objective Data on
Abortion
 Is the choice of abortion responsive to
economic factors?
 Medoff ( 1988)
 Sample : state-level data from 1980
 Model the demand for abortion as a function of
price and other relevant factors
An Economic Analysis of the Demand for
Abortion (Medoff, 1988)
A = - 207.780 - 0.924P + 0.031Y + 4.194SNGL + 4.456LFP
(1.41)
(3.22)
(3.31)
(1.74)
(2.57)
+ 18.287W + 1.207CATH + 43.775M
(1.74)
R2 = .77
N = 50
(1.50)
(2.12)
Where : A = Number of abortion per 1,000 pregnancies of women of
childbearing age (15-45)
P = Price of an abortion
Y = Average income
SNGL = Percentage of woman who are single
LFP = Labor force participant rate
W = Dummy variable to control for women in western states
CATH = Percentage of Catholic population in each state
M = Dummy variable to control for states that provide Medicaid
funding of abortions
Economically Objective Data on
Abortion
 Price effect is negative and statistically
significant
 Implied price of elasticity of demand
 If abortion price
would
= - 0.81
‘s 50%, demand for abortions
40.5%
 Income variable positive and statistically
significant

Implied income elasticity of demand = 0.79
Economically Objective Data on
Abortion (cont.)
 SNGL and LFP positive and statistically
significant
 Single and working women have higher
opportunity cost of time from raising children
 Medicaid funding strongly ‘s demand for
abortions
Conclusions
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
