for Health Care

A Review of the Literature 

and Its Application to the Military 

Health System

Jeanne S. Ringel

Susan D. Hosek

Ben A. Vollaard

Sergej Mahnovski

R

Approved for public release; distribution unlimited

Prepared for the Office of the Secretary of Defense

National Defense Research Institute RHealth 

Health 
iii

PREFACE

This report reviews the health economic research conducted at

RAND and elsewhere in an effort to summarize what this research

has to say about the elasticity of demand for health care and to consider how this set of results applies to the problem of estimating the

demand for health care that is provided by the Department of

Defense to military members, their families, and retirees.

The work reported here was sponsored by PA&E and was carried out

jointly by RAND Health’s Center for Military Health Policy Research

and the Forces and Resources Policy Center of the National Defense

Research Institute. The latter is a federally funded research and development center sponsored by the Office of the Secretary of

Defense, the Joint Staff, the unified commands, and the defense

agencies.
v

CONTENTS

Preface ......................................... iii

Tables.......................................... vii

Summary ....................................... ix

Acknowledgments................................. xvii

Chapter One

INTRODUCTION .............................. 1

A Brief Description of the Military Health System ....... 2

Key Differences Between the Military and Civilian Health

Systems.................................. 3

Chapter Two

METHODS ................................... 9

Description of Elasticity Measures .................. 9

Own-Price Elasticity of Demand.................. 9

Income Elasticity of Demand .................... 10

Cross-Price Elasticity of Demand ................. 11

Special Issues Regarding the Elasticity of Demand for

Health................................... 11

Measures of Health Care Demand ................ 11

Price of Health Care ........................... 12

Time Prices and Health Care .................... 12

Types of Health Care .......................... 13

Interrelationships Between the Demand for Health

Insurance and Health Care.................... 14

Selection Effects.............................. 15
vi The Elasticity of Demand for Health Care: A Review of the Literature

Moral Hazard................................ 15

Provider Behavior ............................ 16

Chapter Three

REVIEW OF THE EMPIRICAL LITERATURE ........... 17

The Elasticity of Demand for Health Care............. 17

Methodologies Used in the Literature.............. 17

Main Findings ............................... 20

Price Elasticity of Demand for Health Care .......... 20

Income Elasticity of Demand for Health Care ........ 27

Time Price Elasticity of Demand for Health Care ...... 28

Price Elasticity of Demand for Specific Types of

Services.................................. 29

Main Findings ............................... 29

Inpatient Versus Outpatient Demand Elasticities ..... 32

Preventive Care Versus Acute Care Demand

Elasticities................................ 34

Price Elasticity of Demand for Prescription Drugs ..... 35

Price Elasticity of Demand for Mental Health Services.. 37

The Elasticity of Demand for Health Insurance ........ 39

Main Findings ............................... 39

Studies on the Price Elasticity of Demand for Different

Health Plans .............................. 41

The Income Elasticity of Demand for Different Health

Plans.................................... 44

The Price Elasticity of Demand for Supplementary

Insurance ................................ 44

Chapter Four

CONSIDERING THE POTENTIAL EFFECTS OF CURRENT

AND PROPOSED CHANGES IN TRICARE BENEFITS .... 47

Expansion of Pharmacy Benefits ................... 47

TRICARE for Life ............................... 48

Elimination of Copayments in TRICARE Prime......... 49

TRICARE Prime Remote ......................... 50

Bibliography ..................................... 51
vii

TABLES

1.1. TRICARE Benefits for Active Duty Family Members .. 4

1.2. TRICARE Benefits for Retirees, Their Dependents, and

Others Under Age 65 ......................... 4

3.1. Key Studies with Price Elasticities for All Services .... 21

3.2. Key Studies with Price Elasticity Estimates for Specific

Medical Services ............................ 30

3.3. Key Studies on the Elasticity of Demand for Health

Insurance ................................. 40
ix

SUMMARY

Understanding the effects of changes in health insurance policies on

the demand for health care services is an important and timely topic.

As the Military Health System (MHS) has evolved over time, it has

begun to adopt cost-containment strategies that have been tested in

private health plans. These strategies have led to changes in many

aspects of the health care services offered to Department of Defense

(DoD) beneficiaries. Each change potentially can affect the number

of people accessing services, the intensity of use, and the cost to the

DoD. The goal of this report is to summarize the research relevant

for considering the effects of policy changes on the demand for DoD

health care services and associated costs.

DIFFERENCES BETWEEN DEMAND FOR HEALTH CARE IN

GENERAL AND MILITARY HEALTH CARE

Very little of the existing literature speaks directly to demand for

DoD-paid health care, which differs in several important ways from

the demand for health care services in general. To use the estimates

from the literature to predict the effects of changes in DoD health

benefit packages on the use of DoD services, one must understand

the differences, which derive from the unusual organizational structure of the MHS. We have identified four key differences. First, active duty personnel have less discretion in seeking care than their

civilian counterparts and some military duties involve higher risk.

Moreover, to ensure that active duty personnel are healthy and fit for

duty, they are provided more frequent preventive and routine care

than would be typical for civilians the same age (Hosek et al., 1995).
x The Elasticity of Demand for Health Care: A Review of the Literature

Changes in MHS benefits can be expected to have little effect on use

by active duty personnel.

Second, many retirees and some active duty spouses are eligible for

other health insurance (Hosek et al., 1995), usually through their current employers. These beneficiaries may elect not to participate in

this other insurance, especially if they must pay a share of the premium. If they do participate, they may obtain their health care

through their other insurance, the MHS, or both. Changes in the

MHS benefits can be expected to affect both the number of beneficiaries relying on the MHS (rather than on other insurance) and the

intensity of service use among all enrollees.

Third, MHS benefits can differ substantially for military treatment

facility (MTF) versus civilian care. As a result, government and

beneficiary costs depend on both the level of demand and its allocation between the MTFs and civilian providers. Costs in other health

plans may also differ according to the mix of providers used, but few

vary benefits in the same way that TRICARE does. Studies that estimate the effects of differential benefits on provider choice may be

useful in assessing MTF-civilian provider choice in TRICARE.

Fourth, military beneficiaries typically use substantially more health

care services than comparable civilians do (Hosek et al., 1995). This

difference may be due to better benefits in the MHS. If this is so, the

general health demand literature may be safely applied because use

by the military is described by the same demand curve as use by the

general population, but with the two groups positioned at different

points on the curve. Alternatively, differences in use might reflect

different demand responses to the same benefits. In this case, the

demand curves differ and the general literature may not be applicable. There is some reason for believing the first explanation. A large

share of active duty personnel and their families receive care free of

charge at MTFs. Out-of-pocket costs for those using civilian care appear to be no more than costs in other plans (Levy et al., 2000).

Although there are a variety of differences between the demand for

health care in general and the demand for DoD health care specifically, the existing empirical research on the demand for health care,

on the demand for health insurance, and on the choice of providers

offers useful information about how people respond to changes in
Summary xi

the price of health care. The differences outlined above merely

provide a framework for applying the existing estimates to the

unique situations faced by DoD.

THE ELASTICITY OF DEMAND

The elasticity of demand is a measure of the responsiveness of product demand to changes in one of its determinants. The demand determinants for which elasticity measures are typically computed are

the price of the good or service, the income of the consumer, and the

prices of related goods or services. Elasticity measures are particularly useful because they focus on the relative magnitudes of changes

rather than the absolute. As such, elasticity measures are free of

units of measurement. This characteristic makes them particularly

useful for comparing demand responses across products, countries,

and individuals.

RESULTS

Elasticity of Demand for Health Care in General

Despite a wide variety of empirical methods and data sources, the

demand for health care is consistently found to be price inelastic.

Although the range of price elasticity estimates is relatively wide, it

tends to center on –0.17, meaning that a 1 percent increase in the

price of health care will lead to a 0.17 percent reduction in health

care expenditures. The price-induced changes in demand for health

care can in large part be attributed to changes in the probability of

accessing any care rather than to changes in the number of visits

once care has been accessed. In addition, the studies consistently

find lower levels of demand elasticity at lower levels of cost-sharing.

The demand for health is also found to be income inelastic. The estimates of income elasticity of demand are in the range of 0 to 0.2.

The positive sign of the elasticity measure indicates that as income

increases, the demand for health care services also increases. The

magnitude of the elasticity, however, suggests that the demand response is relatively small. Studies based on long time series data

tend to report higher income elasticities. The difference in estimates

across time frames is due to the incorporation of the effects of
xii The Elasticity of Demand for Health Care: A Review of the Literature

changes in medical technology in studies that use long time series of

data.

Elasticity of Demand for Specific Classes of Health Care

Services

Although the price elasticity of demand for medical care in general is

relatively low, certain types of care are found to be somewhat more

price sensitive. Preventive care and pharmacy benefits are among

those medical services with larger price elasticities. The finding that

the demand for preventive care is more price sensitive than the demand for other types of care is not surprising. The number of available substitutes for a product is a major determinant of demand

elasticity. In the case of preventive care, a number of goods and services could possibly serve as substitutes. As a result, when the price

of care increases, consumers are able to substitute away from preventive care toward other goods and services that promote health

such as nutritional supplements and healthy foods. In addition, preventive medical services may be seen more as a luxury than a

necessity and, thus, may be put off when the price of such care increases. Further, the opportunity cost of obtaining preventive care is

much higher than it is when the patient is sick, particularly if the illness keeps the individual out of work. It is also likely, that since the

benefits of preventive care accrue in the long-term, they are heavily

discounted. The difference in elasticities may also reflect the fact

that preventive care and prescription drugs are typically not as well

covered by insurance.

Elasticity of Demand for Health Insurance

Apart from studies on the responsiveness of the demand for health

care to price and income, there is growing attention to the responsiveness of demand for different health plans to changes in the price

of insurance. This literature is of particular importance when considering the demand for health care services provided by a particular

health plan. Any change in the out-of-pocket costs of services or

premium costs will have an effect on the number of plan enrollees

and, thus, on the demand for health care services paid for by that

plan.
Summary xiii

According to Royalty and Solomon (1998), “there is no definitely established range of price elasticities [of health plan choice] in the literature.” Econometric studies of health care plan choice vary dramatically not only in their price elasticity estimates but also in the

data sources, econometric methods, and experimental design. For

example, the articles reviewed in this report use datasets of individual employees and their health plan choices in various professional

and demographic settings, such as a single university, 20 firms within

one city, a single company with four plants across the United States,

and a national cross-section, among others. Based on this literature,

the estimates of the elasticity of the demand for health insurance

with respect to price range between –1.8 and –0.1.

USING ESTIMATES FROM THE LITERATURE TO PREDICT

THE EFFECTS OF CHANGES IN THE MHS SYSTEM

The FY 2001 National Defense Authorization Act was signed into law

by President Clinton on October 30, 2000. Although the act contains

numerous changes, four new TRICARE initiatives will have important

effects on uniformed services retirees and their spouses.

• Expanding pharmacy benefits for seniors to include access to

MTF pharmacies, the National Mail Order Pharmacy Program,

and retail pharmacies,

• Making TRICARE a second payer to Medicare (TRICARE for Life),

• Eliminating coinsurance payments under TRICARE Prime for

dependents of active duty personnel, and

• Expanding TRICARE Prime Remote benefits to active duty family

members and nonuniformed service members.

All of these new initiatives expand services and reduce the costs of

health care for some group of MHS beneficiaries. Consequently, we

would expect to see greater demand for MHS services as these policies are implemented. For example, expanding pharmacy benefits to

seniors will likely increase the demand for pharmaceuticals paid for

by MHS as Medicare-eligible beneficiaries who previously paid outof-pocket for prescriptions will now get them through the TRICARE

program. In addition, the reduction in the price of prescriptions will

induce some beneficiaries to purchase a greater number of prescrip-
xiv The Elasticity of Demand for Health Care: A Review of the Literature

tions. Estimates from the literature indicate that a 10 percent decrease in the price of prescriptions will lead to a 2 to 3 percent increase in the quantity demanded. These estimates, however, likely

understate the change in demand that the DoD will face because

they reflect only the change in the number of prescriptions among

current enrollees and not the change in the number of enrollees.

Similarly, making TRICARE a second payer to Medicare is expected

to increase demand for MHS paid services. Studies have shown that

health care use is higher among the elderly who have Medigap (or

supplemental) insurance (for examples, see Link et al., 1980;

Christensen et al., 1987; McCall et al., 1991, Cartwright et al., 1992).

This new initiative will make TRICARE for Life a close substitute for

other Medigap policies. Although none of the previous studies calculate an elasticity of demand specifically for Medicare recipients, we

believe that the estimates for adults in general serve as a lower

bound. The elderly are expected to have a more elastic demand for

health care services, since they typically have more limited incomes

and spend a greater share of that income on health care needs.

In the case of TRICARE Prime, the elimination of copayments for

civilian care provided to active duty dependents will increase the

demand for MHS-paid medical services in two ways. First, the economic literature predicts that reductions in copayments will increase

the number of current enrollees who access any care, particularly

among those who rely on civilian providers. The literature also indicates, however, that the price elasticity of demand for health care is

relatively low at low levels of cost-sharing (see Newhouse et al. 1993).

The current copayments for active duty dependents are relatively

low, thus the effect of eliminating these copayments may be

relatively small. The second effect is that some beneficiaries may

choose to switch between TRICARE plans. The lower out-of-pocket

costs for civilian care may make the Prime option more attractive to

families that had previously chosen the Extra or Standard TRICARE

options. The literature on the elasticity of health care plan choice

suggests that some switching between plans does occur in response

to changes in plan characteristics. The magnitude of such effects,

however, has not been well established.

The expansion of the TRICARE Prime Remote benefits to dependents

of active duty personnel and uniformed service personnel (i.e., per-
Summary xv

sonnel from the Public Health Service, the Coast Guard, and the

National Oceanic and Atmospheric Administration) will likely increase the demand for health care services paid through the

TRICARE program. Most of the affected beneficiaries must now use

TRICARE Standard, which imposes significant copayments. The reduction in out-of-pocket costs may increase the demand for care,

especially if Prime cost-control mechanisms are less effective for this

dispersed population than they are for more concentrated populations.
xvii

ACKNOWLEDGMENTS

We wish to thank Ross Anthony and Susan Everingham for their

thoughtful comments and suggestions throughout the project. In

addition, Katherine Harris provided valuable comments on an earlier

draft of this report. Her suggestions have greatly improved the final

product.
1

Chapter One

INTRODUCTION

Understanding the effects of changes in health insurance policies on

the demand for health care services is an important and timely topic.

As the Military Health System (MHS) has evolved over time, it has

begun to adopt cost-containment strategies that have been tested in

private health plans. These strategies have led to changes in many

aspects of the health care services offered to Department of Defense

(DoD) beneficiaries. Each change can potentially affect the number

of people accessing services, the intensity of use, and the cost to the

DoD.

In this report, we review the extensive economic literature that seeks

to explain how changes in health insurance policies will affect health

care use and the overall cost of providing services. The economic literature typically measures such effects as demand elasticities—i.e.,

how responsive consumer demand is to changes in the good’s own

price, the consumer’s income, or the price of related goods. It is our

hope that the review of the existing literature on health care demand

elasticity will provide a greater understanding of the effects of price

changes on the demand that the DoD faces. Such an understanding

is extremely important when evaluating the effects of new or proposed changes in DoD health plans. Several such changes are being

implemented as directed by the FY 2001 National Defense

Authorization Act that was signed into law by President Clinton on

October 30, 2000. These initiatives will

• Expand pharmacy benefits for seniors to include access to military treatment facility (MTF) pharmacies, the National Mail

Order Pharmacy Program, and retail pharmacies,
2 The Elasticity of Demand for Health Care: A Review of the Literature

• Make TRICARE (the military health plan) a second payer to

Medicare,

• Eliminate coinsurance payments under TRICARE Prime (the

health maintenance organization (HMO) option) for dependents

of active duty personnel, and

• Expand TRICARE Prime Remote to active duty family members

and nonuniformed service members.

This report summarizes the research relevant for considering the effects of policy changes on the demand for DoD health care services

and the associated costs. After reviewing the literature, we return to

these policy changes and discuss how the results from the existing

literature can be used to predict the effects of such changes on use

and costs.

Very little of the existing literature speaks directly to demand for

DoD-paid health care, which differs in several important ways from

the demand for health care services in general. To use the estimates

from the literature to predict the effects of changes in DoD health

benefit packages on the use of DoD services, one must understand

the differences, which derive from the unusual organizational structure of the MHS.

A BRIEF DESCRIPTION OF THE MILITARY HEALTH SYSTEM

The MHS provides health care coverage to a wide spectrum of beneficiaries, including active duty military personnel and their dependents, retired military personnel and their dependents, and survivors

of military personnel. Over the past 15 years, as the active duty force

has been reduced by one-third, the mix of beneficiaries served by the

MHS has shifted away from active duty personnel toward other

beneficiaries. In fact, family members and retirees now make up approximately 80 percent of the population covered by the MHS (GAO,

2000).

In response to growing health care costs, DoD decided to make

changes in the MHS that mirrored those taking place in the civilian

sector. In the mid-1990s, DoD implemented a new managed-care

plan, called TRICARE. TRICARE offers three benefit options. The
Introduction 3

first is TRICARE Prime, an HMO in which all care is provided in MTFs

or by a network of civilian providers. All active duty personnel are

automatically enrolled in Prime and receive most of their care in the

MTFs. Beneficiaries who choose not to enroll in TRICARE Prime are

eligible for MTF care on a space-available basis and have two options

for civilian care: TRICARE Standard, a fee-for-service option with the

same benefits as the pre-TRICARE civilian program (CHAMPUS) and

TRICARE Extra, a preferred provider organization (PPO) that provides enhanced benefits when care is provided by the same civilian

provider network used for Prime.

These civilian-care options are provided to retirees and their dependents until they become eligible for Medicare at age 65. Medicare

then replaces TRICARE as the payer for civilian care, but these beneficiaries remain eligible for MTF care so long as there is space available. Base closures and a shift in MTF priorities to Prime enrollees

have meant that less space is available for Medicare-eligible beneficiaries. Since Medicare benefits are not comparable to TRICARE

benefits, the loss of MTF access has resulted in an erosion of benefits

for this group. Recently, Congress extended TRICARE eligibility to

Medicare-eligible beneficiaries, beginning October 1, 2001.1 We discuss this change further in Chapter Four.

Tables 1.1 and 1.2, which are taken from the TRICARE Handbook

(www.tricare.osd.mil), summarize the benefits available for nonactive duty beneficiaries under age 65 in the different plans before the

implementation of the FY 2001 National Defense Authorization Act.

DoD pays the full cost of all health care for active duty personnel.

KEY DIFFERENCES BETWEEN THE MILITARY AND CIVILIAN

HEALTH SYSTEMS

Military and civilian health care demand differs for several reasons.

First, active duty personnel have less discretion in seeking care than

their civilian counterparts and some military duties involve higher

risk. To ensure that active duty personnel are healthy and fit for

duty, they are provided more frequent preventive and routine care

______________

1Eligibility for additional prescription benefits was initiated six months earlier.
4 The Elasticity of Demand for Health Care: A Review of the Literature

Table 1.1

TRICARE Benefits for Active Duty Family Members

TRICARE

Prime

E-1 to E-4

TRICARE

Prime

E-5 and Up

TRICARE

Extra

TRICARE

Standard

Annual

deductible

None None $150/individual

or $300/family

for E-5 and

above; $50/$100

for E-4 & below

$150/individual

or $300/family

for E-5 and

above; $50/$100

for E-4 and below

Civilian outpatient visit$6/visit $12/visit 15% of negotiated fee20% of allowable

charge

Civilian inpatient admission$11/day

($25 min.)

$11/day

($25 min.)

Greater of $25 or

$10.85/day

Greater of $25 or

$10.85/day

Civilian inpatient mental

health

$20/day $20/day $20/day $20/day

Table 1.2

TRICARE Benefits for Retirees, Their Dependents, and Others Under Age 65

TRICARE

Prime

TRICARE

Extra

TRICARE

Standard

Annual

deductible

None $150/individual or

$300/family

$150/individual

or $300/family

Annual

enrollment fees

$230/individual

or $460/family

None None

Civilian provider

copays:

Outpatient

Emergency

Mental health

$12

$30

$25 ($17 for

group visit)

20% of negotiated

fee

25% of allowable

charge

Civilian inpatient

cost share

$11/day

($25 min.)

Lesser of $250/day

or 25% of negotiated charges plus

20% of negotiated

professional fees

25% of billed

charges plus 25%

of allowed professional fees
Introduction 5

than would be typical for civilians the same age (Hosek et al., 1995).2

Changes in TRICARE benefits can be expected to have little effect on

use by active duty personnel and analyses of demand in the military

system do not apply standard demand research to this group.

Second, many retirees and some active duty spouses are eligible for

other health insurance (Hosek et al., 1995), usually through their current employers. These beneficiaries may elect not to participate in

this other insurance, especially if they must pay a share of the premium. If they do participate, they may obtain their health care

through their other insurance, TRICARE, or both. Changes in

TRICARE will induce changes in the number of beneficiaries who rely

on TRICARE (rather than other insurance) as well as the demand for

care in TRICARE. Thus, the availability of outside health insurance

options makes the demand for DoD health care services more elastic

than the demand for health care in general. Since a number of beneficiaries use TRICARE to supplement their other insurance, the effects of changes in TRICARE can be very complex. Dual coverage is

very rare in the general population, so the literature on the effects of

health plan changes typically disregards these dual-coverage issues.

However, by appropriately combining results from both the health

care and health insurance demand literatures, the more complex

military health demand effects can be analyzed.

Third, as Tables 1.1 and 1.2 illustrate, TRICARE benefits can differ

substantially for MTF versus civilian care. As a result, government

and beneficiary costs depend on both the level of demand and its allocation between the MTFs and civilian providers. Costs in other

health plans may also differ according to the mix of providers used,

but few vary benefits in the same way that TRICARE does.

Fourth, military beneficiaries typically use substantially more health

care services than comparable civilians do (Hosek et al., 1995). This

difference may be due to better benefits in the MHS. If so, the general health demand literature may be safely applied because use by

the military is described by the same demand curve as use by the

______________

2For example, enlisted personnel (except senior ones) have no sick leave. They must

go to “sick call” to be excused from duty, even for the most routine illnesses. Other

personnel, such as pilots and undersea divers, must be certified fit for duty even if they

have only minor health problems (e.g., a cold).
6 The Elasticity of Demand for Health Care: A Review of the Literature

general population, but the two groups are positioned at different

points on the curve. Alternatively, differences in use might reflect

different demand responses to the same benefits. In this case, the

demand curves differ and the general literature may not be applicable. There is some reason for believing the first explanation. A large

share of active duty personnel and their families receive care free of

charge at MTFs. Out-of-pocket costs for those using civilian care appear to be no more than costs in other plans (Levy et al., 2000).3

Therefore, average out-of-pocket costs for health care services are

lower in the MHS and we would expect to see higher use among DoD

beneficiaries. However, there may be other explanations for the

higher levels of use that could imply different demand elasticities.

One such explanation is differing patterns of medical practice between the military and civilian health care systems. MTF resources

during the time period under study by Hosek et al. depended on

historical use. As such, MTF commanders had little incentive to keep

use and costs down. They often also lacked the personnel and space

for efficient clinical practice.4 Similarly, differences in access to care

might alter demand elasticities, but recent data suggest that access in

the MHS is similar to access in civilian health plans.

As we indicated above, the DoD beneficiaries include retired personnel who are eligible for Medicare. These beneficiaries have been eligible only for MTF care, but TRICARE will also supplement their

Medicare coverage for civilian care beginning in FY 2001. Most

studies of health care demand and its sensitivity to price change deal

with the nonelderly population. Although there is not a great deal of

empirical evidence on the relative magnitudes of the elasticity of

demand for health care between elderly and nonelderly populations,

economic theory does provide some predictions. Theory suggests

that the elasticity of demand for a product increases as its budget

share grows. In other words, the demand for products that make up

a large portion of an individual’s budget is expected to be more

sensitive to changes in price. Health care services can be expected to

______________

3As we discuss in Chapter Four, cost-sharing for active duty dependents will decrease

in FY 2002.

4The MHS Optimization Plan spells out a broad set of changes that will be implemented between now and 2007 to enhance the cost effectiveness of its health care delivery system.
Introduction 7

make up a larger share of the total budget for the elderly than for the

nonelderly. The elderly health care budget share is likely to be larger

because the elderly use considerably more health care services than

the nonelderly. As a result, we would expect the elasticity of demand

for health care to be larger for the elderly than for the nonelderly.

Although there are a variety of differences between the demand for

health care in general and the demand for DoD health care specifically, the existing empirical research on the demand for health care,

on the demand for health insurance, and on the choice of providers

offers useful information about how people respond to changes in

the price of health care. The differences outlined above merely provide a framework for applying the existing estimates to the unique

situations faced by DoD.

The remainder of the report is organized as follows. First, we briefly

explain what is meant by the term “elasticity of demand” and describe how it can be measured. We then discuss the three main

methodologies that appear in the literature, pointing out the advantages and disadvantages of each. Chapter Three contains the literature review. We begin the review by discussing the elasticity of demand for health care services in general. We then present estimates

for specific types of services such as preventive care, inpatient care,

and pharmacy. We also describe the literature on health insurance

demand. In Chapter Four, we consider potential changes to the MHS

and discuss how the estimates taken from the economic literature

may help to predict the effects of such changes.
9

Chapter Two

METHODS

DESCRIPTION OF ELASTICITY MEASURES

The demand for a product summarizes the relationship between the

quantity of the good or service desired and the price at which it is

offered for sale. Besides the price of the good, many factors such as

the prices of related goods, changing tastes and preferences, consumer income, or expectations about the future influence the demand for a particular product. The elasticity of demand is a measure

of the responsiveness of product demand to changes in one of these

determinants. The demand determinants for which elasticity measures are typically computed are the price of the good or service, the

income of the consumer, and the prices of related goods or services.

Elasticity measures are particularly useful because they focus on the

relative magnitudes of changes rather than the absolute. As such,

elasticity measures are free of units of measurement. This characteristic makes them particularly useful for comparing demand responses across products, countries, and individuals.

Own-Price Elasticity of Demand

Price elasticity of demand measures the percentage change in

quantity demanded resulting from a 1 percent change in price. The

value of the elasticity of demand for a product varies depending on

the level of price and quantity at which it is evaluated. In other

words, at different combinations of price and quantity demanded,

the elasticity of demand for a particular product can vary significantly. As a convention, elasticity measures reported in the literature
10 The Elasticity of Demand for Health Care: A Review of the Literature

are typically evaluated at the mean value of price and quantity in the

data used in the estimation. In practice, the price elasticity of demand will always be negative. This indicates that as the price of a

good increases all other factors held constant, consumers will demand less of that good. The magnitude of the elasticity estimate

provides a measure of how responsive demand is. If the value of the

price elasticity estimate is greater than one in absolute value, then

demand is said to be elastic. When demand is elastic, consumers are

very responsive to changes in price. As such, a small price change

will lead to a relatively large change in quantity demanded. In contrast, if the value of the elasticity of demand estimate is less than one

in absolute value, then demand is said to be inelastic and consumers

are not very responsive to price changes. The demand for health

care services is expected to be relatively inelastic, in large part because there are few close substitutes for medical services.

Income Elasticity of Demand

The income elasticity of demand measures how responsive consumers are to changes in their level of income. It is measured as the

ratio of the percentage change in quantity demanded to the percentage change in income. The demand for a product can be income

elastic, where consumer demand is very responsive to income

changes, or income inelastic, where income changes have very little

effect on demand. The characteristics of a product can help to predict the magnitude of income elasticities. Products that are necessities are expected to be relatively income inelastic, whereas the demand for discretionary goods is expected to be relatively responsive

to changes in income. Classifying health care services in general into

the category of necessity or discretionary is quite difficult. There is

wide variation across medical services with some, such as treatment

for a heart attack, clearly classified as necessities and others, such as

cosmetic surgery, clearly considered luxuries. Certainly, many types

of services fall somewhere in between. Whether health care demand

is elastic or inelastic with respect to income is an empirical question

that has spurred a large literature.
Methods 11

Cross-Price Elasticity of Demand

The cross-price elasticity measures the effect of a change in the price

of one good or service on the demand for another product. For example, it could be used to measure the percentage change in the

quantity of product x demanded resulting from a 1 percent change in

the price of product y. The sign of the cross-price elasticity depends

on the relationship between the two products. If the goods are substitutes in use then the cross-price elasticity will be positive. The

positive sign reflects the fact that as the price of one good goes up the

demand for a substitute good will increase as consumers switch away

from the product that has become relatively more expensive. In contrast, if two goods are complements in use, goods that are used together, then the cross-price elasticity of demand between them will

be negative. When the price of one good goes up the demand for the

other will fall. The consideration of cross-price elasticities will be

most prevalent when we discuss the elasticity of demand for specific

types of medical services.

SPECIAL ISSUES REGARDING THE ELASTICITY OF

DEMAND FOR HEALTH

The demand for health is somewhat more complicated than the demand for a typical product and estimating the elasticity of demand

for health is less straightforward. In this section we outline the important considerations when estimating health care demand elasticities.

Measures of Health Care Demand

Consumers have demand for health but cannot directly purchase it.

They must purchase health care services that are used to produce

health. The idea that health care has a derived, rather than a direct,

demand was first discussed by Michael Grossman in an article published in 1972.

The amount of health care demanded is sometimes measured by the

quantity of services used, such as inpatient days, outpatient visits, or
12 The Elasticity of Demand for Health Care: A Review of the Literature

prescriptions. More often, it is measured by the total cost of the services, allowing for the combination of services measured in different

quantity units. Either measure can be used to estimate standard

demand elasticities.

DoD is typically interested in determining the effects of policy and

other changes on its costs. Most studies do not express elasticities in

terms of insurer costs. Elasticities measured for total costs and insurer costs are not necessarily equal, particularly when the health

plan has a deductible and out-of-pocket cap. In using estimates of

elasticities from the literature, the DoD analyst must be careful to

apply them correctly.

Price of Health Care

The price schedule for health care services is quite complex. The

price that a consumer pays for health care services depends on the

presence of a cost-sharing plan (coinsurance rates or copayments), a

deductible, an upper limit on out-of-pocket expenditures, and premiums. As such, the price of health services can vary according to

the quantity of services used. This makes the estimation of the price

elasticity of demand for health care services somewhat difficult. To

estimate the true effect of price changes the researcher must be able

to determine the effective price that the consumer would pay for an

additional unit of health services. As an example, it seems likely that

an individual who has reached his or her out-of-pocket expenditure

cap for the year and thus faces a price of zero will make different

choices about health care use than someone who has not yet reached

his or her deductible and thus faces the full price of health care services. The complexity of the price schedule highlights the importance of understanding the context in which an elasticity is estimated

when trying to generalize results from the literature.

Time Prices and Health Care

One portion of the cost of any product is the time it takes to purchase

it. With medical care, the time price can be very important. The
Methods 13

waiting time associated with seeing a physician can have a significant effect on the demand for health care services. Waiting times are

often categorized into time waiting to obtain an appointment and

time spent waiting in the physician’s office. In general, the literature

on the effect of time prices on health care demand focuses primarily

on the time spent waiting in the office. This distinction is often made

because, while the individual waits in the physician’s office, he or she

cannot work (or do other activities) and thus faces an important

tradeoff.

In a system where the out-of-pocket cost to the consumer is very low

or zero, time prices can still ration the use of medical services. Only

those for whom the benefits of medical service outweigh the time

costs will choose to visit the doctor. As a result, we would expect to

see individuals with a lower opportunity cost of time using more

medical services than those with high opportunity costs of time.1

Theory predicts that own-time price elasticities will be negative and

cross-price time elasticities will be positive. The negative own-time

price elasticity indicates that as waiting times increase, the demand

for medical services will fall. As such, it is important to consider the

full costs of medical care, monetary plus time costs, when studying

health care demand.

Types of Health Care

The types of health care services offered vary widely and we might

expect that the elasticity of demand for specific service types would

vary as well. The demand for inpatient services could respond differently to price changes than the demand for outpatient services.

Similarly, we might expect differences in the responsiveness of demand for acute and preventive care. Further, health care services

can include lab work, office visits, pharmaceuticals, x-rays, and a variety of other goods and services. This heterogeneity suggests that

estimating separate demand elasticities for each category of health

services could be quite informative.

______________

1The individual’s market wage is often used as a proxy for the opportunity cost of

time.
14 The Elasticity of Demand for Health Care: A Review of the Literature

Interrelationships Between the Demand for Health Insurance

and Health Care

Understanding the demand for health care paid for by a particular

health plan is somewhat more complex than understanding the demand for health care in general. When considering the demand

faced by an individual plan, there are two important effects of any

change in the out-of-pocket costs of medical services. First, if the

out-of-pocket costs for care in a particular health plan fall, more consumers will choose to join that insurance plan. Additionally, the decrease in cost will lead those already enrolled in the plan to use more

services than before. Therefore, the change in quantity of services

provided resulting from a price change is a combination of changes

in these factors. The total effect of a price change on the demand for

health care services paid for by a particular insurance plan can be

seen as the sum of two separate elasticities. The first captures the effect on demand of changes in the number of enrollees in the health

insurance plan. The second represents the effect of the change in

price on the demand for medical services among current enrollees.

Much of the work on the elasticity of demand for health care has focused on the change in medical services among enrollees.2 As such,

estimates of that portion of the elasticity receive more attention in

our summary of the literature. The implication of this for understanding the demand that the DoD faces is that estimates from the

literature will tend to understate the effect of any change in the outof-pocket costs of health care for DoD beneficiaries. In recent years

there has been a growing literature on the demand for health insurance. The final section of the literature review in Chapter Three

summarizes this recent work and presents estimates of the effect of

price changes on the demand for a particular health plan. In combination, these two sets of estimates provide a fuller picture of health

care demand in a particular health plan.

Determining the change in insurer costs associated with a change in

health care demand requires more information if the health plan

______________

2Estimates of the effect on demand of changes in the number of services used among

current enrollees are obtained from studies of the elasticity of demand for health care

in general where the design of the study focuses on individuals who do not change

health plans.
Methods 15

employs a deductible and out-of-pocket cap. The change in demand

should be determined separately for individuals who do not exceed

the deductible, who exceed the deductible but not the cap, and who

exceed the cap. The insurer’s cost share will then differ for these

three groups. The analyst may also need to consider changes in demand for different providers if the plan’s cost-sharing or the

providers’ costs differ for the same care. All of these complications

apply to TRICARE.

Selection Effects

Adverse selection is an important consideration in the estimation of

demand elasticities for health care. Adverse selection occurs when

persons with poor health tend to choose insurance with high benefits

and persons with good health tend to avoid such insurance because

of its high cost. If adverse selection is present, elasticity estimates

will measure the difference in needs of people with different health

and socioeconomic status in addition to the quantity response to the

price change. In some cases, researchers have been interested in

measuring the degree of adverse selection, using sophisticated statistical techniques to decompose the total effect on demand.

Moral Hazard

Estimating the demand for health care is further complicated by the

presence of moral hazard. Ex ante moral hazard occurs when the

presence of insurance undermines an individual’s incentives to take

actions to help prevent a loss. Ex post moral hazard comes into play

after the injury or illness has already occurred. The presence of insurance shields the consumer from paying for the full cost of medical

services. As a result, the individual consumes more medical services

than he would if he had no insurance (Zweifel and Manning, 2000).

It is particularly important, therefore, for researchers to understand

the role that moral hazard plays in increasing the demand for medical care services. Any change in price will change the incentives that

the individual faces. For example, as the out-of-pocket costs to an

individual fall, he or she bears less of the burden of any health care

service that is used. As a result, individuals demand more health care

services. Estimates of the price elasticity of demand for health care

in the literature will incorporate the effects of moral hazard.
16 The Elasticity of Demand for Health Care: A Review of the Literature

Provider Behavior

Estimating the demand for health care services is a complex process

that must consider both the consumer’s response to changes in price

and the provider’s ability to induce demand (Weiner, 1993).

Physicians may change their patterns of practice, perhaps prescribing more intense treatments, when increased cost-sharing leads to

lower demand for their services. Furthermore, physicians act as an

agent once care is initiated by the patient and may not consider price

in the same way as the patient would.
17

Chapter Three

REVIEW OF THE EMPIRICAL LITERATURE

In this chapter, we provide an overview of the empirical literature on

the elasticity of demand for health care and for health insurance.

First, we discuss briefly the empirical methodologies that are used in

the literature. Then, we focus upon the results from studies of the

demand for health care. We discuss studies that seek to identify a relationship between factors such as income and the price of health

care and the use of health care services. In the final section, we examine the demand for health insurance and we discuss studies on

the relationship between enrollment decisions and changes in the

price of health care insurance.

THE ELASTICITY OF DEMAND FOR HEALTH CARE

SERVICES

There is an extensive literature in economics that seeks to estimate

the elasticity of demand for health care services. The seminal works

in this area were produced during the 1970s and to a large extent

have withstood the test of time. Although many of the studies that

will be discussed in this section also estimate elasticities for specific

services, we choose to focus only on the elasticity of demand for

health care services more generally at this point. The elasticities of

demand for specific types of medical services will be summarized in

the following section.

Methodologies Used in the Literature

The ideal empirical data for estimating the elasticity of demand for

health care would include detailed information on personal charac-
18 The Elasticity of Demand for Health Care: A Review of the Literature

teristics, use of medical services, and the effective price paid for an

additional unit of health care. Most important, in the ideal data, the

observed variations in price and subsequent use would be exogenous. The ideal data, however, do not generally exist. Consequently,

researchers have developed a variety of methodologies that can address many of the issues that arise from the lack of ideal data. The

methodologies typically used in the literature can be classified into

three general categories: experimental, quasi-experimental, and observational. Experimental studies use random assignment into

treatment and control groups to infer the effects of a particular

treatment (Cook and Campbell, 1979). Estimates from experiments

are thought to provide a “gold standard” because the randomization

of people into different treatments avoids the problem of selection

bias in that individuals under study are not able to choose whether to

obtain the treatment. However, there are some disadvantages associated with experimental studies. They can be difficult to design and

implement. In addition, they are extremely costly and take a lot of

time. It can be many years from the time the experiment starts until

the effects can be fully evaluated. Most important for the purposes of

this review, the results from experimental studies may not necessarily be generalizable. The effects that are measured in a closely controlled setting may not reflect what will happen upon wider implementation.

The second category of studies of the elasticity of demand for health

care is quasi-experiments. These studies are similar to experiments

in that there are treatments and outcome measures; however, in

quasi-experiments individuals are not randomly assigned to treatment and control groups (Cook and Campbell, 1979). In the case of

health care demand, the majority of quasi-experimental studies can

be more narrowly defined as natural experiments. Natural experiments identify the effects of treatment using exogenous variations

that occur in the economic environment. For example, Cherkin et al.

(1989) used the introduction of copayments in the Group Health Cooperative of Puget Sound to estimate the effect of price on the demand for health care services. Comparisons of use before and after

the policy change provide the basis for this methodology. The main

issue of concern is that the researcher must be able to control for all

other factors that may have changed at the same time. If not, the estimated effect of the policy change will incorporate the effects of all
Review of the Empirical Literature 19

of the other unobserved factors that changed during the time period

of analysis. As an example, suppose that there was a significant flu

epidemic in the year after a health insurance plan change that implemented copayments. Further assume that no change in use is observed after the plan is implemented. At first blush, one could conclude that copayments do not affect demand for health care. This

conclusion is flawed, however. The change in use, or lack thereof,

reflects both the effect of the change in copayments and the effect of

the difference between the incidence of the flu in the pre and post

time periods. To obtain estimates of the true effect of the policy

change, the researcher must be able to control for other factors that

could have affected use during the time period of analysis. In many

cases, a comparison group (similar to the control group in the experimental design) that does not receive the policy change is used to

help address the question of what would have occurred had the policy not been changed. The extent to which the researcher was able to

control for confounding factors must be considered when interpreting results based on natural experiments.

The final category in the literature is observational studies of the

elasticity of demand for health care. These studies are often based

on survey or administrative data. In such cases, econometric models

are used to estimate the demand for health care. The effect of price

on the demand for health services is identified from the variation in

price across health plans and over time. It can be very difficult to

identify causal effects of treatment using observational study methods. Observed correlations between treatment and outcome measures do not necessarily imply causality. As a result, complicated

models have been developed to deal with the problems associated

with nonexperimental data such as omitted variables, unobserved

heterogeneity, selection bias, and endogeneity. These statistical procedures, however, are not feasible in some cases and, thus, the question of causality may not be answered in all observational studies.

There are several advantages associated with the use of observational

studies. First, they are much less costly to implement than experimental studies and can provide results more quickly. Second, in

some cases random assignment into treatment may not be ethical.

This is particularly true in the case of health care where randomization into the control group might mean that an individual does not

receive a lifesaving treatment. Most important for the purposes of
20 The Elasticity of Demand for Health Care: A Review of the Literature

applying results from the literature, the results from observational

studies may be more generalizable than results from experiments.

Main Findings

Despite a wide variety of empirical methods and data sources, the

estimates of the demand for health care, shown in Table 3.1, are

consistently found to be price inelastic. Although the range of price

elasticity estimates is relatively wide, it tends to center on –0.17,

meaning that a 1 percent increase in the price of health care will lead

to a 0.17 percent reduction in health care expenditures. The priceinduced changes in demand for health care can in large part be

attributed to changes in the probability of accessing any care rather

than to changes in the number of visits once care has been accessed.

In addition, the studies consistently find lower levels of demand

elasticity at lower levels of cost-sharing.

The demand for health is also found to be income inelastic. The estimates of income elasticity of demand are in the range of 0 to 0.2.

The positive sign of the elasticity measure indicates that as income

increases, the demand for health care services also increases. The

magnitude of the elasticity, however, suggests that the demand response is relatively small. Studies based on long time series data

tend to report higher income elasticities. The difference in estimates

across time frames is due to the incorporation of the effects of

changes in medical technology in studies that use long time series

data.

Price Elasticity of Demand for Health Care

The price schedule for health care services can be quite complicated.

As noted above, the effective price that a consumer pays depends on

many factors including coinsurance, deductibles, upper limits on

out-of-pocket expenditures, premiums, and the price of the good or

service itself. A change in any of these factors will affect the out-ofpocket costs of health care to the consumer. In the summary of the

literature below, for each study that is discussed we will identify the

source of price variation.
Utopia R ✺❁❐❆

Table 3.1

Key Studies with Price Elasticities for All Services

Study Methodology

Data/

Population

Price

Measure

Quantity

Measure

Price

Elasticity

Feldstein, 1971 Observational: time-series

regression

AHA survey of hospitals, 1958–1967;NCHS survey, 1963–1964

Coinsurance ratesand plan generosity

Mean hospital stay –0.49

Fuchs andKramer, 1972

Observational:instrumental variables

1966 IRS tabulations Coinsurance rates

and plan generosity

Visits per capita –0.10 to

–0.36

Scitovsky andSnyder, 1972

Natural experiment Palo Alto Group Health Plan, 1966–

1968

Coinsurance rates Physician visits –0.14

Rosett andHuang, 1973

Observational: crosssectional tobit Survey of Consumer Expenditures, 1960 Out-of-pocket costs Medical expenditures –0.35 to –1.5

Beck, 1974 Natural experiment Sample of low-income people in

Saskatchewan, Canada

Copayments Physician

visits

–0.07

Phelps andNewhouse, 1974

Observational Insurance plans in the United States,

United Kingdom, and Canada

Coinsurance rates Medical

expenditures

–0.04 to–0.12

Scitovsky andMcCall, 1977

Natural experiment Palo Alto Group Health Plan, 1968–1972 Coinsurance rates Physician visits –0.29

Wedig, 1988 Observational NMCUES, 1980 Out-of-pocket costs Physician visits –0.16 to

–0.35

Cherkin et al.,1989

Natural experiment Group Health Cooperative of Puget

Sound

Copayments Physician visits –0.04

Newhouse et al.,1993

Experimental RAND HIE Coinsurance rates

across plans

Medicalexpenditures

–0.17 to–0.22

Eichner, 1998 Observational: tobit

regressions

Insurance claims for those coveredthrough a large employer

Out-of-pocket costs Medical

expenditures

–0.62 to–0.75

Review of the Empirical Literature 21
22 The Elasticity of Demand for Health Care: A Review of the Literature

The quantity of health care can be measured in a number of ways. In

the studies that we review, the number of physician visits and total

medical expenditures are the two quantity measures that are predominantly used. In the discussion of each study, as well as in the

summary table, we will identify the health care quantity measure

that the reported price elasticity estimate is based on. This is important to keep in mind when comparing the elasticity estimates across

studies.

Feldstein conducted one of the earliest studies on the price elasticity

of demand for health care in 1971. The results were based on micro

data at the hospital level and were the first of this type to be considered statistically robust. The data for the study were taken from the

American Hospital Association Survey of Hospitals between 1958 and

1967. The effect of price on mean length of stay for hospitalized patients was identified in a time series regression using variations in the

price of hospital stays, coinsurance rates, and proportion of the

population insured across states. Feldstein estimated that the price

elasticity of demand for health care was approximately –0.5. This

elasticity estimate is interpreted to say that a 1 percent increase in

the coinsurance rate will lead to a 0.5 percent reduction in the mean

hospital stay, or that the demand for health care services is relatively

inelastic. A later study by Feldstein (1973) used state-level data to

estimate a two-stage least squares model and obtained a slightly

larger price elasticity estimate of –0.67. The two-stage estimation

procedure was used in an effort to control for the potential endogeneity of the price of insurance.

In a similar vein, Fuchs and Kramer (1972) used aggregate state-level

data to investigate the price elasticity of demand for health care services. The estimates of the elasticity based on net prices ranged between –0.15 and –0.20, which are substantially smaller than the estimates from Feldstein (1971, 1973). These results indicate that the

demand for physician visits is relatively insensitive to changes in

prices. However, there are a number of potential problems associated with the use of aggregate data in the estimation of the price

elasticity of demand. Most important, aggregating over individuals

and service types reduces variation in the data and can lead to aggregation biases.
Review of the Empirical Literature 23

A study by Rosett and Huang (1973) was among the first observational studies of the demand for health that used individual-level

data. The 1960 Survey of Consumer Expenditure was used to analyze

the effect of prices on health care demand. Using constructed measures of coinsurance, Rosett and Huang estimated that the price

elasticity of demand was –0.35 when the out-of-pocket price for

health care is 20 percent of the market price. At higher out-of-pocket

prices, they found much greater sensitivity in medical expenditures

(elasticities up to –1.5). The relatively large demand elasticities may

be due in part to the way they constructed the coinsurance measures. The methodology used could lead to overestimates of price

responsiveness (Zweifel and Manning, 2000).

Using data on insurance plans in the United States, Canada, and the

United Kingdom, Phelps and Newhouse (1974) estimated price elasticities of demand for health care across coinsurance ranges. The

price elasticity was estimated to be –0.12 when coinsurance rates

ranged between 20 and 25 percent. When coinsurance rates

decreased to between 15 and 20 percent, the elasticity was reduced

to –0.07. Further, coinsurance rates ranging from 10 to 15 percent

yielded price elasticity estimates of –0.04. These results indicate that

low levels of cost-sharing will lead to relatively small changes in

health care demand.

Wedig (1988) took a slightly different approach to the question and

examined the connection between health status and price responsiveness of the demand for physician visits. Elasticities were estimated using data from the 1980 National Medical Care Utilization

and Expenditure Survey. The results showed that people who perceived their health status to be fair or poor were less price responsive

(–0.16) than those who reported their health to be good or excellent

(–0.35).

Eichner (1998) used insurance claims data from one large employer

to estimate the price elasticity of demand for health care. To do so,

Eichner isolated the behavioral response to changes in price using

variation in out-of-pocket cost within a plan with an annual deductible during a calendar year. The structure of these plans allowed

the price of care to fall during the calendar year as people reached

their deductible. He interpreted the difference in expenditures

between those who have met their deductible and those who have
24 The Elasticity of Demand for Health Care: A Review of the Literature

not as a behavioral response to variation in the cost of medical care.

The estimates of the price elasticity of the demand for health care

varied between –0.75 and –0.62.

Starting in the early 1970s, many researchers began using the occurrence of natural experiments as an alternative estimation strategy. In

1972, Scitovsky and Snyder studied the effect of the implementation

of cost-sharing requirements in the health plan offered to the faculty

and staff (and their dependents) of Stanford University. A 25 percent

coinsurance rate was implemented in April 1967. Changes in the use

of health care services between 1966 and 1968 were analyzed to determine the effects of coinsurance on demand. The results indicated

that the price elasticity of demand for physician visits was –0.14,

showing that the demand for health is quite inelastic. Since Scitovsky and Snyder were able to use individual-level data, they explored some issues in greater detail than had been possible in the

previous literature. Their results indicated that there is not much

variation across socioeconomic and demographic groups in the demand response to changes in the price of health care. In a related

study, Scitovsky and McCall (1977) found that reduced use of services caused by the institution of coinsurance is not transitory.

Service use remained at the lower level at least through the four-year

follow-up period.

During the same period of time, Beck (1974) studied the effect of copayments on health care use in Saskatchewan, Canada. In 1968, the

health plan provided by the province implemented a program

requiring copayments of $1.50 for each doctor visit.1 Beck analyzed a

sample of over 40,000 individuals in 21,900 households selected at

random. The findings indicated that the price elasticity of demand

for health care services was –0.07. The fact that the elasticity estimate found in this study was somewhat lower than that reported

thus far may be due to a change in physicians’ practice patterns in

Saskatchewan. If physicians responded to lower use by prescribing

more intensive treatments for those who do use their services, the

effect would tend to work in the opposite direction of the individual

demand response and, thus, the estimate provided by Beck would

______________

1The $1.50 copayment in 1968 dollars is equal to $14.48 in 2000 dollars. (These prices

are measured in U.S. dollars.) At the time of the implementation of copayments,

Canadian and U.S. dollars had equivalent value.
Review of the Empirical Literature 25

understate the true effect of prices on the demand for health care

services.

A more recent study that was based on a natural experiment analyzed the effect of copayments on the demand for health care services for individuals insured through Group Health Cooperative of

Puget Sound (GHC) (Cherkin et al., 1989). In July 1985, the plan began requiring copayments of $5 for each outpatient visit and $25 for

each visit to the emergency room.2 Cherkin et al. improved upon the

analyses of the 1970s by including a comparison group, which did

not receive the policy change. The evaluation of use patterns before

and after the policy change yielded price elasticity of demand estimates of –0.04 for all visits. In a related study, Cherkin et al. (1990)

found no difference in demand responses to price changes across income groups. The estimates from these studies are not directly

comparable to those discussed previously. The GHC is a large staff

model HMO in Seattle, Washington. The effect of prices on demand

for health care services is likely to be different for different types of

health plans. The management of care in HMOs increases the constraints on consumers and thus affects their use decisions.

In response to the relatively wide range of price elasticity estimates in

the early health demand literature (from –0.07 in Beck, 1974, to –1.5

in Rosett and Huang, 1973), the government funded a social insurance experiment that was designed to answer a number of important

questions surrounding the demand for health care. The RAND

Health Insurance Experiment (HIE) (Newhouse et al., 1993) ran from

1974 to 1982 and randomized families in six sites into different insurance plans. The plans varied by level of cost-sharing, out-of-pocket

maximum expenditure, and size of deductibles. Although the HIE

was conducted approximately 20 years ago, the results of the related

studies are still considered the “gold standard” for health demand

elasticity estimates. The experimental design enables researchers to

sidestep all of the selection and endogeneity problems associated

with observational studies. The analysis of the HIE compares health

care use across individuals in different insurance plans. It is interesting to note that use of health care services in the HIE was not affected

______________

2The $5 copayment in 1985 dollars is equal to $11.88 in 2000 dollars. The $25 copayment for emergency room visits is equal to $59.39 in 2000 dollars.
26 The Elasticity of Demand for Health Care: A Review of the Literature

by the out-of-pocket maximums. Consequently, for estimation purposes all insurance plans with the same coinsurance structure were

considered the same. For coinsurance rates between 0 and 25 percent, the price elasticity of medical expenditures was found to be

–0.17. Consistent with the patterns seen in observational studies, the

demand for health care was found to be somewhat more price sensitive as the coinsurance rate increased. In the HIE, coinsurance rates

between 25 and 95 percent yielded elasticity estimates of –0.22. The

magnitude of the elasticities estimated from the HIE fall at the lower

end of the range of previous estimates.

Cost-sharing in the HIE was found to significantly reduce per capita

medical expenditures. Among those with free care (0 percent coinsurance), per capita expenditures were found to be 46 percent higher

than among those with a 95 percent coinsurance rate. Furthermore,

increased deductibles regardless of coinsurance rates were found to

reduce health care use (Keeler and Rolph, 1988). The cost-sharing

strategies worked to reduce use by reducing the number of treatment

episodes and not by reducing intensity of treatment once an individual accessed the medical care system (Keeler and Rolph, 1983). The

reductions in episodes were spread across situations both where

medical treatment would be highly effective (an infection that can be

treated with antibiotics) and where medical treatment would likely

provide the fewest benefits (a flu caused by a virus) (Lohr et al.,

1986). This result indicates that cost-sharing is an imprecise way to

reduce less appropriate care.

Although the experimental results of the HIE are viewed as the gold

standard, some issues of external validity have been raised. First, the

study was geographically limited, as it was implemented in only six

sites. Differences in health care use patterns have been observed

across regions and, therefore, the HIE results may not be generalizable to the full population. The HIE sites, however, were chosen to

include places that differed in important ways. Further, the results

from the HIE are old. The health care industry has changed substantially since the experiment was implemented. Managed care has

grown to be a significant portion of the health care plan options offered in most markets. Further, progress with medical technology

and pharmaceuticals has pushed forward rapidly. It is difficult to say

whether the HIE results can predict consumer behavior in a health

care system that has changed significantly. Finally, it is not clear how
Review of the Empirical Literature 27

the results from the HIE can be applied to a whole health care market. There were a few HIE participants in each study site (approximately 1,000 in each). As a result, any one physician might have

only a few patients facing the new cost-sharing regimes and, thus,

they did not feel the effects of reduced demand. It seems likely that if

a cost-sharing plan was widely implemented and the demand for

physician services fell, the behavior of suppliers might change.

Income Elasticity of Demand for Health Care

Although there is a wide literature on the income elasticity of demand, we have chosen to provide only a brief summary of the key

findings. For the purposes of considering policy changes, income is

an important variable, but it cannot be easily manipulated. The effects of changes in variables that the policymaker can control, such

as coinsurance rates and deductibles, warrant greater analysis.

Theoretically, the effect of income on the demand for health care

should be small, if not zero, under full insurance. If consumers have

access to free care, changes in income should not affect their ability

to obtain medical services. The empirical estimates in the literature

are consistent with theory. Phelps (1992) calculated income elasticities based on results from an HIE study (Keeler et al., 1988). He

found that the demand for health care was relatively insensitive to

change in income. The calculations yielded elasticities of 0.2 or less.

This can be interpreted to say that a 1 percent increase in income will

lead to a 0.2 percent increase in the demand for health care. Results

from a number of observational studies are consistent with the finding from data based on the HIE (for examples, see Taylor and Wilensky, 1983; Holmer, 1984).

Income elasticities based on cross-sectional data or on time series

data covering a relatively short period hold the level of available

medical technology constant. As real income in the population increases, the aggregate demand for new medical technologies and

new treatment approaches rises as well and innovation accelerates.

The technical change that occurs will alter the patterns of health care

use. Income elasticities that are estimated from long time series data

typically show much greater sensitivity of health care demand to

changes in income. Feldstein (1971) used data from 1958 to 1967 to

estimate an income elasticity of 0.5. Similarly, McLaughlin (1987)
28 The Elasticity of Demand for Health Care: A Review of the Literature

found an income elasticity of 0.7 using data from 1972 to 1982. A recent study by DiMatteo and DiMatteo (1998) used data from 10

provinces in Canada from 1965 through 1991 and found a similar income elasticity of 0.8. The larger elasticities from the time series

studies reflect the incorporation of the effects of technical change.

In addition, one study evaluating the CHAMPUS Reform Initiative

provides some evidence on the effect of income on the demand for

health care among DoD beneficiaries. Hosek et al. (1993) found that

increasing income reduces the probability of any military outpatient

visits as well as the number of visits among users. Similarly, higher

incomes were found to reduce the probability of any military inpatient visits. The negative correlation between income and use of

military health services likely reflects the fact that higher-income

military families are more likely to use nonmilitary health services.

Time Price Elasticity of Demand for Health Care

It is widely recognized that time prices are an important determinant

of the demand for medical care, but there is very little empirical evidence regarding the sensitivity of health care demand to changes in

time prices. One study, however, does speak directly to the time

price elasticity of demand. Janssen (1992) used data from the National Health Interview Survey from the Netherlands Central Bureau

of Statistics to estimate the demand for health, paying particular attention to the effect of time prices on demand. The time price associated with a doctor visit consists of two parts, the time spent and the

value of the time. Janssen defined the time spent to include travel

time, waiting time, and treatment time. The value of the time used to

visit the doctor is defined in some cases by the individual’s market

wage and by employment status in others. The study found time

price elasticities in the range of –0.09 to –0.14. These results suggest

that a 1 percent increase in the time price of medical care will lead to

approximately a 0.11 percent decrease in the probability of visiting a

general practitioner. For all employment groups, the time price

elasticity of demand is negative and small, suggesting that people are

not very sensitive to changes in time prices. Although the estimates

are clustered together, one of the highest time price elasticities was

found for people who are employed full-time as managers or direc-
Review of the Empirical Literature 29

tors. This result makes sense, since such people would likely have

high opportunity costs of time.

Time costs may be of particular importance within the context of the

MHS, since much of the care is provided at MTFs where there is no

monetary cost to the individual. Under these circumstances, time

costs become particularly important in determining patterns of use.

Many people who are eligible to receive care at MTFs choose to use

other providers that require a copayment. If waiting times are longer

in the MTF setting, this choice likely reflects the effects of time prices

on the demand for health care services.

PRICE ELASTICITY OF DEMAND FOR SPECIFIC TYPES OF

SERVICES

Health care is a widely heterogeneous product. One might expect

the demand for different types of medical services to respond differently to changes in price. In this section, we summarize the health

demand literature that speaks directly about the demand for specific

types of health services. When considering specific types of services,

there is greater opportunity to observe important relationships between goods. For example, one might argue that inpatient and outpatient services could serve as substitutes for one another. Similarly,

lab services and inpatient stays might be expected to be complements. With this in mind, we will identify any cross-price elasticities

that are contained in the literature. In the following sections, we first

present estimates of inpatient and outpatient demand elasticities.

Subsequently, elasticity estimates for preventive and acute care are

discussed. Then, we discuss the elasticity of demand for prescription

drugs. Finally, we review the literature on the elasticity of demand

for mental health services. The estimates from the literature are

summarized in Table 3.2.

Main Findings

Although the price elasticity of demand for medical care in general is

relatively low, certain types of care are found to be somewhat more

price sensitive. Preventive care and pharmacy benefits are among

those medical services with larger price elasticities. The finding that
Utopia R ✺❁❐❆

Table 3.2

Key Studies with Price Elasticity Estimates for Specific Medical Services

Study Method Data/Population Price Measure Quantity Measure Elasticity Estimates

Inpatient vs. Outpatient Services

Newhouse andPhelps, 1974

Observational Center for Health

Administration StudiesSurvey, 1963

Coinsurance rates Inpatient: length of

stayOutpatient: no. of visits

Inpatient: –0.1Outpatient: –0.1

Newhouse andPhelps, 1976

Observational Center for Health Administration Studies Survey,

1963

Coinsurance rates Probability of use Inpatient: –0.17

Outpatient: –0.11

Newhouse et al.,1993

Experiment RAND HIE Coinsurance rates Medical expenditures Inpatient: –0.14 to –0.17

Outpatient: –0.17 to –0.31

Preventive vs. Acute Care

Newhouse et al.,1993

Experiment RAND HIE Coinsurance rates Medical expenditures Preventive: –0.17 to –0.43

Acute: –0.17 to –0.32

Prescription Drugs

O’Brien, 1989 Natural

experiment

Prescription drug use inthe United Kingdom

Copayments No. of prescriptions –0.33

Lavers, 1989 Natural

experiment

Prescription drug use inthe United Kingdom

Copayments No. of prescriptions –0.15 to –0.20

Harris et al.,1990

Naturalexperiment

Group Health Cooperativeof Puget Sound

Copayments No. of prescriptions 10.7% decrease after $1.50

copay initiated

Smith, 1993 Observational National prescription drug

card service data

Coinsurance rates No. of prescriptions –0.10

30 The Elasticity of Demand for Health Care: A Review of the Literature
Utopia R ✺❁❐❆

Table 3.2 (continued)

Study Method Data/Population Price Measure Quantity Measure Elasticity EstimatesHughes andMcGuire, 1995

Naturalexperiment

Data on prescription druguse in the UnitedKingdom

Copayments No. of prescriptions –0.35

Newhouse et al.,1993

Experiment RAND HIE Coinsurance rates Expenditures on

prescriptions

–0.17

Mental Health Services

Hankin et al.,1980

Naturalexperiment

Columbia Health Planclaims data

Coinsurance rates No. of visits –0.02

McGuire, 1981 Observational Joint Information Service

Survey of office-basedpsychiatrists

Out-of-pocket costs No. of visits –1.0

Wells et al., 1982 Experiment RAND HIE Coinsurance rates Expenditures on

mental health care

–0.17

Wallen et al.,1986

Naturalexperiment

United Mine Workers ofAmerica medical claimsdata

Coinsurance rates No. of visits All: –0.32

Men: –0.50Women: –0.31

Frank, 1985 Observational Aggregate state-level data,

1970–1978

Price of psychiatricservices

Per capita visits topsychiatrists

–1.0 to –2.0

Simon et al.,1996

Observationalor quasi–experiment

Claims data from a largeHMO

Coinsurance rates Probability of using

mental health services

–0.17 to –0.28

Review of the Empirical Literature 31
32 The Elasticity of Demand for Health Care: A Review of the Literature

the demand for preventive care is more price sensitive than the

demand for other types of care is not surprising. The number of

available substitutes for a product is a major determinant of demand

elasticity. In the case of preventive care, a number of goods and services could possibly serve as substitutes. As a result, when the price

of care increases consumers are able to substitute away from preventive care toward other goods and services that promote health,

such as nutritional supplements and healthy foods. In addition, preventive medical services may be seen as more discretionary than

necessary and, thus, may be put off when the price of such care increases. Further, the opportunity cost of obtaining preventive care is

much higher than it is when the patient is sick, particularly if the illness keeps the individual out of work. It is also likely that, since the

benefits of preventive care accrue in the long-term, they are heavily

discounted. The difference in elasticities may also reflect the fact

that preventive care and prescription drugs are typically not as well

covered by insurance.

Inpatient Versus Outpatient Demand Elasticities

An early study by Newhouse and Phelps (1974) focused on estimating the price elasticity of demand using data from the 1963 Center for

Health Administration Studies survey. Their estimates serve as a

lower bound on the overall price elasticity as they considered only

the effect of price on the quantity of services used, not the effect of

price on the decision to use any services at all. For hospital inpatient

stays, they found that the quantity of services, measured in terms of

the length of the inpatient stay, was not very responsive to changes in

price. The estimated price elasticity for inpatient services was found

to be –0.1. The elasticity estimates for physician visits were quite

similar. A 1 percent increase in the price of a physician visit would

lead to a 0.06 percent reduction in the number of visits demanded.

In a later study, Newhouse and Phelps (1976) improved upon their

prior methodology by using a two-part demand model to explicitly

measure the effects of price on both the use of any care and the

quantity or intensity of care. Their results suggest that slightly more

than half of the effect of the reduction in demand resulting from an

increase in price is due to the reduction in the number of people who

obtain any care. For inpatient stays, the price elasticity of demand

for any care was –0.17 and the price elasticity of length of stay was
Review of the Empirical Literature 33

–0.06. In the case of outpatient visits, the price elasticity of any use

was –0.11 and the elasticity of demand for visits was –0.08. The Newhouse and Phelps studies (1974, 1976) did not address the issue of

the cross-price elasticity between inpatient and outpatient care.

The most comprehensive results on the effect of price on the demand for inpatient and outpatient services are based on data from

the HIE. Newhouse et al. (1993) provided estimates of elasticity by

type of service received. With coinsurance rates in the range of 0 to

25 percent the price elasticity of demand for both outpatient and

inpatient services was found to be –0.17. When coinsurance rates

increased to 25 to 95 percent, however, the demand for outpatient

services was found to be more price sensitive than the demand for

hospital stays (–0.31 and –0.14, respectively). In a related study, Leibowitz et al. (1985) compared demand responsiveness across age

groups. They found that children’s and adult’s demand for outpatient services is equally responsive to price changes. For inpatient

services, however, price changes have no effect on the quantity of

services demanded for children.

The design of the HIE allowed researchers to address the question of

the cross-price elasticity between inpatient and outpatient services.

One health plan variation included in the HIE required coinsurance

payments for outpatient services but not for inpatient hospital stays.

An analysis by Manning et al. (1987) indicated that there was no

substitution between inpatient and outpatient services. In fact, they

found just the opposite. Inpatient use was actually somewhat higher

in the group that had to pay coinsurance for their stays. Although the

difference is not statistically significant, it could suggest that inpatient and outpatient services are actually complements in use.

The movement toward managed care in the MHS provides a natural

experiment to analyze the effect of price changes on use among DoD

beneficiaries. Goldman (1995) studied the CHAMPUS Reform Initiative (CRI) and found differences in the use response between inpatient and outpatient care. The CRI, a pilot test for TRICARE, covered

850,000 beneficiaries in California and Hawaii. The CRI offered MHS

beneficiaries the choice of enrolling in an HMO or in a PPO. Goldman used a sophisticated statistical model to address self-selection

issues associated with the choice of enrolling in the HMO or PPO.

The results from this analysis showed that the demand for outpatient
34 The Elasticity of Demand for Health Care: A Review of the Literature

care was 16 percent higher in the HMO than in the baseline fee-forservice (FFS) plan. The HMO option involved lower out-of-pocket

costs for civilian visits; however, MTF care remained free in all plans.

Most of this increase under the HMO can be attributed to a greater

probability of any use rather than an increase in the number of visits

per person. It is interesting to note that there does not appear to be

any difference in outpatient use between the PPO and FFS. The aggressive use reviews in the HMO and PPO appear to have decreased

inpatient days relative to FFS. However, the CRI did not appear to

deter inpatient admissions.

Preventive Care Versus Acute Care Demand Elasticities

The literature suggests that the demand for preventive care, or well

care, is somewhat more responsive to price than either acute or

chronic care. Newhouse et al. (1993) used data from the HIE to estimate demand elasticities for each of these categories of care. At

lower levels of coinsurance (0 to 25 percent), the price elasticity of

demand for these service types is quite similar and centers on –0.17.

When coinsurance rates are between 25 and 95 percent, however,

differences in the elasticities of demand are found. The demand for

preventive care is found to be the most price sensitive, with an

elasticity of –0.43. The demand elasticities for acute and chronic are

–0.32 and –0.23, respectively.

Cherkin et al. (1990) provided some insight into the effect of price on

the demand for preventive care based on data from a natural experiment. They found that after the imposition of $5 copayments for

outpatient visits, preventive outpatient visits fell by 14 percent

whereas the number of outpatient visits fell by only 11 percent.3 Although the difference is relatively small, the results from Newhouse

et al. (1993) suggest that as the level of cost-sharing (in this case the

copayment) increases, the demand responsiveness increases as well.

______________

3The $5 copayment in 1983 dollars is equal to $11.88 in 2000 dollars.
Review of the Empirical Literature 35

Price Elasticity of Demand for Prescription Drugs

The demand for prescription drugs is another category of medical

services that has been analyzed in the literature. In 1983, Group

Health Associates implemented a cost-sharing prescription drug

plan in Washington state. Harris et al. (1990) analyzed the effect of a

$1.50 copayment on demand and found a 10.7 percent decrease in

the number of prescriptions. A further increase in the copayment

from $1.50 per prescription to $5 per prescription reduced prescriptions by an additional 10.6 percent.4 Using the numbers reported, we

calculate the own-price elasticity of demand for prescription drugs to

be between –0.05 and –0.08, indicating inelastic demand.

In a similar study, Smith (1993) analyzed the effect of an increase in

prescription drug copayments from $2 to $5 on prescription drug use

for a set of employer groups covered by one national managed care

company.5 This study found a price elasticity of demand for pharmaceuticals equal to –0.10. This elasticity can be interpreted as a 1 percent increase in the price of prescription drugs leads to a 0.1 percent

decrease in the number of prescription claims. Smith noted, however, that although the number of prescriptions fell in response to

the price increase, there was an offsetting increase in the ingredient

costs per prescription. This suggests that physicians compensated

for the increased price to consumers by prescribing larger amounts

per prescription. In addition, this study found that the increase in

drug copayments led to a 10 percent decrease in employer costs per

person and an increase in employee costs.

A number of studies of the price elasticity of demand for prescription

drugs use data from the United Kingdom. Copayments for prescriptions were implemented beginning in 1968. O’Brien (1989) took advantage of the natural experiment and estimated a price elasticity of

–0.33. Further, the study found a positive cross-price elasticity of

0.17 between prescription and over-the-counter drugs. A positive

cross-price elasticity indicates that two goods are substitutes in use.

Hughes and McGuire (1995) used a more complicated estimation

______________

4The $1.50 and $5 prescription drug copayments are equal to approximately $4 and

$12, respectively, in 2000 dollars.

5The increase in copayments from $2 to $5 per prescription in 1989 dollars is equal to

an increase from $3.62 to $9.06 in 2000 dollars.
36 The Elasticity of Demand for Health Care: A Review of the Literature

model and found similar results using data from the United Kingdom. Lavers (1989), using data from the United Kingdom for the

years 1971 through 1982, found prescription drug elasticities that

were somewhat lower. His results suggest that a 1 percent increase

in price will lead to a reduction in the number of prescriptions

somewhere in the range of 0.15 to 0.20 percent.

Results from the HIE indicate that prescription drug use is responsive to cost-sharing. The per person prescription expenditure in the

free care plan was nearly two times higher than the per person expenditure in the plan with a 95 percent coinsurance requirement

($82 and $46, respectively) (Newhouse et al., 1993). The reduction in

drug expenditures, however, can be attributed in large part to the

differences in visit rates between the two plans. The prescription

drug cost per visit was found to be quite similar across plans. Since

there was no independent variation in the prescription drug coinsurance (they were the same as the visit coinsurance rates), it is difficult

to isolate the effect of price on prescription drug demand from the

HIE data. The study concluded that the elasticity of demand for prescription drugs is similar to the elasticity of demand for health care in

general.

Although there are numerous studies on the elasticity of demand for

prescription drugs, very few focus on the elderly population

(Grootendorst et al., 1997). This group should be of particular interest because they typically have higher medical care needs and costs

and their population is growing rapidly. A study undertaken in

Canada by Grootendorst et al. (1997) sought to fill this gap in the literature. They used data from the Ontario Health Survey to study the

effect of first-dollar prescription drug coverage on drug use by seniors. At age 65, individuals in Ontario become eligible for the Ontario Drug Benefit Plan. The study compared prescription drug use

before and after the statutory date of eligibility. The study found an

upward shift in prescription drug use by seniors at age 65 even after

controlling for health status and other demographic factors. In addition, the results suggest that the increase in prescription drug use is

driven by increases in drug volume among users rather than by increases in the probability of any use. Consistent with this result is

the finding that persons with poorer reported health status are more

likely to increase prescription drug use with first-dollar coverage.
Review of the Empirical Literature 37

Price Elasticity of Demand for Mental Health Services

Studying the demand for mental health care can be more complicated than studying demand for other specific types of medical care.

Mental health insurance benefits have historically been much more

limited than benefits for general medical care. Recent parity laws,

however, have changed the market for specialty mental health services by requiring equal coverage of mental health and general medical care. As the parity laws have only recently been implemented,

their effect on the use of mental health services is not yet fully understood. An additional aspect making the demand for mental

health care more difficult to measure is that people often feel a

stigma associated with mental health care. Because of this, people

may not file insurance claims for mental health treatment if their insurance is through their employer. Consequently, a larger portion of

mental health care may be self-paid and will not be reflected in the

claims databases that are often used to estimate the medical care

demand equations. In addition, the perceived stigma may also affect

self-reported use of mental health services in surveys.

Much of the evidence on the elasticity of demand for mental health

care comes from natural experiments. In these studies, the variation

in the price of services is generated by the introduction of or changes

in the level of copayments. In 1978 the Columbia Health Plan in

Maryland increased copayments from $2 to $10 per mental health

visit.6 Hankin et al. (1980) showed that the increase in price led to a

decrease in the number of mental health visits per 1,000 population

covered from 414.4 to 404.7. These results suggest an elasticity of

demand equal to –0.02 for outpatient mental health services. Hankin

et al. noted that although this elasticity estimate is quite low, over the

same time period the Columbia Health Plan increased access to

mental health services by increasing treatment staff. The decrease in

waiting periods and appointment delays likely had an offsetting effect on use and, thus, the price elasticity estimate is biased downward.

In 1978, the United Mine Workers of America entered into a new

agreement with their employers regarding health benefits provisions.

______________

6The increase in copayments from $2 to $10 in 1978 dollars is equal to an increase

from $8.72 to $43.58 in 2000 dollars.
38 The Elasticity of Demand for Health Care: A Review of the Literature

The new agreement required copayments for all physician visits.

This natural experiment was studied by Roddy et al. (1986). The introduction of $5 copayments was found to reduce the number of

mental health visits per 1,000 enrollees from 110.15 to 60.07.7 The

elasticity of demand for mental health services was found to be –0.32,

suggesting that a 1 percent increase in price leads to a 0.32 percent

decrease in the demand for outpatient mental health visits. This

finding indicates that the demand for mental health services is inelastic but is at least as large as the price elasticity of demand for

general medical care. In a related article, Wallen et al. (1986) studied

the differential effect of the copayments on the use of mental health

services between men and women. They found that men are more

sensitive than women to changes in the price of a mental health visit.

The elasticities are estimated to be –0.50 and –0.31, respectively.

In two related articles, Simon et al. (1994, 1996) studied the effect of

the institution of and subsequent increase in the required copayments for mental health services within an HMO. They found a reduction of 33 percent (56 percent) in the probability of any mental

health service use when $20 ($30) copayments were introduced.8

These findings produce elasticity of demand estimates ranging from

–0.17 to –0.28. These elasticities are based on the probability of any

use and are thus interpreted somewhat differently from the other estimates presented in this section. These elasticity estimates suggest

that a 1 percent increase in the price of mental health services will

lead to a 0.17 to 0.28 percent decrease in the rate of any mental

health service use among the enrollee population. Simon et al. found

very little effect from the introduction of the $20 copayment on the

visit rate among service users.

Studies based on observational data have found elasticities that are

quite a bit larger than those found in the studies based on natural

experiments. McGuire (1981) used data from the Joint Information

Service Survey of office-based psychiatrists in 1973. He concluded

that the elasticity of demand for psychotherapy is –1.0 or greater.

The study, however, is limited by the adequacy of the data. Because

______________

7The $5 copayment in 1978 dollars is equal to $21.79 in 2000 dollars.

8The $20 and $30 copayments in 1991 dollars are equal to $30.12 and $45.18, respectively, in 2000 dollars.
Review of the Empirical Literature 39

of the structure of the sample, only those in treatment were included

and heavy users of mental health services were overrepresented.

This estimate of the price elasticity found by McGuire is relatively

large, but it is not outside the range of other observational estimates.

Frank (1985) used state-level data from 1970 to 1978 and found elasticity estimates in the range of –1.0 to –2.0.

The RAND HIE also looked at the effect of copayments on mental

health service use. Wells et al. (1982) concluded that the demand for

ambulatory mental health care and ambulatory medical care exhibit

similar responses to variations in price generated by copayments.

THE ELASTICITY OF DEMAND FOR HEALTH INSURANCE

Apart from studies on the responsiveness of the demand for health

care to price and income, there is growing attention to the responsiveness of demand for different health plans to changes in the price

of insurance. This literature is of particular importance when considering the demand for health care services provided by a particular

health plan. Any change in the out-of-pocket costs of services or

premium costs will have an effect on the number of plan enrollees

and, thus, on the demand for health care services paid for by that

plan. In this section, we review studies of the effects of changes in

health insurance plans on the demand for health insurance. We focus on the choice between different health plans and do not discuss

studies on the decision whether to purchase any insurance at all.9

First, we present the main findings in the literature. Then, we discuss the studies in more detail (see Table 3.3).

Main Findings

According to Royalty and Solomon (1998), “there is no definitely

established range of price elasticities [of health plan choice] in the literature.” Econometric studies of health care plan choice vary dramatically, not only in their price elasticity estimates but also in the

data sources, econometric methods, and experimental design. For

______________

9For a recent study on the decision to purchase insurance, including a literature review, see Marquis and Long (1995).
Utopia R ✺❁❐❆

Table 3.3

Key Studies on the Elasticity of Demand for Health Insurance

Study Methodology Population Under Study Elasticity Definition Price ElasticityCutler andReber, 1996

Natural experiment 10,000 Harvard University employees Change in PPO enrollment resulting from a 1 percent increase in out-of-pocket premium –0.3 to –0.6

Marquis andPhelps, 1987

Experiment Families in RAND

Health InsuranceExperiment

Change in enrollment of full supplementaryinsurance resulting from a 1 percent increasein premium

–0.6

Short andTaylor, 1989

Observationalstudy

Nationallyrepresentative crosssection dataset fromNational Medical CareExpenditure Survey(NMCES), 1977

1) Change in probability of enrollment in “highoption” FFS relative to “low option” FFS from a1 percent increase in net premium2) Change in probability of enrollment in HMOrelative to FFS plan from 1 percent increase innet premium

–0.14–0.05

Royalty andSolomon,1998

Observationalstudy

Panel data of StanfordUniversity Emp.

Change in percentage enrolled resulting from a1 percent increase in premiums

–1.0 to –1.8 (logit)–3.7 to –6.2 (fixedeffects)

Barringerand Mitchell,1994

Observationalstudy

Payroll benefits fromsingle company inUnited States

Changes in the fraction of people choosing aplan relative to a 1 percent increase in the premium

–0.1 to –0.2

Hosek et al.,1995

Observationalstudy

Military personnel Change in probability of choosing the civilian

plan relative to a 1 percent increase inpremium

–0.6

Feldman, etal., 1989

Natural experiment 20 firms in Minneapolis Change in enrollment in a plan with 50 percent of the overall market due to a 1 percent increase in the premium –0.15 to –0.53

40 The Elasticity of Demand for Health Care: A Review of the Literature
Review of the Empirical Literature 41

example, the articles reviewed in this report use datasets of individual employees and their health plan choices in various professional

and demographic settings, such as a single university, 20 firms within

one city, a single company with four plants across the United States,

and a national cross-section, among others. Some of these are panel

datasets, and others are purely cross-sectional. Studies on the demand for health insurance tend to be either observational (among

others, Merrill, Jackson, and Reuter, 1985) or natural experiments

(among others, Cutler and Reber, 1996). However, as an offspring of

the RAND Health Insurance Experiment, one study examines the

demand for supplementary insurance based on a randomized experiment (Marquis and Phelps, 1987).

When estimating price elasticity, the possibility of adverse selection

needs to be considered if the health of plan enrollees is a concern.

However, if we are simply interested in the effects of price changes

on the market share for each plan, then the presence of adverse selection is not important. Adverse selection occurs when people with

relatively high expected expenditures on health care choose a relatively generous insurance plan. When these anticipations appear to

be accurate and actually realized, the more generous insurance plan

may have to increase premiums, resulting in further selection between people with different anticipated health expenditures. Adverse selection is likely to be manifested in differential enrollment

over a period of years. Therefore, the long-run response to a change

in (relative) premiums will be larger than the short-run response, as

we will see in the next subsection.

It is difficult to obtain health insurance price elasticity estimates

from cross-sectional plan choice studies, because there is typically

very little variation in premiums across plans and any observed

variation is correlated with quality of or access to care. Therefore, results from studies based solely on cross-sectional data should be interpreted carefully.

Studies on the Price Elasticity of Demand for Different Health

Plans

Cutler and Reber (1996) investigated enrollment decisions when the

relative prices of an HMO and a PPO health plan changed. Harvard
42 The Elasticity of Demand for Health Care: A Review of the Literature

University employees could choose between two plans: a low-cost

HMO plan that restricts choice of providers and provider income and

a high-cost PPO plan with fewer restrictions on choice and more

generous provider reimbursement. In 1995, Harvard University

moved from a system of subsidizing generous insurance to a system

of paying a fixed contribution independent of plan choice (some 80

percent). The price elasticity, defined as the percentage change in

PPO enrollment resulting from a 1 percent change in the out-ofpocket premium, was estimated to be –0.3 in the first year and –0.6

in the second year. The policy change also induced substantial adverse selection. As a result, the long-run demand response was three

times higher, and the market for more generous insurance appears to

have been eliminated entirely.

In a similar study, Buchmueller and Feldstein (1997) reported results

from a natural experiment where the University of California (UC)

system made changes to employee health insurance benefits that resulted in increased premiums for many employees. The study found

that consumers were quite sensitive to changes in out-of-pocket

premiums and were willing to switch health plans in response to

small premium changes. More specifically, they estimated that 26

percent of enrollees would switch to another plan when premiums

rose by $10 per month. As a comparison, only 5 percent of individuals whose premium remained constant switched to a different plan.

It is likely that the estimates from this study serve as an upper bound.

The UC system provided standardized benefits across the different

plans. As a result, the primary differences between plans were outof-pocket premiums and the list of approved providers. This factor

makes the comparison across plans relatively straightforward for

consumers. In less-controlled situations where the services covered

vary between plans, the consumer’s decision to change health plans

is more complex as the plans may not be close substitutes.

Royalty and Solomon (1998) used a panel dataset from the Stanford

University Benefits Office to estimate price elasticities for health insurance plan choices. The price variation that identified the elasticity estimates came from differences in premiums across plan

choices. The price elasticity calculations ranged from –1.0 to –1.8 in

their simple logit estimations and –3.7 to –6.2 in their fixed effects

model. Their goal was to investigate the extent of price responsiveness by employees in a managed competition market and how
Review of the Empirical Literature 43

“transition costs” depress this price elasticity. Such transition costs

include doctor-patient relationships and other characteristics that

are difficult to quantify. The authors found a “striking, although not

always statistically significant, difference in the estimated price elasticities by group that go in the direction predicted if there are greater

costs in switching health plans for those who are older, sicker, or who

have worked at Stanford longer.” Thus, younger and healthier employees were more price sensitive.

Feldman et al. (1989) determined the price elasticity of health plan

choice using data from a survey of employees in 20 Minneapolis

firms conducted in 1984. The firms employed 7.2 percent of the

Twin Cities workforce. The key findings were that (1) employees

were less likely to choose health plans with higher monthly out-ofpocket premiums, (2) employees prefered health plans that offered

preventive coverage, and (3) fee-for-service plans tended to be preferred over IPAs and HMOs (other things equal), but this effect diminished as the number of years the plan was offered increased.

One difficulty in interpreting the results of this study is that the estimated own-price elasticity depends on both the market share of the

health plan itself and the share of alternatives within the same nest.

According to Royalty and Solomon (1998), the Feldman et al. results

imply that a health plan with 50 percent of overall market has price

elasticities ranging from –0.53 to –0.15, depending on the share of the

plan within its nest. Plans with very small enrollments thus have

even larger elasticities, and very large plans have elasticities close to

zero. Royalty and Solomon have criticized the study for not including interactions of income with plan attributes, potentially biasing

price elasticities.

Short and Taylor (1989) use data from the 1977 National Medical

Care Expenditure Survey (NMCES) to estimate two elasticities—one

for the choice between two FFS plans and one for the choice between

a FFS and an HMO. The price elasticity of the probability of enrolling

in the “high option” FFS relative to the “low option” FFS based on

premium differences was –0.14. The price elasticity of enrolling in an

HMO relative to FFS was –0.05.

Barringer and Mitchell (1994) estimated the effect of changes in premiums and deductibles on employees’ preferences for four types of

health care plans. The data came from employee payroll benefit
44 The Elasticity of Demand for Health Care: A Review of the Literature

records from a single company with four plants across the United

States. The authors found that increasing the traditional FFS premium by 10 percent reduced the fraction choosing the plan by 4 to 9

percent. A 10 percent rise in the deductible of the traditional FFS led

to a change in market share of 0 to 1 percent. Doubling the traditional FFS deductible implied a market share decline of 3 to 4 percent. A 10 percent increase in salary corresponded to a 1 to 2 percent

increase in the traditional FFS. The price elasticities with respect to

changes in premium were in the range of –0.1 to –0.2.

In a study of the demand for health care in the military, Hosek et al.

(1995) examined the choice of enrollment in a civilian plan versus a

military health plan for active duty and retired families. The authors

calculated a price elasticity of demand for health plan choice of –0.6.

This finding indicates that a 1 percent increase in the premium level

for the civilian plan leads to a 0.6 percent decrease in the probability

of choosing this plan. The magnitude of this elasticity is quite similar

to other estimates from the literature that are based on the civilian

population.

The Income Elasticity of Demand for Different Health Plans

Family income likely has an effect on the choice between different

health plans. A study of the CHAMPUS Reform Initiative provides

some evidence of this effect and estimates of the income elasticity of

demand for health plan choice. Hosek et al. (1993) found that a 10

percent increase in household income decreased the probability that

a family would enroll in CHAMPUS Prime (the HMO choice) by 0.24

percentage points. Using the information provided in that report, we

calculate an income elasticity of demand for enrollment in CHAMPUS Prime as –0.27. This suggests that a 1 percent increase in income will reduce the probability of enrollment in the HMO option by

0.27 percent.

The Price Elasticity of Demand for Supplementary Insurance

As part of the RAND Health Insurance Experiment, Marquis and

Phelps (1987) estimated the demand elasticity for supplementary insurance. Each family was presented a hypothetical offer to supplement its insurance coverage by reducing the amount of its annual
Review of the Empirical Literature 45

maximum dollar expenditure (MDE), beyond which the plan paid

100 percent. There were three options: a one-third reduction in the

MDE, a two-thirds reduction, or full coverage. The authors estimated the probability that a family would express interest in the insurance product.

The “loading fee,” which is equal to the expected payout from the insurance plan (defined as the difference between the price and the

benefits) divided by the benefits,10 was used as a measure of the

price of supplementary insurance. The expected payout was based

on expected expenditures on health care and the amount of coverage. Generally speaking, when the loading fee (i.e., the price measure) is low, it is attractive to buy insurance. The results showed that

an increase in the loading fee decreases the interest in all offered

supplementary insurance options and that demand for supplementation could be sufficiently large to diminish responses to copayment

changes. Clearly, if people supplement away any copayments, the

use-reducing effects of cost-sharing may be affected negatively. The

estimate of the price elasticity of the demand for full supplementary

insurance is –0.6.

______________

10Thus: loading fee = (price–benefits)/benefits
47

Chapter Four

CONSIDERING THE POTENTIAL EFFECTS OF

CURRENT AND PROPOSED CHANGES IN

TRICARE BENEFITS

The FY 2001 National Defense Authorization Act was signed into law

by President Clinton on October 30, 2000. Although the act contains

numerous changes, four new TRICARE initiatives will have important

effects on uniformed services retirees and their spouses.

• Expanding pharmacy benefits for seniors to include access to

MTF pharmacies, the National Mail Order Pharmacy Program

(NMOP), and retail pharmacies,

• Making TRICARE a second payer to Medicare (TRICARE for Life),

• Eliminating coinsurance payments under TRICARE Prime for

dependents of active duty personnel, and

• Expanding TRICARE Prime Remote benefits to active duty family

members and nonuniformed service members.

In this final chapter, we briefly describe how the demand literature

applies to these changes.

EXPANSION OF PHARMACY BENEFITS

The expansion of pharmacy benefits for Medicare-eligible MHS

beneficiaries will likely lead to increases in the demand for prescription drugs provided through the TRICARE program. The new prescription coverage requires no enrollment fee, but participants will

be required to make modest copayments for the prescriptions they
48 The Elasticity of Demand for Health Care: A Review of the Literature 

receive. If individuals choose to obtain prescriptions outside the

network, they will be required to pay a deductible and somewhat

higher copayments per prescription.

Previously, some Medicare-eligible beneficiaries obtained prescriptions at MTF pharmacies and others paid for prescriptions themselves or through other insurance. Demand for prescriptions provided through TRICARE will increase because Medicare-eligible

beneficiaries who previously paid themselves will now finance their

prescriptions through TRICARE and some who used other insurance

will switch to TRICARE.1 For example, the CBO (2000) estimates that

approximately 360,000 additional people will use the NMOP benefit.

Many of these seniors will be able to fill their prescriptions at lower

out-of-pocket prices and so they will purchase greater numbers of

prescriptions. The results from the civilian literature suggest that the

price elasticity of demand for prescription drugs is in the range of

–0.3. This means that when the price of prescriptions falls by 1 percent the demand for prescriptions will increase by 0.3 percent. This

increase in demand will occur in part because consumers will substitute away from using over-the-counter drugs that are now relatively

more expensive toward prescription drugs. The results from the literature indicate that with a 1 percent reduction in the price of prescription drugs, the demand for over-the-counter drugs will fall by

0.17 percent.

TRICARE FOR LIFE

The second major change to the MHS makes TRICARE the second

payer to Medicare. Under the new law, enrollment in Medicare Part

B is required for participation in the second payer plan, unless the

individual was Medicare eligible before April 1, 2001. Having TRICARE as a second payer will substitute for the Medigap insurance

that most senior military beneficiaries have and will eliminate most

of their out-of-pocket health care costs. This reduction in the effective price can be expected to lead to greater demand for health care

services. TRICARE will pay most of the costs not paid by Medicare at

prior demand levels, replacing Medigap and self-financing. It will

______________

1Some beneficiaries may switch from MTF pharmacies to civilian pharmacies, but the

change in demand from this group should be small.
Considering the Potential Effects of Current and Proposed Changes in TRICARE 49

also finance a share of any demand increase resulting from lower

patient cost-sharing.

Although most of the economic studies that we have summarized focus on the nonelderly adult population, there is evidence to suggest

that seniors do respond to price decreases with increases in use. As

evidence, numerous studies have shown that, among Medicare

recipients, use of health care services is higher for those who have

Medigap supplemental insurance (for examples, see Link et al., 1980;

Christensen et al., 1987; McCall et al., 1991; Cartwright et al., 1992).

These studies are particularly relevant because, as we indicated

above, the new law makes TRICARE a substitute for other Medigap

policies. Unfortunately, none of these studies provide priceelasticity estimates. Therefore, we cannot directly compare the level

of price sensitivity between the elderly and nonelderly adult populations. However, we expect that the estimates from the literature may

serve as a lower bound for the elasticity of demand for health care

and health insurance among the elderly. Senior citizens are typically

expected to have more elastic demands for goods and services. This

is due in part to the fact that health expenditures make up a larger

portion of the total budget for senior citizens than for other adults.

ELIMINATION OF COPAYMENTS IN TRICARE PRIME

In the case of TRICARE Prime, the elimination of copayments for

civilian care provided to active duty dependents is likely to have two

effects on the demand for MHS-paid medical services. First, the economic literature predicts that reductions in copayments will increase

the number of current enrollees who access any care, particularly

among those who rely on civilian providers. The literature also indicates, however, that the price elasticity of demand for health care is

relatively low at low levels of cost-sharing (see Newhouse et al.,

1993). The current copayments for active duty dependents are relatively low, ranging from $6 to $12 per visit. Therefore, the effect on

use of eliminating these copayments may be relatively small.

Further, TRICARE Prime enrollees will now face the same price for

services obtained through civilian doctors or through MTFs. To the

extent that some people had previously chosen to use MTF services

because of the lower cost, the elimination of copayments for civilian

care could lead to some substitution from MTF care to civilian care.
50 The Elasticity of Demand for Health Care: A Review of the Literature 

Although this may not lead to an increase in the number of total

physician visits among current enrollees, the shift from one type of

provider to another could have cost implications for the MHS.

The second effect of the elimination of copayments in TRICARE

Prime is that some beneficiaries may choose to switch between TRICARE plans. The lower out-of-pocket costs for civilian care may

make the Prime option more attractive to families that had previously chosen the Extra or Standard TRICARE options.2 The literature

on the elasticity of health care plan choice suggests that some

switching between plans does occur in response to changes in plan

characteristics. The magnitude of such effects, however, has not

been well established.

TRICARE PRIME REMOTE

The expansion of the TRICARE Prime Remote benefits to dependents

of active duty personnel and uniformed service personnel (i.e., personnel from the Public Health Service, the Coast Guard, and the National Oceanic and Atmospheric Administration) will likely increase

the demand for health care services paid through the TRICARE program. Most of the affected beneficiaries must now use TRICARE

Standard, which imposes significant copayments. The reduction in

out-of-pocket costs may increase the demand for care, especially if

Prime cost-control mechanisms are less effective for this dispersed

population than they are for more concentrated populations.

______________

2Families eligible for health insurance through the spouse’s employer would be expected to find TRICARE relatively more attractive. However, this effect will be negligible as very few active duty families now use other insurance.
51

BIBLIOGRAPHY

Barringer, M. W., and O. S. Mitchell (1994), “Worker’s preferences

among company-provided health insurance plans,” Industrial and

Labor Relations Review 48(1):141–152.

Beck, R. G. (1974), “The effects of copayment on the poor,” Journal of

Human Resources 9:129–142.

Buchmueller, T. C., and P. J. Feldstein (1997), “The effect of price on

switching among health plans,” Journal of Health Economics

16(2):231–247.

Cartwright, W. S., T.-W. Hu, and L.-F. Huang (1992), “Impact of

varying Medigap insurance coverage on the use of medical services of the elderly,” Applied Economics 24:529–539.

Cherkin, D. C., L. Grothaus, and E. H. Wagner (1989), “The effect of

office visit copayments on preventive care services in an HMO,”

Inquiry 27(1):24–38.

Cherkin, D. C., L. Grothaus, and E. H. Wagner (1990), “The effect of

office visit copayments on utilization in a health maintenance organization,” Medical Care 27(11):1036–1045.

Christensen, S., S. H. Long, and J. Rodgers (1987), “Acute health care

costs for the aged Medicare population: Overview and policy options,” Milbank Quarterly 65(3):397–425.

Congressional Budget Office (CBO) (1988), Reforming the Military

Health Care System, Washington, D.C.
52 The Elasticity of Demand for Health Care: A Review of the Literature

Congressional Budget Office (May 1, 2000), Congressional Budget

Office Cost Estimate; S.2087 Military Health Care Improvements

Act of 2000, as introduced February 23, 2000, available at

http://www.cbo.gov/showdoc.cfm?index=2011&sequence=0&fro

m=6.

Cook, T. D., and D. T. Campbell (1979), Quasi-Experimentation: Design and Analysis Issues for Field Settings, Rand McNally College

Publishing Company, Chicago, Illinois.

Cutler, D. M., and S. Reber (1996), “Paying for health insurance: The

tradeoff between competition and adverse selection,” Working

Paper, No. 5796, National Bureau of Economic Research, New

York.

Cutler, D. M., and R. J. Zeckhauser (1999), “The anatomy of health insurance,” Working Paper, No. 7176, National Bureau of Economic

Research, New York.

DiMatteo, L., and R. DiMatteo (1998), “Evidence on the determinants

of Canadian provincial government health expenditures: 1965–

1991,” Journal of Health Economics 17:211–228.

Eichner, M. J. (1998), “The demand for medical care: What people

pay does matter,” American Economic Review 88(2):117–121, May.

Feldman, R., et al. (1989), “The demand for employment-based

health insurance plans,” Journal of Human Resources 24(1):115–

142.

Feldstein, M. S. (1971), “Hospital cost inflation: A study of nonprofit

price dynamics,” American Economic Review 60:853–872.

Feldstein, M. S. (1973), “The welfare loss of excessive health insurance,” Journal of Political Economy 81(1):251–280.

Frank, R. G. (1985), “Pricing and location of physician services in

mental health,” Economic Inquiry 23:115–133.

Fuchs, V. R., and M. J. Kramer (1972), Determinants of expenditures

for physicians’ services in the United States, 1948–1968, Occasional

Paper No. 117, National Bureau of Economic Research, New York.
Bibliography 53

General Accounting Office (GAO) (2000), “Observations on proposed

benefit expansion and overcoming TRICARE obstacles,” Statement of Stephen P. Backhus, Director, Veterans’ Affairs and

Military Health Care Issues GAO/T-HEHS/NSIAD-00-129.

Getzen, T. E. (2000), “Health care is an individual necessity and a national luxury: Applying multilevel decision models to the analysis

of health care expenditures,” Journal of Health Economics 19:259–

270.

Goldman, D. P. (1995), “Managed care as a public cost-containment

mechanism,” RAND Journal of Economics 26(2):277–295.

Goldman, D. P., et al. (1995), “The effects of benefit design and managed care on health care costs,” Journal of Health Economics 14:

401–418.

Grootendorst, P. V., et al. (1997), “On becoming 65 in Ontario: Effects

of drug plan eligibility on use of prescription medicines,” Medical

Care 35(4):386–398.

Grossman, M. (1972), “On the concept of health capital and demand

for health,” Journal of Political Economy 80(2):223–255.

Hankin, J. R., D. M. Steinwachs, and E. Charmain (1980), “The impact

of a copayment increase for ambulatory psychiatric care,” Medical

Care 18(8):807–815.

Harris, B. L., A. Stergachis, and L. D. Ried (1990), “The effect of drug

copayments on utilization and cost of pharmaceuticals in a health

maintenance organization,” Medical Care 28(10):907–917.

Holmer, M. (1984), “Tax policy and the demand for health insurance,” Journal of Health Economics 3:203–221.

Hosek, S. D., et al. (1993), Evaluation of the CHAMPUS Reform

Initiative: Volume 3, Health Care Utilization and Costs, RAND

R-4244/3-HA, Santa Monica, California.

Hosek, S. D., B. W. Bennet, et al. (1995), The Demand for Military

Health Care: Supporting Research for a Comprehensive Study of

the Military Health-Care System, RAND MR-407-1-OSD, Santa

Monica, California.
54 The Elasticity of Demand for Health Care: A Review of the Literature

Hughes, D., and A. McGuire (1995), “Patient charges and the utilization of NHS prescription medicines,” Health Economics 4(3):213–

220.

Janssen, R. (1992), “Time prices and the demand for GP services,”

Social Sciences and Medicine 34(7):725–733.

Keeler, E. B., and J. E. Rolph (1983), “How cost sharing reduced medical spending of participants in the health insurance experiment,”

Journal of the American Medical Association 249(16):2220–2227.

Keeler, E. B., and J. E. Rolph (1988), “The demand for episodes of

treatment in the health insurance experiment,” Journal of Health

Economics 7(4):337–367.

Keeler, E. B., J. L. Buchanan, J. E. Rolph, et al. (1988), The Demand for

Episodes of Treatment in the Health Insurance Experiment, RAND

R-3454-HHS, Santa Monica, California.

Lavers, R. (1989), “Prescription charges, the demand for prescriptions and morbidity,” Applied Economics 21:1043–1052.

Leibowitz, A., W. G. Manning, et al. (1985), “The effect of cost sharing

on the use of medical services of children: Interim results from a

randomized controlled trial,” Pediatrics 75(5):942–951.

Levy, R. A., R. Miller, and P. Branman (2000), The DOD Health Care

Benefit: How Does It Compare to FEHBP and Other Plans? Center

for Naval Analyses, Research Memorandum D0001316.A1,

Washington, D.C., May.

Link, C. R., S. H. Long, and R. F. Settle (1980), “Cost sharing, supplementary insurance, and health services utilization among the

Medicare elderly,” Health Care Financing Review 2(2):25–31.

Lohr, K. N., R. H. Brook, C. J. Kamberg, et al. (1986), “Effect of cost

sharing on use of medically effective and less effective care,” Medical Care 24(9 Suppl):S31–S38.

Manning, W. G., J. P. Newhouse, N. Duan, et al. (1987), “Health insurance and the demand for medical care: Evidence from a randomized experiment,” American Economic Review 77(3):251–277.
Bibliography 55

Manning, W. G., J. P. Newhouse, N. Duan, et al. (1988), Health insurance and the demand for medical care: Evidence from a randomized experiment, RAND R-3476-HHS, Santa Monica, California.

Marquis, M. S., and S. H. Long (1995), “Worker demand for health insurance in the non-group market,” Journal of Health Economics

14:47–63.

Marquis, M. S., and C. E. Phelps (1987), “Price elasticity and adverse

selection in the demand for supplementary health insurance,”

Economic Inquiry 25(2):299–313.

McCall, N., T. Rice, J. Boismier, et al. (1991), “Private health

insurance and medical care utilization: Evidence from the

Medicare population,” Inquiry 28(3):276–287.

McGuire, T. (1981), Financing Psychotherapy: Costs, Effects, and

Public Policy, Ballinger Publishing Company, Cambridge, Masschusetts.

McLaughlin, C. (1987), “HMO growth and hospital expenses and use:

a simultaneous-equations approach,” Health Services Research

22(2):183–202.

Merrill, J., C. Jackson, and J. Reuter (1985), “Factors that affect the

HMO enrollment: A tale of two cities,” Inquiry 22:388–395.

Newhouse, J. P., and C. E. Phelps (1974), “Price and income elasticities for medical care services,” in M. Perlman, ed., The Economics

of Health and Medical Care, Macmillan, London.

Newhouse, J. P., and C. E. Phelps (1976), “New estimates of price and

income elasticities,” in R. Rosett, ed., The Role of Health Insurance

in the Health Services Sector, National Bureau of Economic Research, New York.

Newhouse, J. P., and the Insurance Experiment Group (1993), Free

For All? Lessons from the Health Insurance Experiment, Harvard

University Press, Cambridge.

O’Brien, B. (1989), “The effect of patient charges on the utilization of

prescription medicines,” Journal of Health Economics 8(1):109–

132.
56 The Elasticity of Demand for Health Care: A Review of the Literature

Phelps, C. E. (1992), Health Economics, HarperCollins, New York.

Phelps, C. E., and J. P. Newhouse (1974), “Coinsurance, the price of

time, and the demand for medical care services,” Review of Economics and Statistics 56:334–342.

Phelps, C. E., S. Hosek, J. Buchanan, et al. (1984), Health Care in the

Military: Feasibility and Desirability of a Closed Enrollment System, RAND R-3145-HA, Santa Monica, California.

Rice, T., and K. R. Morrison (1994), “Patient cost sharing for medical

services: A review of the literature and the implications for health

care reform,” Medical Care Review 51(3):235–287.

Roddy, P. C., J. Wallen, and S. M. Meyers (1986), “Cost sharing and

use of health services. The United Mine Workers of America

health plan,” Medical Care 24(9):873–876, September.

Rosett, R. N., and L. F. Huang (1973), “The effect of health insurance

on the demand for medical care,” Journal of Political Economy

81:281–305.

Royalty, A. B., and N. Solomon (1998), “Health plan choice: Price

elasticities in a managed competition setting,” Journal of Human

Resources 34(1):1–41.

Scitovsky, A. A., and N. M. McCall (1977), “Coinsurance and the demand for physician services: Four years later,” Social Security

Bulletin 40:19–27.

Scitovsky, A. A., and N. M. Snyder (1972), “Effect of coinsurance on

use of physician services,” Social Security Bulletin 35(6):3–19.

Short, P. F., and A. K. Taylor (1989), “Premiums, benefits, and employee choice of health insurance options,” Journal of Health Economics 8:293–311.

Simon, G. E., L. Grothaus, M. L. Durham, et al. (1996), “Impact of visit

copayments on outpatient mental health utilization by members

of a health maintenance organization,” American Journal of Psychiatry 153(3):331–338.
Bibliography 57

Simon, G. E., M. VonKorff, and M. L. Durham (1994), “Predictors of

outpatient mental health utilization in a health maintenance organization,” American Journal of Psychiatry 151:908–913.

Smith, Dean (1993), “The effects of copayments and generic substitution on the use and costs of prescription drugs,” Inquiry 30:189–

198.

Taylor, A. K., and G. R. Wilensky (1983), “The effect of tax policies on

expenditures for private health insurance,” in J. Meyer, ed., Market

Reforms in Health Care, American Enterprise Institute, Washington, D.C.

Wallen, J., P. Roddy, and S. Meyers (1986), “Male-female differences

in mental health visits under cost-sharing,” Health Services Research 21(2):341–350.

Wedig, G. J. (1988), “Health status and the demand for health,” Journal of Health Economics 7:151–163.

Weiner, J. (1993), “The demand for physician services in a changing

health care system: A synthesis,” Medical Care Review 50(4):411–

449.

Wells, K. B., E. Keeler, and W. G. Manning (1982), “Patterns of outpatient mental health care over time: Some implications for estimates of demand for benefit design,” Health Services Research

24(6):773–789.

Zweifel, P., and W. G. Manning (2000), “Moral hazard and consumer

incentives in health care,” in A. J. Culyer and J. P. Newhouse, eds.,

Handbook of Health Economics, Elsevier, New York.