The Implications of Cost-Effectiveness

Analysis of Medical Technology:

Methodological Issues and Literature

Review

September 1980

NTIS order #PB81-144602
Library of Congress Catalog Card Number 80-600160

For sale by the Superintendent of Documents, U.S. Government Printing Office

Washington, D.C. 20402

f i
Foreword

This volume is a background paper for OTA’S assessment, The Implications of

Cost-Effectiveness Analysis of Medical Technology. That assessment analyzes the

feasibility, implications, and usefulness of applying cost-effectiveness and cost-benefit

analysis (CEA/CBA) in health care decisionmaking. The major, policy-oriented report

of the assessment was published in August 1980. In addition to the main report, there

will be five background papers: 1) the present document which addresses methodological issues and reviews the CEA/CBA literature, 2) a psychotherapy case study, 3) a

diagnostic X-ray case study, 4) 17 other case studies of individual medical technologies, and 5) a review of international experience in managing medical technology.

Another related report was published in September of 1979: A Review of Selected Federal Vaccine and Immunization Policies.

Background Paper #l: Methodological Issues and Literature Review, parts of

which are based substantially on work done for OTA by Dr. Kenneth Warner of the

University of Michigan, was prepared by OTA staff. In preparing this paper, OTA

consulted with members of the advisory panel to the overall assessment; with the authors of the case studies prepared for the assessment; and with numerous other experts

in economics, medicine, ethics, and health policy.

Drafts of this paper were reviewed by the advisory panel chaired by Dr. John Hogness, by the Health Program Advisory Committee chaired by Dr. Frederick Robbins,

and by approximately 75 other individuals and groups representing a wide range of

disciplines and perspectives. We are grateful for their assistance.

&“+e

JOHN H. GIBBONS

Director

iii
Advisory Panel on The Implications of

Cost-Effectiveness Analysis of Medical Technology

John R. Hogness, Panel Chairman

President, Association of Academic Health Centers

Stuart H. Altman

Dean

Florence Heller School

Brandeis University

James L. Bennington

Chairman

Department of Anatomic Pathology and

Clinical Laboratories

Children’s Hospital of San Francisco

John D. Chase

Associate Dean for Clinical Affairs

University of Washington School of Medicine

Joseph Fletcher

Visiting Scholar

Medical Ethics

School of Medicine

University of Virginia

Clark C. Havighurst

Professor of Law

School of Law

Duke University

Sheldon Leonard

Manager

Regulatory Affairs

General Electric Co.

Barbara J. McNeil

Department of Radiology

Peter Bent Brigham Hospital

Robert H. Moser

Executive Vice President

American College of Physicians

Frederick Mosteller

Chairman

Department of Biostatistics

Harvard University

Robert M. Sigmond

Advisor on Hospital Affairs

Blue Cross and Blue Shield Associations

Jane Sisk Willems

VA Scholar

Veterans Administration
OTA Staff for Background Paper #1

Joyce C. Lashof, Assistant Director, OTA

Health and Life Sciences Division

H. David Banta, Health Program Manager

Clyde J. Behney, Project Director, Implications of Cost-Effectiveness

Analysis of Medical Technology

Bryan R. Luce, Senior Analyst

Chester Strobel, Research Associate

Virginia Cwalina, Research Assistant

Kerry Britten Kemp, Editor

Shirley Ann Gayheart, Secretary

Nancy L. Kenney, Secretary

Principal Contractors

Kenneth E. Warner, School of Public Health

University of Michigan

Rebecca C. Hutton, Foundation for Medical Care Evaluation

of Southeastern Wisconsin

OTA Publishing Staff

John C. Holmes, Publishing Officer

Kathie S. Boss Debra M. Datcher Joanne Mattingly
Contents

Chapter Page

l. Introduction and Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2. Methodological Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

3. Literature Review... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

4. Methodological Findings and Principles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

APPENDIXES

A. Analysis of the Growth and Composition of

the Health CareCEA/CBA Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

B. Bibliography on CEA/CBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

C. Abstracts of Selected Entries From the Bibliography onCEA/CBA. . .......101

D. Description of Other Volumes of the Assessment . . . . . . . ...............120

E. Health Program Advisory Committee, Authors of Case Studies. . .........122

OTHER REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ........127
1 .

Introduction and Background

,

,’
. . — — — —— ——

Contents

Definitions of CEA and CBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

History of CEA/CBA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Health Care and CEA/CBA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Growth and Composition of the Health Care CEA/CBA Literature

Decision Techniques Related to CEA/CBA. . . . . . . . . . . . . . . . . . .

Organization of the Report. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

TABLE

Table No.

. . . . . . . . . . .

● ✎✎✎✎☛✎☛☛✎ ✎

✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎

✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎

✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎

✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎ ✎

Page

. 3

. 5

. 6

. 7

. 13

. 14

1. Numbers of Health Care CEA/CBAs by Medical Function and Year . . . . . . . .

LIST OF FIGURES

Figure No.

1. Diffusion of Health Care CEA/CBAs by Year . . . . . . . . . . . . . . . . . . . . . . . . .

2. Diffusion of Health Care CEA/CBAs in Medical and Nonmedical Health Care

Journals by Year. . . . . . . . . . . . . . . . . . .....,.,..........*...,. *

. 11

Page

. 9

. 10
1

Introduction and Background

With the desires to control costs, enhance

quality, and improve access to health care has

come the need to identify, and to understand

what is meant by, cost-effective medical care.

Two closely related evaluative techniques—

cost-effectiveness analysis and cost-benefit analysis (CEA and CBA, respectively)—are being

used or advocated with increasing frequency to

address this need. As measured by contributions

to the literature, professional interest in these

techniques and in their findings grew exponentially through the past decade. A reading of this

literature, combined with discussions with numerous individuals and groups, indicates considerable excitement, widespread confusion,

and a growing caution about the methods, implications, and usefulness of CEA and CBA in

health care.

As a result of these cost-related concerns and

the growth of interest in CEA and CBA, OTA

was asked by the Senate Committees on Labor

and Human Resources and on Finance to examine the feasibility, usefulness, and implications

of using cost-effectiveness information in decisions relating to medical technologies. The reDEFINITIONS OF CEA AND CBA

The terms cost-effectiveness and cost-benefit

analysis refer to formal analytical techniques for

comparing the negative and positive consequences of alternative projects. Each of us engages in CEA/CBA-like thinking every day, frequently subconsciously. “And ultimately, something like (CEA/CBA) must necessarily be employed in any rational decision” (729).

In this report, the term CEA/CBA is used to

refer to the class of techniques that includes both

CEA and CBA. In practice, the comparison of

costs and benefits is accomplished through a

spectrum of approaches, ranging from sophisticated computer-based mathematical programing using large amounts of epidemiological and

suiting assessment, which includes this background paper on methodology, examines cost

effectiveness by asking three major questions:

●

●

●

What is the technical, or methodological

validity of CEA and CBA when used to as- .

sess certain types of medical technologies

within certain settings?

What are the implications of using CEA or

CBA? That is, what are the value and ethical, legal, political, medical, health, and

economic implications?

Can CEA and CBA be used appropriately

in health care areas such as reimbursement,

health planning, individual physician decisionmaking, or prepaid group practice?

The present background paper focuses on aspects of the first question. All three questions

are examined in the main report of the assessment. (That main report and the four other

background papers are described briefly in app.

D.) This volume critically examines the methods

of cost-benefit and cost-effectiveness analysis

and reviews the literature on CEA and CBA in

health care.

other data to partially intuitive, best-guess estimates of costs and benefits. Some analyses may

take into account the results of clinical trials of a

technology and model the technology’s effect on

health outcomes. Others may assume that the

alternative technologies under study have equal

effectiveness and concentrate on the difference

in costs involved.

Thus, there is a continuum of analyses that

examine costs and benefits. One end of the continuum comprises what will be referred to as

“net cost” studies. In net cost studies the emphasis is on costs, and such studies in the past

have often assumed benefits or efficacy to be

equal. At the other end of the continuum are

3
analyses that attempt to relate the use of technologies under study to specific health-related

outcomes and to compare the costs of the technologies to the differential health benefits.

Thus, CEA/CBA includes a set of analytical

techniques, differentiated by the specific costs

and benefits that are considered and the manner

in which they are analyzed.

Both CEA and CBA require analysts to identify, measure, and compare all of the relevant

costs and consequences of alternative means of

addressing a given problem. The objective of

CEA/CBA is to structure and analyze information in a manner that will inform and thereby

assist policy makers. It is these individuals, and

not analysts, who will decide which, if any, of

the competing program or technological alternatives will be proposed or implemented.

The principal technical distinction between

CEA and CBA lies in the valuation of the desirable consequences of programs. In CBA, all

such consequences—benefits—are valued, like

costs, in numerical terms, almost always dollars. Conceptually, therefore, CBA permits an

assessment of the inherent worth of a program

—Do the benefits exceed the costs?—as well as

comparison of competing program alternatives

—Which of several programs generates the

largest excess of benefits over costs? With all

costs and benefits measured in the same (monetary) unit, CBA is designed to allow comparisons of similar or of widely divergent types of

programs. Thus, in theory at least, CBA might

be used to decide whether certain public resources should be allocated to construction of a

dam or to construction of a hospital.

In CEA, certain basic desirable consequences

are not valued in monetary terms, but rather are

measured in some other unit. In health care

CEAS, common measures include years of life

saved and days of morbidity or disability

avoided. The reason for a nonmonetary measure of program effectiveness is either the impossibility or undesirability of valuing important outcomes in dollars and cents. Unlike the

bottom line of a CBA, a CEA is not a net monetary value; rather, it is expressed in units such as

“dollars per year of life saved. ” CEA permits

comparison of cost per unit of effectiveness

among competing program alternatives designed to serve the same basic purpose. Unlike

CBA, however, the technique does not allow

comparison of programs having widely different objectives—because the effectiveness or

outcome measures differ—nor does it permit

assessment of the inherent worth of a program.

Is a cost of $50,000 per year of life saved acceptable? Obviously, this last question requires a

social and political judgment; it is not a technical matter.

Choice of CEA or CBA will depend on technical considerations, the predisposition of analysts and their clients, and on the type of question being addressed. Neither technique is necessarily superior to the other. CBA may be the

theoretical ideal, since it permits direct comparison of the desirable and undesirable consequences of diverse programs, but problems of

benefit valuation are myriad, particularly in

social welfare areas such as health care. CEA

avoids the methodologically difficult and morally ambiguous task of assigning monetary values to such nonmonetary measures as years of

human life. By rejecting the monetary measure

of CBA, however, the CEA analyst loses a unifying metric with which to weigh and compare

different types of effectiveness. HOW are two

programs to be compared when one program

averts many deaths but has limited effect on disability, and the other prevents considerable disability but averts only a few deaths? Methodological advances (such as measures of qualityadjusted life years) may in time ameliorate this

inadequacy, but considerable barriers to using

CEA to evaluate programs with significantl y

different effects still remain.

Both CEA and CBA can be used for purposes

of planning for the future or evaluating past

program performance. As planning tools, the

techniques involve prospective analysis, i.e., an

attempt to predict the costs and benefits (or effectiveness) of alternative future programs.

Analysis may draw on past or existing programs

for data and ideas as to how to model the structure of the future programs, but the focus remains distinctly prospective. In addition, as

evaluation tools, CEA and CBA involve retrospective assessment of the realized costs and
benefits (or effectiveness) of existing or past programs. Frequently, a retrospective evaluation

will have a prospective or planning intent: The

question is asked, should a program be continued into the future and, if so, how should it

be modified?

Finally, in this brief introduction to CEA/

CBA, it is useful to distinguish these techniques

from others that are frequently confused with

them. The two “sides” of a CEA or CBA—assessment of a program’s costs and desirable

consequences—are important forms of analysis

in their own right. The latter—assessment of

effectiveness—is traditionally the focal point of

evaluation in health care. A wide variety of

evaluative approaches, including randomized

clinical trials and epidemiological studies, form

the basis of assessment of the efficacy or effectiveness of numerous medical and public health

practices (405). Similarly, though less commonHISTORY OF CEA/CBA

The common-sense principles of CEA/CBA

have been promoted for centuries. Formal application of CEA/CBA, however, is a phenomenon of the present century. In 1902, the River

and Harbor Act directed the Corps of Engineers

to assess the costs and benefits of river and harbor projects. In 1936, the Federal Flood Control

Act required that “the benefits (of projects) to

whomsoever they may accrue must be in excess

of the estimated costs, ” though the Act provided

no guidance as to how benefits and costs were to

be defined and measured. In the same decade,

both the Tennessee Valley Authority and the

Department of Agriculture implemented program budgeting systems which included rudimentary attempts at formal CEA/CBA. Official

Government criteria for appraisal of river development projects were first enunciated by the Bureau of the Budget in 1952 (753).

Early in the Kennedy administration, the Defense Department, under Secretary McNamara,

adopted a program budgeting system which employed CEA/CBA to evaluate alternative defense projects. Success in these endeavors, comly, the costs of certain programs or technologies

are assessed in a cost analysis which treats effectiveness only implicitly or tangentially. Finally,

risk-benefit analyses compare the desirable outcomes of a practice with the undesirable but

noneconomic ones. Thus, in risk-benefit analysis, the ability of a surgical procedure to alleviate pain or prolong life might be compared with

its operative mortality and postoperative morbidity. Ideally, CEA/CBA represents a merging

of all of the concerns addressed by these evaluative techniques. Further, the validity of any

CEA or CBA is directly dependent on the validity of the efficacy information on which it is

based.

The relative advantages and disadvantages of

CEA and CBA, as well as the technical problems

of both and the implications of their differences,

are examined in detail later in this report.

bined with a burgeoning Federal budget, led

President Johnson in 1965 to require the implementation of planning-programing-budgeting (PPB) systems throughout the Federal bureaucracy. CEA/CBA represented both the

spirit and the letter of the new initiative to rationalize Government resource allocation decisionmaking (475).

PPB met with mixed and limited success, reflecting a lack of resources to implement it effectively, political and bureaucratic opposition to

it, and unrealistic expectations of its role and

potential (729). The formal system did not survive for long, though many Washington observers believe it left a legacy of continuing improvement in the use of rational analysis in

Government decisionmaking (748). And recently, the philosophy and logic of CEA/CBA and

PPB have been reincarnated in the form of zero

based budgeting.

As formaI evaluative techniques, CEA/CBA

assess public sector resource allocation decisions

where conventional private sector techniques,
such as capital budgeting and return-on-investment analysis, will not suffice. Commonly, the

inadequacy of conventional private sector techniques reflects the absence of a smoothly functioning market to allocate resources as desired,

resulting from either technical problems or distributional considerations. The former motivated the early applications of CEA/CBA. An

example is the provision of national defense,

which does not occur in the private sector because national defense is what is known as a

pure public good, defined as a good which,

when provided for one individual, benefits all

individuals, since no one can be excluded from

receiving the benefits and since one person’s

consumption of benefits does not reduce their

availability for other people. It is impossible to

“sell” national defense in a private marketplace,

because consumers are aware that they will receive it free if it is provided for anyone else, and

if they were to buy it themselves, they would be

providing it free to everyone else. Therefore, national defense will exist only if it is supplied by

the public sector.

‘Other sources of technical market failure are closely related to

the “pure public good” problem. These include significant economies of scale —i. e., decreasing average costs as the size of a project

increases (e. g., a dam) —and externalities—loosely, costs or benefits experienced by other than the immediate decisionmaker (e.g.,

pollution of a downstream community’s water supply by a firm

dumping waste material upstream ). This report will not elaborate

on these sources of market failure, but merely emphasize that they

require nonmarket decisionmaking and hence provide candidates

for CEA/CBA (753).

HEALTH CARE AND CEA/CBA

In the period of a decade, society’s principal

health system goal has shifted from increasing

access to health care to controlling the rapidly

inflating costs of care. The dilemma today is in

containing costs without sacrificing desired benefits such as improved access to health care and

quality. Thus, a logical approach would seem to

be to identify and reduce the use of tests, procedures, and visits which are medically ineffective, unnecessary, or excessively expensive relative to their limited effectiveness. Increasing

numbers of procedures and medical devices are

being cited as candidates for attention as skeptiIt is no accident that the origins of CEA/CBA

lie in the area of water resource management

and that the Department of Defense was PPB’s

showcase in the 1960’s. Dams, irrigation projects, and the like have significant characteristics

of public goods, yet market analogs permit the

valuation of most of the projects’ most significant costs and benefits. For example, a dam may

produce electricity, which has a direct market

value, and provide flood control and irrigation,

where property values, insurance policies, and

crop prices and yields serve to value benefits or

costs. In the case of defense, once an objective

has been agreed upon, evaluation of alternative

projects may lend itself to CEA, a technique

used to compare programs oriented toward attainment of the same quantified, but not monetarily valued, outcomes.

In the Federal PPB area, CEA/CBA has

achieved less consistent success in social welfare

areas, including education and health programs

(751), than in the areas of water resource management and defense. The problems in applying

these analytical techniques in social welfare

areas include frequent disagreement on appropriate outcome measures and the valuing of redistributions of money, educational resources,

access to health care, and so on. The benefits of

redistribution—the seeking of a more just and

humane sharing of society’s resources—are particularly difficult to quantify and value.

cism about the value of much medical technology replaces the enthusiasm of former years. Interest in and encouragement of the analysis of

the safety and efficacy and, more recently, cost

effectiveness of technology has accompanied the

growing concern with health cost inflation

(405).

Public efforts to improve financial access to

care—primarily through medicare and medicaid—account for the rapid growth in Government’s share of the national health care bill.

Combined with increasing depth and breadth of
Ch. 1—Introduction and Background ● 7

private insurance coverage, social programs

have reduced the linkage between receipt of

health care services and financial liability for

them. Third-party payment is particularly extensive in the highest cost component of the

health care system—hospital care, where Government and private insurance pay over 90 percent of the total bill (720).

The consequence of the growth in third-party

liability is that most medical resource consumption decisions are divorced from liability for

their financial implications. Thus, a physician

may order an additional lab test which has a

very low probability of improving a diagnosis,

but which will not impose any direct and immediate additional financial burden on the insured

patient.2 Russell has observed that “. . . as

third-party payment has increased over the

years, the benefit required to justify a decision

in the eyes of doctors and patients has declined.

This has led to increased- use of resources in

2A typical failure to comprehend fully the role and implications

of third-party reimbursement is represented in the propensity of

some critics to blame physicians for overuse of certain procedures.

The assumption that physicians should perform the appropriate

social cost-benefit calculation perhaps puts them in an untenable

position: To represent society’s Interests, they may be asked to

deny a patient a procedure which might benefit the patient and in

any case would not harm the patient economically. This can be

regarded as violating the medical ethic of representing the patient

best interest, Were the patient responsible for paying the cost of

the procedure, then the physician’s cost-benefit calculation might

weigh the patient’s economic sacrifice against the potential for

medical benefit.

GROWTH AND COMPOSITION

OF THE HEALTH CARE CEA/CBA

Chapter 3 and, to a lesser extent, chapter 2 of

this volume are based in large part on an extensive review of the health care CEA/CBA literature. A detailed descriptive analysis of the composition of that literature, including trends over

time, is presented in appendix A, A portion of

that analysis is presented here, however, as

background for chapters 2 and 3.

A bibliography on CEA/CBA in health care is

presented in appendix B. This bibliography contains approximatelv 600 references, Primarily

many ways—including the introduction of technologies that otherwise might not have been

adopted at all and, more often, the more rapid

and extensive diffusion of technologies that had

already been adopted to some extent. ”3 In some

respects, the principal constraint on the provision of care is the state of the art and the availability of technology.

Thus, a number of factors have come together

to create a perceived need for formal evaluation

on the economic and medical implications of individual technologies: The market’s ability to

evaluate and ration has deteriorated to the point

where it plays a minor role at best; as a Nation,

we want to assure equitable access to needed

medical care and to minimize care which is ineffective, unnecessary, harmful, or excessively

costly; we want to contain health care costs

which currently impose significant burdens on

many citizens and whose continuing real growth

threatens everyone; and we confront an array of

new and future medical technologies that may

be introduced into the practice of medicine with

little regard for their cost implications (705). In

this environment, attention has turned to nonmarket means of assessing and controlling medical resource allocation. CEA and CBA have

been attracting interest as possible techniques

for performing the assessment function.

LITERATURE

from the years 1966 through 1978. OTA’S analysis of this literature shows a clear and dramatically growing interest in health care applications

of CEA/CBA. As described in appendix A, each

of the references was classified according to the

following dimensions: 1) year of publication, 2)

type of analysis (CEA or CBA), 3) publication

audience, 4) medical function of the technology,

5) physical nature of the technology (drug, device, etc. ), 6) decision orientation (e.g., societal

perspective), and 7) subject matter. Only a minority of the bibliographic citations are actual
CEA/CBAs. The majority address CEA/CBA

or CEA/CBA-related issues. Several citations,

however, are connected to CEA/CBA only

through their titles; their actual content is either

cost or effectiveness related alone.

Widespread interest in health care CEA/CBA

seems to be a phenomenon of the 1970’s. Figure

1 shows the growth in the numbers of published

CEA/CBAs and the numbers of CEA/CBA-relevant articles. This growth has greatly surpassed

the increase in the overall medical literature.

Figure 2 shows that the growth has been especially rapid in medical journals as compared to

nonmedical health care journals. This trend is

suggestive of an increased economic consciousness on the part of physicians, but it does not

allow any firm conclusion to that effect.

Prior to 1975, the annual number of CBAS

generally exceeded the number of CEAS. The

reverse has been true since then. The reasons for

this shift are difficult to determine. Some discussion of possible explanations is included in

appendix A, and an examination of the differences between CEA and CBA, and the implications of those differences, can be found in chapters 2 and 3.

Analysis of the literature by medical function

of the technology under study shows that prevention and diagnosis each account for slightly

over a quarter of the references, with treatment

accounting for the remaining 44 percent. Recently, however, there has been a shift away

from studies of prevention, which dominates the

other two categories in the earlier years, and

toward those of diagnostic technologies and

treatment technologies. (See table 1.) In terms of

decision orientation, health care CEA/CBAs retain as their principal orientation a societal

perspective on problems, though studies with an

individual practitioner orientation seem to be

becoming increasingly common.

Given the strength of recent growth in the literature and social forces promoting future consciousness of cost effectiveness, OTA anticipates continued significant growth in the literature over the next several years, particularly in

the medical literature. It is possible that the relative preference for CEA over CBA will increase.

Table l.— Numbers of Health Care CEA/CBAs

by Medical Function and Year (1968-78)

Number of CEA/CBAs by Medical Function —. - .—————

Prevention Diagnosis Treatment Other a

Year

1966. . . .

1967. . . .

1968. . . .

1969. .,

1970. . . .

1971 . . . .

1972. . . .

1973. . . .

1974. . . .

1975. . . .

1976. . . .

1977. ., .

1978. .,

Total

(1) (2) (3) (4)

0.0 0.0 0.0 5

0.0

2.5

1.5

3.0

6.5

7.0

14.5

2.5

5.0

15.0

12.5

18.0

0.3

3.0

0.5

2.0

3.5

2.0

4.0

5.0

10.0

16.0

17.0

25.5

88.0 88.8

1.7

3.5

2.0

3.0

4.0

4.0

10.5

14.0

14.5

28.0

37.5

18.5

141.2

3

6

2

8

11

14

15

22

22

33

35

31

207

a

lncludes mixes of all three functions (prevention, diagnosis, and treatment).

administration, general, and unknown

SOURCE Off Ice of Technology Assessment

Concern with the cost effectiveness of technology has motivated much of the recent CEA/

CBA work in health care, and this motivating

concern probably will persist for several years.

The single disease class that has captured the

most attention in the literature is also the Nation’s current leading cause of death: cardiovascular disease (CVD). More than two dozen papers in the bibliography concern CVD, and an

additional 16 citations relate to hypertension

screening and treatment. Other major disease

problems have also received considerable attention. Cancer screening programs have been the

subject of over 20 papers, including 9 on breast

cancer screening (27,95,230,267,303,313,375,

376), although cancer treatment per se has not

received attention. ~ Eighteen papers have addressed mental illness problems and programs

(31,99,113,218,223,351,352,353, 369,414,580),

and 18 others pertain to dental care (49,59,75,

126,127,187,229,245,283, 331,390,518). Drug

abuse (24,186,225,243,265,266,269,278,326,

328,358,444,464,486) and alcoholism (259,268,

281,474,532) combined account for a similar

number of references. Renal disease, the subject

of 18 papers, has received attention dispropor4

Primary prevention of cancer also has received no attention in

this literature, but many opportunities for primary prevention lie

outside of the conventional personal health care system. Studies of

the costs of air p(>llutic~n, for example, and of the benefits of abatement do concern themselves with cancer prevention.
Ch. 1–Introduction and Background ● 9

Figure 1.— Diffusion of Health Care CEA/CBAs by Year (1966-77)

104

96

88

80

72

64

o

16

8

0

Key

.

.

.

.

1 1 i 1 1 I I I 1 I I J

1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977

Year

— Number of CEAS + CBAS per year from column 3 of table A-2, app. A — — — CEAs + CBAs + related papers per year, from column 5 of table A-2 app. A

SOURCE Off Ice of Technology Assessment

67-774 0 - 80 - 2
1O ● Background Paper #l: Methodological Issues and Literature Review

Figure 2.— Diffusion of Health Care CEA/CBAs in Medical and Nonmedical Health Care Journals

by Year (1966.77)

48

44

40

36

32

~ 28

&

%Q

~ 2 4

a)

e

z

20

16

12

8

4

0

1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977

Year

Key: CEAs and CBAs in medical journals, per year (from column 1, table A-3, app. A)

. — — CEAs and CBAs in nonmedical health care journals, per year (from column 3, table A-3, app. A)

SOURCE Off Ice of Technology Assessment
tionate to its prevalence, but reflective of the

political and economic importance associated

with public funding of dialysis (80,146,298,327,

361,363,367,459,471,520). The Federal Government’s mid-] 960’s interest in disease control

programs, and in kidney disease in particular,

made this the only disease problem to have

more than one citation in the period prior to

1969.

Two general classes of health problems—

communicable diseases and birth defects—have

captured considerable attention. A variety of

communicable diseases (including cholera, influenza, malaria, measles, polio, rubella, tuberculosis, and venereal disease) have been the subject of over two dozen papers (1,23,65,100,101,

160,173, 180,289,297,368,377, 406,438,461,472,

473,506). Since the detection and treatment of

communicable disease have distinct “public

goods” characteristics, 5

they are logical subjects

for CEA/CBA, and it is not to surprising to find

that half of all the communicable disease papers

date from before 1974. By contrast, another

class of problems—the prevention of birth defects—has been studied much more in recent

years, with only 2 of 15 papers predating 1974

(34,114, 221,246,370). Several birth defect disease problems have received isolated attention

(e.g., Down’s syndrome, spina bifida, Tay -

Sachs disease), but at least one—phenylketonuria —has been the subject of three studies

(78,517,553),

Several disease problems emerge in the guise

of surgical procedures intended to treat them.

Each of the following operations is the focal

point of at least one reference in the bibliography: radical cystectomy (63), tonsillectomy (68), cholecystectomy (191), herniorrhaphy

(222,394), appendectomy (398), synovectomy

(416), joint replacement (534), and hysterectomy (103,275). In addition, there is a large number of papers relevant to surgery and CEA/

CBA but not identifiable with a specific surgical

procedure (3,39,40,74,214,231). Many of the

surgery-related papers were contributions to a

recent book on the subject (73).

Close to 30 papers were classified as nonspecific screening and prevention (43,87,105,106,

107,109,133,157,158,227, 239,309,320,362,428,

455,458 ,478,484,489,497,535). Some of these

related to particular activities (e. g., multiphasic

screening (87, 105,106, 107)), while others discussed CEA/CBA issues more generally.

In recent years, a great deal of policy discussion and regulatory activity has concentrated on

the adoption, diffusion, and use of expensive,

sophisticated capital equipment. Thus, it was

with considerable interest that OTA explored

whether such equipment had been the focal

point of numerous CEA/CBAs. With one exception—the computed tomography (CT) scanner—the answer is a striking no, The CT scanner was the most talked about medical technology of the 1970’s, and both the quantity and nature of the general interest are reflected in the

CEA/CBA literature on CT. Some 18 citations

are on this technology, all but 2 of them published in 1977 and 1978 (2,26,28,32,42,83,166,

167,169,211,300,301,317, 408,527,541,559,594) .

Will other equipment-embodied technologies

emerge as the subject of much attention in the

literature? As the controversy on specific technologies grows, particularly related to their cost

implications, additional CEA/CBA papers can

be anticipated. Electronic fetal monitoring is an

example of one such technology which has already been the subject of several papers (34,35,

435,436). The work of the National Center for

Health Care Technology, combined with general interest and concern, might increase the proportion of CEA/CBA literature focusing on

equipment-embodied technologies.

A variety of services accounted for a significant proportion of the articles. Some of these

services have relatively tangible outcomes and

hence are good candidates for CEA/CBA. Six

studies of pharmaceutical services basically involve issues of efficiency, with equity concerns

of less importance (20,357,592,599). Aside from

moral considerations, some studies related to

reproductive health lend themselves to reason-
ably objective analysis. An obvious example,

abortion, was the subject of only one paper during the period covered (338), though continued

policy debate and development may lead to increased analytical interest (84). In addition, the

literature review yielded several articles on

family planning and on maternal and child

health programs.

Other services address social needs that are

extremely difficult to quantify in a meaningful

fashion. In general, one would expect that such

services would not receive a great deal of attention in literature which places a premium on

quantification and measurement. Exceptions

most likely would reflect a policy of unusual

social importance. Above, it was noted that 1 8

CEA/CBA-relevant articles in the mental health

area were found. Similarly, there were a dozen

papers on geriatric services (148,149,286,319,

568), and an additional four papers on institutional versus home care, with the patient type

not indicated (121,321,348,486). Given current

problems and anticipated growth in the elderly

population, continued interest in this subject

matter would not be surprising. Two other

areas of considerable current interest are occupational health and rehabilitation. The literature search identified more than 10 articles on

relevant topics (21,61 ,89,111,112,141,174,175,

270,373,423,546).

Program services is not the only area in which

social importance recommends analysis while

quantification problems limit it. Manpower

programs illustrate another area in which technical innovations—often, in this case, substitution of one type of personnel for another—produce outcomes which are difficult to quantify

usefully. Nevertheless, analysts have made a

dozen contributions on this subject (82,90,120,

142,226,316,374,437).

Related to the dearth of equipment-specific

studies, relatively few diagnostic procedures,

apart from screening procedures, have been the

subject of CEA/CBA attention. A few procedures have received isolated discussion—for example, fiberoptic laparoscopy and colonoscopy

(224), sigmoidoscopy (581), and gastrointestinal

exams (207)—but only radiology has received

frequent attention (2,26,28,32,42,83,166,167,

169,211,300,301,317,408, 430,431,433,527,541,

559,594). Weinstein (569) has identified the

evaluation of diagnostic procedures as deserving of CEA/CBA efforts. His plea is supported

by the growing body of literature which indicts

the increasing use of diagnostic tests as a major

source of medical cost inflation (752). The evidence suggests that everyday, mundane tests are

at least as significant contributors to that inflation as the more sophisticated and expensive

technologies (745), yet the former have received

very little CEA/CBA attention. Again, problems of measuring and valuing the outcomes of

diagnostic procedures stand in the way of ready

application of CEA/CBA (360,559),

In closing this section, two other areas which

seem underrepresented in the literature should

be mentioned. For the last several decades,

drugs have epitomized the scientific growth of

medicine and dramatically altered the practice

and outcomes of health care. Drugs have been

the subject of hundreds of biochemical and medical studies, and within the social sciences, of

numerous analyses of medical technical change.

Yet aside from implicit and tangential interest in

them (e.g., as a component of hypertension

management), drugs have not often been the

subject of CEA/CBA analysis. (See, however,

reference 190 for a case study on cimetidine. )

Finally, the literature reveals very little evidence of attempts to compare the costs and benefits (or effectiveness) of specific medical interventions with nonmedical interventions to

deal with health problems. Although this background paper focuses on medical approaches,

one might have anticipated identification in

OTA’s literature search of a few studies which

cross the medical-nonmedical border. With the

exception of early Department of Health, Education, and Welfare efforts (240), however,

studies of this type were not found. Conceivably, heightened awareness of prevention alternatives (743) will motivate formal efforts to

grapple with medical-nonmedical comparisons

in the future.
DECISION TECHNIQUES RELATED TO CEA/CBA

Other bodies of literature are related to the

application of CEA/CBA in health care, but

OTA, in the attempt to set reasonable bounds

for this inquiry, did not systematically explore

these. For example, more attention could have

been given to the areas of decision analysis,

multiple objective programing, and health

status indexes (HSIs). In all three of these areas,

there is a rich and growing health-related literature. In omitting them during our literature

search, OTA did not identify some applications

specifically related to CEA/CBA in health care.

Each area will be considered briefly below.

Decision analysis is a collection of analytical

methods used to assist in making decisions under uncertainty. This technique commonly uses

the familiar decision tree diagram, depicting alternative decision pathways (or “branches”)

each of which is accompanied by a probability

that a certain event will occur (335,558). Since

CEA/CBA studies ordinarily include many uncertain variables, some element of decision analysis may often be desirable, as is discussed by

Schweitzer (478). (For an excellent review of decision analytic application to health care, see

reference 735. )

Multiple objective (or multiobjective) programing is another field of study whose application may be important to the use of CEA/CBA

in the health field, but which has received relatively little attention partially because the general field itself is quite new. Multiobjective programing is a subfield of mathematical programing, which in turn lies within the discipline of

operations research. For a comprehensive, but

non-health-related, discussion of the subject, see

Cohon, 1978 (719). Essentially, multiobjective

programing consists of a set of analytical techniques, such as linear programing, which attempts to find solutions to a problem which has

more than one objective. The rationale behind

the use of these techniques is that many problems—especially public policy ones—which require decisions, have multiple objectives, many

of which may be conflicting. That is, by achieving one objective, another objective must be sacrificed. The purpose of multiobjective programing in public policy decisionmaking is for the

analyst to provide the decisionmaker with options and their probable consequences. As Cohon describes it (719), when a problem is solved

for a single objective, and when there actually

are multiple objectives, one of two undesirable

events is apt to occur: Either some objectives are

ignored, and therefore treated as if their value

were zero; or the analyst, in an attempt to combine objectives, assigns relative weights to

them. Either of these actions results in the analyst’s actually making the key decisions which

are supposed to be made by the decisionmaker.

In multiobjective programing, by contrast, the

analyst describes the degree to which each objective is or is not met as a result of each course

of action. With the analytic process accomplished, decisionmakers are then faced with the

political process of deciding which course of action to follow.

HSI research is the third field which is not fully assessed in this report. Nevertheless, a preliminary investigation suggests that the field is

maturing in an orderly, scientific manner, that

the body of literature is growing fairly rapidly,

and that HSI research holds significant promise

for future evaluation of all social and technological interventions which affect the public’s

health status.

The Federal agency that has been most interested in HSI research and application has

been the National Center for Health Statistics

(NCHS), whose job it is to monitor and report

on the Nation’s health and whose Health Interview Survey instrument has played a key role in

much of the HSI work noted below. Located

within NCHS is the Clearinghouse on Health

Indexes, an office which maintains a current

computerized and indexed bibliographic file on

all health-index-related literature. Quarterly,

the Clearinghouse publishes the “Bibliography

on Health Indexes” which includes annoted

citations of recent published and unpublished

studies.

OTA’s preliminary review of the HSI literature revealed several significant research
groups that are active in health status measurement. The San Diego group, working on the

“Health Index Project, ” has done pioneering

work in developing both survey instruments

and relative weighting scales for physical health

measures which include values for levels of wellbeing (functional status and symptom-problem

indicators) and disease transitional probabilities

(e.g., 726,731,732,733,741,742). Another group

is working on the “Sickness Impact Profile

(SIP)” study, which includes multiple weighting

scales and one overall scale for physical and social health as well as general health perceptions

ORGANIZATION OF THE REPORT

Chapter 2 examines issues relating to the

methodology of CEA/CBA, essentially organized by the components of analysis. It is oriented less toward describing the methodology of

CEA/CBA as conducted in practice than toward

describing the components of an ideally conceived CEA/CBA process. Consequently, it

should not be construed as a practical “cookbook” for use by someone wishing to learn how

to “do” a CEA/CBA. Chapter 3 is a critical review of the published literature of CEA/ CBAs.

It describes how the components of CEA/CBA

have been addressed in actual practice. Chapter

4 contains OTA’s findings in regard to the methods of CEA/CBA. It also includes a set of 10

principles of analysis developed by OTA to

guide an approach to formal analysis.

(e.g., 707,708,728). A third group at RAND is

developing multiple indexes, using an expanded

definition of health, consisting of physical, mental, and social health and general health perceptions (79,711). This research effort is part of the

RAND Health Insurance Study and will be used

to help assess the impact that various insurance

mechanisms have on health status.

OTA’s discussion of the aforementioned research is not meant to indicate that other research in the area of HSIs is either not being

done or not being done well.

There are five appendixes. Appendix A is an

analysis of the growth and composition of the

health care CEA/CBA literature. Appendix B is

a bibliography of CEA/CBA in health care. It

includes a discussion of the criteria for inclusion

of items in the bibliography. Appendix C is a

collection of abstracts of items in the bibliography of appendix B, including the 19 case studies

of medical technologies prepared as part of

OTA’s full assessment, The Implications of

Cost-Effectiveness Analysis of Medical Technology. A brief description of the main report and

other background papers of OTA’s assessment

is presented in appendix D. Appendix E lists the

members of the OTA Health Program Advisory

Committee and the authors of case studies conducted as part of this assessment.
2.

Methodological Issues
. .... . 

b

Contents

Introduction. , . . . . . . . . . . . . . . . .

Page

I . . . . . , . . ● . , “. . ● 17 . . . . . . . . . . . . . . . . . . . . . .

Defining the Problem, Objectives, and

Assessing Production Relationships . .

Marginal Valuations. . . . . . . . . .

Joint Production Considerations .

Alternatives . . . . . . . . . . . . . . . . . . . . . , . .

20

21 .

21

● ✎✎✎ ✎✎✌ ✎✎✎ ✎✎✎ ✎✎✎ ☛✎✎ ✌✎✎ O* CC CO* ,

. . . .

... ... ... ... *.. .** 00 **O***** *

● . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ● . . .

Identifying, Measuring, and Valuing Benefits/Effectiveness and Costs ., . . . . . . . .

Benefits/Effectiveness . . . . . . . . . . . . . . . . , ., , . . . . . . . . . . . . . . . ● , . . . . . .

costs. . . . ● . . . . . . . . . . . . . . . . . . . . . ● . . . . . . . . . . . . . . . . . ● . . . . . . . . . ● .

Valuing Benefits and Costs Over Time: Discounting. ., ., ., . . . . . . . . . . . . . . . . .

Setting the Discount Rate . . . . . . . . . ... , . . . . . . . . . . . . . . . . . . . . . . . . . .

Valuing Nonmonetary Benefits/Effectiveness Over Time . . . . . . . . . . . . . . . .

22

23

27

29

29

30

.

Addressing Problems of Uncertainty: Sensitivity Analysis

Examining Ethical Issues. . . . . . . . . . . . . . . . . . . . . . . . .

Presenting and Interpreting Findings. . . . . . . . . . . . . . . . .

Linking Analysis to Policy Implementation . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . 31

. .........,.., . 32

,.. ... ... .,. ,. , c e, 33

. ...*........*.*** . 35

s

t

c
2

Methodological Issue;

INTRODUCTION

Applications of cost-effectiveness analysis/

cost-benefit analysis (CEA/CBA) can be quite

complex, especially in the field of health care.

The effort to apply CEA/CBA, therefore, requires a systematic and often rigorous approach, The problem to be solved may not be

obvious, nor may its objectives. Is the problem

one of health? If so, what is its scope? Is the objective to reduce deaths? Or deaths due to cardiovascular disease? Or is the problem one of efficiency? Is it to determine the best way to find a

cancerous lesion? Or to lose weight? The answers to questions such as these help to determine the scope and nature of the analysis.

The framework for the analysis is also partially determined by the perspective of the evaluator. In reviewing an insurance package to evaluate a preventive service for a client, for example, a private health insurer probably would

limit his or her concern to a comparison of the

costs of providing the preventive service with

the projected decrease in costs due to a decrease

in future medical care utilization. From the perspective of the private health insurer, therefore,

the problem has to do with the efficiency of the

preventive program. The perspective of society

as a whole is a broader one. Society’s concerns

would necessitate measuring not only the direct

medical cost savings (if any), but also the indirect costs (such as lost (or saved) time associated

with treatment, recovery, illness, or death) and

the amount and value of life, limb, and misery

involved, The benefits derived by the private

sector, therefore, may be a subset of or different

from the benefits derived by society as a whole.

In this chapter, the methodologies of both

CEA and CBA are presented. First, the theoretically preferred orientation that a CEA/CBA

should have is presented. Ordinarily, for example, a health problem rather than a given technology or procedure would be an “ideaI” focus

of an analysis, because this orientation will

allow the anaIyst to study alternative means to

achieve some specified health objective. Following a discussion of identifying, measuring, and

valuing benefits/effectiveness and costs, the implications of—and approaches to—special probIems that confront the analyst are discussed.

These problems include valuing costs and benefits that occur over time, reducing uncertainty

or making estimates in the face of uncertainty,

and taking into account the concept of equity.

Also discussed are alternative methods for

presenting findings and interpreting the results

of a CEA/CBA. Finally, the inherent limitations of the technique are identified.

Throughout this chapter, CEA and CBA are

assumed to be fundamentally the same technique, in that both are structured methods that

are designed to assist a decisionmaker in the

allocation of resources. In actual practice, however, CBA attempts to measure all costs and

benefits of a given process/technology and to

value them in monetary terms, whereas CEA ordinarily attempts to measure and value the resources expended and to compare them to only

health status changes. In CEA, therefore, the

final product is usually presented in terms such

as cost per life or cost per year of life saved, or

cost per degree of blood pressure lowered, and

so forth. Although this more limited approach

to assessing the worth of a technology is often

practical, especially when the decisionmaking

setting is limited in scope, a broader approach

to assessing the worth of a technology may be

more applicable for generaI public poIicy. For

instance, in the case of a county health department seeking to know the most cost-effective

method of controlling alcoholism, measures

such as the cost per cured/prevented alcoholic

may be sufficient information on which to base

a decision. However, at a higher public policy

level, a local health systems agency, for example, may need to set priorities among such diverse projects as an alcoholism program, a

17
18 ● Background Paper #1: Methodological Issues and Literature Review

health education program, an immunization

program, and a mobile coronary care program.

Its decision process will require more as well as

different types of information, such as the specific populations affected in each case, the relative changes in health status, future health care

expenditures, reimbursement possibilities, and

political acceptability. At the national level,

even more diverse programs compete with one

another, requiring more diverse information

such as changes in productivity (e.g., for alcoholism programs), criminal activity (e.g., for

drug programs), property loss, social security

payments, health care expenditures as well as

health status. Therefore, as the policy perspective broadens, the information requirements for

resource allocation decisions also broaden.

This chapter describes the methods of CEA/

CBA from a broad policy perspective, a perspective which Congress will ordinarily have.

The principal departure from conventional wisdom is that OTA assumes that the use of CEA in

public policy decisions —like that of CBA—ordinarily requires a comprehensive examination

of all relevant costs and benefits. In addition,

since CEA does not value all variables in a common (monetary) metric the way CBA does, it

will be argued that the benefit/effectiveness part

of a CEA can be analyzed in unlike terms (e.g.,

money saved, population groups treated, and

disability days avoided). This approach has inherent limitations. First of all, CEA so broadly

construed is contrary to what many analysts

consider CEA to be. Second, with the results of

a CEA presented as the cost per “array” of

health and nonhealth benefits/effectiveness,

such analysis will not permit easy comparisons

between programs. As stated in chapter 1, however, the position taken by this report is that

CEA and CBA are not decisionmaking techniques, but rather systematic methods to compare the costs and significant effects of a given

course of action.

This expanded concept of CEA/CBA is not

meant to imply that other more limited studies

are not useful or valid, especially in resource allocation decisions of a more limited scope. As

chapter 3 shows, many technically excellent

analyses examine only the more important benefits/effectiveness. The purpose of the expanded

definition of CEA is simply to place this analytical technique in a more general perspective, especially in light of its use in the public policy

arena.

DEFINING THE PROBLEM, OBJECTIVES, AND ALTERNATIVES

Ideally, a health care CEA/CBA should start

with a broadly defined health problem such as

premature death, excessive disability, or unnecessary pain and suffering. A broad problem

definition would lead to equally broad objectives—to reduce premature deaths, excessive

disability, or unnecessary pain and suffering.

Alternative means of achieving such broadly

defined objectives are numerous, encompassing

a wide scope of possible programs. In theory,

the programs need not be limited to the field

of health care per se; alternative means of

enhancing health include airport safety procedures and environmental pollution control, as

well as immunization programs and surgical interventions.

In fact, the ultimate health care CEA/CBA

- would provide guidance for society’s allocation

of money in order to maximize the society’s

health status. An approach this broad, however, would require not only technical sophistication beyond that of the current methods, but

also the ability to shift funding among widely

divergent programs, such as immunization activities, cancer research, emergency treatment

systems, automobile safety, and fire and police

protection.

Many public and private health-related programs in our pluralistic society are, in effect,

fairly autonomous, however, and shifting funds

from one program to another is difficult. In the

real world, therefore, the identifiable health

problem addressed through analysis may be

more realistically limited to deaths or disability

due to a given disease. Limiting the scope of the

problem, in turn, limits the objectives and nar-
Ch. 2—Methodological issues ● 19

rows the alternatives. For instance, the problem

that is defined may be confined to a given disease and the objective to that of reducing the resulting deaths and disability. Possible alternate

actions include preventing the disease as well as

curing or ameliorating it, but a still narrower

definition of the problem—such as that of curing existing disease—would preclude prevention. However, as the scope narrows, the alternative possibilities can often be examined in

greater depth, a counterbalancing advantage.

As a general rule, when an analyst examines a

variety of alternatives, time and other limited

resources preclude consideration of all or even

many viable specific programmatic alternatives.

In such cases, a possible strategy is to select

representatives of diverse programs (e. g., treatment, screening, medical prevention, nonmedical prevention). Needless to say, the analyst

should select programs not clearly dominated

by others of the same type. Thus, a comparison

of kidney disease treatment with prevention

programs would not fairly represent the treatment end of the spectrum by selecting only inpatient dialysis, since both outpatient dialysis

and home dialysis are viable options.

A CEA/CBA can also start from an entirely

different focus. For instance, instead of examining alternative means of ameliorating a societal

health problem, the analysis may consider the

ability of a given technology to accomplish specific objectives. That is, rather than addressing

the general problems of excess mortality or even

mortality due to heart attacks, either of which

could include solutions outside the scope of the

health care system, the analysis may examine

the cost of a mobile coronary care unit relative

to its ability to reduce mortality. This reduction

in scope may have the advantage of allowing

more detail, and possibly more rigor in the analysis, but it sacrifices the ability to consider relevant alternatives in solving the overall health

problem.

A particularly perplexing problem for CEA/

CBAs concerns technologies in which a causeand-effect relationship to health status is not

established, although an association is widely

believed. An obvious example is a diagnostic

procedure (e.g., an X-ray). In the case of such

technologies, objectives must often be defined in

terms of intermediate outcomes (e.g., number of

blood tests per minute or amount or quality of

information produced). Analyses in which the

objectives are so defined beg the question of the

ultimate value of the diagnostic procedure, and

may thereby call into question the value of the

CEA/CBA itself.

For a CEA/CBA to be technically possible,

the principaI objectives should be quantifiable;

when that is not possible, reasonable proxies

should be available. This requirement places a

severe constraint on the evaluation of health

care procedures, the reason being that key objectives are often intangible. Unfortunately,

such a constraint tends to place analysts and

policymakers in a double bind, because health

resource allocation decisions are often required

irrespective of the ability to quantify objectives.

When key objectives cannot be adequately

measured, the temptation is to measure only the

quantifiable objectives, relegating the intangibles to inconspicuous footnotes or ignoring

them altogether. Thus, a hospice program

which may be adopted in the absence of formal

analysis, on the basis of the intangible benefits

of dying with dignity and without pain, may be

rejected under the scrutiny of a formal, rigorous

CEA/CBA, based solely on economics—since

the only quantifiable objective may be the reduction of health care cost.

The principal danger of performing a CEA/

CBA when the important objectives are not

quantifiable is that the results may be misrepresented or misinterpreted: That which is quantified may take on undue importance; that

which is not, regardless of its importance, may

be ignored. Thus, not only is it advantageous

for an analysis to be premised originally on a

health problem, but the important objectives or

reasonable proxies should also be quantifiable.

In structuring the analysis, therefore, it is important to array the objectives in priority at the

outset, and then to analyze the quantifiability of

each one.

There are at least two exceptions to the above

statements. First, sometimes a minor objective

by itself may indicate the desirability of a program even when the major objectives are not
20 • Background Paper #1: Methodological Issues and Literature Review

quantifiable. In the case of the hospice program

cited above, for example, although the principal

purpose may be humanitarian in nature and

thus impossible to quantify adequately, medical

cost savings, although a much lesser consideration, may be sufficient to indicate adoption.

Notice that this exception to the decision rule

applies in only one direction: In the aforementioned case, the lack of medical cost savings

would ordinarily not be sufficient in itself to indicate rejection. The second exception arises in

the case of a CEA/CBA being performed from a

nonsocial perspective. Often, this type of analysis has an orientation strictly toward minimizing health care costs; hence, the broader societal

health objectives can be subordinated by a more

narrow economic concern.

A final note concerns the overall responsibility of the analyst with respect to the scope of the

study. On the one

ASSESSING

Just as defining

hand, it is helpful if the analysis provides information regarding the marshalling of resources in the most efficient manner conceivable, within the context of society’s

overall principles, regardless of artificial constraints, whether they be legal, political, or

customary in nature. Although some alternatives may not be feasible under the present legal

structure, or may be politically or economically

unacceptable, a thorough analysis might identify them (e.g., see reference 335). On the other

hand, in the interest of realism, the analyst

should (when feasible, and to the extent of the

analyst’s knowledge) identify those alternatives

that are politically, legally, and economically

feasible at the present time. The broader scope is

important for stressing what could be accomplished in the long term, but often only if society

is willing to challenge some of its more established institutions. The narrower scope is important for stressing what can be accomplished

in the short run, given the existing system.

PRODUCTION RELATIONSHIPS

the problem, objectives, and

alternatives is essential in establishing the overall conceptual framework for the analysis, defining the process of health care is essential in establishing the technical framework for the analysis. That is, in order to evaluate the worth of a

health care technology, we must know the resources (people, money, equipment, supplies)

which are used, the manner in which they are

combined, and the outcome (the saving of life/

limb, the increase in happiness, the decrease of

pain or of number of hospital days) which is

produced. Health outcome is ideally measured

in terms of net changes in health status.

Often, there is more than one way to produce

a given product. Take the relief of a headache as

an example. The input might be a head and

shoulder massage, an aspirin, or acupuncture.

As evidenced by the last example (acupuncture),

sometimes we know how to produce an output

without actually understanding the precise manner in which it is produced. In most cases, different inputs and varying amounts and combinations of the inputs result in varying quantities

and qualities of the output. Therefore, comparing one production process with another can be

very complex.

In health care CEA/CBAs, production relationships are related to the problem which is

defined. Narrowly defined problems with intermediate outcomes are the most easily characterized: The production of an X-ray or a blood test,

for example, is reasonably well understood; the

production of a change in health status is not.

Efforts to assess the effectiveness of health care,

therefore, have often avoided measuring

changes in health status. Early efforts to evaluate health care measured the amount and quality of the inputs, implicitly assuming that more

doctors and more nurses were better than fewer,

that board-certified specialists were better than

general practitioners, newer facilities were better than older, and that the latest technology

was better than the existing technology. In 1969,

Donabedian suggested that quality of care be

measured in terms of structure, process, and

outcome (723). Structure refers to the inputs,

process refers to the manner in which health
Ch. 2—Methodological issues ● 21

care is practiced as defined by some norm (i. e.,

the manner in which inputs are combined), and

outcome refers to the success of health care in

terms of health status. Most of the subsequent

success in evaluating health care has been in the

area of “process” evaluation and has taken the

form of peer review and medical audit, such as

is employed by the Professional Standards Review Organizations. More recently, there has

been encouraging work in measuring outcome

in terms of health status changes (406,78,79,

516) which has been made possible by the pioneering work of several groups of researchers

who are developing techniques that measure

health status (708,726,741).

Part of the reason that the results of health

care are so difficult to understand is that there

are numerous intervening, or exogenous, variables which complicate the analysis—variables

such as age of patient, degree of patient compliance, environmental changes, and genetics.

As a result of these variables, analysts sometimes use elaborate mathematical models to try

to simulate both the disease process and the production process (e.g., see reference 335). One of

the more basic techniques currently in use is

decision theory, a diagrammatical expression of

probable outcomes. In some instances, when

outputs of a process are known but the process

by which they are produced is not well understood, analysts can make use of operations research techniques which mathematically manipulate the quantity of inputs and the manner in

which they are combined to “simulate” the production and/or disease process. These methods

are known generically as simulation techniques.

Despite the technical aura of much of the terminology, simulation methods can be helpful in

simplifying a complex process into what are

believed to be the essential relationships. They

can be used to examine the changing nature of

the outputs as both inputs and the manner in

which they are combined are varied.

To assist in public policy decisions, analysts

may perform a CEA/CBA by studying a process

retrospectively, and then extrapolating the results into the future. In such cases, certain

potential complications should be noted. For example, many studies are done on a small scale,

and the observed input-output reIationships

cannot necessarily be assumed to be the same on

a large scale (as any baker knows, quadrupling

the ingredients does not successfully produce a

loaf of bread which is four times the normal

size). An even more complex problem is that of

the rate of technological change. To assume that

a complex technological process will not change

over time is obviously foolish, but to predict

how it will change is fraught with uncertainty

(e.g., see reference 559). Other problems include

predicting the efficiency gained by learning better how to use a new technology, and predicting

relative changes in future costs of inputs (e. g.,

labor v. capital). Finally, what works in one setting may not work in another. A technology applied in an urban setting may not work in a rural one; a carefully controlled study in a teaching hospital may demonstrate a technology’s

efficacy—or potential effectiveness—but may

not be useful in predicting its actual effectiveness outside that special setting (405).

Marginal Valuations

The worth of a technology should be assessed

at what economists term “the margin. ” That is,

the analysis should seek to compare the added,

or marginal, cost of producing the next unit of

benefit (see reference 559). In an evaluation of

computed tomography (CT) scanning, the issue

is not any longer whether the technology itself is

cost effective, but, rather, whether the various

applications of the technology are cost effective.

Should CT be used for confirming suspected

brain disease/trauma, or for ruling out brain

disease/trauma when persistent headaches are

presented? In what instances are body scans

indicated—or cost effective? In general, the

relevant inputs or costs which must be considered in a CEA/CBA of a health care technology

will be tied to whether the technology is already

in place or whether it has yet to be adopted/

purchased.

Joint Production Considerations

Finally, many technologies have multiple applications, and the technological process being

studied is seldom applied in isolation. These two
22 ● Background Paper #I: Methodological issues and Literature Review

considerations can have enormous effects on

cost and benefit calculations. For instance, since

a single blood test can be and is often used as a

source of information for numerous diseases

and bodily functions, analyzing the cost effectiveness of drawing blood for only one purpose

is inadequate if the total cost is used; it either

overstates the associated costs, understates the

potential benefits, or both. Likewise, a CEA of a

Pap smear program should be done in recognition of the fact that many other health evaluations are not only possible but are ordinarily

performed during the examination, whether formally or informally. That is, the woman who is

given a Pap test may be screened for other pelvic disorders, high blood pressure, fever, skin

rashes, weight problems, wife battering, and

many other conditions, all of which carry certain potential benefits and all of which should

be assigned some of the cost (or, conversely, less

cost should be assigned to the Pap test); or the

CEA should be evaluating the complete ob-gyn

examination rather than just a Pap test (335). Of

course, including the effects of joint production

adds greatly to the problems of measurement

and valuation, but these difficulties in no way

diminish the conceptual importance of their full

consideration in a complete analysis. Oftenf for

instance, a very small incremental, or marginal,

increase in cost to an existing production process, can have large benefits—other times, the reverse is true.

Thus, in order for the health care production

process to be adequately described, a causal

relationship of inputs to outputs should be

demonstrated, joint production effects should

be considered, and the effects of exogenous

variables should be examined. In addition, the

analysis of the use of an existing technology

should include marginal changes of costs and

benefits. Unfortunately, many variables are

much easier to describe conceptually than they

are to measure empirically.

As mentioned earlier, however, since many

diagnostic procedures have intermediate outcomes as their objectives, a direct association

with health status change may not be known. In

such cases, if inputs and outputs cannot be

shown to be causally related, at least an associative relationship (however distant) to some

health problem should be noted.

IDENTIFYING, MEASURING, AND VALUING

BENEFITS/EFFECTIVENESS AND COSTS

At the heart of every CEA/CBA is the identification, measurement, and valuation of relevant costs and benefits/effectiveness associated

with the production process. The identification

and measurement procedures for both techniques are essentially the same; it is in the valuation process that the two techniques differ.

The reader will recall that CBA ordinarily requires that all costs, effects, and benefits be valued in monetary terms, whereas CEA requires

that only nonhealth status changes be so valued.

But there are other differences between the two

techniques.

One of the inherent difficulties in describing

the elements of both CBA and CEA simultaneously—as is done in this report—is that, despite

conceptual similarities of the two methodologies, details sometimes differ for technical reasons. The classification of costs and benefits/effectiveness is one example. It is convenient to

look on “costs” as those resources which one

must give up in order to gain some benefit or desired effect. Conversely, benefits are those resources which are gained from the expenditure

of other resources used to produce them. These

definitions hold for the “costs” of buying or implementing the technology being assessed and

for the health “benefits” attributable to the technology. But what about the medical cost savings

which may result? Are they benefits, or are they

negative costs (i. e., to be subtracted from the

technology’s cost)? The answer is either. In

CBA, costs are generally considered to be only

those costs directly associated with the technology being assessed (which includes the expenditure of “indirect” costs such as time and lost

productivity). All changes in resources resulting
Ch. 2—Methodological Issues ● 23

from those costs, including medical cost savings, are considered to be benefits, some of

which are positive, some are negative. In CEA,

on the other hand, generally all net medical/

health resource changes are compared with all

net health status changes (516), which requires

that medical cost savings be treated as negative

costs, rather than as benefits. In this report, for

the convenience of exposition, medical cost reductions will be considered under the discussion

of benefits.

In the following two sections, both benefits

and costs will be discussed in terms of their identification, measurement, and valuation.

Benefits/Effectiveness

Identification

One primary advantage of a CEA/CBA is the

requirement that all relevant aspects of the use

of technology be considered explicitly. With

respect to the identification of benefits, this implies that the analyst may look beyond the obvious, beyond that which is intended, sometimes so far beyond that the effects are several

orders or generations away. The analyst should

look for effects through not only his/her own

eyes, but perhaps also from the perspectives of

society, private individuals, and private institutions as well. That which one person perceives

as a benefit or cost may be perceived by another

in an entirely different light. Consider elective

hysterectomy, for example. The patient weighs

as costs the financial costs plus the psychological/physical trauma against the benefits of preventing pregnancy, uterine cancer, or both;

whereas the health insurer may weigh only the

cost of the operation with expected reduction in

future maternity or gynecological care costs (see

reference 304).

The effects of technology in the health field

can be far reaching and varied; they can also be

obvious as well as obscure. They often follow

directly from the problem under consideration,

the objectives specified, and the framework in

which the problem is approached. Not all benefits or effects are positive—some may be negative (e. g., deaths due to surgery) and some may

be indeterminant (e.g., incurable disease maybe

discovered). Regardless, all effects should be

identified and enumerated. To identify all benefits/effectiveness, each of the following categories should be considered: 1) personal benefits/effectiveness, 2) health resource benefits/

effectiveness, 3) other economic benefits/effectiveness, and 4) social benefits/effectiveness.

Personal benefits/effectiveness.—The primary purpose of health care technology is to enhance the health and well being of individuals;

consequently, the expected benefits/effectiveness should be examined in light of individuals’

personal health objectives such as lowered anxiety, alleviated pain, reduced risk of sickness or

death, enhanced quality of life, and so forth.

Seldom will the analyst come to the conclusion

that an individual has seen the doctor for a

checkup or given up smoking in order to save

future medical bills, which is not to say that

medical expenses are unimportant. However,

CEA/CBAs frequently attach great significance

to medical cost reduction, while often ignoring

patients’ personal motives (see reference 304).

Health resource benefits/effectiveness.—A

direct result of the use of health care technology

is the change in use of other health care resources. For instance, preventive programs are

often advocated because they are thought to enhance health and thus decrease future medical

expenses. However, procedures such as screening may discover disease to such an extent that

direct medical costs are, in the short run, actually increased. This phenomenon is likely to be

observed when asymptomatic individuals are

screened for socially latent problems such as venereal disease, mental illness, and drug abuse

and for chronic conditions such as hypertension. Regardless of whether future medical costs

are decreased or increased in the aggregate,

shifts in medical resources will almost certainly

occur and these shifts should be identified.

Other economic benefits/effectiveness.—Secondary effects resulting from changes in health

status are often strictly economic: Healthy people are more productive than are sick people.

These effects should also be identified. From

certain points of view, such as the family’s, society’s, or the firms’, they may be very important,

whereas from the health insurer’s point of view,
24 ● Background Paper #1: Methodological Issues and Literature Review

they may be totally irrelevant. Consequently,

an efficiency study performed by a health care

provider for an insurance firm may ignore such

economic considerations; a socially oriented

CBA/CEA should not.

Social benefits/effectiveness.—Finally, society has collective objectives which stem from its

underlying values and traditions—objectives

which are not strictly economic and not directly

related to health status. These objectives may be

concerned with the equitable distribution of

medical care—ensuring that the poor have adequate access to health services—or with protecting the rights of the unborn, the mentally ill, or

the comatose patient. Also, health and medical

care resources may be employed to compensate

certain of the Nation’s citizens for the lack of

adequate housing, nutrition, employment, or

parental care. All of these effects, intended or

not, should be explicitly identified.

The special case of intermediate outcomes.

—Notwithstanding the ultimate goal of improving health and welfare, many technologies, particularly diagnostic ones, can best be evaluated

only in terms of intermediate outcomes such as

blood counts per minute, clarity of X-ray film,

or number of pounds lost per week. This methodological limitation is an especially disturbing

one, since diagnostic information often leads to

increased use of other diagnostic and therapeutic resources, resulting in higher expenditures

(569). There are, however, certain benefits from

diagnostic technologies which can easily be

overlooked: Such technologies often provide for

patient reassurance; they may avoid therapeutic

interventions; and they may assist in furthering

medical knowledge. Health promotion programs also are often difficult to assess in terms

of improved health status, resulting in the

necessity of measuring intermediate outcomes.

Examples are weight control and antismoking

programs.

Therefore, when final outcomes resulting

from a health care process cannot be adequately

identified, intermediate outcomes should be

identified and the uncertainty of the link with

final health status ought to be noted.

Measurement

Benefits/effectiveness initially should be

counted in whatever units are most appropriate:

Medical cost savings/expenditures are counted

in dollars; reduced disability in days (or weeks,

months, years); reduced mortality in years;

changes in health status in well-years. Likewise,

intermediate outcomes are counted as number

of blood tests taken, number of persons examined, and so forth.

Some benefits/effectiveness are difficult to

measure because they may be only partiall y

known, or not known at all. As was discussed in

the section regarding the production of health,

the efficacy and/or effectiveness of many interventions has not been demonstrated, and in

those cases where it has, the technique seldom is

efficacious and/or effective 100 percent of the

time. In an earlier report (405), OTA found little

evidence that health care technologies have been

adequately and systematically evaluated. Without valid efficacy/effectiveness and safety information, the value of CBA/CEAs may be

greatly diminished. Furthermore, even when

there is good evaluative research on the technology in question, the information may not be

directly applicable to the setting in which the

technology will be used. Much of the good research is done under nearly ideal conditions

such as in a controlled or partially controlled

environment with the best data by the best researchers and clinicians; since applications of

the technology will not normally have the benefit of such conditions, the projected “benefits”

may be significantly overestimated. In any case,

probability theory and sensitivity analysis can

be used to embrace the concept of uncertainty, a

subject which is explored more thoroughly in

another section below.

Unfortunately, the intangible benefits/effectiveness are difficult to measure, although they

are often the more important ones. The personal

and societal benefits/effectiveness listed above,

such as relief from anxiety and pain, for example, can often be estimated only by indirect

methods such as patient satisfaction questionnaires, or by techniques which simulate an indi-
Ch. 2—Methodological issues ● 25

vidual’s willingness to pay for the result. In the

main, however, intangible benefits/effectiveness cannot be adequately measured—and consequently must remain only “identified. ” This

should not eliminate the desirability of the analyst’s including a statement of their probable importance.

Valuation

Valuing benefits/effectiveness is the next step

of the process. Basically, the objective at this

stage is to determine their worth. Sometimes the

value is self-evident, such as when the benefit is

money saved. Since the techniques of CBA and

CEA are designed to compare cost with benefit

or effectiveness, the analysis is much easier

when both sides are measured in money—for instance, spending $100 in order to save $350 is

easily understood. Many of the applications of

health care CEA/CBAs concern benefits/effectiveness which are not easily translated into

money, however, and there is disagreement concerning their worth. Some health care technologies save lives, limbs, days of disability, and

discomfort; other technologies produce information (e. g., X-rays and laboratory procedures). What are these benefits/effectiveness

worth? The answers seldom are obvious.

Valuation of benefits is further complicated

by the problems of risk-averseness associated

with individual preferences. For instance,

McNeil, et al. (736) demonstrated that patients

preferred radiation treatment over surgery for

lung cancer even though surgery provided the

better chances for survival. The explanation

given was that the surgery itself carried with it a

risk of immediate death, and, consequently, patients preferred the assurance of a certain, but

perhaps shorter, life to facing the risk of immediate death. In addition, patients were willing to

trade off a perceived increased quality of life

with longevity. Valuing such individual preference is difficult and, even more important, recognizing that they even exist is easily overlooked. (For a more thorough discussion of risk

preference and risk behavior, see reference 755. )

The attempt to value benefits/effectiveness

often poses serious problems, perhaps even

more extreme than the problems their measurement poses. In those cases where measurement

is deemed impossible, impractical, or unreliable, attempts to valuate may not only provide

no further useful information, but may actually

mislead the reader by implying that the results

are more valid than they actually are. An example of this may be the value of bereavement support in a hospice program. This benefit can certainly be identified, but it is not easily measured. Attempting to place a dollar value on it

would probably be misleading.

Much of the controversy surrounding the valuation of health outcomes centers around the

value of life, an issue which is directly pertinent

only to CBA, since CBA alone expresses all

costs and benefits in dollars. The oldest and

most common method of valuing life is the socalled “human capital” approach, which values

life in terms of earnings potential. The value is

computed by summing the earnings lost due to

premature death or to disability; conversely, it

is done by summing the expected future earnings saved by postponing death or avoiding disability. All future moneys are discounted to a

present value at some specified rate. (Discounting is discussed in another section below. )

One of the first problems encountered by human capital theorists was the problem of consumption: If, conceptually, life is valued in

terms of its financial return to society, should

not the individual’s own consumption be excluded from the benefit calculation? However,

this solution would require valuing life at zero

for those who consume all they earn, and valuing life negatively for those who deficit spend.

Regardless of whether earnings are considered

net of consumption, though, the human capital

method is really valuing livelihood—i.e., one’s

earning potential—not life.

The human capital approach also poses distasteful problems such as valuing men more

highly than women, since males have traditionally earned more than females. Likewise, the

working population is valued more than the

very young or the very old, and whites more

than nonwhites. In addition, this method fails to

value other effects such as the psychic costs of

death to friends and relatives.

b 7-774 0 80 3
26 ● Background Paper #1: Methodological Issues and Literature Review

Although the human capital approach has enjoyed wide application (owing principally to the

absence of a better method), few people are satisfied that the value of life can truly be captured

solely by estimating earnings potential. This has

led to interest in other methodologies.

A conceptually more appealing approach is

the “willingness-to-pay” technique (e.g., 470).

The idea is to attempt to capture the value, to an

individual, of reducing the risk of death or disability by small amounts, and using the information to imply the value of life itself. This

method has its own conceptual problem in that

the imputed values are still income related: A

rich person will be willing and able to pay more

to reduce the risk of death than will a poor person. Also, there is a question as to whether an

individual can understand what a small reduction in statistical probability of death means.

Nevertheless, the willingness-to-pay approach is

the only technique that attempts to estimate individual perceptions as to one’s own worth,

which, presumably, includes such diverse notions as personal values, risk averseness, family

obligations, age, income, personal desires, and

even a philosophical outlook on life. Despite its

conceptual appeal, however, there is no indication that such a method can arrive at a consistent value for all human life. It also ignores the

value of one’s life to others in society.

Other methods of valuing life have attempted

to make use of imputed values from life insurance holdings and from jury verdicts. The

former suffers from the same conceptual problem as the human capital method since “earnings” not “life” is insured; the latter suffers from

gross inconsistencies (291). Neither method has

found much acceptance.

Notwithstanding the unending criticism of the

techniques to value life, the concept is an important one. Klarman writes (291):

As Mishan observes, a rough measure of a

precise concept is superior to a precise measure

of an erroneous concept. It is agreed that the notion of the value of human life, apart from livelihood, is sound. And a numerical estimate of

this value would be useful in comparing how

worthwhile alternative programs are. Comparisons of programs would gain in relevance and

aptness if all benefits were counted, including

saving of human life or gains in life expectancy.

This potential gain is much more likely to be realized if all benefits are entered into the model,

rather than having some appear only in footnotes.

CEA attempts to avoid this valuation controversy by simply counting the lives or years of

life saved (or lost) and not transforming the

numbers into money. Once money is allocated

to save lives, however, the value of life is implied—an important point which is easily overlooked. Notice that in CBA, the analyst must

choose a value to complete the analysis; in

CEA, the policy maker chooses the value, albeit

indirectly. For instance, when analysts assess

competing life-saving programs using CBA,

they must choose a specific value (or range of

values) for life. The most attractive program, in

terms of the analysis, is that which computes to

have the highest net benefit; if benefits exceed

costs, adoption of the program would ordinarily be recommended. Analysts using CEA, however, compute the cost per life or year of life

saved. Although the most attractive alternative

is that which provides the most effectiveness for

a given cost, the decision to adopt the “best”

program depends on the implied value which

the policymaker places on life, or on health

status change. For instance, of several lifesaving programs, the most attractive may cost

$100,000 per life saved. The decision to adopt

that program depends on whether the policymaker thinks that $100,000 per life saved is

reasonable.

A common misconception regarding the two

techniques is that CEA avoids value judgments.

In fact, many value judgments are made, albeit

often implicitly. These include judgments such

as the equating of different lives—is a young life

worth the same as an old one? Judgments such

as the equating of years of life—is 1 year of life

for 15 people equal to 15 years for 1 person?

Judgments such as equating all days of disability—is the day lost due to the common cold

equal to that lost due to surgery? Clearly, CEA

is not value neutral.

Time-related distortions.—Since many benefits/effectiveness of health care technologies oc-
Ch. 2—Methodological Issues ● 27

cur during widely varying intervals of time,

analysts must somehow place them in perspective in order to allow comparisons to be made.

That is, they must be able to compare the value

of reducing $1 of medical cost today with reducing it next year, with saving a life today with

saving it next year, and so forth. The accepted

practice is to transform each future effect to a

present value by means of a discount rate,

which is similar to an interest rate. Discounting

has long been used for the valuation of financial

resources, but in the health care field it has only

recently been applied to the valuation of nonfinancial resources (78,79,406,572). (A more

complete discussion on discounting is presented

in a separate section below. )

Valuing multiattributed outcomes. —As

noted previously, many individual processes in

health and medical care produce widely divergent outcomes, ranging from diagnostic information to the reIief of pain to the prolongation

of life. Not only is each of these outcomes difficult to measure (if, indeed, the outcomes are

ever identified) and to value in its own right, but

the various outcomes are also difficult to compare with one another. For instance, how much

pain is worth a life? That would be a difficult

question even if pain could be accurately measured. Nevertheless, conceptually, the issue of

comparing outcomes is important, and recently,

considerable progress has been made in weighting outcomes so that health status changes can

be combined. In a recent report, for instance,

OTA used the concept of quality-adjusted life

years to evaluate the cost effectiveness of

pneumococcal vaccine (406). This technique attempts to weight differences in health status in

relation to good health. Thus, a day of good

health is assigned the value of “1, ” a day of

death the value of “O,” and days of sickness, depression, or disability values somewhere between these extremes. For instance, total disability may be assigned a value of 0.1, while a slight

disruption of daily life due to the common cold

may be assigned a value of 0.9.

Valuing intermediate outcomes.—Above it

was suggested that in certain cases, often when

evaluating preventive or diagnostic technologies, intermediate outcomes may be valid objectives, but their measurement begs their

worth. What is the value of an X-ray? A blood

test? Or a physical examination? Often, no value can be assigned to these outcomes. When this

is the case, it is incumbent on the analyst to note

that it is and to state the extent to which the

technology is associated with final outcomes as

well as their probable importance to the study’s

result.

costs

Identification

In this report, the term “costs” refers to the

resources expended to produce an intended benefit or effectiveness. For instance, the costs of a

screening program would include the amount of

services provided (personnel time, supplies,

capital expenditures), as well as the patients’

time which is forgone in the use of the service.

Care should be taken to identify all resources

which are expended or which must be expended.

In general, the concept of “opportunity cost” is

the true cost of a program. That is, the cost is

equal to the value of the opportunities which are

lost as a result of the investment in the program.

Initially, costs should be identified in terms of

the actual resources used in the production process—person hours, supplies, and so forth. In

structuring the analysis, it is helpful to consider

costs as a broader concept than simply financial

resources.

Identifying the proper financial costs is always easier conceptually than it is in actuality.

In the health care field, this task is even more

difficult because charges often do not reflect true

costs, a fact which is sometimes due to unsophisticated accounting procedures and other

times due to the deliberate subsidization of one

service by another. Hospitals, for instance, are

known to operate some services, such as maternity wards, at a loss while operating certain ancillary departments, such as diagnostic laboratories, at a profit. The same was found true for

neonatal intensive care (see reference 71).

Also, since many resources in the health field

are often erroneously thought to be “free,” some

costs may be understated. A good example is
28 ● Background Paper #1: Methodological Issues and Literature Review) .

the cost of volunteer time, where, under the opportunity cost concept, volunteer time is worth

that which is forgone by its use. For example,

rather than working in a hospital ward, the volunteer may have worked for the heart association. Or the service rendered by a volunteer

may ordinarily be one which the organization

must otherwise buy.

In other instances, owing to market imperfections, inappropriate use of resources may be

used which can lead to the overstating of costs.

Physicians giving immunizations, registered

nurses making beds, and dentists cleaning teeth

are examples.

Next, the identification of the technological

resource costs will depend on the stage of the

technology’s development. For a new technology, costs may be difficult to identify, but

should include the R&D costs as well as the

capital costs associated with purchasing and operating the equipment. For an established technological process, where the analysis concerns

the level of use, marginal operating costs can

dominate. One potential problem of using past

performance to project future costs is that costs

may change as a result of increased efficiency,

technological change, or changes in scale.

Other reasons why costs are difficult to identify are: 1) some costs, such as overhead, are

common to many products; 2) some technologies produce multiple outcomes—if the CEA/

CBA study concerns only one, the analyst must

somehow determine which costs must be included, which are to be ignored, or how they are

to be shared; and 3) often, during the production process other tasks are or can be performed

at minimal incremental cost.

Measurement

Initially, measurement should consist of

counting the minimum resources or units of

service required to produce the intended benefit

or effectiveness. Generally, this step in the evaluation will follow naturally from the identification process. In cases where substitution of resources is possible, however, care must be taken

to count the generic service required. Thus, the

number of hours of immunizations, of making

beds, and of cleaning teeth should be counted,

not the number of physician, nurse, or dentist

hours required to accomplish the respective

tasks. The same argument can be used for measuring volunteer time.

Measuring costs when joint production factors must be considered is extremely difficult,

often not very reliable, but may be critical to the

validity of the analysis. Ignoring joint production effectiveness simply because it is hard to

measure can lead to a considerable overstatement of costs.

Valuation

Most analysts believe that valuation of costs

poses substantially fewer problems than valuation of benefits, because many cost resources

have a real or easily imputed market value. In

cases where costs reflect opportunity costs and

where they are measured in dollars, valuation is

essentially complete, except when the costs occur during different periods of time, in which

case discounting is required. When costs are

measured in generic terms, such as type and

amount of services provided, valuation can be

relatively difficult and sometimes controversial.

This is because the professions in the health field

often successfully restrict others from performing tasks, which could otherwise be safely performed at a more economical level (749). Nevertheless, the analyst should critically evaluate the

resources required to accomplish the job, taking

note of political, legal, or technical constraints

to providing the service at the most efficient

level possible.
Ch. 2—Methodological Issues ● 29

VALUING BENEFITS AND COSTS OVER TIME: DISCOUNTING

Costs and benefits seldom occur at the same

point in time. But in order for valid comparisons to be made, they can be treated as if they

all occurred in the present, through the application of a method termed discounting.

The rationale for discounting future costs and

benefits stems from the fact that resources can

be productively invested for future gains, as

well as from the observation that people expect

to be rewarded for postponing gratification. For

instance, in order to induce individuals to save,

interest must be paid, even in the absence of inflation. The rate of interest determines the future value of the amount invested. Thus, $100

invested at 5-percent interest will become $105

in 1 year. Discounting is the reverse process:

$105 next year has a “present value” of $100

when the discount rate is 5 percent.

Thus, just as an amount, p, invested at interest, i, has a future value of:

p (1 + i) in year 1

p (1 + i)2 in year 2

and

p (1 + i)n in year n

an amount of money, p, n years in the future at

discount rate, i, has a present value of:

p

(1 + i)

n

Likewise, a stream of future benefits or costs

is the sum of each amount, discounted at rate, i,

from whichever year the benefit/cost is incurred.

There is general agreement among economists

and policy makers that discounting future moneys is conceptually correct. However, there is no

consensus as to the rate which should be used

and there is still some confusion as to the proper

method of valuing future nonmonetary benefits/effectiveness. Fortunately, when benefits/

effectiveness occur over a long time, almost any

discount rate used makes them less and less important to the outcome of the analysis in a fairly

short period of time (480). This phenomenon results in making the rate used and the uncertainty

of future events less important than they otherwise would be.

Setting the Discount Rate

The particular rate chosen can have a substantial impact on the outcome of the analysis,since investment in health programs often

means spending present moneys, which are not

discounted, for future benefits, which are. In

such programs, the higher the discount rate, the

less attractive the program appears. As an example, suppose we spend $1,000 today, expecting to save $2,000 in medical costs 10 years

later. In order to compare the expected benefit

($2,000 savings) with the costs of the program

($1,000), we must discount the benefit to its estimated “present value. ” Consider the varied results using different discount rates:

cost . . . . . . . . . . . . . . . . . . .. $1,000 (present dollars)

Benefit. . . . . . . . . . . . . . . . . . . . .. $2,000 (in year 10)

Discount Present value Present value of

rate (70 ) of benefit net benefit (B – C.)

o $2,000 $1,000

5 1,228 228

7 1,017 17

10 771 – 228

And, if the benefit were not realized for 20

years, the results would be:

Discount Present value Present value of

rate (%) of benefit net benefit (B – C)

o $2,000 $1,000

5 754 – 246

7 517 – 483

10 297 – 709
30 ● Background Paper #I: Methodological Issues and Literature Review

Many programs in the health field have even

longer benefit time horizons. Thirty years is not

uncommon, especially for prevention or health

promotion programs such as antismoking clinics and pap testing. Thus, we see the power of

discounting and the resultant importance of the

choice of rate.

Most economists believe that the correct rate

is the opportunity cost of capital in the private

sector, subject to certain adjustments (e. g., the

adverse effect of pollution produced by private

sector investments). That is, society could opt to

invest the money in the private sector and earn

“benefits” at a substantial rate (perhaps as high

as 15 percent) which represents the opportunity

that is lost by investing in the health program.

An alternative argument, also persuasive, is

that the discount rate for social programs is considerably lower than the opportunity cost of

capital since society’s objectives include the

equitable distribution of benefits to future generations. Klarman (291) refers to this argument

as reflecting society’s “social rate of time preference. ” Referring to the numerical examples in

the text above, the reader will note that low discount rates result in future benefits’ appearing

more attractive. That is, society would more

readily invest money in the present to reap future health benefits if a low rate were used (706).

In any case, whether the correct rate is the private cost of capital or a lower social rate, agreement would still not be reached on the precise

number because of the fact that interest rates

vary not only across time but also across investment opportunities in any single point in time.

In the absence of agreement, the accepted method to treat this uncertainty is to present the

results testing several rates—a technique generally referred to as sensitivity analysis. (Sensitivity analysis is discussed in a separate section

below. )

Valuing Nonmonetary

Benefits/Effectiveness Over Time

with the same benefit which is saved in the present? In CBA, all such benefits are transformed

into monetary terms, a controversial process

discussed earlier, and then discounted the same

as any other future financial asset. In CEA,

however, benefits are expressed in nonmonetary

terms such as lives or years of life saved. Should

these be discounted as well? Weinstein and Stason (575) presented a persuasive argument in the

affirmative. One way to explain the need for

discounting future nonmonetary benefits is to

assume no discounting, and for the sake of clarity, to assume no inflation. Consider a lifesaving program which costs $1,000 and saves,

immediately, 10 years of life (i. e., $100 is spent

per year of life saved). Assume also a linear relationship between costs and benefits, If that

$1,000 were invested at 5-percent interest instead of being spent on the life-saving program,

in 1 year we would have $1,050 which could be

used to save approximately 101⁄2 years of life; in

2 years there would be $1,102 which could be

used to save over 11 years of life; and so forth.

Therefore, unless a year of life is valued more

highly in the present than in the future, the rational decision will always be to put off spending the money for an additional year. Discounting all benefits/effectiveness to present values

avoids this irrational incentive.

In conclusion, then, although the discounting

of future benefits/effectiveness and costs is conceptually correct, there is not, nor is there soon

likely to be, consensus regarding the rate for

two general reasons. The first is technical in

nature: Interest rates vary across both time and

investment opportunities. The second is conceptual: The discount rate can reflect the private

opportunity cost of capital, or a lower social

rate of time preference. The results of CEA/

CBAs should be presented using several discount rate estimates in order to examine the influence of the rate on the results—again, a technique referred to as sensitivity analysis, discussed immediately below.

How does one compare the value of a life or a

day of disability which is saved in the future,
Ch. 2—Methodological Issues • 31

ADDRESSING PROBLEMS OF UNCERTAINTY:

SENSITIVITY ANALYSIS

Discussions in the preceding sections have

noted the uncertainty of knowledge regarding

the etiology of disease and regarding diagnostic

and curative techniques. Superimposed on these

variables are changing personal habits, interactive environmental conditions and often unforeseeable future technological developments. In

addition, there is lack of agreement as to the

magnitude of health status changes and the value of the discount rate. How can we have confidence in predicting results in the face of all this

uncertain y?

One possible answer is to place the results obtained from analysis in perspective, to examine

closely the assumptions upon which the analysis

rests, and to test the sensitivity of the results to

reasonable changes in these assumptions.

Uncertainty can be classified into that which

is due to random events and that which is due to

ignorance. Unfortunately, many events in the

health field suffer from both types. The first,

random type, refers to events which occur according to a probability distribution. In general,

these are events associated with large numbers.

An example is the number of heart attacks occurring in a large population at any given time.

This event is thought to be random and is statistically predictable. It is different from the

chance of a heart attack occurring to an individual, which is dependent on nonrandom variables such as a person’s living habits and genetic

heritage. In some instances, events in the health

field are thought to be random, but their probability distribution is not known, which makes

prediction more difficult.

The second, and more troublesome, type of

uncertainty is due to ignorance. Sometimes the

problem is simply lack of information—we do

not know what causes cancer, or what triggers

certain allergic reactions—in which case we

have the option of buying more information,

either through more research, more time, or

both, In other instances, the uncertainty is due

to future events over which we have no control

—women may smoke more, or there may not be

an influenza epidemic this year—in which case

the best we may be able to do is to examine

trends or use expert opinion.

When evaluating a health care technology or

program in the face of the unknown, the analyst

has a rather impressive sounding arsenal of

techniques. For random events, probability theory can be used, often through the application

of decision analysis, which is a diagraming of

the possible courses of action, each branch accompanied by a known or imputed probability.

When probabilities are not known, expert judgment can be substituted. Thus, without knowing the cause or even the dynamics of a given

random process, the analyst can attempt to predict the likelihood of an outcome. But there are

other techniques from the field of operations research such as Monte Carlo and Markov Chain

methods which allow manipulation of a simulated process until the outcome mirrors empirical findings such as incidence rates of a disease

(see reference 335). These analytical methods

can provide valuable insight as to what process

may be occurring. They may also provide a

false sense of security to a policy maker, since

the terminology and the technical sophistication

which is required often mask the tenuous

assumptions on which the methodologies rest.

Sensitivity analysis is the examination of an

uncertain event under different assumptions.

Earlier we discussed discounting, concluding

that the precise discount rate was unknown, and

that a consensus may never be reached. Under

this uncertainty, one logical course for the analyst is to test the sensitivity of the results to several discount rates. For instance, one can test a

low, high, and middle value—an approach

which is most helpful when there is a wide range

of reasonable estimates. Or one can incrementally change the rate about the suspected mean

—an approach that is feasible when the range of
32 ● Background paper #l: Methodological Issues and Literature Review

possibilities is relatively narrow. In either case,

if the results of the study vary widely when the

different values are used, one can have less confidence in any single set of results. Conversely,

if the results change little, then the precise rate

may be unimportant. In some CEA/CBAs, the

decision criteria rest on the rank order of alternatives, not the absolute values involved, and

the analyst need only determine whether the

ranking itself is disturbed.

There are other approaches that increase the

confidence one can place in analysis in the face

of uncertainty (744). For instance, a technique

known as “worst case analysis” can be done by

assigning to the uncertain variables values that

least help the program (i.e., which the analyst

believes to be the preferred one). If the program

still is preferred, one can have more confidence

in recommending it. Another method is termed

“break-even analysis, ” in which assumptions

are varied until some minimally acceptable result is obtained; one can then ask whether the

assumptions are realistic. For example, a CBA

requires a value to be placed on life, yet there is

no generally accepted value. The value can be

varied upward, starting from zero, however,

until the analysis indicates that the program is

acceptable; then the value for life can be examined. Perhaps it is so low (say $1,000) that all

would agree that life was worth at least that

amount. In such a case, analysis can proceed

EXAMINING ETHICAL ISSUES

Ethical issues permeate both the process and

the use of CEA/CBAs in health care. Some of

these issues have already been touched on (e.g.,

valuing life), others have only been hinted at

(e.g., using uncertain information). In general,

there are powerful ethical arguments both for

and against using CEA/CBA-type studies to

help make decisions. The arguments for using

CEA/CBA center around the concept that

“some information is preferable to no information, ” whereas the arguments against tend to be

based on the actual or potential misuse of the

technique. Here, we will present a brief discussion of the ethical issues involved. Readers who

more confidently in the face of the extreme uncertainty of this critical variable. In other instances, the analysis will not indicate adoption

of the program unless a very high value is

placed on life. Here, the preferred course of action may not be so apparent. Techniques such as

worst case and break-even analyses are often

more helpful in identifying exceptionally good

programs than in ruling out bad ones. Nevertheless, these and other similar techniques can be

helpful in reducing uncertainty.

To summarize, sensitivity analysis can produce three important results:

1.

2.

3.

It can demonstrate the substantial dependence of a conclusion on a particular assumption.

It can demonstrate that an assumption

does not significantly affect a study’s conclusion, and hence that the tenuousness of

the assumption is not a source of concern.

It can establish a minimum or maximum

value which a variable must have for a

program to appear economically worthwhile.

Finally, uncertainty can often be reduced; it

should never be ignored. Results of a CEA/CBA

should be accompanied by statements regarding

the confidence which the reader can place in

them. A sensitivity analysis is most helpful in

this regard.

are interested in a more detailed discussion of

this topic are referred to appendix D of the main

report of this OTA assessment. That appendix

—“Values, Ethics, and CBA in Health Care”-

was prepared for OTA by the Hastings Center.

Some of the ethical arguments against using

CEA/CBA stem from the fact that the delivery

of health care itself has strong ethical overtones.

For instance, many public policies are directed

at eliminating or reducing financial and social

barriers to health care. Because CEA/CBA is

looked on by some as a rationing mechanism
Ch. 2—Methodological Issues ● 33

based on costs, there is bound to be resistance to

its use.

From a methodological standpoint, the ethical arguments against using CEA/CBA concern

the difficulty in valuing that which is often most

important: life, pain, happiness. They also concern the misuse of information. There is the fear

that quantified variables will take on undue significance, and that assumptions will be treated

as if they were fact. These arguments are particularly compelling since both the analyst and the

decisionmaker may be responsible for such

problems. For instance, this assessment finds

that the process of CEA/CBA is subject to systematic methodological bias, whereby a given

analysis can be “legitimately” performed in a

variety of ways, each of which may affect the

interpretation of the results. In addition, the

policy maker may ignore the traditional caveats

that are often, but not always, provided by the

analyst.

There are also many other inherent problems

that have ethical overtones, such as: 1) the value

of a benefit may vary across individuals, or may

be perceived to be different between the individual, society, or the relevant program (e. g.,

third-party payer), 2) the value of the benefit

may differ between generations, 3) the value of

quality of life is difficult to assess in comparison

with other effects such as increased longevity,

thus making tradeoffs difficult to analyze.

The counterarguments—by those in favor

of using CEA/CBA—acknowledge the ethical

problems, but say that if used in the proper

perspective such analyses can help by making

explicit the assumptions on which decisions are

based. The Hastings paper (app. D of the main

report) concludes: “We are persuaded that, in an

important sense, the defenders of cost-benefit

analysis are correct when they argue that policy

decisions in the health field are being made daily

on shaky grounds anyway, and that cost-benefit

analysis is at least an attempt—however imperfect—to ground those decisions in real needs

and real possibilities. The problem is not that

cost-benefit analysis is not objective and not

value-free, but rather that objectivity and valuefreedom are unjustifiably attributed to it. ”

PRESENTING AND INTERPRETING FINDINGS

We have mentioned the limitations to which

most CEA/CBA studies are subject: the uncertainty of many key variables; the difficulty of

identification and measurement of benefits and

costs; the inability to value and incorporate

many effects, such as ethical ones.

Implied throughout this chapter is the technical complexity of many studies. This type of

study can lead to misinterpretation of results

since: 1) the intended audience is often public officials or health care professionals, who may not

be technically oriented, and 2) study findings

are often reported in capsule form such as a

news brief and are often introduced in the professional literature in abstract form. Consequently, the writers and analysts must be particularly careful in the way they present the

results and interpret them for the reader. The

presentation of the findings should identify the

important variables and should discuss the confidence that the reader can place in the values

that were used. A review of the findings and the

significance of the sensitivity analysis, if used, is

ordinarily necessary to place the results of the

study in proper perspective.

There are also certain technical considerations that can significantly alter the way in

which a study is interpreted. The first is the use

of net benefit (that is, benefit minus cost), rather

than the cost-benefit ratio as a criterion to compare programs. The former (net benefit) approach is usually preferred, especially when the

alternative programs are widely variant in

scope. As an illustration, consider two programs:

Program A costs $2,OOO and reaps gross benefits of $4,000; program B costs $2 million and
34 ● Background Paper #1: Methodological Issues and Literature Review

reaps gross benefits of $3 million. A net benefit

approach yields the following results:

Program A Program B

$4,000 – $2,000= $2,000 $3 million – $2 million

=$1 million

Clearly, program B is preferred, given the ability to finance the project and setting aside for the

example all considerations of equity and distributional effects.

However, a benefit-cost ratio (B/C) would

yield the following results:

Program A Program B

$4,000 $3 million

$2,000 =2 $2 million

= 1.5

Now, program A is clearly preferred. Notice

that the ratio gives the reader no indication of

the size of the expected benefits, nor the size of

the program. Also, although program A gives a

better rate of return for the money invested,

there is no reason to believe that it can be increased in scale and still maintain the high rate

of return.

The B/C ratio is also sensitive to whether an

effect of a health program is considered as a

benefit or as a negative cost. In the discussion of

costs and benefits, it was pointed out that medical cost savings, resulting from an investment

in disease prevention/health promotion, are

treated as negative costs in a CEA (i.e., the “savings” are subtracted from the costs) and as benefits in a CBA. This distinction is technically important only when a cost-benefit ratio is employed; when costs and benefits are netted, it

makes no difference whether a particular item is

considered a benefit or a negative cost.

The interpretation of an analysis can also be

distorted as a result of problems of scale. For example, if it is impossible to compare equal cost

or equal effectiveness alternatives in a CEA, costeffectiveness ratios can be misleading. Consider

the following hypothetical case presented in

tabular form:

Lives saved

cost Program A Program B

$100,000 10 —

$200,000 – 15

C/E $10,OOO per $13,333.33 per

life saved life saved

According to the strict ratio rule, program A is

preferred; it costs less per life saved. But if there

is no possibility of replicating program A (i. e.,

saving another 10 lives for an additional expenditure of $100,000), might we not prefer program B? For $100,000 more than the cost of program A, it saves an additional five lives. Is that

not a worthwhile expenditure? It is at this point

that the question becomes largely a social or political one. CEA has contributed information

which may inform and assist social decisionmakers, but it has not produced an economically preferable conclusion. However, the CEA

technique is usually used to compare alternative

means to achieve some objective. In this case,

the decision to invest has already been made,

and the analysis is used to choose the most efficient method. Thus, if the decision has been

made to reduce deaths due to heart disease, the

cost per life saved may be compared between

blood pressure screening programs, inpatient

coronary care units, mobile coronary care units,

and cardiopulmonary resuscitation classes for

the general public. Alternatively, when operating under a budget constraint, the number of

lives saved per dollar amount available is compared between programs.

A related point is that an analysis for an existing technology should be performed at the

margin. That is, the additional cost of using one

more unit should be compared to the additional

benefit derived. In some instances, the additional cost is so small that one additional unit

will be extremely cost effective even if the expected benefits are small. In other instances, the

additional cost may not be large but the added

benefit is infinitesimal. Neither of these subtle,

but valuable, insights will necessarily be gained

if the analysis uses only average (as opposed to

marginal) costs and benefits. A marginal analysis will help to determine the optimal size of a

program and the point at which a given technology is no longer cost effective (468,559).
Ch. 2—Methodological Issues ● 35

LINKING ANALYSIS TO POLICY IMPLEMENTATION

As noted at the outset, a CBA/CEA should

consider all the relevant costs and benefits/effectiveness, regardless of to whom they may accrue or when they may occur. Also, although an

analysis can take on a program or organizational perspective as well, a CEA/CBA is ordinarily

performed from a societal point of view. In

identifying the appropriate societal costs and

benefits/effectiveness, these variables need to be

viewed from perspectives other than that of society, in order to make the analysis more relevant to public policy decisions.

It is frequently noted that ours is a pluralistic

society —one with many individuals and institutions making decisions that ultimately affect the

allocation of society’s resources. The field of

health care is no different. “Society” does not

make decisions; private consumers, physicians,

Congress, administrators of hospitals, managers of philanthropic organizations, and officials of medicare or medicaid and of local government agencies, and other people within society do. In addition to considerations of societal

efficiency, their decisions depend on such diverse notions as reimbursement guidelines,

community interests, the attracting of professional staff, intangible humanitarian objectives,

pride, financial solvency, and sometimes institutional survival (335,336).

Also, because of the manner in which health

care in the United States is organized and financed, there is ample reason to believe that the

objectives of key private individuals and institutions have an entirely different focus than the

objectives of society. For instance, in health

promotion/disease prevention programs, costs

are often incurred by a private party in the present, whereas benefits usually accrue in the distant future—and they accrue to others as well as

to the party who funded the program.

On the other end of the spectrum are diagnostic and therapeutic procedures. For these, private incentives tend toward overutilization. The

procedures are often paid for by insurance on a

fee-for-service basis; hence, increased utilization

tends to be financially rewarding to the provider

without being costly to the patient. This situation has given added emphasis to nonmarket

controls such as the certificate-of-need process

that health systems agencies require of an institution for major capital investments. Likewise,

the current interest in a hospital, or systemwide,

revenue cap perhaps stems in part from the lack

of financial incentives toward cost-decreasing

technologies (758).

All these reasons, then, lead to questioning of

the applicability of traditional, societally oriented CEA/CBAs. The problem is similar to

that of a mass screening program when there

has been made no provision for treating discovered disease. In both cases, the information produced is very important, but is useless unless a

system is in place to use it. Just as the answer in

the case of the screening program is not to discard the screening, the answer in the case of

CEA/CBA may not be to discard the technique.

The answer in part is to make the analysis more

relevant—by attempting to identify the private

objectives, and by noting when they conflict

with and when they support society’s objectives.

If this is done well, decisions may better reflect

reality.
3.

Literature Review
Contents

Page

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Methodology and Review Articles: Conveying Principles andPractice to the

Health Care Community. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Defining the Problem, Objectives, and Alternatives. . . . . . . . . . . . . . . . . . . . . . . . 41

Assessing Production Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

Identifying, Measuring, and VaIuing Benefits/Effectiveness and Costs . . . . . . . . . . 45

Benefits/Effectiveness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . * . $ * * **.**.... 48

Valuing Benefits and Costs Over Time: Discounting. . . . . . . . . . . . . . . . . . . . . . . . 50

Addressing Problems of Uncertainty: Sensitivity Analysis . ............. . . . . 50

Examining Ethical Issues. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Presenting and Interpreting Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Linking Analysis to Policy Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3 ■

Literature Review

INTRODUCTION

Application of cost-effectiveness analysis/

cost-benefit analysis (CEA/CBA) to health care

represents a fairly new endeavor. The novelty of

CEA/CBA within medicine has both positive

and negative reflections. On the one hand, the

growth in the literature demonstrates considerable enthusiasm for the technique; perhaps

more importantly, it may indicate increasing

cost consciousness within the medical community. Further, it might signal an increased awareness of the idea that a comparison of costs and

benefits has always been an implicit value of

health care decisionmaking—and that to allow

resource allocation decisions to continue to be

made, perhaps unwittingly, without more explicit consideration of the costs in relation to

benefits is not desirable. On the other hand, the

enthusiasm for CEA/CBA is often undisciplined, perhaps reflecting the inevitable growing

pains of any field of inquiry. The vast majority

of literature contributions whose titles identify

them as related to CEA/CBA have serious technical flaws or conceptual weaknesses in structure or interpretation.

Also included in the literature are many important exceptions to this general assessment.

Several studies exhibit both the desired technical

features and the potential to lend insight into

important issues of health resource allocation.

Through such examples, as well as direct “instruction” (e. g., articles that review methods,

cited below), a small cadre of skilled practitioners of CEA/CBA seems to be providing the intellectual leadership to improve the general

quality of the literature and advance the state

of the art. This group includes both physicians

and economists, and several of the recent exemplary studies have resulted from multidisciplinary collaboration (e.g., 472,575).

Two contextual aspects of the evaluation presented in this chapter warrant emphasis at the

outset. First, many of the limitations of health

care CEA/CBAs are endemic to—and, more importantly, inherent in—almost all CEA/CBAs.

For example, the inability of most health care

CEA/CBAs to incorporate distributional considerations (177,179) is shared by CEA/CBAs

on education, defense, energy, transportation,

and so on. This chapter attempts to identify generic CEA/CBA problems and to distinguish

them from problems that are specific to the

health care literature. The chapter also distinguishes problems that are resolvable from those

that are inherent in the process of analysis.

Second, literature reviews often restrict their

attention to the most prominent articles and

books in the literature, as is the case in the

earlier reviews of health care CEA/CBA identified in appendix A. There is a logic to this

approach: These publications reflect and indeed

create the state of the art; because they are

widely read, they have an influence on professional thinking and on future contributions to

the literature disproportionate to their numbers.

Nevertheless, such publications constitute only

the most visible portion of the literature. The

10, 20, or 30 articles repeatedly cited in health

care CEA/CBA reviews represent considerably

less than a tenth of the publications that can be

readily identified as part of this literature, often

by explicit inclusion of the words “cost-benefit”

or “cost-effectiveness” in their titles. A few such

publications are clearly mislabeled; many others

are on the right track but are so “poorly” handled that a CEA/CBA purist might exclude

them from a CEA/CBA bibliography. Even

though the less well-known publications have a

readership and general influence far smaller

than that of the more prominent contributions,

however, they may constitute the principal exposure of many practicing health professionals

to the language, concepts, and applications of

CEA/CBA.

In order to capture the essence of what CEA

CBA means to health professionals, it is impor39
40 ● Background Paper #1 : Methodological Issues and Literature Review

tant to critique the entirety of the literature.

Thus, this review represents an attempt to integrate typical-practice and state of the art features of the literature. The basis of the review is

an assessment of general tendencies in the literature as a whole, including the 90 percent that to

a large extent has escaped attention in previous

reviews. Common problems and deficiencies are

frequently counterbalanced by reference to successful attempts to address the deficiencies.

Thus, while this review adopts a generally critical stance toward the literature, it acknowledges

the many examples of technical proficiency in

the practice of health care CEA/CBA. For a review that concentrates on the high-quality end

of the spectrum, the reader is referred to the recent paper by Weinstein (569).

METHODOLOGY AND REVIEW ARTICLES: CONVEYING

PRINCIPLES AND PRACTICE TO THE HEALTH CARE COMMUNITY

All good studies inform readers about CEA/

CBA methods, either implicitly through its application (e.g., 122) or explicitly through discussion of methodological issues (e. g., 148). Recent

books have served several functions: attempting

to convey basic principles, break new methodological ground, and demonstrate the utility of

CEA/CBA through specific applications (73,

516). Over the years, however, there has been

only a handful of articles written solely to present or to evaluate the state of the art in health

care CEA/CBA.

During the period studied (1966-78), the first

two such articles were published in the first 2

years of the period. In 1966, Crystal and Brewster (722) wrote an introduction to CEA/CBA in

the health field. In 1967, Klarman published the

first of two prominent reviews he has written,

this one appearing in the American ]ournal of

Public Health (295). From then until 1972, no

significant health care review or methodology

contributions appeared in print, with the exception of a chapter by Grosse (241) in a book oriented toward students of economics and policy

analysis. That chapter is particularly noteworthy for its review of CEA/CBA applications

in the Department of Health, Education, and

Welfare (HEW) during the author’s tenure as an

HEW official, Grosse conveyed much of the

same material 2 years later in an article published in 1972 (240), though again the audience

was not specifically health care professionals.

That same year, however, witnessed publication of a book that has become one of the health

care community’s most widely read and frequently cited contributions, Cochrane’s Effectiveness and Efficiency: Random Reflections on

Health Services (97). This short book appears to

have had a profound and sustained impact in

turning the thoughts of health care professionals

toward issues of resource scarcity and the link

between efficiency and equity. It is at least

possible that Cochrane’s book played a significant role in the rapid growth in health care

CEA/CBA that began in 1973.

The most often-cited review and discussion of

health care CEA/CBA is Klarman’s second article (291), which appeared in 1974. The following year, Dunlop (153) published a review that

characterized the early literature, thus providing some interesting contrasts with current

CEA/CBA practice. In 1975, the major portion

of an issue of the New England Journal of Medicine (NEJM) was devoted to a discussion of

CEA/CBA methodology and to several illustrations of its application. To many observers, this

NEJM issue stands as a landmark in the evaluation of medical practice. It should be noted that

none of the previous reviews had been published

in a medical journal.

Two years later, another issue of NEJM offered readers a package of two articles and an

editorial, including a discussion of CEA methodology (574), a sophisticated application of it

(516), and an important, thoughtful treatment

of the limitations of formal analysis, including

the potential for a “tyranny of numbers” and

associated disregard of equity considerations
Ch. 3—Literature Review • 41

(177). Many health services researchers consider

this package, combined with Weinstein and Stason’s book (575), to be a milestone in health care

CEA/CBA.

A recent review was presented at an Urban

Institute Conference on Medical Technology in

December 1978 (569). This paper offered a stateof-the-art assessment of the literature and a

review of “a nonrandom sample” of health care

CEA/CBAs. The most noteworthy feature of

the paper is the author’s discussion of remaining

methodological issues. Although several of the

issues have been of concern since the inception

of formal CEA/CBA, others represent subtle,

sophisticated problems, the existence of which is

testimony to progress on more basic issues. Indeed, the paper serves as a vivid reminder simultaneously of the frustrating, seemingly intractable problems of CEA/CBA, and of the

gradual yielding of some of them to sustained

conceptual and empirical struggle.

DEFINING THE PROBLEM, OBJECTIVES, AND ALTERNATIVES

In a review of the early health care CBA literature, Dunlop (153) concluded that the most

common use of CBA had been to analyze disease-specific programs of intervention. By beginning with disease problems, several early

analyses had the opportunity to explore a wide

range of alternative interventions. For example,

the interest of LeSourd, et al. (327) in identifying efficient means of grappling with kidney disease led these investigators to compare the costs

and benefits of a variety of programs ranging

from prevention of disease to treatment of renal

failure. Similarly, Acton (4) employed both

CBA and CEA to examine several alternative

prehospital programs for reducing deaths due to

myocardial infarction. Even in studies of narrower problems—for example, the treatment of

existing disease—comparison of alternatives

characterized much of the early analyses. Thus,

the focus of Klarman, et al. (298) On kidney disease treatment precluded consideration of

prevention alternatives, but the authors examined all of the major therapeutic alternatives.

Most of the contributions to the early literature shared a focus on a problem and specific

objectives that had a distinct health (or disease)

starting point. At the extreme, HEW analysts

used CEA and CBA to examine resource allocation across a wide variety of disease and accident control programs (240,241). More narrow

problem definitions implied fewer and less disparate alternatives, but the health relevance of

the objective was generally clear. Thus Weisbred’s (577) examination of the costs and benefits of medical research was restricted to the case

of polio, but the analysis centered on the health

consequences of polio research and consequent

prevention of the disease.

In recent years, there have been numerous attempts to use CEA/CBA to analyze programs

having cIear health relevance (e.g., 122,472,

473,573), but two factors seem to be increasing

the proportion of studies whose health relevance

is implicit, tangential, or simply unclear. The

first is a tendency to assume that certain programmatic outcomes are desirable, without

questioning their ultimate health implications.

Common examples are studies that conclude

that certain screening efforts are “cost effective”

because they are inexpensive, but that lack any

exploration of the costs and health effectiveness

of followup of the cases found (133). The second

is a technical factor and reflects the current importance of cost containment as a health policy

issue. Much analysis has moved from a focus on

promoting health toward concern with achieving efficiency in the provision of existing health

services, including particularly a group of intermediate medical services whose ultimate health

impact cannot be discerned. In this case, the

question becomes how to provide a medically

accepted service most efficiently, without being

able to evaluate definitively (if at all) its health

implications.

Illustrative of this phenomenon is the CEA/

CBA literature on computed tomography (CT)

scanning, the single most studied technology of

67-774 0 - 80 - 4
42 ● Background Paper #1: Methodological Issues and Literature Review

the last 2 years examined in OTA’s bibliographic search (1977-78). As observed in chapter 1,

the CT scanner is the only expensive, equipment-embodied technology to have been the

subject of considerable CEA/CBA attention,

but it may be in the vanguard in this respect,

rather than being an exception. Furthermore,

the CT scanner exemplifies the difficulties involved in evaluating diagnostic procedures

(360,558,559), an area that has been identified

as deserving of much greater CEA/CBA effort

(569). Despite sharing the same technology–the

scanner—as a starting point, the authors of the

numerous CEA/CBAs diverge significantly in

their perceptions of the objectives of scanning

and hence in their evaluations of its cost effectiveness. At one extreme, the diagnostic effectiveness of scanning is assumed, with no attempt to link diagnosis to either patient management or outcome; cost effectiveness is measured

as the cost savings from using the CT scanner,

as opposed to alternative techniques, to perform

a given volume of diagnoses (211). At the other

extreme, effectiveness is defined in terms of effects in disease management and patient outcome (28). The latter seems the socially most

desirable concept of effectiveness, but the problems in its determination are substantial, and it

misses additional benefits such as those associated with decreasing patients’ uncertainty, directing short-term patient management, and

contributing to greater medical understanding

(2,32). Needless to say, the differing objectives

result in widely varying assessments of the desirability of scanning.

Determining objectives for purposes of analysis is frequently regarded as a trivial exercise,

but examples from the literature illustrate that it

may require considerable thought and that the

absence of such effort can damage the quality of

analysis. A failure to appreciate the limits of a

selected objective can mislead both analyst and

decisionmaker. For example, when HEW analysts decided to compare the cost effectiveness

of alternative disease control programs, they selected lives saved as the measure of effectiveness. This variable (and variants on it, such as

life-years or quality-adjusted life years (QALYs)

saved) is a common measure of health impact in

CEAs, but it is not a comprehensive one. HEW

analysts recognized this by observing that an arthritis control program could never be justified

on the basis of lives saved, but that the program

ranked as one of the better investments when

the benefits associated with disability avoided

were taken into account in a CBA framework

(240). Fairly few health care CEAs make explicit

reference to the nature of the biases their effectiveness measures introduce. It may be that

many such biases have not even occurred to the

analysts.

Fein (177) has noted the tendency of health

care CEA/CBAs to “relegate to a footnote” a

variety of nonquantifiable benefits (e. g., caring,

or reduction of pain). With a reference to both

intangible benefits and distributional effects that

cannot be valued, he noted that as “the numbers

gain currency . . . a ‘climate of opinion’ is created: that which is measured is important and

vice versa. ” This problem is common to analysis

in virtually all areas, though its importance is

probably greatest in the social welfare fields

such as health, education, and justice. In some

cases, though, benefits that are difficult to quantify or value have escaped even footnoting. For

example, in an otherwise sophisticated CEA

comparing hysterectomy and tubal ligation as

sterilization alternatives, Deane and Ulene (134)

ignored the preferences of the women involved.

The authors carefully analyzed the direct costs

of the procedures and indirect costs of complications and later disease, but the emotional reactions and feelings that might be expected to

dominate many women’s decisions received no

consideration in their analysis. Problems of

measuring and valuing intangible benefits pervade the health care CEA/CBA literature. They

are exacerbated by the failure of many analysts

to identify such benefits in specifying objectives.

In recent years, there appears to have been a

narrowing of problem definition in health care

CEA/CBA. Accompanying this has been a reduction in the number and scope of alternatives

examined through CEA/CBAs. The extreme—

an analysis of a single program or procedure,

with the only “alternative” being its absence—

has become reasonably common in the literature. Another development, exemplified by the

analyses of Eddy (157,158) and Schoenbaum, et
Ch. 3—Literature Review ● 43

a]. (472,473), represents an intermediate position between a single-program analysis and a

comparison of numerous qualitatively diverse

alternatives: Several analysts are using mathematical techniques to design or determine the

optimal (i. e., most cost-effective) structure of a

program by analyzing the effects of changes in

several parameters and assumptions (e. g., compliance rates, diagnostic accuracy, therapeutic

effectiveness). In essence, such analysts are examining a large number of “programs” of a single type. Even though confining analysis to a

single program type implies limitations, this approach holds the promise of making significant

contributions to policy understanding and program development.

ASSESSING PRODUCTION RELATIONSHIPS

Technical aspects of analysis clearly differentiate high-quality analyses from the more typical contributions. Nowhere is this more evident

than in the modeling of production relationships. A summary characterization of the difference is this: The better studies carefully consider

and address production issues, whereas the typical contributions adopt a “black box” approach

to production (that is, they observe existing programs’ inputs and outputs and ignore current inefficiencies and predictable future changes).

In part, this difference is legitimate, reflecting

the diverse purposes of analyses. Many of the

better studies have a prospective, or planning,

intent. The studies are oriented toward predicting the costs and benefits or effectiveness of

alternative future programs, so the analysts

model idealized versions of these future programs, recognizing significant variations from

current similar programs when such exist (e. g.,

scale, efficiency, relative costs, technological

change). By contrast, many of the more typical

analyses have a retrospective or evaluative purpose. In these the analysts wish to assess the performance of a program in terms of its realized

costs and outcomes. Even for this type of assessment, however, it is usually important to examine the black box of production so as not to attribute to inputs outcomes that occur by chance.

When the purpose is retrospective evaluation,

the identification and measurement of experienced inputs and outcomes are appropriate.

Often, however, it appears that authors who

have a prospective planning objective in mind

have not thought through the limitations of ex

post evaluation. Implicit in their analyses is the

assumption that existing programs are accurate

models of the alternative futures. Occasionally

this may be reasonable, but the assumption is

fraught with hazards. Common errors in the literature include:

●

●

●

●

●

failure to account for scale effects, i.e., taki ng an existing program (e. g., a worksite

hypertension screening and treatment program) and assuming that a national program intended to serve (say) 1,000 times as

many people will require 1,000 times as

many inputs (i. e., costs) and produce 1,000

times the output;

failure to consider how environmental factors might alter program inputs and outcomes (e. g., assuming that the production

function for an urban worksite hypertension screening and treatment program

would serve as a valid model for planning a

nationwide screening and treatment effort

both inside and outside of work settings);

ignoring predictable technical changes over

time (e.g., assessing the “future” of CT

scanning, assuming that the technology —

and hence inputs and outcomes—will not

change from what exists at present);

ignoring predictable increases over time in

the efficiency of operation of a technology

or program, i.e., the “learning curve” phenomenon (e. g., assuming that the performance of program personnel will not improve over time as they gain familiarity

and experience);

ignoring likely shifts in the relative costs of

inputs (e. g., the price—wage rate—of labor

rising more rapidly than the price of equipment) and consequent changes in the mix of

inputs used;
44 ● Background Paper #1: Methodological Issues and Literature Review

●

●

failing to identify avoidable inefficiencies in

the existing “model” program and thus inputing them to the structure and operation

of future programs; such inefficiencies

could reflect an inefficient input mix (e. g.,

having a high-priced technician perform a

function which could be automated inexpensively) or an inappropriate use of technology (e. g., condemning CT scanning as

exorbitantly expensive because it is used indiscriminately, rather than limiting uses to

those which are medically and economically justifiable); and

conversely, failing to anticipate that both

the inputs and outcomes of a carefully

monitored program in a major medical center may not be replicated as the program

diffuses into general practice.

Most of these deficiencies of ex post evaluation for prospective planning become more severe the more novel the technology or program

in question. A familiar, established, and successful program is more likely to represent a

good model for planning purposes than is a

new, or, especially, an experimental program.

Yet a major role of a forward-looking CEA/

CBA ought to be to assess the potential costs

and benefits (effectiveness) of a program before

it has diffused throughout the medical system.

CT serves as an excellent example of the great

difficulties of undertaking useful analysis early

to influence planning and decisionmaking.

These difficulties span the spectrum of applications of CEA/CBA, but they are particularly severe in an area such as medicine in which technological change occurs rapidly and frequently.

It was exceedingly difficult to perform an adequate analysis of CT scanning prior to its diffusion. Yet all of the studies in the literature relied

on that early experience for data, and most of

the early studies failed to anticipate changes that

have already occurred, only a few years following publication of the studies. Furthermore, anticipated changes in radiological technology

may make CT scanning technically obsolete

within a few years, yet the nature and amount

of relevant information are not adequate to incorporate this factor into an analysis intended

to assist planning. The CEA/CBA literature on

the CT scanner does not address this issue.

Formal modeling is difficult, a simple fact that

may account for the lack in much of the literature of imaginative, useful characterization of

production relationships. At a minimum, modeling requires talent in disciplined conceptualization; frequently, it also necessitates application of specific mathematical or formal

modeling skills. The latter, in particular, are not

available in abundant supply. Medical education generally includes no consideration of such

skills, and few analysts with appropriate training from other disciplinary backgrounds have

devoted their attention to health care CEA/CBA

issues. There are, of course, notable exceptions.

By example, through methodological contributions, and by direct discussion of issues, numerous authors improve both the current and future

state of the art of assessing production relationships. Review articles have communicated basic

principles, improving the critical abilities of

readers and, one would hope authors of future

studies. Specific CEA/CBAs in the literature

have illustrated skillful conceptualization, use

of mathematics, and formal modeling techniques (e.g., 22,122,134,157,159,479,480,516).

Mathematics and formal modeling can intimidate, impress, and confuse the uninitiated. In

order to put the formalism into proper perspective, it is imperative that authors clarify the implications of both explicit and implicit assumptions in the modeling and emphasize the limitations of their studies. There is a significant risk

that the uninitiated will be overly impressed

with formalism, so the caveats should be more

than simple disclaimers. Yet only a minority of

health care CEA/CBAs have taken this requirement seriously (e.g., 122,516).

High-quality analysis of production relationships does not require sophisticated modeling

efforts. A few studies have exhibited both elegant conceptualization and structural simplicity. For example, in their analysis of the national swine flu immunization program, Schoenbaum, et al. (473) considered the effects of varying acceptance rates, probability of an epidem-
Ch. 3—Literature Review ● 45

ic, and other factors in a manner that was tech- unsophisticated, the clarity of studies such as

nically sound and readily understandable. Par- this one probably serves to educate and to build

ticularly in the medical literature, which is read interest in well thought out CEA/CBAS.

by an audience that generally is mathematically

IDENTIFYING, MEASURING, AND VALUING

BENEFITS/EFFECTIVENESS AND

Benefits/Effectiveness

A central concern of many health care CEA/

CBAs, both conceptually and empirically, is

adequately capturing the health consequences of

programs. Only one such consequence lends itself to unassailable, objective measurement: reductions in mortality. Another common, if not

universally accepted, measure of health improvement, however, is reduced days of morbidity or disability. Neither of these measures

accounts for variations in the quality of the resulting days of less impaired health. Analysts

have adopted a few means of adjusting for this

quality factor, but to date there has been

nothing approaching consensus on specific

methods of adjustment.

Analysts’ inability to quantify satisfactorily

certain health benefits appears to be the primary

reason for their exclusion from formal calculations. A second reason is the difficulty of identifying what it is that patients seek and receive

from health care. As noted above, comprehensive analyses of the tangible costs and benefits

of treatment alternatives have sometimes ignored the emotional or psychological motivations that may lead patients to prefer one treatment over another, as if the patients were merely inputs into a physical production function

(134). In other words, patients’ objectives and

values are not limited to measurable physical

health improvement, and if patients’ objectives

do not represent social concerns, the very

reason for considering a health program is challenged. 1

‘There are instances in which the patients’ objectives and values

may be considered irrelevant, or at least secondary, to society’s

values. Care of the severely mentally ill patient represents an extreme example. Externalities and paternalism provide more common justifications. An example is a requirement that children receive certain immunizations prior to enrolling in school.

Obviously, the significance for an individual

CEA/CBA of the inability to quantify certain

benefits depends on the relative importance of

those benefits in the program under consideration. Certain health problems present seemingly

insurmountable barriers to the objective measurement of their benefits, yet their importance

has prompted analysts to grapple with them in a

CEA/CBA framework. Examples include mental retardation (99), mental illness (463), a n d

care of the terminally ill. Without succeeding in

quantifying the intangibles, the efforts of

analysts to deal with problems such as these

have contributed to an increased understanding

of the nature of the problems and the associated

programs.

For many health programs, the principal

health benefits are the more tangible, or quantifiable, reductions in mortality, morbidity, and

disability. Nevertheless, CEA/CBA assessment

of benefits (effectiveness) is far from problem

free. How does one measure and value benefits

(effectiveness) in units that are commensurable

with each other or with costs? Days of morbidity avoided, for example, are not directly comparable to days of mortality avoided.

In the health care CEA/CBA literature, there

are three principal approaches to this problem:

1) accepting it as an unresolvable problem, and

selecting a single (presumably dominant) outcome as the index of benefit or effectiveness; implicit in this approach is the assumption, or

hope, that nonmeasured benefits vary proportionately and positively with the single outcome

measure; 2) employing an index of health effects

or of health status; and 3) adopting one of two

methods of valuing major outcomes in monetary terms. The first two of these provide effectiveness measures for CEAs, while the third
46 ● Background Paper #1: Methodological Issues and Literature Review

yields the monetary benefit measurement

needed for CBAs. A fourth approach, rarely

found in the literature, would be to not force an

aggregation of effects or benefits. A possible

“array” method is discussed in chapter 4.

The first approach—the most common one in

the literature—is the easiest to accomplish and

perhaps to understand. It is also, however, the

least conceptually appealing, because of its unsatisfactory (often implicit) assumption that decreases in mortality, for example, correlate

highly with decreases in such factors as morbidity, pain, and suffering. A prominent example,

noted earlier, comes from the mid-1960’s HEW

disease control program analysis in which “lives

saved” served as the proxy for all health benefits

in the CEA comparison of programs. As the

analysts observed, “lives saved” as the effectiveness measure relegated arthritis to the bottom of the list of cost-effective programs. When

the programs were compared by means of costbenefit calculations, however, the ability to

reduce arthritis-related morbidity and disability

made the arthritis control program appear quite

competitive with the programs that saved the

most lives (240).

The single-measure index of effectiveness continues to dominate health care CEAs, but modifications point the way toward more refined

measures of health benefits. “Lives saved” is a

gross but important index of effectiveness for

many health programs. “Life-years saved” adds

an element of quality to the nature of deaths

averted. 2 This measure has been employed in

several CEAs. A further refinement involves adjusting the life-years to reflect the quality of

those years. Klarman, et al. (298) provided an

early example of quality adjustment in their

CEA study of alternative renal disease treatments. They argued that a year of life with a

well-functioning transplanted kidney was superior to a year of life on dialysis—given the time,

inconvenience, and discomfort associated with

the latter. Consequently, they arbitrarily valued

“’Life-years saved” is not clearly preferable to “lives saved. ”

Everyone would agree that more years saved per death averted is

preferable to fewer (other things being equal); but is lo-years

saved for one person preferable to 4 years saved for each of two

people? The answer is inherently subjective.

a year of life on dialysis as equal to 0.75 year

with a transplanted kidney.

The idea of quality-adjusting provided the basis for Weinstein and Stason’s (575) use of an index of health effects in their study of hypertension screening and treatment programs. Their

QALY involves adding changes in life expectancy to changes in quality-adjusted life expectancy

resulting from reduction in morbidity, and subtracting changes in quality-adjusted life expectancy due to iatrogenic illness and treatmentinduced side effects. Selection of appropriate

weights remains arbitrary and hence a problem.

An earlier attempt to develop a health status index produced weights (ranging from O to 1) that

corresponded to a spectrum from death to complete health (726). Despite the conceptual appeal

of such an index, the inherent weighting problems plus the so far inadequate empirical data

base have led to very limited CEA/CBA application of this type of index (79).

The third approach to valuing benefits in

commensurable units is to translate all quantifiable outcomes into monetary terms—benefit

measurement for CBA. A common approach,

monetary assessment of benefits is also the most

controversial approach in the evaluation of

health care programs. The principal issue, as

discussed in chapter 2, is the valuation of human life. As indicated in chapter 2, the human

capital approach employs a market measure of

the value of life, whereas willingness-to-pay

asks how people value their own lives, subject

to their ability to back up their valuations with

economic resources. Willingness-to-pay has

considerable conceptual appeal, but to date no

one has succeeded in developing techniques to

produce consistent and meaningful estimates of

willingness-to-pay (4). The human capital approach has its own conceptual attributes, but

with its imputation that the worth of a life is

determined solely by productivity, it has fallen

into disfavor among many practitioners of

health care CEA/CBA. Since the human capital

approach is empirically more manageable and

consistent, however, the vast majority of CBAs

have employed this form of valuation. This is

not to suggest, however, that the approach invariably has been applied correctly. Benefits
Ch. 3—Literature Review ● 47

should be measured as the costs of illness

avoided. Some analysts have used existing costof-illness estimates as direct measures of benefit, without recognizing that many of the illnesses avoided would have occurred years into

the future and hence that benefits should have

been discounted. This has had the effect of inflating benefit estimates, in some cases considerably (309).

In any given study, beyond the choice of a

basic approach to measuring benefits lies determination of the specific measure(s). In CEAs,

the effectiveness measure is often reasonably

obvious, with different analysts selecting similar

measures, thereby facilitating cross-study comparisons. Treatment of kidney failure provides

an example in which different analysts have selected the same measure of effectiveness—lifeyears saved—and despite a difference of 10

years in publication dates, their analyses have

produced consistent results (298,513). For some

topics, however, effectiveness measures are less

obvious, with the result that different investigators have selected qualitatively distinctive

measures and undertaken analyses that produced quite different and not directly comparable results. The problem seems especially relevant to the area of diagnosis (360). Its presence

in the literature can be anticipated to grow if

analysis of diagnostic procedures increases, as

some observers believe it should (569). Resolution of the problem, if possible, may lie in imaginative efforts to translate diagnostic accuracy

into effects on patient management and health

outcome. Among the CT papers, only Baker

and Way’s (28) attempted to do this. Their scaling of effects involved arbitrary and subjective

judgments, but Baker and Way’s effort stands

out as one of the few published attempts to

bridge the diagnosis-health outcome gap.

The literature includes few examples of such

efforts to grapple with challenging assessment

problems. Nevertheless, other approaches have

been adopted. A few studies identify and array

noncomparable measures of effects, including

rank-ordered ones (148). The argument underlying this approach is that if effects are important but cannot be measured in a common metric, decisionmakers will find it more useful and

less misleading to see them arrayed in an “unfinished” CEA (i.e., one lacking a “bottom line”

cost-effectiveness ratio) than to have one or

more of them dropped for the sake of calculating a “final” cost-effectiveness ratio. Despite its

“in completeness,” the CEA by Doherty, et al.

(148), for example, contributed information and

structure which can facilitate understanding of a

policy issue.

Consistent definition of effectiveness can vary

across health care functions. For example, mental retardation illustrates a substantive health

problem for which assessments of prevention v.

treatment necessarily involve quite different,

noncomparable measures of effectiveness. Prevention of retardation (e. g., through phenylketonuria (PKU) screening), is commonly valued in a cost-benefit framework for its ability to

avoid expenses of institutionalization and other

care by preventing the birth of retarded children; that is, the benefits of the program are future costs avoided (e.g., 78,79,482). By contrast, many of the desired effects of programs

providing care for an existing group of the retarded are less tangible and less economically

oriented; the “costs avoided” metric is clearly

inadequate (99). Obviously, the preventiontreatment effectiveness distinction is by no

means universally applicable. Analysts have

successfully relied on a consistent outcome

measure in comparisons of prevention and

treatment alternatives for kidney disease (327),

myocardial infarction (4,122), and others.

In addition to addressing all of the problems

noted above, analysts must identify and acquire

data needed to measure benefits. The quality of

data is rarely examined carefully in health care

CEA/CBAs, yet it is a common constraining

factor across most studies. Obviously, assessment of the health outcomes of a variety of procedures depends on the availability of valid,

reliable experimental or epidemiological data;

such data do not always exist, and even when

they do, they are not always accessible. Benefit

valuation for CBA requires in addition that such

data be translated into their economic implications. The methods for doing this are conceptually clear, and solid empirical assessment of the

costs of illness has been performed (385,721,
48 • Background Paper #I: Methodological Issues and Literature Review

747). Nevertheless, there are significant variations from one study to the next, implying that

use of differing estimation procedures and data

could compound spurious variations in benefit

estimates introduced by the use of different

health-outcome data sources. The issue of the

reliability and validity of cost-of-illness estimates is currently under study in a contract

funded by the National Center for Health Services Research. The National Institutes of Health

is in the process of publishing a bibliography of

some 2,000 references relating to cost-of-illness

estimation.

Data for several health care CEA/CBAs have

relied on subjective rankings, surveys, and the

like (4,28,78,79). The issue of how valid and

reliable such data can be has yet to be resolved,

though several studies find considerable variation depending on how survey questions are

phrased (4,550). Clearly, conceptual and empirical work on benefit assessment measures is a

pressing need in health care CEA/CBA (569).

Analysts in the United States have access to

more numerous and varied data sources than do

investigators in many other countries. Compared to the ideal, however, even U.S. data

sources exhibit serious deficiencies. Many surveys are plagued by poor methods, producing

unreliable data that contribute to misleading

analyses (565,740). The national data collection

effort is hindered by considerable duplication of

effort and inconsistency across data sets, both

resulting in part from a lack of interagency

coordination .

3 The development of better organized and planned basic data collection is essential to improving the quality of health care

CEA/CBA.

Two remaining benefit assessment issues are

noted here, with discussion deferred to later sections. One is the practice of discounting benefits, occasionally handled well in the literature,

frequently ignored. The other is analysts’ handling of distributional or equity concerns.

3This problem is discussed in some detail in Selected Topics in

Federal Health Statistics (74o), a report prepared by OTA in June

1979.

costs

Apart from the problems of measuring and

valuating benefits/effectiveness, the literature

reveals numerous examples of poor or inaccurate measurement and valuation of costs. Deficiencies associated with cost assessment are frequently more insidious than those associated

with benefit assessment, because authors commonly devote less attraction to them. Since authors often do not discuss cost analysis problems, they fail to alert readers to them; furthermore, the analysts themselves in many cases

seem unaware of the deficiencies of their approach, data sources, etc.

Costs are a reflection of resources consumed.

Thus, many of the difficulties that have plagued

cost assessment are perfectly analogous to those

discussed above in the examination of analysts’

handling of production relationships. Rather

than repeat that discussion, this section simply

notes several common problems: 1) often analysts have measured realized (ex post) costs in

an analysis intended for prospective planning

without allowing for learning, technical, and

economic changes which seem likely to occur;

2) they have failed to distinguish the cost implications of running programs under optimal v.

average conditions; 3) they have not always accounted for the differential valuation of costs

occurring at different points of time (the discounting problem, discussed in the next section).

Just as there are problems unique to benefit

assessment (e.g., valuation of lives saved), certain problems hinder cost analysis in particular.

Chief among these in the health care literature is

the use of inaccurate or inadequate proxies for

true costs—a significant problem because of its

pervasiveness and, evidently, the failure of

many investigators even to be aware of it. A

major source of inaccuracy is the use of market

prices as measures of costs. The assumption that

prices closely mirror true costs seems reasonable

in some smoothly functioning markets, but

market imperfections can distort the relationship between input prices and their true opportunity costs. This common problem reaches its

extreme—and hence introduces the most significant distortions—in cost assessment in health
Ch. 3—Literature Review ● 49

care programs, particularly those associated

with hospitals. In health care CEA/CBAs, the

use of prices in lieu of true opportunity costs

generally means adoption of published charges

(e.g., from hospital billings or insurance

charges) as the index of cost. Although occasionally analysts recognize that charges may not

accurately mirror costs, very often the problem

is not even acknowledged (92). The vast majority of health care CEA/CBAs employ charges

uncritically, frequently introducing potentially

large errors in the estimation of the true costs of

the programs in question. At a minimum, analysts ought to explore the relationships between

charges and actual market costs.

Inadequate cost assessment often results from

failure to take into account costs which are real

but hidden. For example, very few health care

CEA/CBAs account explicitly for the costs of

patients’ time traveling to medical facilities and

waiting for and receiving services. CBAs occasionally capture some of this by valuing lost

productivity, but, most commonly, lost productivity measurement relates only to days of morbidity, disability, or mortality avoided, and not

to hours involved in seeking and receiving care;

and lost productivity is not the only time cost

associated with health care services.4 This problem is exacerbated, however, by the fact that

many employees are covered (e. g., through sick

leave) for time off from work for medical visits.

Thus, neither the physician nor the patient perceives the time as “lost,” and analysts sensitive

to the time-cost issues might overlook the fact

that the time imposes real costs on society (e.g.,

physical productivity lost).

‘That people value such lost time is demonstrated by the willingness of many individuals to accept significant charges from private

physicians m lieu of waiting a long time in lower cost medical clinics. The waiting-time mechanism of rationing medical services is

highly inefficient socially, producing a “deadweight loss, ” that is,

patients lose their free time, and no one gains directly from that

loss.

A second example of reaI costs that have

escaped attention in health care CEA/CBAs is

the value of volunteers’ time mentioned in chapter 2.

An unresolved cost assessment issue is whether analysts ought to assume efficiency in program operation or build in “slack” for likely inefficiencies. The former is appropriate for evaluating the ideal, but the latter seems more likely

to reflect what will come to pass should the program be implemented. This issue has received

virtually no attention in the empirical literature. Common practice has been to measure resources used in programs, rather than to identify efficient resource use, but only a few studies

suggest that the investigators have even contemplated the difference.

A technical cost issue of considerable importance derives directly from the discussion in an

earlier section of the relative lack of attempts by

analysts to distinguish marginal from average

resource consumption. Most commonly, authors have used average total costs of existing

programs to predict the costs of program expansion, modification, etc. When capital costs are

substantial or marginal costs vary significantly,

failure to distinguish marginal from average

costs can produce, and often has produced, misleading cost estimates. Although some analysts

have demonstrated sensitivity to the distinction,

direct extrapolation from average costs dominates the health care CEA/CBA literature.

As in the case of benefit measurement, data

availability and quality problems hinder effective cost analysis. For example, data on charges

are relatively accessible, but many cost data (in

particular, data needed to reflect opportunity

costs) are not. The current interest in cost containment has promoted governmental efforts to

acquire more and better cost information, but

the acquisition and appropriate use of cost data

will linger as a major problem in CEA/CBA for

years to come.
50 ● Background Paper #l: Methodological Issues and Literature Review

VALUING BENEFITS AND COSTS OVER TIME: DISCOUNTING

The discounting of benefits and costs realized

over time is one of the most technical features of

CEA/CBA. It is also one of the principal sources

of analytical weakness in the health care literature. Owing to the potentially profound influence of discounting on valuation of costs and

benefits (effectiveness), the absence of discounting in numerous health care analyses severely

discredits those analyses. In addition, the failure

of some investigators to test the sensitivity of

their findings to the value of the discount rate

raises questions about the robustness of those

findings. (Sensitivity analysis is discussed in the

next section of this chapter. )

The literature is replete with examples of the

total absence of discounting. In the studies that

have employed discounting, the basic method is

generally sound; that is, discounting has been

done either technically well or not at all. However, only a minority of the studies that have

used discounting have included examination of

the effects of the value of the discount rate on

the bottom line regarding net benefits or cost effectiveness. Yet, as several of these studies demonstrate, when significant realization of costs or

benefits occurs well into the future, the discount

rate selected and the method of discounting can

play pivotal roles in determination of a program’s value (513,572). For example, in her

study comparing programs to treat or prevent

myocardial infarction, Cretin (122) tested the

sensitivity of her cost-effectiveness estimates to

variations in the discount rate. The prevention

program—screening of school-age children for

high cholesterol—necessarily involved benefits

deferred well into the future. With costs and

benefits undiscounted, the net cost per year of

life saved ranged from $2,441 to $2,855, depending on assumptions. Discounting at 5 percent produced a cost per year of life saved of

from $9,353 to $12,640. At 10 percent, discounting caused the figures to leap to $66,660 to

$94,460. These estimates compared with a range

of $1,782 to $6,100 per year of life saved by

treatment alternatives, depending on the program and the discount rate. Cretin’s article not

only demonstrated the proper application of

discounting, but it emphasized the dramatic effect that varying the discount rate can have on

net cost estimation and hence on comparison of

program alternatives.

A general CEA/CBA discounting question

has received attention in the recent health care

literature: Should effectiveness measures be discounted? Empirically, the question has been

answered in the affirmative by Cretin (122),

Stange and Sumner (513), and Weinstein and

Stason (573), each of whom discounted effectiveness measures of mortality avoided in the

future. The logic of discounting effectiveness is

quite appealing, but the practice is fairly novels

‘Some analysts have argued that society’s interests in intergenerational equity, and in the future more generally, imply a social

rate of time preference lower than the opportunity cost of capital,

and hence that the former (lower) rate should be used to discount

“benefits (effectiveness) and the latter (higher) to rate costs. This

conceptual issue has not arisen in the empirical studies in the

health care CEA/CBA literature. However, it is interesting to note

that both individual and public decisions suggest that people often

behave in quite the opposite manner. For example, conscious decisions to continue smoking imply a heavy discounting of the future

relative to immediate gratification. At the societal level, public decisions to fund renal dialysis, rather than kidney disease research,

screening, and prevention suggest a high social rate of time preference. Of course, this logic assumes that, as individuals and a collectivity, we can interpret the abstraction of a future death averted

by prevention as the same “commodity” as postponement of the

death of a visibly ill individual. Obviously, we cannot do this.

Nevertheless, behavior and decisions are far from being consistent

with a low social rate of time preference.

ADDRESSING PROBLEMS OF UNCERTAINTY:

SENSITIVITY ANALYSIS

The discount rate is only one of numerous po- noted in chapter 2, it is a rare study that can be

tentially significant influences on the magnitude carried from conception to empirical conclusion

of cost and benefit (effectiveness) estimates. As without the necessity of the analyst’s making
Ch. 3—Literature Review Ž 51

assumptions to substitute for uncertainties, data

unavailability, conceptual problems, and so on.

Despite this, it is not common practice in health

care CEA/CBAs to test the significance of assumptions. Frequently, analysts do not carefully distinguish between assumptions and

sound empirical observations.

Of the possible uses of sensitivity analysis to

address uncertainties, only one has been applied

with any degree of frequency in the literature:

the direct testing of findings to determine if they

are sensitive to important assumptions. Even

this most common application of sensitivity

analysis has been used rather infrequently, and

with a few notable exceptions, it has been used

primarily for testing sensitivity to discount

rates. The ability of sensitivity analysis to determine whether a major uncertainty precludes a

definitive analysis does not appear to have encouraged analysts to tackle health care evaluation problems in which such uncertainties were

obvious at the outset. Nor have analysts used

measurable costs and benefits to establish minimum or maximum values for quantified variables in order for a program to appear worthwhile. However, a few studies have approximated such uses of analysis. Centerwall and

Criqui’s (86) assessment of thiamine fortification of alcoholic beverages allowed them to

avoid valuing health benefits, since net cost savings were positive.

Cretin’s (122) testing of the sensitivity of findings to variations in the discount rate illustrates

art appropriate use of sensitivity analysis in its

most common application. As Cretin’s analysis

demonstrated, program evaluation is highly

sensitive to discounting when significant benefits (or costs) are deferred well into the future, a

characteristic of many prevention programs.

Discounting the costs of the cholesterol screening program by 10 percent instead of 5 percent

increased costs per year of life by over 600 percent; for the treatment alternatives, the benefits

of which are more immediate, however, the corresponding increase in costs was on the order of

50 percent. The potential for such dramatic differences explains why “responsible analysts usually offer the user of analysis a sensitivity

analysis with respect to the discount rate used”

(569).

The authors of several of the more highly regarded studies have also tested the sensitivity of

findings to other uncertainties. For many health

care programs, patient acceptance or compliance is both a crucial variable and uncertainty,

and hence a worthy candidate for sensitivity

testing. The literature provides several examples. Schoenbaum, et al. (473) examined the effect of acceptance on the optimal structuring of

the national swine flu immunization program.

Eddy’s (158) analysis of breast cancer screening

also related such factors to program design.

Weinstein and Stason’s (573) study of hypertension control demonstrated how patient compliance can influence the outcomes of a CEA of disease management.

The literature offers only a few examples of

sensitivity analysis applied to other cost and

benefit (effectiveness) estimations, but those few

are instructive. For example, LeSourd, et al.

(327) found that the absolute magnitudes of individual benefit-cost ratios of kidney disease

control alternatives were quite sensitive to

variations in program size, target screening

group, etc., but the relative rankings of the major programmatic alternatives (e.g., screening v.

treatment, and within the latter, transplantation

v. center dialysis v. home dialysis) were unaffected by the tested variations. In addition to

testing sensitivity to the discount rate, Cretin

(122) included high and low direct cost estimates

for the screening program. The analysis demonstrated less sensitivity to the direct cost estimation than to discounting.

The use of sensitivity analysis reflects a more

sophisticated appreciation of CEA/CBA than

that which characterizes most of the existing

health care literature. At one level, inclusion of

thoughtful sensitivity analysis multiplies the

number of figures in an analysis and can add

considerable complexity to the presentation and

interpretation of findings. However, both logic

and empirical evidence indicate that the assumptions of an analysis can affect results significantly. Thus, both the credibility and useful-
52 ● Background Paper #1: Methodological Issues and Literature Review

ness of CEA/CBA would be increased by more

frequent and judicious use of sensitivity analysis. With the exception of a handful of highquality studies, the existing health care CEA/

CBA literature lacks credibility in part because

issues of sensitivity are addressed so rarely.

The use of sensitivity analysis carries with it a

risk: A “solid” finding can dissolve under the

EXAMINING ETHICAL ISSUES

As noted earlier, one of the limitations of

CEA/CBA is its inability to handle distributional issues. Health care CEA/CBAs rarely

have grappled seriously with distributional issues, Obviously, selection of a topic to study

may be an implicit statement of concern with

distributional issues, though it is expressed in

terms of the objective of the analysis rather than

as an analytical variable in the CEA/CBA (e.g.,

the relatively large CEA/CBA literature on

mental illness or geriatric services). Health care

CEA/CBA should not be singled out for its failure to incorporate distributional considerations

successfully. This is the general state-of-the-art

and perhaps reflects one of the inherent limitations of this form of analysis. But emphasis on

this limitation is particularly important in the

health care literature where a readership relatively unfamiliar with the technique may be unduly impressed by formalism and its derivative

conclusions, failing to place those conclusions in

their proper distributional context. Many health

care CEA/CBAs identify this concern, but it

seems buried by the analysis which follows and

thus is frequently ignored (177).

The literature offers few examples of attempts

to address the problem of differentially valuing

scrutiny of sensitivity analysis, and “nonresults”

are less exciting and potentially less acceptable

than definitive ones. Nevertheless, intellectually

and from the perspective of the policymaker, accurate nonresults clearly are preferable to artificially precise ones. The bulk of the existing

literature does not allow distinguishing between

these.

the costs and benefits accruing to different

groups of people directly. Nevertheless, the

equity concern most often debated in the literature— the valuation of life—clearly relates to

this fundamental problem, for in CBA benefits

are estimated according to one’s productivity

(the human capital approach) or affluence (the

willingness-to-pay approach). Less often recognized is that CEA effectiveness measures presumed to be “value-free” generally imply values. The trend of the literature away from CBA

and toward CEA may reflect growing distaste

for explicit valuation of life or the belief that

both conceptual and empirical limitations make

the effort a “quixotic quest for a value of life”

(569). Of course, alternatively, or in addition,

the growing preference for CEA may simply reflect the fact that CEA is easier to understand

and perform.

The appropriate handling of distributional

issues remains one of the least developed features of CEA/CBA in the health care literature

and elsewhere. Even though both theoretical

and empirical progress can be anticipated (569),

the major problems of dealing with equity concerns seem unlikely to be resolved in the foreseeable future.

PRESENTING AND INTERPRETING FINDINGS

As emphasized throughout this report, two often seriously restrict the possibility of arriving

factors place a major responsibility on analysts at unequivocal, definitive conclusions; 2) the

to present and interpret their findings carefully readership of health care CEA/CBA is generally

and clearly: 1) technical limitations (inherent in unsophisticated about the techniques of this

analysis or in the abilities of particular analysts) form of analysis, though this situation is chang-
Ch. 3–Literature Review ● 53

ing. In addition, numerous readers will focus

on, if not limit their attention to, the abstracts

and conclusions of articles.

An overall assessment of the health care

CEA/CBA literature suggests that relatively few

analysts have addressed this responsibility successfully. Those few are generally the authors of

the studies identified as technically high quality.

Of course, the handling of the presentation and

interpretation of findings is a characteristic

against which the quality of analyses is judged,

but it appears that a thoughtful, useful conclusion to an analysis tends to follow a technically

and conceptually well-conceived study. Examples abound. The analysis by Schoenbaum, et

al. (473) clearly identified factors that could influence the success and optimal structure of the

national swine flu immunization program. Cretin’s (122) concluding analysis and remarks

clarified the crucial role of discounting and demonstrated the need to interpret the sensitivity

analysis. Cretin purposefully and constructively

made it impossible for the reader to conclude

that there was an obvious “best” approach to reducing the toll of myocardial infarctions. Stason

and Weinstein (516) discussed how compliance

and a variety of other factors could affect their

conclusions, though Fein (177) still found it necessary to emphasize limitations. Doherty, et al.

(148) emphasized information organization and

presentation in their assessment of health programs for the elderly; they refused to “reduce”

their analysis to a “bottom line. ” The authors of

all such studies seem to be motivated by “the

philosophy that it is not so much the results of a

[CBA/CEA] that are likely to have an impact on

policy as the process of structuring information

in a systematic framework that highlights the

key uncertainties and the most important value

tradeoffs” (569). This is inevitably reflected in

these analysts’ presentation and interpretation

of their findings.

By contrast, most health care CEA/CBAs

seem oriented toward a “bottom line’ ’—generally the estimation of a benefit-cost or cost-effectiveness ratio. Aside from questions of measurement underlying the cost and benefit (effectiveness) components of these ratios, even this

basic “bottom line” has been technically misinterpreted in numerous studies. At the extreme,

at least one article with a title beginning “CostBenefit Ratio . . .“ does not contain a single

cost-benefit ratio. Few analysts exhibit awareness of the deficiencies of a benefit-cost ratio as

compared with a measure of net benefits. The

benefit-cost ratio clearly dominates in empirical

health care CBAs.

Cost-effectiveness ratios, and the words “cost

effective, ” are employed even more uncritically

than are benefit-cost ratios in CBAs. In many

articles, “cost effective” refers to one of the two

words but not both: That is, some authors have

employed “cost effective” when they mean that

a program or technology is effective, irrespective of cost; and other authors have used “cost

effective” to connote “cheap, ” irrespective of effectiveness. There are several instances of purported CEAs in which only a single program or

technology is examined and is then adduced as

being cost effective, despite the absence of an

alternative against which to compare it (133).

Subtleties of technical interpretation of CEA/

CBA “bottom lines” largely have escaped attention in the health care literature. Only a few

analyses demonstrated awareness that “cost effectiveness” of a use of a technology need not

imply overall cost effectiveness. For example, in

certain delivery settings, an automated electrocardiograph (EKG) may be more cost effective

than a manually read EKG, but if the ease and

availability of the former lead to excessive use,

the national EKG bill might actually rise without necessarily contributing to improved health

(18). Perhaps the most dramatic demonstration

of the difference between average and marginal

cost effectiveness was Neuhauser and Lewicki’s

(397) estimation that the cost per additional case

of colon cancer found by repeated stool guaiacs

rose from under $1,200 for the first stool guaiac

to $47 million for the sixth!

Even when the use of a ratio or net benefit

measure is technically correct, lost in such a

number are the assumptions that underlie it and

the intangible unmeasured costs and effectiveness that are excluded from it. A few studies

have presented results in a manner that makes

these factors clearer. The most common strategy has been careful discussion of how the “bot-
54 Ž Background Paper #1: Methodological Issues and Literature Review

tom line” could be affected by such factors. A1- and their (noncommensurable) effects. This apternatively, some authors have presented ranges preach does not yield a conclusion as to which

of results reflecting sensitivity to assumptions of several competing programs is the “best,” but

(122,327). A third approach, less commonly it does array alternative sets of consequences efadopted, has been to step back from the bottom fectively and thereby might aid decisionmakers

line and provide a tabular display of programs by clarifying tradeoffs (148).

LINKING ANALYSIS TO POLICY IMPLEMENTATION

In health care studies as elsewhere, the gap

between CEA/CBA studies and policy formulation almost invariably has been bridged by a

leap of faith that assumes a theoretically desirable program can be translated readily and

directly into an operational one. Health care

CEA/CBAs always have had a policy orientation, but the literature is nearly devoid of

empirical attempts to make the adjustments

(needed to reflect political and cost realities)

proposed in the new literature linking analysis

to policy implementation (336). Health care

CEA/CBA perhaps should not be faulted for

this lack; the implementation literature is simply

too new.

Luft (336) in a contribution to the implementation literature, used two health care examples,

development of freestanding surgicenters and

use of work evaluation units “for objective

testing of functional work capacity to supplement the usual information concerning the

health status of patients who have recently had

a myocardial infarction. ” Through these examples, he demonstrated how role players’ differing interests can block implementation of socially desirable programs, and how analysts can use

recognition of differing interests and influences

in developing predictive CBAs. Empirical application of this important conceptual contribution

might increase the realism and usefulness of

CEA/CBAs.

CONCLUSION

The assessment in this chapter of the quality

of the health care CEA/CBA literature has relied primarily on judgments of how the practice

of analysis compares with a set of theoretical

Though not formally employing Luft’s approach, a few studies have observed how interests might be expected to block or inhibit implementation of socially desirable programs. In

a recent study which concluded that in certain

large delivery settings, automated electrocardiography may represent a cost-effective alternative to traditional manual readings, for example, the investigators suggested that diffusion

of this technology might be inhibited by cardiologists, to whom it could represent a threat to

reading fees and a change in referral patterns

(18).

Another proposal that can be found in the literature is that analyses should build in a consideration of the sensitivity of basic findings to

unanticipated cost overruns. We are not aware

of any health care CEA/CBAs that have done

this, but there are numerous examples of studies

in which it might have been done. One example

is the study by Schoenbaum, et al. (473). These

analysts could not have anticipated the Guillain-Barre syndrome—and the resultant costs—

which accompanied the national swine flu immunization program. The program experienced

significant additional production and distribution costs, however, and the analysts might

have explored the implications of unanticipated

cost overruns. Analyses of future proposed public health programs might consider doing so.

standards. Two caveats related to this approach

must be recognized. One is that words like “cost

effective” have been used in the literature much

more freely than they would have been had all
Ch. 3—Literature Review ● 55

authors meant to adhere to strict CEA/CBA

definitions. Nevertheless, since articles employing these words freely contribute to the

health care community’s perception of the

meaning of terms and uses of analysis, it is appropriate to include them in a review of CEA/

CBA literature.

The second caveat is that several of the standards of ideal (or idealized) analysis may be unattainable. If so, a review of the literature will

necessarily have a critical tone. Many of the

flaws of the health care CEA/CBA literature reflect inherent, or at least very common, analytical problems. Examples include difficulties incorporating distributional concerns into formal

analysis and deficiencies of data accessibility,

quality, and consistency. Some common CEA/

CBA problems impose unusually severe burdens

on health care studies. The difficult and often

controversial valuation of less tangible costs

and benefits, such as the saving of life and reduction of physical suffering and emotional distress, is often central to the health care analyst’s

chore. Even more basicalIy, the estimation of

production relationships seems particularly

challenging in health care, where the difficulty

of attributing health outcomes to health care inputs has led many scholars to rely for evaluation on intermediate (nonoutput) measures such

as structure and process. Technical change occurs with such extraordinary rapidity that

forward-looking health care CEA/ CBAs are

particularly handicapped. Furthermore, even

some commonly accepted “second-best” CEA/

CBA practices are hard to justify in health care

CEA/CBA, one example being the use of market prices as measures of true opportunity costs.

Not all of the flaws in the health care literature are attributable to inherent difficulties.

The relative novelty of CEA/CBA in health care

seems to account for the exaggerated importance of several errors. Representative are the

absence or mishandling of discounting and the

presentation of purported CEAs that examine

only one program (i. e., no alternatives) and

conclude that it is cost effective. More significant is the tendency of investigators to use

purely retrospective evaluation of existing programs to develop policy proposals for the future, with little or no regard for the changes that

will transform the structure and functioning of

such programs. Many studies are plagued further by the “black box” approach to ascertaining production relationships: The identification

of inputs and outputs without devoting sufficient attention to the efficiency of production,

or even to basic questions of causation versus

correlation.

By contrast, the best of health care CEA/

CBA makes the novelty of the literature a

source of encouragement. A handful of skilled

analysts are breaking methodological and substantive ground, working on evaluative techniques, and producing informative, thoughtprovoking analyses. In recent years, investigators have demonstrated how analysis can yield

insight into the nature of timely policy issues

(473),’ contribute to efficient program planning

(158), grapple with technical evaluation problems (573), and address inadequately studied

technical aspects of medicine, such as diagnosis

(360,559). Such works may presage a variety of

interesting, useful developments in a field whose

novelty provides a set of wide-open methodological and substantive opportunities.

Illustrative of recent methodological developments of considerable promise is the growing

analytical comprehensiveness of CEAs and the

trend away from comparing direct program

costs with single-outcome measures of effectiveness (e.g., “lives saved”). Recent efforts to

incorporate indirect costs and develop more inclusive indexes of effectiveness (e. g., QALYs)

have begun to transfer a major virtue of CBA–

its comprehensiveness—to CEA, while greatly

reducing the accompanying problem of explicitly valuing noneconomic health benefits. Several

studies demonstrate comprehensive cost ac -

counting, with both positive costs and “negative

costs”—indirect economic benefits—aggregated

“The analysis of the national swine flu immunization program

(473) was conceived, in part, as an experiment to see whether a

formal analysis, relying heavily on concurr~~nce [~t expert (~p]ni(~n

(through use d a Delphl), could be accomplished qu{ckly–pr[(~r

to a p(llicy decision —and still prwtuce usetul lntOrmatlOn. Despite

its lim i tat i(>ns —tailure to anticipate w>cial, legal, and medical

problems and their ec(>n[~mic sequelac —the analysis served t[> ln -

f(~rm and put issues into perspective for much ot the health care

community.
56 ● Background Paper #1: Methodological Issues and Literature Review

on the cost side of the CEA equation. The remaining noneconomic values constitute the programs’ effectiveness. In some instances, the remaining effectiveness measure is a simple single

outcome —sterilization, for example (134)–

while in others it is a more complex index, such

as QALYs in hypertension control (573). In still

others, effectiveness measurement or valuation

is made irrelevant by the fact that complete cost

accounting indicates a positive net benefit before “remaining effectiveness” is taken into account (86). The narrowing of the gap between

CBA and CEA is made vividly clear by this last

case. It is also interesting to note that Cretin

(122) called her study a CBA, yet she did not

place a dollar value on years of life saved and

she presented results in terms of costs per added

years of life—a typical CEA “bottom line. ” One

might be tempted to dismiss this as a case of

mislabeling, but in fact the growing economic

sophistication and comprehensiveness of CEAs

have introduced a healthy terminological

ambiguity.

OTA’s assessment of the quality of the literature has relied on a comparison of practice to a

set of theoretical standards. Nevertheless, there

are other bases for assessment of quality. For example, if one believes that quality is best reflected in the validity and reliability of results,

one might seek internal or external measures of

validity and reliability. An example of an internal measure is comparison of findings across

studies of the same topic. To be sure, one must

be wary of one study’s replicating the method of

earlier studies, or of use of the same data

sources leading to a shared bias (i. e., consistent

but not valid results). In the absence of a shared

bias, however, consistency of results is suggestive of meaningful findings.

The literature does provide a few cases of

multiple analyses of a single subject. Studies of

renal disease treatment offer an excellent example. Two contemporary analyses ranked treatment alternatives in the same order —transplantation being most cost effective in one study

(298) and cost beneficial in the other (327), followed in both studies by home dialysis, and

last, center dialysis. These results were confirmed in a study published 10 years later using

more recent data (513), Similarly, three separate

studies of PKU screening concluded that this is a

socially desirable medical practice (78,517,553).

By contrast, analyses of CT scanning have produced widely discrepant findings, reflecting differences between head and body scanning, technical changes (realized and anticipated) over the

time period covered by the studies, and differences in investigators’ perspectives as to what

constitutes effectiveness in scanning or, more

generally, in diagnosis (2,28,211). Although a

systematic comparison of analyses on single

subjects was not attempted in this review, that

might prove to be an enlightening approach to

evaluating the literature.

Assessment of the quality of individual contributions to the literature has received primary

attention in this chapter. Chapter 1 and appendix A examined the overall composition of the

literature, but “quality” judgments were limited

to observation of the conspicuous absence of

certain substantive concerns, such as important

disease problems (e.g., diabetes) and medical

techniques (e.g., a large number of diagnostic

techniques other than screening). Here it should

be noted that an interesting indication of the

overall composition of the literature is the mix

of CEA/CBAs with positive and negative findings. If some medical practices are socially and

economically desirable and others undesirable

(or of questionable desirability), one might expect a “balanced” literature to include a good

mix of positive and negative findings. A lack of

balance certainly need not reflect poorly done

individual studies. Rather, it might result from

analysts’ having a systematic bias in favor of

studying desirable or undesirable programs. For

example, if CEA/CBA were applied primarily

to analyzing programs whose worth has been

challenged, one might anticipate a preponderance of negative findings in the health care

CEA/CBA literature. A preponderance of positive findings could follow from medical professionals’ analyzing (or commissioning analyses

of) projects whose diffusion into practice they

favor. Dominance of either positive or negative

findings might reflect systematic underestimation or overestimation of either benefits or

costs. For example, as discussed above, few
analyses include a realistic assessment of the

costs of implementing a policy and of the possible dilution of benefits that may follow. These

factors should produce overly optimistic results,

i.e., they introduce a distinct bias toward

positive findings. On the other hand, many

health care programs are characterized by important intangible benefits, the value of which

frequently is not incorporated into analysis.

This factor introduces a bias toward unduly

negative findings.

The reading of the literature suggests a dominance of studies having positive findings. To be

sure, there are notable exceptions, with some

analyses producing distinctly negative findings

(28,365,397,570) and surprisingly few deriving

equivocal results (11). 7 Also, there may be a

shift taking place, with movement from the

positive toward the negative. This could reflect

the general questioning of medical technology

and growth of cost consciousness, both of which

emerged strongly in the 1970’s.

Chapter 1 noted that this report was restricted

to considering personal health care services. In

concluding this review of the literature, it seems

appropriate to observe that the community of

health care CEA/CBA analysts seems to have

established a similar boundary. Unless policymakers and analysts remain cognizant of the

existence of that border and its implications,

this limitation can mislead technical aspects of

analysis and, more importantly, reinforce

narrower views of health resource allocation.

A prominent example of a technical problem is

7

It can be argued that it takes a strt~ng c[>nstituti(>n to present

equ iv(~cal tin dings. There is a c(~mm(>n perceptl(]n that the pub] icati(~n market prefers “deflnit]ve” to ambl,guous findings. Th]s is retlected ]n the CEA CBA literature In which equivocal results seem

tt~ be much milre rare than probability ie~ wc~uld lead ~~ne t[> expect.

Alth{>ugh OTA s literature search disc[>vered a prep~~nderance of

St udle~ WI t h pc~sl t IVC t lndlngt, there appeared t(> be many m[~re

~t udie~ w] th negative than with amblgu(~u~ tlndings, Thcm with

amb]guc~us tlndlngs tend t(} be c(~mpetent analy~es, their ambiguity [}ften re[ Iect Ing alit~wance f(}r variation in uncertain parameters

(e.g. , 122 ~.

the recent emphasis on measuring “net healthcare cost” in CEAs (574). The socially relevant

concept should perhaps be net social cost, in

which net health-care cost is but one important

component.

One of the drawbacks that can arise from limiting policy analysis to medical care parochialism is a failure to explore the possibility of costeffective alternatives to personal health services.

In the effort to reduce mortality and disability

due to motor vehicle accidents, how might highway safety efforts—technical (e. g., safer road

surfaces and shoulder barriers), legal (e. g., increased law enforcement), etc.—compare with

improved emergency medical services? To reduce hypertension-related mortality and morbidity, what is the appropriate mix of medical

interventions and community health education

on risk avoidance? There is a paucity of comparative analyses crossing the medical-nonmedical, or personal health-public health, border. A

noteworthy exception is comparison of community water fluoridation with a variety of individual treatment approaches to preventing dental caries. Noting this paucity is not meant to

reflect adversely on either existing or future individual contributions to the health care literature—the quantity and importance of analyses

of specific medical problems and technologies is

sure to grow, a development to be desired.

Rather, it is to suggest that policymakers, health

planners, and individual health practitioners

would benefit from the widening of perspective

that “border-crossing” analyses could offer.8

8A budgetary pragmatist might argue that medical and nonmedical resource allocatic)ns are bureaucratically independent, with

border-crossing reallocations extremely unlikely, and hence that

border-crossing analysls i~ n(>t worthwhile. Alth(~u~h this may be

true in the short run, relative rew~urce all<~cati(lns do change over

time and might be resp(~nsi~’e to analytical Input. Clearly, this is

[>ccurring at present in the new Federa I G(>vern men t prevention

initiatives within HEW ( 743). Mt>re to the p(~in t, however, is

OTA’S finding that one important strength of analysis is its ability

to affect thinking ab(>ut prt~blems—perspective-and n(>t the mahIng of explicit resource al Ic}cat i[ln dec isit~ns.

57-774 0 - 80 - 5
4

Methodological Finding;

and Principles
Contents

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..........

Methodological Limitations . . . . . . . . . . . . . . . . . . . . . . ........9 . . . . . . . . . . .

Weaknesses Inherent in CEA/CBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Weaknesses Due to Immaturity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..=.

Ten Principles of CEA/CBA Methodology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

I.Define Problem. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.State Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..

3. Identify Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4. Analyze Benefits/Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5.Analyze Costs. . .............0...........00.. .. ... ... .............. .

6. Differentiate Perspective of Analysis . . . . . . . . . . . . . . . . . . . . . ........

P. Perform Discounting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8. Analyze Uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9. Address Ethical Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

l0.Interpret Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Other Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Nonaggregated Analysis—AnArraying Technique . . . . . . . . . . . . . . . . . . . . . . . .

63

63

64

64

65

65

65

65

66

66

66

66

66

66

67

68

Table No.

2. Ten General Principles of

Figure No.

Page

Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

FIGURE

Page

3. The Relationship Between Health Statistics, Health Indicators, and

Health Indexes.. . . . . . . . . . . . . . . . . . . . . . . . . . . .: . . . . . . . . . . . ....”..”” 63
4.

Methodological Findings and Principles

INTRODUCTION

OTA’s assessment discovered no consensus

among analysts and practitioners as to a standard method of cost-effectiveness analysis/costbenefit analysis (CEA/CBA), although it did

find agreement that no one method is appropriate for any two classes of technologies or for

any two situations under which a technology is

being assessed. In general, the disagreement on

precise methodology is due more to the inherent

nature of the analysis, the type and stage of development of the technology being analyzed,

and the general social and political environment

of decisionmaking than it is to the maturity of

the methodology of CEA/CBA.

OTA believes that the fundamental approach

to CEA/CBA should be based on clear, logical

thinking, using explicit criteria within the

framework of generally accepted methodological principles. OTA also considers the distinction between CEA and CBA to be largely academic and believes that valuation of intangibles,

such as life and quality of life, should be governed more by factors external to the analysis

than by the methodological approach itself.

This latter point requires further comment.

During the Case Study Authors’ Workshop,

conducted as part of this assessment, it was

agreed that certain aspects of the method which

is chosen for a given analysis will be governed

by the intended audience. This finding, in effect,

implies that CEA/CBA is subject to systematic

methodological bias. One example of such bias

would be limiting the scope of a study to compare certain alternatives but not others, e.g.,

comparing respiratory therapy treatments with

each other but not including the option of no

treatment (468). Another example would be

considering some effects or benefits but not

others, e.g., examining direct economic costs

and benefits of alternative therapies but not examining convenience or anxiety factors (304).

Such systematic bias is not wrong methodologically; rather, it is a reflection of the fact that

CEA/CBA is often part of a political process.

For instance, if a health systems agency wishes

to assess the value of an alcoholism program, or

if alcohol/drug abuse proponents wish to argue

for increasing funding for their programs, it is

legitimate–methodologically and politically—

to estimate net societal economic gain, including

increased productivity (i. e., lost wages averted).

On the other hand, if the Health Care Financing

Administration is trying to determine whether,

and for whom, artificial heart surgery or bone

marrow transplant should be reimbursed, the

use of increased productivity as a criterion may

be less acceptable politically.

A related consideration is whether an analysis

is being used to propose increased funding for a

new or an existing program, or whether it is being used to recommend curtailment of an existing program. In the former case, almost any factor which helps to make the case for increased

funding is politically acceptable—including increased wages of a more productive population.

In the latter case—curtailing a health program—

it is often unacceptable to use net changes in

wages as a criterion, since many feel that programs should not be denied on the basis, even in

part, of a person’s potential earning ability.

OTA’s finding, therefore, is that since there are

a variety of acceptable ways to perform a CEA/

CBA, and since the results of an analysis often

are affected by the methods chosen, it is very

important that the process of the analysis be explicit in order to allow for public scrutiny. In a

sense, the process of a CEA/CBA may be more

important than the results.

In addition, OTA finds a paucity of—and

consequently a need for—improved data, without which good analyses are impossible. For example, efficacy and effectiveness information

for many technologies is generally not avail61
able; health care utilization data are often either

not available or not available in a standard or

accessible format; and cost data are often inaccurate and also nonstandardized. Members of

the advisory panel for the assessment and case

study authors expressed the conviction that

since each specific analysis often requires a

unique data set that will not be available in even

the best of routine data collection systems, better routine data collection—although desirable

and possibly necessary for better analyses—is

ordinarily not sufficient. Therefore, an optimum mix of routine data collection and studyspecific data collection needs to be defined, and

when studies are funded, attention should be

given to include funds for data collection.

The National Center for Health Statistics

(NCHS) is an agency within the Office of the

Assistant Secretary for Health of the Department of Health and Human Services and is one

of the principal health services research agencies

of the Federal Government. NCHS has played a

major role in the development of national health

statistics policy and programs. Under its current

mandate—the Health Services Research, Health

Statistics, and Medical Libraries Act of 1974

(Public Law 93-353)–NCHS is responsible for

collecting and disseminating health data including information on the costs of illness,

health care, and health financing.

The importance of data collected by NCHS

cannot be overemphasized. Such information as

incidence and prevalence rates of diseases, natural history of disease, medical care utilization,

work loss, surgical rates, and premature mortality is crucial to CEA/CBA. NCHS has conducted cost-of-illness studies, and these have

been used in other agencies’ CBAs and CEAs.

Currently, NCHS staff are coordinating an interagency Public Health Service Cost of Illness

Committee which is examining the state-of-theart of estimating costs of illness and disability.

There is also an expanding literature related

to health status measurement. This maturing

field is important to health care technology

assessment in general and CEA/CBA in particular. It may have the potential to capture, in a

very useful format, aggregate measures of, and

changes in, health status which are much more

inclusive than single health statistics or health

indicators, such as mortality rates or disability

rates. The relationship between health statistics,

health indicators, and health indexes has been

characterized by Murnaghan (738) and is shown

in figure 3. Health statistics can be thought of as

basic data such as number of hospital admissions. Health indicators are processed data that

aggregate information of similar type and are

often expressed in terms of percentages, rates,

and ratios. The main methodological issue in regard to health indicators is reliability, not

validity (738). Health status indexes (HSIs),

however, are considerably more complex and

controversial. In general, such indexes attempt

to combine multiple indicators such as disability

and death into a single expression. Usually an

index scale is used (e.g., a scale from zero to 10,

where zero represents death and 10 represents

perfect health). The methodological issues in regard to health indexes are reliability (i.e., do repeated measurements provide the same information?), validity (i. e., is the relative weighting

system correct?), and definitional consistency

(i.e., what constitutes “health’’?).

Notwithstanding the considerable progress in

solving these methodological issues (e.g., 708,

711,732,733), OTA finds, with notable exceptions (406,516), considerable reluctance within

the general health care research community to

accept the validity of HSIs. Part of this reluctance seems to be related to the immaturity of

the research effort. For instance, there are

several concurrent research efforts underway to

develop an HSI, each method being related but

still quite different from the others. Also, as

noted above, reliability and validity studies are

still underway. The other major reason for the

reluctance of the research community to accept

and use HSIs seems to be a lack of understanding of the techniques. For instance, although

most serious CEA/CBA analysts are aware of

the HSI literature and of its potential in their

own work, evidently, very few of them have

assessed for themselves its validity, Consequently, in their own writing most researchers

are content to acknowledge the HSI research underway, but few feel confident in actually using

it. In summary, OTA finds that research efforts

to develop indexes of health are producing im-
Ch. 4—Methodological Findings and Principles ● 63

Figure 3.—The Relationship Between Health Statistics, Health Indicators, and Health Indexes

Health

statistics

Health

indexes

Health

indicators

SOURCE Off Ice of Technology Assessment

portant results, but that these efforts have

neither been fully evaluated nor widely accepted

by the applied research community. The lack of

acceptance is probably more related to the imMETHODOLOGICAL LIMITATIONS

The methodological weaknesses or shortcomings of CEA/CBA are of two general types:

1) those that are inherent in this form of analysis, and 2) those that are due to the lack of maturity in the state of the art of CEA/CBA and to

the lack of analyst expertise and experience with

CEA/CBA in health care. The latter can be expected to diminish as more experience accumulates. The 10 principles for analysis presented

later in this chapter are directly relevant to

lessening what will be referred to below as

“weaknesses due to immaturity. ” The “weaknesses inherent in CEA/CBA, ” however, are

likely to remain significant barriers to the

maturity of the field and to the neglect of evaluation than to a rejection of the methodology.

Further study of the validity and usefulness of

HSIs appears to be warranted.

usefulness of

sionmaking.

CEA/CBA in health care deciWeaknesses Inherent in CEA/CBA

Examples of weaknesses which are considered

as inherent are: 1) the difficulty of predicting

with precision the costs and benefits of new or

not yet existing programs or technologies,

2) fundamental problems in quantifying or valuing certain important but less tangible health

benefits, 3) controversy over the appropriate

discount rate, 4) the inability of analyses to adequately incorporate equity considerations, and
5) the inevitability of significant uncertainty of

important variables even in a perfectly managed

study. In addition, the rapidity and profundity

of change in technological medicine exacerbate

the analytical process, a problem felt particularly acutely because the point at which an analysis

might have the most significant impact on

health resource allocation—before a technology

has diffused into widespread medical practice—is also the point at which uncertainties are

most often encountered. Although sensitivity

analysis sometimes can demonstrate that inherent technical analytical problems do not affect

qualitative conclusions, nevertheless such difficulties frequently preclude a definitive assessment of a program. In any case, the uncertainties which pervade analyses severely restrict the

potential of studies, however high quality, to

resolve definitively the “close calls” in which

alternative programs are similar in both cost

and effectiveness.

Another inherent weakness, discussed earlier,

concerns the systematic methodological bias

which results when CEA/CBA studies are tailored to consider certain costs and benefits/

effectiveness and not others, Such bias, due

either to political considerations or to the type

and stage of the technology being evaluated, is

inevitable.

Weaknesses Due to Immaturity

Many of the problems associated with the application of CEA/CBA in the health field are

due to the relative newness of the technique. In

some cases, the problems stem from a lack of

agreement among the research community (e.g.,

concerning the precise specification of costs, the

inclusion of future medical costs saved). In

other cases, sufficient information is unavailable (e. g., population-based utilization data are

not known, or efficacy and safety are unknown). Also related to the relative newness of

CEA/CBA is the finding that the number of

studies demanded is greater than the number

analysts can perform. Consequently, insufficiently trained program staff, health care practitioners, and public policy analysts are doing

analyses—often failing to follow generally accepted, but until now not widely disseminated,

principles of analysis (e.g., discounting costs

and benefits, performing sensitivity analysis,

identifying alternative programs, and measuring opportunity costs).

Although there are fairly few examples of

technically high-quality CEA/CBA studies in

the health literature today, this situation may

change as the state of the art of CEA/CBA matures and as analysts and decisionmakers gain

more experience with CEA/CBA in health care.

There should be a reduction in the number of

problems due to immaturity such as: inappropriate or inaccurate specification of production

relationships; inadequate identification of alternatives, measurement or valuation of costs or

benefits; lack of discounting of future costs and

benefits; and failure to examine sensitivities. Although one should not underestimate the difficulty of producing a technically high-quality

study, in principle such problems can be resolved; clearly the practice of analysis can and

should improve over time. Also, in time, both

analysts and policymakers may better understand the inherent limitations of CEA/CBA so

as to make use of such analyses in a more realistic perspective. Thus, the usefulness of CEA/

CBA seems likely to increase in the future. The

10 principles of analysis presented below are

suggested as one method of minimizing not only

weaknesses of immaturity, but also weaknesses

that are inherent to the technique.

TEN PRINCIPLES OF CEA/CBA METHODOLOGY

There is widespread agreement that 10 basic circumstances under which a societally oriented

principles of CEA/CBA methodology apply re- analysis takes place. These 10 principles are disgardless of the technology being assessed or the cussed below. (See table 2.)
Table 2.—Ten General Principles of Analysis

(for CEA/CBA methodology)

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

Define problem.

State objectives.

Identify alternatives.

Analyze benefits/effectiveness.

Analyze costs.

Differentiate perspective of analysis.

Perform discounting.

Analyze uncertainties.

Address ethical issues.

Interpret results.

SOURCE Off Ice of Technology Assessment

1. Define Problem

The problem should be clearly and explicitly

defined and the relationship to health outcome

or health status should be stated. The problem,

for example, could be expressed in terms such as

“excess infection rate” or “excess deaths. ” The

broader the definition of the problem, the more

relevant alternatives there are to examine: “Excess deaths, ” for example, could lead to comparing any preventive or therapeutic program

which decreases mortality; excess deaths due to

cancer, however, would limit the scope of study

considerably; and excess deaths due to cervical

cancer would limit it further. Nevertheless,

whatever the scope, as long as the focus is on a

health problem, the study can focus on alternative means to solve the problem or, conversely,

to increase health status. Some studies, however, must necessarily focus on the efficient use

of a technology. This is particularly true of

diagnostic technologies, where the ultimate

health problem may be far removed from the

use of the technology.

2. State Objectives

The objectives of the technology being assessed should be explicitly stated, and the analysis should address the degree to which the objectives are (expected to be) met. In general, the objectives will be governed by the way in which

the problem is defined: The broader the problem

definition, the broader the objectives. Ordinarily, it is most relevant for the objectives to be in

terms of lowering morbidity, disability, or mortality or, alternatively, increasing well-being.

When the objectives are stated in terms of decreasing costs, the relationship between costs

and health benefits is often lost, sometimes resulting in untenable assumptions of equal efficacy across treatment modalities. Often, objectives are stated in terms of achieving a certain

level of benefit for the least cost, or, conversely,

achieving the most benefit per dollar cost.

3. Identify Alternatives

Alternative means (technologies) to accomplish the objectives should be identified and subjected to analysis. The number of alternatives

and the relevancy of the analysis wiIl increase as

the scope of the identified problem is increased.

Whereas there are numerous means to lower

death rates, for example, there are relatively

fewer ways to lower deaths due to a specific

disease, and even fewer ways to do this by employing a particular technology. One of the

most difficult questions to answer in analyzing

the cost effectiveness of a given intervention

(such as Pap screening) is “cost effective compared to what?”

4. Analyze Benefits/Effectiveness

All foreseeable benefits/effectiveness should

be identified, and when possible should be

measured. The relevant benefits/effectiveness of

health care technology in the health field often

follow directly from the problem under consideration, the objectives specified, and the framework in which the problem is approached. Not

all benefits/effectiveness are positive—some

may be negative (e.g., deaths due to surgery)

and some may be indeterminate (e.g., incurable

disease may be discovered). Each of the following categories should be considered: 1) personal

benefits/effectiveness, such as alleviated pain,

reduced risk of sickness or death, enhanced

quality of life, lowered anxiety, 2) health resource benefits/effectiveness such as increases

and decreases in health care expenditures, 3)
other economic benefits/effectiveness such as

increased productivity, and 4) social benefits/

effectiveness such as the equitable distribution

of medical care. When possible, and if agreement can be reached, it is helpful to value benefits in common terms in order to make comparisons across alternative programs easier.

5. Analyze Costs

All expected costs should be identified, and

when possible should be measured in dollars. In

general, the concept of “opportunity cost” is the

most correct way to consider the costs of a program. That is, the costs are equal to the value of

the opportunities which are forgone because of

the investment in the program.

6. Differentiate Perspective of Analysis

When private benefits and costs differ substantially from social benefits and costs, and if a

private perspective is appropriate for the analysis, the differences should be identified, Although CEA/CBA is generally considered a tool

of social policy, it is helpful and important to

recognize that private incentives differ from

public incentives and since health care delivery

is often funded, always demanded, and usually

delivered by the private sector, its (the private

sector’s) perspective may be very important to

the relevancy of the analysis. For instance, the

social benefits of elective procedures such as

elective hysterectomy, cancer screening, and

many psychotherapy programs are apt to differ

markedly from the private benefits. Typically, a

CEA will identify the “social” benefits in terms

of cost reduction, whereas the primary private

objective (i e., expected benefits) of the patient

may be decreased anxiety.

7. Perform Discounting

All future costs and benefits should be discounted to their present value in order for them

to be compared with one another. Discounting

can be thought of as a reverse interest rate. It is

used to take into account phenomena such as

the observation that, all things being equal, people prefer benefits (including health benefits)

today rather than at a future time. Although

there is no firm agreement as to the precise discount rate to use, if future benefits of alternative

programs are roughly proportionate to one

another, the rate which is chosen makes little

difference to the outcome of the analysis.

8. Analyze Uncertainties

Key variables should be analyzed as to the

importance of their uncertainty to the results of

the analysis. That is, a “sensitivity analysis”

should be performed. In its simplest form sensitivity analysis is nothing more nor less than the

application of common sense when one is not

sure of a fact: It is the examination of the uncertain event under different assumptions. Sensitivity analysis can indicate both when more information is needed and when insufficient information is irrelevant.

9. Address Ethical Issues

Ethical issues should be identified, discussed,

and placed in appropriate perspective relative to

the rest of the analysis and the objectives of the

technology. Many health care programs have as

their primary objective the equitable distribution of services; other programs include it as one

of many objectives; still other programs affect

the distribution of society’s goods and services

without an explicit intention to do so. A CEA/

CBA should identify all these effects. When possible, it should also measure them. Although

such effects cannot ordinarily be valued, however, they are often germane, and sometimes

essential, to the measure of worth of a health

program.

10. Interpret Results

The results of the analysis should be discussed

in terms of validity, sensitivity to changes in

assumptions, and implications for policymaking

or decisionmaking. This is important both because the intended audience is often a public

official or a health care professional, neither of

whom may be technically oriented, and because

study findings are often reported in capsule

form such as a news brief, and are often intro-
duced in the professional literature in abstract tential to mislead the reader, a hazard which can

form. Results of CEA/CBA often have the po- be greatly reduced by proper interpretation.

OTHER FINDINGS

In addition to conforming to the aforementioned 10 principles, all quantitative analyses

should specify data sources, be written as clearly and as nontechnically as possible, and be subjected to peer and other types of review, including public scrutiny when appropriate, especially

regarding assumptions upon which the outcome

of the analyses may rest. In general, the more

technical the analysis, the more important that

the review be formalized and conducted by individuals who can challenge the methodology that

is employed. Reviews of those CEA/CBAs that

are not too technical, however, may facilitate

public scrutiny regarding the validity and, especially, the appropriateness of key assumptions.

Such scrutiny may be useful because the application of CEA/CBA in the field of health policy

is only part of a larger political process.

Since this report is primarily designed to examine the policy implications of using CEA/

CBA for health care resource allocation decisions, the methodological process which is envisioned is substantially different from what

would be discussed if this report were being

written for the academic research community.

It is necessary to make this distinction because CEA/CBA can be a very complex undertaking analytically and often requires a massive

data gathering effort. For instance, disease progression transition rates must often be assigned

and mathematical models must capture the dynamics of the process; the effects of medical intervention may need to be estimated by professional opinion or empirically evaluated through

epidemiological observation or by formal clinical trials; joint production costs may need to be

estimated using sophisticated dynamic programing techniques; and so forth. All this is expensive, time consuming, and apt to require

very specialized computer support, analytical

skills, and clinical judgment. On the other hand,

the real world dictates that health resource

allocation decisions must often be made without

the benefit of such resources—that is, with little

time, money, and technical expertise. These

suboptimal conditions, however, do not relieve

decisionmakers from the responsibility of

weighing the consequences of decisions.

Since CEA/CBA is being spoken of or advocated as a mechanism to assist policy makers in

making rational choices between competing objectives, OTA was asked to assess the technique

for that purpose. The findings are that, as formally applied, the methodology could often be

too complex, expensive, and time consuming if

used as a routine method for decisions by public

policy makers. In fact, the cost-effectiveness case

studies conducted as part of this assessment

serve to highlight the immaturity of the technique itself. Initial drafts of more than half of

the studies, all of which were performed by respected health care researchers, were considered

by reviewers to be inadequate with respect to

the relevancy/usefulness of the results, the

validity of the methodology, the tenuousness

(or error) in the key assumptions, and/or the

validity of the data used. Clearly, the field is not

yet fully defined.

Nevertheless, the logic behind using CEA/

CBA, even at an operational or policymaking

level, appears sufficient to suggest that the

10 principles previously enumerated can and

should be followed under most circumstances.

In no way, however, does this finding suggest

that a complete analysis is either easy or unnecessary. There is clearly a need for ongoing and

sophisticated studies of the cost effectiveness of

specific technologies as well as a need for advancing the state of the art itself. For instance,

much good research has been done in developing and testing a composite index which de-
68 • Background paper #l: Methodological Issues and Literature Review

scribes the health status of a population at any skills, or understanding of the inherent limitagiven point in time (e.g., 707,711,731,732,733). tions. Defining a more practical, limited apThat type of work should continue and perhaps preach to the methodology seems clearly approshould receive more emphasis. Nevertheless for- priate and does not diminish the worth of, or

mal CEA/CBAs, however valid and effective need for, more sophisticated approaches under

potentially, can be inappropriately used by de- different circumstances.

cisionmakers who lack the necessary resources,

NONAGGREGATED ANALYSIS–AN ARRAYING TECHNIQUE

Since many of the methodological weaknesses

of CEA/CBA may be hidden, aggravated, or in

fact caused by the practice of deriving a costbenefit or cost-effectiveness ratio—that is, a

numerical bottom line—the possibility of not

aggregating the often complex sets of calculations should be investigated and considered.

Rather than aggregating, analysts might explicitly list or ARRAY all the elements which are

included in, or would be affected by, decisions.

When costs and effectiveness could be quantified, that would be done; when they could be

combined, that would also be done. Whenever

one or more important nonquantifiable variables would otherwise either be left out or be relegated to a footnote, however, no effort to arrive

at a single combined benefit value would be

made. A nonaggregated or array method of

analysis would give decisionmakers a greater

number of elements to consider, but it would

also make intangible or nonquantifiable factors

more explicit, and thus might also help force

consideration of those factors by decisionmakers commensurate with the factors’ significance.

The arraying method can either be highly quantitative and analytical, using multiobjective programing techniques, or when that is not desirable or possible, it can be presented more qualitatively.
Appendixes

Appendix A: Analysis of the Growth and Composition of the

Health Care CEA/CBA Literature

Appendix B: Bibliography on CEA/CBA

Appendix C: Abstracts of Selected Entries From the

Bibliography on CEA/CBA

Appendix D: Description of Other Volumes of the Assessment

Appendix E: Health Program Advisory Committee; Authors of

Case Studies

NOTE: The original versions of the analysis of the growth and composition of the

CEA/CBA literature, the bibliography, and many of the abstracts were prepared for OTA by Kenneth Warner and Rebecca Hutton.
Page

Appendix A: Analysis of the Growth and Composition of the Health Care

CEA/CBA Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

Appendix B: Bibliography on CEA/CBA. ., . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Appendix C: Abstracts of Selected Entries From the Bibliography on CEA/CBA .. 101

Appendix D: Description of Other Volumes of the Assessment . ..............120

Appendix E: Health Program Advisory Committee; Authors of Case Studies. .. ..122
Appendix A.—Analysis of the

of the Health

Growth and Composition

Care CEA/CBA Literature

As measured by contributions to the professional

literature, interest in health care applications of CEA

and CBA has grown dramatically over the past decade. This appendix analyzes the extent and nature of

the growth in this literature and examines its substantive content. An assessment of the quality of contributions to the literature was presented in chapter 3.

The method of the analysis of the growth and composition of the health care CEA/CBA literature that

appears in this appendix is described in the first section below. The second section offers an empirical

characterization of the magnitude and nature of the

literature, examining the diffusion over time of

health care CEA/CBA interest in several dimensions:

numbers of publications; the mix of medical and nonmedical publication vehicles; relative preferences for

CEA and CBA; medical functions emphasized; physical nature of subjects of study; and the decision orientation of analyses. Specific substantive topics and

areas of interest which have dominated the attention

of authors were analyzed in chapter 1. The material

covered by that review accounts for roughly half of

all the entries in the bibliography in appendix B. That

section of chapter 1, therefore, should be regarded as

part of this analysis.

Method

The empirical analysis in this appendix derives

from counts and classifications of over .500 of the references in the bibliography of CEA and CBA in

health care (app. B). With a few exceptions, the bibliography consists of references from the years 1966

through 1978, including CBAs and CEAs concerning

personal health services, reviews and comments on

such literature, and discussions of CEA/CBA methodology directed specifically to health care professionals. Appendix B includes a description of the bibliography’s contents, rules for inclusion or exclusion

of references, and the literature search process.

Each reference from the years 1966 through 1978

was classified according to the following dimensions:

1. year (1966 -78);

2,

3,

4.

type of analysis (CBA, CEA, general or unknown);

publication vehicle (medical journal; journal

intended primarily for nonphysician health

professionals, administrators, or health services researchers; nonhealth);

medical function of the program or technology

(prevention; diagnosis; treatment, divided into

cure, rehabilitation, maintenance, or pallia5.

6.

7.

tion; administration; some or all of the above

or unknown);

physical nature of the program or technology

(technique, drug, procedure, equipment, personneI, system, some or all of the above or unknown);

decision orientation (i. e., whose decision? individual, organization, society, unknown ); and

subject matter (a specific program or technology, review article, methodology, combinations of these).

Classification involved numerous arbitrary judgments. Man y of the assignments depended on the

content of abstracts or even the wording of titles.

Where available information suggested that each of

two (and very occasionally three) categories was appropriate, half (or a third) credit was assigned to

each. For example, in the “medical function’ dimension, certain screening programs were recorded as

half prevention and half diagnosis. (A comprehensive blood pressure control program was counted as

one-third for each of prevention, diagnosis, and

treatment. ) For “type of analysis, ” a few studies

presented both cost-benefit and cost-effectiveness

estimates. Accordingly, these were scored as one-half

CBA and one-half CEA. The “unknown” or “other”

categories were used liberally when it was difficult or

impossible to categorize references accurately.

Although the possibility remains that many of the

assigning were not optimal, OTA is unaware of any

significant sources of bias. Thus, at a minimum the

quantitative analysis should provide an accurate

qualitative characterization of the size, nature, and

contents of the literature.

Growth and Character of the Literature

Diffusion

The magnitude and rate of growth of the health

care CEA/CBA literature are indicated in table A-1

and figure A-1. Table A-1 records the annual numbers of CEAs, CBAs, and related publications for the

years 1966 through 1978. The annual sum of identifiable CEAs and CBAs (column 3) is plotted in figure

A-1, as is the total of all CEA/CBA-relevant references (column 5).

As the data vividly demonstrate, widespread interest in health care CEA/CBA is a phenomenon of the

1970’s. Prior to 1970, the annual number of health

care CEA/CBAs and related publications never exceeded 16; after 1970, the number was never less than

-1
Table A-l.— Numbers of Health Care CEA/CBAs by Year (1966-78)

CBA s

a CEA s

b CBAs + CEAs Other c Total

Year — .

(1) —(2) (3) = (1) + (2) (4) (5) = (3) + (4) ——— ——. — —-— —

1966 . . . . . . . . . 4.5

—.

0.5 5 0 ‘ 5

1967 . . . . . . . . . 4.0 1.0 5 0 5

1968 . . . . . . . . . 6.5 4.5 11 4 15

1969 . . . . . . . . . 2.5 1.5 4 2 6

1970 . . . . . . . . . 3.0 9.0 12 4 16

1971 . . . . . . . . . 9.5 10.5 20 5 25

1972 . . . . . . . . . 14.5 5.5 20 7 27

1973 . . . . . . . . . 25.5 16.5 42 2 44

1974d . . . . . . . . 19.0 17.5 36.5 7 43.5

1975d . . . . . . . . 17.0 21.5 38.5 13 51.5

1976 . . . . . . . . . 40.5 36.5 77 15 92

1977 . . . . . . . . . 31.5 47.5 79 23 102

1978 . . . . . . . . . 33.0 ———— 38.0 ——— 71 22 93

Total. . . . . . . 211.0 210.0 421 104 525.0

a — — .

All All papers identified as CBAs in title or otherwise known. O 5 Indicates half CEA and half CBA

bAll papers ldentified as CEAs in title or otherw!se known O 5 indicates half CEA and half CBA

CAII other papers, inlcluding those the title of which does not state CEA or CBA. also general methodology Papers, etc

dFract(onal entries for 1974 and 1975 reflect the incluslon of one article that appeared in a journal with publicatlon date

December 1974/January 1975

SOURCE Off Ice of Technology Assessment

25. The two curves in figure A-I exhibit the characteristics of the classic diffusion process (759), with

“take-off” occurring around 1970 and diffusion proceeding at an almost exponential rate throughout the

decade. The nature of the data is such that it is impossible to tell whether the curves have reached an

“inflection point, ” a point beyond which growth in

the literature will proceed at a progressively slower

rate.

The proliferation of professional journals might be

expected to result in increased numbers of publications on many subjects, without representing a genuine increase in relative interest in the subject. To provide perspective, one can compare the growth in the

health care CEA/CBA literature with that of the

overall number of citations in Index Medicus. Over

the entire period studied (through 1977, since 1978

was not yet completed when the data were acquired)

Index Medicus citations increased from 157,000 to

260,000 articles, a growth of two-thirds (66 percent).

By comparison, the CEA/CBA literature grew by a

factor of from 14 to 20 (using column 3) and column

5 data from table A-1, respectively). Even in very recent years, growth in the latter considerably outpaces

that of the overall medical literature. For example,

from 1975 to 1977, the number of contributions to

the CEA/CBA literature doubled, while Index Medicus citations rose less than 10 percent. Clearly, the

1

The c(mnt of papers revealed sllghtly }ewer tor 1978 than t(~r 1Q77, and

growth in the numtwr of papers In 1977 was relativel y Ilttle compared to

that In 1 ~7b. An inllect](ln po]nt may have been reached. Barring any

changes In the en~,lr(mmcnt, continued d)ttuslon may be gradual, As

observed lmmt, dla tell, below, however, the envlr{)nmcn[ I\ chan~lng In

\lgn it icant way~ wh]c h may i,ery well accelerate d]ttu~]on,

rate of growth of the health care CEA/CBA literature

vastly exceeds that of the medical literature in general.

The usual “mechanics” of a diffusion process suggest continued growth in the number of publications,

but this general tendency should be reinforced in the

early 1980’s by several influences in the health care

environment: Establishment of the National Center

for Health Care Technology, with its authority to

assess the safety, efficacy, and cost implications of

medical technologies should foster analytical activity; publicity associated with other governmental efforts should increase awareness and interest; a similar effect can be anticipated to follow activities within the medical profession, such as the AMA’s Resident Physicians Section’s recent publication of its report on cost-effective care; growth in attention to

health economics issues in medical school curricula

should promote interest and understanding among

young physicians; and most generally, but probably

most importantly, continued concern about the high

and growing costs of care should itself generate

numerous attempts to assess the cost effectiveness of

medical technologies (703).

Publication Vehicles

Table A-2 shows the distribution by year of the

health care CEA/CBA literature by type of publication. The purpose is to examine what proportion of

the literature has been intended primarily for a physician audience, as reflected in publication in medical

journals, and how this proportion has changed over

time.
Figure A-l.— Diffusion of Health Care CEA/CBAs by Year (1966-77)

104

96

88

80

72

64

(n

h

: 56

n

z

z

f 48

z

40

32

24

16

8

0

/’ /

/

0

f

I 1 I 1 1 I I I I I 1 I

973 1974 1975 1976 1977

67-774 0 - 80 - 6
Year

1966 ..... :

1967 . . . . . . . . .

1968 ....... .

1969 . . . . . . . . .

1970 ....... .

1971 . . . . . . . . .

1972 . . . . . . . . .

1973 ....... .

197 4

e 

. .

1975 e 

. .

1976 ....... .

1977 . . . . . . . . .

1978 . . . . . . . . .

Total . . . . . . .

Table A-2.— Numbers of Health Care CEA/CBAs by

Type of Journal and Year (1966-78)

Number of CEA/CBAs by type of journal

Medical - Nonmedical

c

journals a NEJ M

b

journals Other d

Total

(1) (2) (3) (4) (5)=(1)+(3)+(4 )

0 ‘-” o 1

-

4 5

0 0 1 4 5

4 2 6 5 15

2 1 2 2 6

4 1 6 6 16

10 0 7 8 25

6 0 15 6 27

11 1 19 14 44

23 1 7.5 13 43.5

20 7 15.5 16 51.5

44 5 30 18 92

44 5 27 31 102

42 8 25 26 —— 93

211,0 3 1

-

162.0 153 525.0

a

Journals read primarily by Physicians Excludes nursing, dental, public health, hospital Journals, etc. Includes psychiatric

journals

bNew Eng/andJourna/of Medm/rre

CAll other ,Ournals Includes non. pflyslclan.orl~ nted flealthjoljrna S, economics journals, policy analysls journal s,etc

dBooks, chapters In books, unpublished PaPers. etc

‘Fractional entries for 1974 and 1975 reflect the Incluslon of one article that ameared In a Iournal with Dubllcatlon date

December 1974/January 1975

SOURCE Off Ice of Technology Assessment

Figure A-2 plots columns 1 and 3 of table A-2 to illustrate the diffusion paths of medical and nonmedical journal articles. Although the paths follow each

other closely, the graph shows a shift from a rough

parity prior to 1973 to a clear majority of medical

journal articles after 1973. In other words, the rate of

growth of the medical literature has exceeded that of

the nonmedical journal literature, particularly in recent years. This shift is clearly suggestive of a growing economic consciousness in the medical profession.

Column 2 in table A-2 records the annual number

of CEA/CBA articles in the New England journal of

Medicine (NEJM), Several of the best, most influential health care CEA/CBAs have been published in

NEJM (see ch. 3), hence its isolation here. It is interesting to observe that prior to 1975, the number of

CEA/CBA-relevant contributions in NEJM exceeded

one only once (in 1968), NEJM has published several

relevant articles each year since 1975. Some observers believe that medical interest in CEA/CBA received its biggest boost from publication of the controversial July 31, 1975, issue of NEJM which was devoted to CEA/CBA studies and discussions of their

methodology and usefulness. (See the methodology

review article section of ch. 3.)

Mix of CEAs and CBAs

Columns 1 and 2 of table A-1 distinguish analyses

identified as CBAs from those identified as CEAs.

Prior to the most recent years, the annual number of

CBAs generally exceeded the number of CEAs. Since

1975, the reverse has been true, supporting the statement in a recent review by Weinstein that CEA “has

been gaining in acceptance relative to benefit-cost”

(569). The reason is not obvious. Weinstein attributes the shift to “the conceptual limitations of the

(human capital) approach and the empirical barriers

to the willingness-to-pay approach. ” Complementary or alternative explanations relate to the apparent

relative conceptual simplicity of CEA: Analysts use

CEA because it is easier for the economic layperson—e.g., the physician—to understand; also, the

recent relative growth in the literature in medical

journals appears to include relatively more contributions by physicians, who, as economic laypersons,

may find CEA easier to perform than CBA.2 Economists’ traditional preference (at least in nonhealth

care areas) for CBA may reflect a general conceptual

bent toward valuing and directly comparing the positive and negative consequences of activities. It also

probably reflects the successful use of CBA in early

applications in which benefits were reasonably amenable to monetary valuation (e.g., water resource

management).
Figure A-2.–Diffusion of CEA/CBAs in Medical and Nonmedical Health Care Journals by Year (1966-77)

48

44

40

36

32

~ 28

iiCl CJQ

~ 24

a)

E

2

20

16

12

8

.

.

.

.

I

.

.

A

.

/ .

/

/ e

/ ’ \

4

/ ’

- - 9 J

o

1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977

Year

Key{ CEASand CBASin medtcal journals per year (from CO I umn 1 table A 3 app A)

.— — CEAS and CBAS (n nonmedlcal health carp lournals per year (from column 3 table A 3 a~p AI

SOURCE Off If e of TPC hnrdr)qy AssPssrnent
Medical Functions

Tables A-3 and A-4 present categorizations of literature contributions by the general medical function

which is the substantive focus of each paper. Table

A-3 includes three broad categories (prevention, diagnosis, and treatment, plus a fourth miscellaneous

category). Table A-4 breaks down treatment functions by their purpose: cure, rehabilitation, maintenance, or palliation.

Among the three broad categories, prevention and

diagnosis each account for more than a quarter of the

studies over the entire period, while the various types

of treatment total just under half.3 If one divides the

years covered into the period preceding 1974 and the

period from 1974 through 1978, however, there is a

significant shift in the relative mix, away from prevention and toward diagnosis and treatment. During

the most recent 5 years, the numbers of both diagnosis- and treatment-oriented papers have exceeded the

pre-1974 totals by a factor of four or five. By con-

‘[n th]s recent review, Welnsteln (5b9 I observed. ‘Elagnostlc procedures,

apart from screening tests, have received I I t tle a t tentlon. This OTA dndiyst+’ attribution o} nearly a quarter ()} the c(xiable literature to dlagno~ls IS

not necessarl] y at variance WI t h this obwrvd t Ion, since It Includes many

+creenlng pr~)grams in the diagno~l~ category

Table A-3.—Numbers of Health Care CEA/CBAs by

Medical Function and Year (1966-78)

Number of CEA/CBAs by medical function

Prevent ion Diagnosis Treatment Other a

Year (1) (2) -— — (3) (4)

1966 . . . . . . . . . . . . 0.0 0.0 0.0 5

1967 . . . . . . . . . . . . 0.0 0.3 1.7 3

1968 . . . . . . . . . . . . 2.5 3 0 3.5 6

1969 . . . . . . . . . . . . 1.5 0 5 2.0 2

1970 . . . . . . . . . . . . 3.0 2 0 3.0 8

1971 . . . . . . . . . . . . 6.5 3 5 4.0 11

1972 . . . . . . . . . . . . 7.0 2 0 4.0 14

1973. ..., . . . . . . . 14.5 4 0 10.5 15

1974 . . . . . . . . . . . . 2.5 5 0 14.0 22

1975 . . . . . . . . . . . . 5.0 100 14.5 22

1976 . . . . . . . . . . . . 15.0 160 28.0 33

1977 . . . . . . . . . . . . 12.5 17.0 37.5 35

1978 . . . . . . . . . . . . 18.0 255 18.5 31

Total . . . . . . . . . 88.0 88.8 141.2 207

a

lncludes mixes of all three functions (prevent Ion, diagnosis, and treatment), administration, general, and unknown

SOURCE” Office of Technology Assessment

Table A-4.—Numbers of Health Care CEA/CBAs by

Treatment Function and Year (1966-78)

Number of CEA/CBAs by treatment function

Cure Rehabilitation Maintenance Palliation Total

Year (1) (2) (3) (4) (5) = (1)+ (2)+ (3)+ (4)

1966 . . . . . . . . 0.0 0.0 0.0 0 0.0

1967 . . . . . . . . 1.3 0.3 0.0 0 1.7

1968 . . . . . . . . 1.0 1.0 1.5 0 3.5

1969 . . . . . . . . 1.5 0.0 0.5 0 2.0

1970 . . . . . . . . 0.5 1.0 1.5 0 3.0

1971 . . . . . . . . 2.0 1.0 1 #o o 4.0

1972 . . . . . . . . 2.5 0.0 0 4.0

1973 . . . . . . . . 4.5 3.5 2,5 0 10.5

1974 . . . . . . . . 5.0 7.5 1,5 0 14.0

1975 . . . . . . . . 6.5 3.0 5.0 0 14.5

1976 . . . . . . . . 10.5 6.5 11.0 0 28.0

1977 . . . . . . . . 25.0 4.5 8.0 0 37.5

1978 . . . . . . . . 8.5 4.0 6.0 0 18.5

Total . . . . . . 68.8 33.8 38.5 0 141.2

SOURCE: Office of Technology Assessment

——
trast, the number of prevention-oriented contributions is only 50 percent greater than that of the earlier

period (see table A-3).

This shift seems consistent with the relative growth

in the medical journal share of the literature, assuming that physicians are relatively more interested in

diagnosis and treatment, as opposed to prevention,

than are nonphysician health professionals (including

both providers and health services researchers).

Also, consistent with the principal early nonhealth

care applications of CEA/CBA, early health care

CEA/CBAs concentrated relatively more on health

care “public goods, ” including especially communicable disease control, than on individual patient care,

a growing concern today. Several excellent communicable disease prevention studies are found in the recent medical literature, but this is one of the few

substantive areas in which the number of pre-1974

papers actually exceeded the number of 1974 through

1978. (See ch. 1.)

The shift away from prevention may not be permanent. The widespread perception that “technology” is a major villain in medical cost inflation, combined with the general medical orientation toward

diagnosis and treatment, has contributed to growing

interest in diagnostic and treatment technology, both

in the CEA/CBA literature and in individual physician decisionmaking concerning the use of such technology. These interests will likely be sustained in the

near future. However, the Federal Government’s recent emphasis on prevention (743), increasing public

acceptance of the ideas of disease prevention and

health promotion, and the conscious linking of prevention to cost containment (e. g., 564) may promote

renewed interest in prevention-oriented CEA/CBA.

Table A-4 shows that half of all treatment-oriented

papers are concerned with curative treatments, and

the remaining half are divided roughly equally between medical rehabilitation and maintenance. Reflecting the inherent subjectivity and difficulty of

quantifying “pain relief, ” “comfort,” etc., the literature included not a single contribution that could

be identified as dealing with palliation. The relative

mix of treatment functions has not changed significantly in recent years. Of note is the unusually large

number of cure-oriented papers in 1977.

Physical Nature of Subjects of Study

Is there a growing emphasis in health care CEA/

CBA on individual technologies? OTA’s examination

of the literature permits only an impressionistic answer. In attempting to categorize subjects by their

physical nature, OTA was incapable of definitively

assessing the vast majority as either technique, drug,

procedure, equipment, personnel, or system. Most

seemed to represent a mix of two or more categories;

consequently, they were included in the “miscellaneous” category.4 Even some which could be categorized were categorized with a feeling of discomfort. A

study of the cost effectiveness of CT scanning appears on the surface to belong under “equipment”

(where it was categorized), yet that same study emphasizes the important role of the new technicians

needed to operate the scanner.

A principal impression is that the literature covers

a broad spectrum of types of programs and technologies, with procedures being the best represented category. In recent years, there appears to have been distinct growth in the attention devoted to equipmentembodied technologies, with CT scanning leading the

way with some 18 references since 1975. (See ch. 1.)

Decision Orientation

The original intent of CEA/CBA was to assist in

social decisionmaking, i.e., to identify and value program costs and benefits from a societal perspective.

Businesses and individuals have long employed the

ideas behind CEA/CBA to grapple with decision

problems, but the CEA/CBA label seems to be applied with increasing frequency to analyses whose

decision-assisting perspective is narrower than that

of “society. ”

Table A-5 permits an exploration of the distribution of “decision orientation” in the health care

CEA/CBA literature and of changes in the distribution over time. The table suggests that the social

perspective has dominated the literature over the entire period studied, accounting for roughly 70 percent

of all publications in both the early and most recent

years; if anything, its dominance has grown slightly

over time. Nevertheless, it is also true that articles

oriented toward individual (e. g., practitioner) decisionmaking have increased most rapidly in recent

years. Comparing the pre-1974 period with the years

1974 through 1978, one observes a near doubling of

the share of papers oriented toward the individual

perspective. This growth has come at the expense of

papers with an organizational orientation. While the

latter two categories together account for fewer than

30 percent of the literature contributions, the shift

may be significant.

4

In no year dId OTA manage to categorize m{we than 40 percent t~t the

references as other than mtwelldneous. and ab(wt 20 percent was typlcdl

A table of the counts IS not presenteci, becau~e the mlx in the spec]tlc categories, based on so few (lbwrvati(ln<, IS not necessarily reprewntat]ve
Table A-5.—Numbers of Health Care CEA/CBAs by

Decision Orientation and Year (1966-78)

Number of CEA/CBAs by decision orientation

Individual Organization Society Unknown

Year (1) -- (2) (3) (4)

1966. , . . . . . . . . . . 0 0 3

-

2

1967 . . . . . . . . . . . . 0 0 5 0

1968 . . . . . . . . . . . . 0 4 9 2

1969 . . . . . . . . . . . 0 2 2 2

1970 . . . . . . . . . . . . 1 3 7 5

1971 . . . . . . . . . . . . 4 2 14 5

1972. . . . . . . . . . . . 2 5 12 8

1973. . . . . . . . . . . . 2 7 27 8

1974a . . . . . . . . . . . 5.5 2 21 15

1975a . . . . . . . . . . . 2.5 11 24 14

1976. . . . . . . . . . . . 12 4 49 27

1977. . . . . . . . . . . . 13 4 50 35

1978. . . . . . . . . . . . 8 7 50 28

Total . . . . . . . . . 50 51 -

273 151

aFraC~lOnal entries for 1974 and 1975 reflect the [ncluslon of one article that appeared In a Iournal with publication date

December 1974/January 1975

SOURCE Offlceof Technology Assessment

Summary

Table A-6 summarizes highlights of this empirical

description of the literature, Breaking the period into

the “early” years (those prior to 1974) and “recent”

Table A-6.—0verview of Trends in Health Care

CEA/CBA Literature (1966-73 and 1974-78)a

——.—-

1966-73 1974-78

Average annual number of publications. 18 76

Publications in medical journals as

percent of total journal publications. . 39% 62%

CEAs as percent of CEAs + CBAs . . . . . 41 53

Percent of articles on:

Prevention . . . . . . . . . . . . . . . . . . . . . . . 44 22

Diagnosis . . . . . . . . . . . . . . . . . . . . . . . . 19 31

Treatment . . . . . . . . . . . . . . . . . . . . . . . . 36 47

Percent of articles with orientation of:

Individual, . . . . . . . . . . . . . . . . . . . . . . . 8 16

Organization . . . . . . . . . . . . . . . . . . . . . . 21 11

Society . . . . . . . . . . . . . . . . . . . . . . . . . . 71 74

——— aAlldlfterenceS slgnlflcan~atp = 005

SOURCE Offlceof Technology Assessment

years (1974-78) represents an arbitrar y decision

based on observationof trends. Nevertheless, it is interesting to note that this dividing line (or one a year

earlier) seemed appropriate for all of the phenomena

of interest. No explanation is offered as to why this

was the case.

As the table indicates, recent years have witnessed

dramatic growth in the number of contributions to

the health care CEA/CBA literature (item 1). More of

this growth has occurred in medical than in nonmedical journals (item 2), and CEA is gaining favor relative to CBA (item 3). The early prominence of studies

with a substantive prevention theme has diminished,

while studies related to diagnosis and treatment have

become more popular (item 4), Health care CEA/

CBAs retain as their principal orientation a societal

perspective on problems, though studies with an individual practitioner orientation are becoming increasingly common (item 5).
Appendix B.— Bibliography on CEA/CBA

Contents and Development of

the Bibliography

The bibliography includes approximately 600 references for CEAs and CBAs on personal health services topics, reviews and comments on such literature,

and discussions of CEA/CBA methodology directed

specifically to health care professionals. It is intended

to be as comprehensive as possible for the years 1966

through 1978. Given the lag between publication and

indexing and citation, several articles and books published in 1978 may have been missed. Included in the

bibliography are a few references from before 1966,

several from 1979, and a few from 1980, though no

systematic attempt was made to identify references

outside of the 1966-78 period. Excluded from the bibliography are scores of CEA/CBAs on health-relevant nonmedical subjects (e. g., traffic safety and

control of environmental pollution), as well as dozens of books and articles on CEA/CBA methodology

that are addressed to a general nonhealth technical

audience (e. g., 737).

The line determining inclusion in or exclusion from

the bibliography was not invariably a fine one. In

general for methodology articles, borderline references were excluded. Thus, certain prominent articles

which have had substantial impact on health care

CEA/CBA are not found in the bibliography (though

some are listed in “Other References”) because they

were not necessarily directed at a health care audience. The seminal work of Rice on measuring the cost

of illness is a good case in point (721,746), as is the

related work of Acton and others on measuring the

value of life (4,470, 730,761). These studies reside at

the heart of a long-lived CEA/CBA intellectual debate, and each has formed the basis of numerous attempts to value the health benefits of programs; but

the issues and techniques transcend categorization as

health care methodologies. They are equally relevant

to numerous human welfare programs outside of the

personal health services arena. Similarly, several excellent studies of the social costs of specific illnesses

are excluded because they are not CEA/CBAs of efforts to reduce these costs.

Whereas the rule for tangentially related methodolo gy references was exclusion, OTA adopted a policy of inclusiveness when classifying references as

CEA or CBA. As described immediately below, the

literature search relied heavily on published and

computer-based indexes. Many of the studies which

purport to be CEAs or CBAs are not CEAs/CBAs under the definitions of chapter 1. At the extreme, for

example, at least one article whose title advertises it

as presenting a cost-benefit ratio does not include any

such comparison of costs and benefits (47). Rather

than weed out such references, OTA included all

studies which are known to be CEA/CBAs or which

are presented as such in their titles. Chapter 3 identifies most of the studies commonly held in high

regard.

References included in the bibliography were obtained from four sources: 1) computer-assisted literature searches, 2) published professional literature indexes, 3) reference lists of individual articles, papers,

and books, and 4) communication with leading

health services researchers, including the members of

the Advisory Panel to this OTA assessment.

Two computer-assisted literature searches provided numerous references. MEDLARS covered relevant citations from Index Medicus. For the years

1966 through 1975, this search covered the subject

heading “Cost and Cost Analysis” (which, until 1976

included CEA and CBA). From 1976 to the present,

the search was limited to the Index Medicus subject

heading “Cost Benefit Analysis, ” a heading introduced in 1976 which includes both CEA and CBA.

The second computer-assisted search was conducted

by the National Health Planning Information Center,

using the key words “cost-benefit analysis” and

“cost-effectiveness analysis. ”

For the months postdating the MEDLARS search,

Index Medicus was consulted directly. Published indexes also supplied many relevant economic studies

not included in Index Medicus. Beginning with the

1966 editions, two indexes of economic literature

were selected: the Index of Economic Articles and the

Journal of Economic Literature (prior to 1969 entitled

the Journal of Economic Abstracts).
1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

Abel-Smith, B., “Cost-Effectiveness and CostBenefit in Cholera Control, ” WHO Chron. 27:

407, October 1973.

Abrams, H. L., and McNeil, B., “Computed

Tomography: Cost and Efficacy Implications, ”

Am, J. Roentgenol. 131:81, July 1978.

Abt, C., “The Issue of Social Costs in CostBenefit Analysis of Surgery, ” in Costs, Risks,

and Benefits of Surgery, edited by J. P. Bunker,

et al, (New York, N. Y.: Oxford University

Press, 1977).

Acton, J., Evaluating Public Programs To Save

Lives; The Case of Heart Attacks (Santa Monica, Calif.: RAND Corp., 1973).

Measuring the Social Impact of Heart

and Circulatory Disease Programs: Preliminary Framework and Estimates, report prepared for the National Heart and Lung Institute, National Institutes of Health (Santa Monica, Calif.: RAND Corp., 1975).

Adelstein, S., and McNeil, B., “A New Diagnostic Test for Pulmonary Embolism: How

Good and How Costly, ” N. Eng. J. Med. 299:

305, August 1978.

Aikawa, J., “Proceedings: The Cost-Effectiveness of the C .U. Computerized Clinical Laboratory System, ” Biomed. Sci. Instrum. 10:89,

April 1974.

Akehurst, R. L., and Holterman, S., “Application of Cost-Benefit Analysis to Programmed

for the Prevention of Mental Handicap, ” in

Major Mental Handicap: Methods and Costs of

Prevention, Ciba Found. Symp. 59 (New York,

N. Y.: Elsevier, Excerpta Medica, 1978).

Albert, D., “Decision Theory in Medicine: A

Review and Critique, ” Milbank Mere. 56:362,

summer 1978.

Albritton, R., “Cost-Benefits of Measles Eradication: Effects of a Federal Intervention, ” Pol.

Anal. 4:1, winter 1978.

Allanson, J., “School Nursing Services: Some

Current Justifications and Cost-Benefit Implications,” J. Sch. Health 48:603, Decembe r

1978.

Altman, S. H., and Blandon, R. (eds. ), Medical

Technology: The Culprit Behind Health Care

Costs? proceedings of the Sun Valley Forum on

National Health, DHEW publication No.

(PHS) 79-3216 (Washington, D. C.: U.S. Government Printing Office, August 1977).

Alvord, D., “Innovation in Speech Therapy: A

Cost-Effective Program,” Except. Child, 43:

520, May 1977.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

American Dietetic Association, Costs and

Benefits of Nutritional Care—Phase 1 (Chicago, Ill.: ADA, October 1979).

Angle, C., et al., “The Myelodysplasia and Hydrocephalics Program in Nebraska: A 15-Year

Review of Costs and Benefits, ” Nebr. Med. J.

62:391, November 1977.

Armstrong, B., and Armstrong, R., “Tympanostomy Tubes: Their Use, Abuse, and CostBenefit Ratio,” Laryngoscope 89:443, 1979.

Aron, W., and Daily, D., “Short- and LongTerm Therapeutic Communities: A Follow-Up

and Cost-Effectiveness Comparison, ” Int. J.

Addict, 9:619, 1974.

Arthur D. Little, Inc., “Automated Electrocardiography in the United States, ” HRA

23075-0212 (Hyattsville, Md.: Health Resources Administration, August 1976).

Cost-Effectiveness in Traffic Safety

(Washington, D. C.: Praeger Publications,

1968).

Ashmole, R., et al., “Cost Effectiveness of Current Awareness Sources in the Pharmaceutical

Industry,” Proc. R. Soc. Med. 66:459, M a y

1973.

Atherley, G., et al., “An Approach to the Financial Evaluation of Occupational Health, ” J.

Soc. Occup. Med. 26:21, January 1976.

Averill, R., et al., “A Cost-Benefit Analysis of

Continued Stay Certification,” Med. Care 15:

158, February 1977.

Axnick, N., et al., “Benefits Due to Immunization Against Measles, ” Pub. Health Rep. 84:

673, August 1969.

Backhaut, B., “Refining Cost Benefit Estimates

of Methadone Programs, ” Natl. Conf. Methadone Treat. Proc. 2:1227, 1973.

Bagdonoff, M., “Cost Allocation and the Evaluation of New Procedures, ” Arch. Intern. Med.

130:295, August 1972.

Bahr, A., “Efficacy of Computed Tomography

of the Head in Changing Patient Care and

Health Costs: A Retrospective Study, ” Amer.

J. Roentgenol. 131:45, July 1978.

Bailar, J., “Screening for Early Breast Cancer:

Pros and Cons,” Cancer 39:2783, 1976.

Baker, C., and Way, L., “Clinical Utility of

CAT Body Scans, ” Am. J. Surg. 136:37, July

1978.

Balatskii, O., “An Approach to the Determination of the Economic Effectiveness of Investment in Public Health, ” Matekon, 12:84, spring

1976.
30.

31.

32.

33.

34.

35.

36.

37.

38.

39.

40.

41.

42.

43.

Banerjie, A., “Cost-Benefit Analysis of Health

Measures at LocaI Level: A Plan for a Pilot

Project,” Indian J. Public Health 16:141, July

1972.

Banta, H. D., and McNeil, B., “Cost and Benefits of ETC Therapy for Depression, ” paper

presented at the conference on “ECT: Efficacy

and Impact, ” New Orleans, La., Feb. 22-25,

1978 (to be published by the National Institute

of Mental Health).

, and McNeil, B., “Evaluation of the CT

Scanner and Other Diagnostic Technologies, ”

Health Care Mgt. Rev. 3:7, winter 1978.

and Sanes, J., “Assessing the Social Impacts of Medical Technologies, ” J. Comm.

Health 3:245, spring 1978.

, and Thacker, S., “Assessing the Costs

and Benefits of Electronic Fetal Monitoring, ”

Obstet. Gyn. Surv. 34:627, 1979.

, and Thacker, S., “Costs and Benefits

of Electronic Fetal Monitoring: A Review of the

Literature, ” DHEW publication No. PHS

79-3245 (Hyattsville, Md.: National Center for

Health Services Research, 1979).

Barach, A., “The Indiscriminate Use of IPPB,”

~. A.M.A. 231:1141, March 1975.

Baram, M., “Regulation of Health, Safety, and

Environmental Quality, and the Use of CostBenefit Analysis, ” report to the Administrative

Conference of the U. S., Washington, D. C.,

Mar. 1, 1979.

Barnes, B., “An Overview of the Treatment of

End-Stage Renal Disease and a Consideration

of Some of the Consequences, ” in Costs, Risks,

and Benefits of Surgery, edited by J. P. Bunker,

et al. (New York, N, Y.: Oxford University

Press, 1977).

“Cost-Benefit Analysis of Surgery:

Current Accomplishments and Limitations, ”

Am. J. Surg. 133:438, April 1977.

, et al., “Evaluation of Surgical Therapy

by Cost-Benefit Analysis, ” Surgery 82:21, July

1977.

Barrett, T., et al., “Making Evaluation Systems

Cost-Effective, ” Hosp. Comm. Psych. 3:173,

March 1977.

Bartlett, J., et al., “Evaluating Cost-Effectiveness of Diagnostic Equipment: The Brain Scanner Case, ” Br. Med. J. 2:815, Sept. 16, 1978.

Bay, K., et al., “The Worth of a Screening Program: An Application of a Statistical Decision

Model for the Benefit Evaluation of Screening

Projects,” Am. J. Public Health 66:145, February 1976.

44.

45.

46.

47.

48.

49.

50.

51.

52.

53.

54.

55.

56,

57.

Bendixen, H., “The Cost of Intensive Care,” in

Costs, Risks, and Benefit of Surgery, edited by

J. P. Bunker, et al. (New York, N. Y.: Oxford

University Press, 1977).

Bennett, M., and Winchester, J., Heart and

Circulatory Problems in New Mexico: A Benefit\Cost Perspective (Albuquerque, N. Mex.:

University of New Mexico Medical Center,

1977).

, et al., “Balancing Quality and Cost in

Health Care: An Example of Culturing for

Streptococcus Bacteria, ” paper presented at the

Annual Meeting of the American PubIic Health

Association, Los Angeles, Calif., Oct. 18,

1978.

Bennett, W., “Cost-Benefit Ratio of Pretransplant Bilateral Nephrectomy, ” J.A.M.A. 235:

1703, Apr. 19, 1976.

Bentkover, J., and Drew, P., “Cost-Effectiveness/Cost-Benefit of Medical Technologies: A

Case Study of Orthopedic Joint Implants, ” in

The Implications of Cost-Effectiveness Analysis of Medical Technology/Background Paper

#2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington,

D. C,: in press, 1980).

Berman, E., “Cost-Benefit Analysis of Selected

Preventive Dentistry Programs” (McLean, Va.:

Mitre Corp., December 1971).

Berry, R., Jr., “Cost and Efficiency in the Production of Hospital Services, ” Milbank Mere.

52:291, summer 1974.

Berwick, D., et al., “Screening for Cholesterol:

Costs and Benefits, ” in Genetic Counseling,

edited by H. Lubs and F. Delacuz (New York,

N. Y.: Raven Press, 1976).

Binner, P., et al., “Workload Levels, Program

Costs, and Program Benefits: An Output Value

Analysis, ” Adm. Merit. Health 3:156, spring

1976.

Blair, H., “Capsule of the Cost-Effective Health

Care Conference, ” J. Med. Assoc. Ga. 67:891,

November 1978.

Bloom, B., and Peterson, O., “End Results,

Costs and Productivity of Coronary-Care

Units,” N. Eng. J., Med. 288:72, January 1973.

Blount, J., “Gonorrhea Epidemiology: Insuring

the Best Return for Resources Expended, ” J. Reprod, Med. 11:125, September 1973.

Blumstein, A., and Cassidy, R., “Benefit-Cost

Analysis of Family Planning, ” Socio-Econ.

Plan, Sci. 7:151, 1973.

Boddy, F., “Cost-Effectiveness, Cost-Benefit

Analysis and the Use of Audiovisual R e -
58.

59.

60.

61.

62.

63.

64.

65.

66.

67.

68.

69.

70.

71.

sources,” Scott. Med. J. 16:117, January 1971.

Boden, L., “Cost-Benefit Analysis: Caveat

Emptor, ” Am. J. Public Health 69:1210, December 1979.

Boggs, D., “Applying the Techniques of Cost

Effectiveness to the Delivery of Dental Services,” J. Public Health Dent. 33:222, fall 1973.

Boissoneau, R., “Point of View: Cost Effectiveness in the Health Care System, ” J. Am, Diet.

Assoc. 66:504, May 1975.

Bond, M., et al., “An Occupational Health

Program: Costs vs. Benefits, ” Arch, Environ.

Health 17:408, September 1968.

Bredin, H., and Prout, G., Jr., “One-Stage

Radical Cystectomy for Bladder Carcinoma:

Operative Mortality, Cost-Benefit Analysis, ”

Trans. Am, Assoc. Genitourin. Surg, 68:47,

1976.

, et al., “One-Stage Radical Cystectomy

for Bladder Carcinoma: Operative Mortality,

Cost/Benefit Analysis, ” J. Urol. 117:447, April

1977.

Brian, E., et al., “Cost-Benefit Analysis of Installation of a Spectra System at Santa Monica

Hospital” (Los Angeles, Calif.: University of

Southern California, 1976).

Brodsky, L., and Scherzer, N., “An Analysis of

Alternative Gonorrhea Control Programs in

New York City–March, 1971,” in Analysis of

Urban Health Problems, edited by I. Leveson

and J. Weiss (New York, N. Y.: Spectrum Publications, Inc., 1976).

Brooks, R., “Cost-Benefit Analysis of Patients

Treated at a Rheumatism Center, ” Ann .

Rheum. Dis. 28:655, November 1969.

Brown, J., “Reducing the Cost of Medical Care:

Prevention as a Cost Effective Measure, ” Tex.

Med. 75:73, March 1979.

Brown, S., “A Case Study of Medical Efficacy:

Tonsillectomy” (Washington, D. C.: National

Academy of Sciences, Institute of Medicine,

1975).

Bryant, N., et al., “Comparison of Care and

Cost Outcomes for Stroke Patients With and

Without Home Care, ” Stroke 5:54, JanuaryFebruary 1974.

Bryers, E., and Hawthorne, J., “Screening for

Mild Hypertension: Costs and Benefits, ” J.

Epid. Comm. Health 32:117, September 1978.

Budetti, P., McManus, P., Barrand, N., and

Heinen, L. A., “Costs and Effectiveness of Neonatal Intensive Care, ” in The Implications of

Cost-Effectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of

Medical Technologies, prepared by OTA, U.S.

72.

73.

74.

75.

76.

77.

78.

79.

80.

81.

82.

83.

84.

85.

Congress (Washington, D. C.: in press, 1980).

Bunker, J., “Risks and Benefits of Surgery, ” in

Benefits and Risks in Medical Care: A Symposium Held by the Office of Health Economics, edited by D. Taylor (Lutan, England:

White Crescent Press, 1974).

, et al. (eds.), Costs, Risks and Benefits

of Surgery (New York, N. Y.: Oxford University Press, 1977).

et al. (eds.), “Surgical Innovation and

Its Evaluation,” Science 200:937, 1978.

Burt, B. (cd.), The Relative Efficiency of Methods of Caries Prevention in Dental Public

Health, proceedings of a workshop at the University of Michigan, Ann Arbor, Mich., June

5-8, 1978.

Burt, M., Policy Analysis: Introduction and

Applications to Health Programs (Washington,

D. C.: Information Resources Press, 1974).

Burton, G., et al., “Respirator y Care Warrants

Studies for Cost-Effectiveness, ” Hospitals 49:

64, Nov. 16, 1975.

Bush, J., et al., “Cost-Effectiveness Using a

Health Status Index: Analysis of the New York

State PKU Screening Program, ” in Health

Status Indexes: Proceedings of a Conference,

edited by R. L. Berg (Chicago, Ill.: Hospital Research and Educational Trust, 1973).

, et al., “Health Status Index in CostEffectiveness Analysis of PKU Program, ” in

Health Status Indexes: Proceedings of a Conference, edited by R. L. Berg (Chicago, Ill.:

Hospital Research and Educational Trust,

1973) .

Buxton, M., and West, R., “Cost-Benefit Analysis of Long-Term Haemodialysis for Chronic

Renal Failure, ” Br. Med. J. 2:376, May 17,

1975.

Carlson, D., “Cost-Effectiveness of Laboratory

Improvement Programs: The Viewpoint From

the Private Sector, ” Health Lab Sci. 14:199,

July 1977.

Carr, A., “Cost-Effective Nursing, ” Nurs.

Times 74:906, June 1, 1978.

Carrera, G., et al., “Computed Tomography of

the Brain in Patients With Headache or Temporal Lobe Epilepsy: Findings and Cost-Effectiveness,” J. Comput. Assist, Tomogr. 1:200,

April 1977.

Catford, J., and Fowkes, F., “Economic Benefits of Day Care Abortion, ” Comm. Med.

1:115, May 1979.

Centerwall, B., “Prevention of the WernickeKorsakoff Syndrome: An Updated Cost-Benefit Analysis, ” N. Eng, J. Med. 300:320, Febru-
86.

87.

88.

89.

90.

91.

92.

93.

94.

95.

96.

97.

98.

99.

ary 1979.

and Criqui, M., “The Prevention of

Wernicke-Korsakoff Syndrome: A Cost-Benefit Analysis, “ N. Eng. J. Med. 299:285, 1978.

Chadwick, J., et al., “Cost and Operational

Analysis of Automated Multiphasic Health

Testing,” HSM 110-69-411, PB 193880 (Menlo

Park, Calif.: Stanford Research Institute, June

1970).

Chamberlain, J., “Human Benefits and Costs of

a National Screening Program for Neural-Tube

Defects, ” Lancet 8103(2):1293, 1978.

Chapalain, M., “Perinatality: French Cost-Benefit Studies and Decision on Handicap and Prevention, ” in Major Mental Handicap: Methods

and Costs of Prevention, Ciba Foundation

Symposium 59 (New York, N. Y.: ElsevierNorth Holland Publishing Co., Excerpta Medica, 1978).

Chapman, C., “Nursing-A Cost-Benefit Analysis, ” R. Soc. Health J. 96:208, October 1976.

Charles, E., Jr., et al., “Economics of the Coronary Artery Bypass, ” paper presented to

Health Economics Research Organization,

American Economic Association Annual Meeting, Chicago, 111., Aug. 30, 1978.

, et al., “Spinal Cord Injury: A Cost

Benefit Analysis of Alternative Treatment

Models, ” Paraplegia 12:222, November 1974.

Chawla, M., and Steinhardt, B., “Episode of

Care Accounting Methodology for a Cost-Effectiveness Approach to Quality Assurance in a

HMO, ” PHS-HSM-110-73-402 (Bethesda, Md.:

Public Health Service, May 1975).

Chen, M., et al., “Maximizing Health System

Output With Political and Administrative Constraints Using Mathematical Programming, ”

Inquiry 13:215, September 1976.

Christie, D., “Screening for Breast Cancer: The

Role of Mammography, ” Med. J. of Aust.

2:398, Sept. 17, 1977.

Civetta, J., “The Inverse Relationship Between

Cost and Survival, ” J. Surg. Res. 14:265 ,

March 1973.

Cochrane, A., Effectiveness and Efficiency:

Random Reflections on Health Services (London: Burgess & Son Ltd., Nuffield Provincial

Hospitals Trust, 1972),

Cohen, J., “On Determining the Cost of Radiation Exposure to Populations for Purposes of

Cost-Benefit Analysis, ” Health Phys. 25:527,

November 1973.

et al., Benefit-cost Analysis for Menta l

Retardation Programs, Theoretical ~onsidera -

100.

101.

102,

103.

104.

105.

106.

107.

108.

109.

110.

111.

112,

113.

tions and a Model for Application (Ann Arbor,

Mich.: University of Michigan, Institute for the

Study of Mental Retardation and Related Disabilities, 1971).

Cohn, E., “Assessing the Costs and Benefits of

Anti-Malaria Programs: The Indian Experience, ” Am. J. Public Health 63:1086, December

1973,

, “Assessment of Malaria Eradication

Costs and Benefits, ” Am. J. Trop. Med. Hyg.

21:663, September 1972.

Cohodes, D., Listening to Babies: Benefit-Cost

Analysis and Its Application to Fetal Monitoring (Cambridge, Mass.: Urban Systems Research and Engineering, Inc., n.d. ).

Cole, P., “Elective Hysterectomy: Pro and

Con,” N. Eng. J. Med. 295:264, 1976.

Cohen, M., et al., “Cost Analysis of Alternative Health Examination of Modes, ” Arch.

Intern. Med. 137:73, January 1977.

, et al., “Cost Analysis of a Multiphasic

Screening Program, “N. Eng. J. Med. 280:1043,

May 8, 1969.

, et al., “Dollar Cost Per Positive Test

for Automated Multiphasic Screening, ” N.

Eng. J. Med. 283:459, 1970.

, et al., “Multiphasic Checkup Evaluation Study: Preliminary Cost Benefit Analysis

for Middle Aged Men, ” Prev. Med. 2:236, June

1973.

Collis, P., et al., “Adenovirus Vaccines in Military Recruit Populations: A Cost-Benefit Analysis, ” J. Infect. Dis. 128:745, December 1973.

Committee for the Study of Inborn Errors of

Metabolism, “An Economic Perspective on

Evaluating Screening Programs, ” in Genetic

Screening: Programs, Principles, and Research

(Washington, D. C.: National Research Council, 1975).

Committee on Interstate and Foreign Commerce, U.S. House of Representatives, “Cost

and Quality of Health Care: Unnecessary Surgery, ” report by the Subcommittee on Oversight and Investigations (Washington, D. C.:

U.S. Government Printing Office, January

1976).

Conley, R., The Economics of Vocational Rehabilitation (Baltimore, Md.: Johns Hopkins

University Press, 1965).

“Issues in Benefit-Cost Analyses of the

Vocational Rehabilitation Program, ” Am. Rehabil. 1:19, November-December 1975.

, “Mental Retardation: An Economist’s

Approach, ” Merit. Retard. 14:20, December

1976.
114.

115.

116.

117.

118.

119.

120.

121.

122.

123.

124.

125.

126.

127.

128.

129.

130.

131.

132.

and Milunsky, A., “The Economics of

Prenatal Genetic Diagnosis,” in The Prevention

of Genetic Disease and Mental Retardation,

edited by A. Milunsky (Philadelphia, Pa.:

Saunders, 1975).

“Cost-Effective Health Care, ” editorial, Nurs.

Times 72:119, Jan. 29, 1976.

“Cost-Effectiveness of Health Services, ” N.

Eng. J. Med. 278:1069, May 9, 1968.

“Cost-Effectiveness Studies, ” Br. Med. J. 2:848,

Sept. 23, 1978.

“Costs and Benefits, ” editorial, Lancet 2:7889,

Nov. 9, 1974.

“Costs and Benefits of Hysterectomy, ” letter,

N. Eng. J. Med. 295:1085, Nov. 4, 1976.

Crabtree, M., “Application of Cost-Benefit

Analysis to Clinical Nursing Practice: A Comparison of Individual and Group Preoperative

Teaching, ” J. Nurs. Admin. 8:11, December

1978.

Creese, A., et al., “Hospital or Home Care for

the Severely Disabled: A Cost Comparison, ”

Br. J. Prev. Soc. Meal, 31:116, June 1977.

Cretin, S., “Cost-Benefit Analysis of Treatment

and Prevention of Myocardial Infarction, ”

Health Serv. Res. 12:174, summer 1977.

Criley, J., et al., “Mobile Emergency Care

Units: Implementation and Justification, ” Adv.

Cardiol. 15:9, 1975.

Cromwell, J., and Gertman, P., “The Early Detection of Cancer: Some Economic Issues, ” paper presented at a conference of the American

Society of Preventive Oncology, New York,

N. Y., February 1977.

Crystal, R., and Brewster, A., “Cost-Benefit

and Cost-Effectiveness Analyses in Health

Field: An Introduction,” Inquiry 3:3, 1966.

Cuzacq, G., and Glass, R., “The Projected Financial Savings in Dental Restorative Treatment: The Result of Consuming Fluoridated

Water, ” J. Public Health Dent, 32:52, winter

1972.

Davies, G., “Fluoride in the Prevention of Dental Caries I,” Br. Dent. J. 135, July 1973.

“Fluoride in the Prevention of Dental

Caries ii,” Br. Dent, J. 135:131, Aug. 7, 1973.

, “Fluoride in the Prevention of Dental

Caries 111,” Br. Dent. J. 135:173, Aug. 21, 1973.

, “Fluoride in the Prevention of Dental

Caries IV,” Br. Dent. J. 135:233, Sept. 4, 1973.

, “Fluoride in the Prevention of Dental

Caries V,” Br. Dent. J. 135:293, Sept. 18, 1973.

“Fluoride in the Prevention of Dental

Caries VI, ” Br. Dent, J. 135:333, Oct. 2, 1973.

133.

134.

135.

136.

137.

138.

139.

140.

141.

142.

143.

144.

145.

146.

147.

Dawson, P., et al., “Cost-Effectiveness of

Screening Children in Housing Projects, ” Am.

. Public Health 66:1192, December 1976.

Deane, R., and Ulene, A., “Hysterectomy or

Tubal Ligation for Sterilization: A Cost-Effectiveness Analysis, “ Inquiry 14:73, March 1977.

Deinard, A., et al., “Screening of a High-Risk

Ambulatory Female Population for Urinary

Tract Infection: A Cost-Effectiveness Study, ”

Minn. Med. 60:123, February 1977.

Department of Health, Education, and Welfare, Disease Control Programs: Arthritis

Washington, D. C.: U.S. Government Printing

Office, 1966).

Disease Control Programs: Cancer

(Washington, D. C.: U.S. Government Printing

Office, 1966).

Disease Control Programs: Delivery of

Health Services for the Poor (Washington,

D. C.: U.S. Government Printing Office, 1967).

Disease Control Programs: Kidney

Disease: Program Analysis (Washington,

D. C.: U.S. Government Printing Office, 1967).

Program Analysis: Maternal, and

Child ‘Health Care Programs (Washington,

D. C.: U.S. Government Printing Office, 1966).

Desimone, A., “Individualizing Rehab Plans

for Cost-Effective Gains, ” Soc. Rehabil. Rec.

2:24, December 1974-January 1975.

Dhillon, W., and Bennett, A., “A Cost-Performance Analysis of Alternative Manpower

Technology Combinations for Delivering Primary Health Care” (McLean, Va.: Mitre Corp.,

1975).

Dickhaus, E., “Economic Evaluation of Missouri Automated Radiology System, MARS: A

Case Study, ” dissertation, William Woods College, Fulton, Me., May 1974.

Dickinson, L., “Evaluation of the Effectiveness

of Cytologic Screening for Cervical Cancer:

Cost-Benefit Analysis, ” Mayo Clin. P. 47:550,

August 1972.

Dittman, D., and Smith, K., “Consideration of

Benefits and Costs: A Conceptual Framework

for the Health Planner,” Health Care Mgt.

Rev., fall 1979.

Dodge, W., “Cost Effectiveness of Renal Disease Screening, ” Am. J. Dis. Child 131:1274,

November 1977.

Doherty, N., and Powell, E., “Effects of Age

and Years of Exposure on the Economic Benefits of Fluoridation,” J. Dent, Res. 53:912 ,

August 1974.
148.

149.

150.

151.

152.

153.

154.

155.

156.

157.

158.

159.

160.

161.

, et al., “Cost-Effectiveness Analysis and

Alternative Health Care Programs for the Elderly, ” Health Serv. Res. 12:190, summer 1977.

, et al., “The Use of Cost-Effectiveness

Analysis in Geriatric Day Care, ” Gerontologist

15:412, October 1975.

Donabedian, A., et al., “The Numerology of

Utilization Control Revisited: When To Recertify, ” Inquiry 14:96, March 1977.

Dormer, E., “Cost-Benefit Evaluation of Alternative Hospital Structures, ” in Systems Science

in Health Cur-e, edited by A. Coblenta and J.

Walter (London: Taylor and Francis, 1977).

Doyle, L., et al., “Attacking the Cost Crisis, ”

Int. Med. J. 153:298, April 1978.

Dunlop, D., “Benefit-Cost Analysis: A Review

of Its Applicability in Policy Analysis for Delivering Health Services, ” Soc. Sci. Med. 9:133,

March 1975.

Dyckman, Z., “A Cost-Benefit Analysis of Federal Support for Medical Education, ” in Evaluation in Health Services Delivery, proceedings

of an Engineering Foundation Conference,

South Berwick, Maine, Aug. 19-24, 1973.

Eddy, D., “The ACS Report on the Cancer-Related Health Checkup: Recommendations and

Rationale, ” report to the American Cancer

Society, New York, N. Y., February 1980.

“Measuring the Effectiveness of Therapeutic Surgical Procedures: A Master Plan, ” in

Medical Technology Research Priorities, edited

by J. Wagner (Washington, D. C.: Urban Institute, March 1979).

, “Rationale for the Cancer Screening

Benefits Program Screening Policies: Implementation Plan, Part III, ” report to the National Cancer Institute, Blue Cross Association,

Chicago, Ill., 1978.

Screening for Cancer: Theory, Analysis, and Design (Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1980).

“Screening for Colon Cancer: A Technology’ Assessment, ” in The Implications of

Cost-Effectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of

Medical Technologies, prepared by OTA, U.S.

Congress (Washington, D. C.: in press, 1980).

Ekblom, M., et al., “Costs and Benefits of Measles Vaccination in Finland, ” Scand. J. SO C.

Med. 6:111, 1978.

Emlet, H., Jr., “Definition of Cost Analysis,

Cost-Effectiveness Analysis, and Cost-Benefit

Analysis in Medicine” (Falls Church, Va.: Analytic Services, Inc., Jan. 24, 1969).

162.

163.

164.

165.

166.

167.

168.

169.

170,

171.

172.

173.

174.

175.

176.

, et al., Estimated Health Benefits and

Cost of Post-Onset Care for Stroke (Arlington,

Va.: Analytic Services, Inc., September 1973).

, et al., “Use of Cost-Benefit Analysis in

Solutions to National Health Problems, ” May

1968.

Evans, W., Cost-Effectiveness Studies, National Health Watch, Inc., 1977.

Evens, R., and Jest, R., “The Cranial Efficacy

and Cost Analysis of Cranial Computed Tomography and the RadionucIide Brain Scan, ”

Sem. Nuc. Med. 2:129, 1977.

, and Jest, R., “Economic Analysis of

Body Computed Tomography Units Including

Data on Utilization, ” Radio. 127:151, 1978.

, and Jest, R., “Economic Analysis of

Computed Tomography Unit, ” Am. J. Roentgenol. 127:191, 1976.

, et al., “The Clinical Efficacy and Cost

Analysis of Cranial Computed Tomography

and the Radionuclide Brain Scan, ” Sem. Nucl.

Med. 7:129, April 1977.

, et al., “Utilization, Reliability, and

Cost Effectiveness of Cranial Computed Tomography in Evaluating Pseudotumor Cerebri,” Am. J. Roentgenol. 129:263, August 1977.

, et al., “Utilization of Head Computed

Tomography Units in Installations With Greater Than Two-and-a-Half Years’ Experience, ”

Radio. 131, June 1979.

, et al., “Utilization of Head Computed

Tomography Units in Installations With Greater Than One-and-a-Half Years’ Experience, ”

Radio. 131:695, June 1979.

Fabricius, J., “A Cost Benefit Analysis of Different Types of Pacemakers, ” Scand. J. Thorac.

Cardiovasc. Surg. t 1978.

Farber M., and Finkelstein, S., “A Cost Benefit

Analysis of a Mandatory Premarital RubellaAntibody Screening Program, ” N. Eng. J. Med.

300:856, April 1978.

Fast, J., “Feasibility Study for the Evaluation of

Methodologies for Cost-Benefit Analysis of

Restoration Services in Rehabilitation” (Falls

Church, Va., October 1978).

Feigenson, J., “Stroke Rehabilitation: Effectiveness, Benefits, and Cost, Some Practical

Considerations, ” Stroke 10:1, January-February 1979.

, et al., “A Comparison of Outcome and

Cost for Stroke Patients in Academic and Community Hospital Centers, ” J. A.M.A. 240:1878,

1978.
177.

178.

179.

180.

181.

182.

183.

184.

185.

186.

187.

188.

189.

190.

Fein, R., “But On the Other Hand: High Blood

Pressure, Economics and Equity, ” N. Eng. J.

Med. 296:751, Mar. 31, 1977.

Economics of Mental Illness (New

York, N. Y.: Basic Books, 1958).

“On Measuring Economic Benefits of

Health ‘Programs, “ in Ethics and Health Policy,

edited by R. Veatch and R. Branson (Cambridge, Mass.: Ballinger, 1976).

Feingold, A., “Cost Effectiveness of Screening

for Tuberculosis in a GeneraI Medical Clinic, ”

Public Health Rep. 90:544, November-December 1975.

Felch, W., “The Routine Physical and Examination—Opiate of the Masses. Is It Worth the

Cost? An Overview of the Problem, ” J. Term.

Med. Assoc. 69:177, March 1976.

Feldstein, M., “Measuring the Costs and Benefits of Health Services, ” Regional Office for

Europe (Copenhagen: World Health Organization, June 1966).

Feldstein, P., “Financing Hypertension: The

Costs and Benefits of Government Intervention, ” The Hypertension Coordinating and

Planning Corp. of Southwestern Michigan,

June 1974.

Fenwick, A., “The Costs and a Cost-Benefit

Analysis of an S. Mansoni Control Programme

on an Irrigated Sugar Estate in Northern Tanzania, ” Bull. WHO 47:573, 1972.

Ferguson, R., “Cost and Yield of the Hypertensive Evaluation: Experience of a CommunityBased Referral Clinic, ” Ann. Intern. Med. 82:

761, June 1975.

Fernandez, P., “Costs and Benefits of Rehabilitation of Heroin Addicts, ” dissertation, Claremont Graduate School, Calif., 1972.

Field, H., and Jong, A., “Cost Effectiveness of

Bussing Pupils to a Dental Clinic, ” HSMHA

Health Rep. 86:222, March 1971.

Fineberg, H., “Clinical Chemistries: The High

Cost of Low-Cost Diagnostic Tests, ” in Medical Technology: The Culprit Behind Health

Care Costs? edited by S. H. Altman and R.

Blandon, proceedings of the 1977 Sun VaIley

Forum on National Health, DHEW publication

No. (PHS) 79-3216 (Washington, D. C.: U.S.

Government Printing Office, 1979).

“Life, Death . . . and Dollars, ” T h e

Sciences 18:30, December 1978.

, and Pearlman, L., “Benefit and Cost

Analysis of Medical Interventions: The Case of

Cimetidine and Peptic Ulcer Disease, ” in The

Implications of Cost-Effectiveness Analysis of

Medical Technology/Background Paper #2:

191.

192,

193.

194.

195.

196.

197.

198.

199.

200.

201.

202.

203.

204.

Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington,

D. C.: in press, 1980).

Fitzpatrick, G., et al., “Cost-Effectiveness of

Cholectstectomy for Silent Gallstones, ” in

Costs, Risks, and Benefits of Surgery, edited by

J. P. Bunker, et al. (New York, N. Y.: Oxford

University Press, 1977).

Fitzpatrick, P., “Cost-Effectiveness in Cancer, ”

Can, Med. Assoc. J, 111:652, October 1974.

Flagle, C., “Some Approaches to Cost-Benefit

Analysis and Evaluation in Cardiovascular

Disease, ” Cardiovasc. Res. Cent. Bull. 15:29,

July-September 1976.

Foley, H., et al., “The Cost-Effectiveness of a

Mental Center: An Experiment, ” in Evaluation

in Health Services Delivery, proceedings of an

Engineering Foundation Conference, South

Berwick, Maine, Aug. 19-24, 1973.

Foltz, A., and Kelsey, J., “The Annual Pap

Test: A Dubious Policy Success, ” Milbank

Mere. 56:426, fall 1978.

Foote, A., et al., “Controlling Hypertension: A

Cost-Effective Model, ” Prev. Med. 6:319, June

1977.

Forst, B., “An Analysis of Alternative Periodic

Health Examination Strategies, ” in BenefitCost and Policy Analysis, 1972, edited by W.

Niskaren, et al. (Chicago, Ill.: Aldine, 1973).

“The Grisly Analytics of Death, Disability and Disbursements, ” paper presented at

the 40th National Meeting of the Operations

Research Society of America, Anaheim, Calif.,

October 1971.

Francis, G., et al., “The Economic Benefits of

Early Diagnosis and Training for Handicapped

Children, ” Am. Correct. Ther. J. 30:47,

March-April 1976.

Fraser, R., “Canadian Hospital Costs and Efficacy, ” paper prepared for the Economic Council of Canada (Ottawa: Information Canada,

January 1971).

Freeman, R., et al., “Economic Cost of Pulmonary Emphysema: Implications for Policy on

Smoking and Health,” Inquiry 13:15, March

1976.

Fudenberg H., “The Dollar Benefits of Biomedical Research: A Cost Analysis, ” J. Lab. Clin.

Med. 70:353, 1972,

Fulchiero, A., et al., “Can PSROs Be Cost Effective?” N. Eng. J. Med. 299:574, 1978.

Galliherr H., “Cost-Effective Planned Lifetime

Schedule of Pap Smears: Estimated Maximal

Potentials” (Ann Arbor, Mich.: University of
Appendix B-- Bibliography on CEA/CBA ● 87

205.

206.

207.

208.

209.

210.

211.

212.

213.

214.

215.

216.

217.

Michigan, Department of Industrial and Operations Engineering, March 1976).

Garrison, L., “Studies in the Economics of

Surgery, ” dissertation, Stanford University,

Palo Alto, Ca]if., 1978.

Geiser, E., and Menz, F., “The Effectiveness of

PubIic Dental Care Programs, ” Med. Care. 14:

189, March 1976.

Gelfand, D., et al., “Costs of Gastrointestinal

Examinations: A Comparative Study, ” Gastroin. Radio. 3:135, June 25, 1978.

Geller, N., and Yockmowitz, M., “Regional

Planning of Maternity Services, ” Health Serv.

Res. 10:63, 1975.

Gellman, D., “Cost-Benefit in Health Care: We

Need To Know Much More, ” Can. Med.

ASSOC . J.. 111:998, Nov. 1, 1974.

Gelman, C., “Health Economics. The Cost of

Illness, Cost-Benefit and Cost-Effectiveness

Analysis of Screening Programs: Cost Analysis, ” in Multiphasic Health Testing/Screening

Systems State of the Art (New York, N. Y.:

American Health Foundation, 1970).

Gempel, P., et al., “Comparative Cost Analysis: Computed Tomography vs. Alternative Diagnostic Procedures, 1977-1980” (Cambridge,

Mass.: Arthur D. Little, Inc., December 1977).

General Accounting Office, U.S. Congress,

Treatment of Chronic Kidney Failure: Dialysis,

Transplant, Costs, and the Need for More Vigorous Efforts (Washington, D. C,: U.S. Government Printing Office, 1975).

Giauque, W., “Prevention and Treatment of

Streptococcal Sore Throat and Rheumatic

Fever—A Decision Theoretic Approach, ” dissertation, Harvard University, Graduate

School of Business Administration, Cambridge, Mass., 1972.

Gilbert, J., et al., “Progress in Surgery and Anesthesia: An Evaluation of Therapy, ” in CostEffectiveness Analysis: New Approaches in Decision making, edited by J. Goldman (Washington, D. C.: Praeger Publications, 1967).

Gill, R., “Emergency Ambulance Service (A)

and (B), ” in Cases in Urban Management,

edited by J. Russell (Cambridge, Mass.: MIT

Press, 1974).

Gillum, R., et al., “Screening for Hypertension:

A Rational Approach,” J. Comm. Health 4:67,

fall 1978.

Ginsberg, A., and Off send, F., “An Application of Decision Theory to a Medical Diagnosis/Treatment Problem, ” IEEE Trans. Sys. Sci.

Cyb. 4:355, September 1968.

218.

219.

220.

221.

222.

223.

224.

225.

226.

227.

228.

229.

230.

231.

232.

Ginsberg, G., et al., “Costs and Benefits of Behavioral Psychotherapy: A Pilot Study of Neurotics Treated by Nurse-Therapists, ” Psychol.

Med. 7:685, November 1977.

Glasgow, J., “Cost-Benefit and Cost-Effectiveness Analyses in the Health Field, ” paper

presented at the National Regional Medical

Programs Conference and Workshop on Evaluation, University of Chicago Center for Continuing Education, Sept. 28-30, 1970.

Glass, N., “Cost-Benefit Analysis and Health

Services,” Health Trends 5:51, 1973.

“Economic Aspects of the Prevention

of Down’s Syndrome, ” in Systems Aspects of

Health Planning, edited by N. Bailey and M.

Thompson (Amsterdam: Elsevier-North Holland Publishing Co., 1975).

, and Russell, I., “Proceedings: CostBenefit Analysis in the Health Service—A Case

Study of Elective Herniorrhaphy,” Br. J. Prev.

Soc. Med. 28:68, February 1974.

, et al., “Cost-Benefit Analysis and the

Evaluation of Psychiatric Services, ” Psychol.

Med. 7:701, November 1977.

Goldhaber, S., et al., “Effects of the Fiberoptic

Laparoscope and Colonoscope on Morbidity

and Cost, ” Ann. Surg. 179:160, February 1974.

Goldschmidt, P., “A Cost-Effectiveness Model

for Evaluating Health Care Programs: Application to Drug Abuse Treatment, ” Inquiry 13:29,

March 1976.

Gerry, G., et al., “Cost-Effectiveness of Cardiopulmonary Resuscitation Training Programs, ” Health Serv. Res. 12:30, spring 1977.

Grab, B., and Cvjetanovic, B., “Simple Method for Rough Determination of the CostBenefit Balance Point of Immunization Programmes, ” Bull. WHO 45:536, 1971.

Gragono, A., “Temporal Units for Expressing

Cost Effectiveness, ” letter, N. Eng. J. Med.

297:284, Aug. 4, 1977.

Grainger, R., “Cost-Benefit Analysis: Application to Dental Services, ” J. Can. Dent. Assoc.

39:693, October 1973.

Gravelle, H., “The Economic Evaluation of

Screening for Breast Cancer: A Tentative

Methodology,” May 1976.

Green, J., “Cost-Benefit Analysis of Surgery:

Some Additional Caveats and Interpretations, ”

in Costs, Risks, and Benefits of Surgery, edited

b y J. P. Bunker, et al. (New York, N. Y.: Oxford University Press, 1977).

Green, L., “The Potential of Health Education

Includes Cost Effectiveness, ” Hospitals 50:57,

May 1976.
233.

234.

235.

236.

237.

238.

239.

240.

241.

242.

243.

244.

245.

246.

247.

248.

, “Toward Cost-Benefit Evaluations of

Health Education: Some Concepts, Methods,

and Examples, ” Hlth. Educ. Monog. 2, 1974.

Green, V., “Cost-Effectiveness and Hospital

Environmental Sanitation,” Can. Hosp. 47:34,

July 1970.

Griffith, J., and Chernow, R., “Cost Effective

Acute Care Facilities Planning in Michigan, ”

Inquiry 14:229, 1977.

Griner, P., “Cost Versus Effectiveness of Laboratory Studies, ” J. Term. Med. Assoc. 69:179,

March 1976.

“Treatment of Acute Pulmonary Edema: Conventional or Intensive Care?” Ann. Intern. Med. 182:1102, 1973.

Grosse, R., “Analysis in Health Planning, ” in

Analysis of Public Systems, edited by A.

Drake, et al. (Cambridge, Mass.: MIT Press,

1972).

“Cost-Benefit Analysis in Disease Control Programs, ” in Cost-Benefit Analysis,

edited by M. Kendall (New York, N. Y.: American Elsevier, 1971).

“Cost-Benefit Analysis of Health Services,” Ann. Am. Acad. Polit. Soc. Sci. 399:89,

January 1972.

“Problems of Resource Allocation in

Health,” in Public Expenditures and Policy

Analysis, edited by R. Haveman and J. Margolis (Chicago, Ill.: Markham Publishing Co.,

1970).

Guillette, W., et al., “Day Hospitalization as a

Cost Effective Alternative to Inpatient Care: A

Pilot Study,” Hosp. Comm. Psych. 29:525,

August 1978.

Gumbhir, A., and Brown, W., “Cost-Benefit

Analysis of Unit Dose Drug Distribution Systems: A Conceptual Approach, ” Hosp. Top.

53:35, May-June 1975.

Gunn, A., “Cost Effectiveness? It’s Time to

Blow the Whistle, ” Crit. Care Med. 6:352, September-October 1978.

Haber, Z., and Leatherwood, E., Jr., “A Dental

Program for Head Start Children in New York

City: A Retrospective Study of Utilization and

Costs,” Med. Care 7:281, July-August 1959.

Hagard, S., et al., “Preventing the Birth of Infants With Down’s Syndrome: A Cost-Benefit

Analysis,” Br. Med. J. 1:753, Mar. 27, 1976.

, et al., “Screening for Spina Bifida Cystica: A Cost-Benefit Analysis, ” Br. J. Prev. Soc.

Med. 30:40, March 1976.

Hamilton, J., “A Method for Estimating the

Cost, Growth Rate, and Efficiency of Radioiso249.

250.

251.

252.

253.

254.

255.

256.

257.

258.

259.

260.

261,

262.

263.

264.

tope Laboratories, ” Am. J. Med. Technol. 34:

473, August 1968.

Hannan, E., and Graham, J., “A Cost-Benefit

Study of a Hypertension Screening and Treatment Program at the Work Setting, ” Inquiry

15:345, December 1978.

Hannan, T., “The Benefits and Costs of Methadone Maintenance,” Public Policy 24:197,

spring 1976.

The Economics of Methadone Maintenance (’Lexington, Mass.: D.C. Heath and Co.,

Lexington Books, 1975).

Harder, E., “Searching for Cost-Effective

Measures That Also Improve Care, ” Hospitals

51:155, April 1977.

Harris, G., “Introduction to Cost-Benefit Analysis Applied to New Health Technologies, ”

prepared by Arthur D. Little, Inc. (Hyattsville,

Md.: Health Resources Administration, Bureau

of Health Planning and Resources Development, December 1977).

Havia, T., et al., “The Re-Use of Previously

Implanted Pacemakers, ” Scand. J. Thorac.

Cardiovasc. Surg., 1978.

Hawkins, B., “Cost-Benefit Analysis as a Tool

To Evaluate Capital Acquisitions, ” Hospitals

52:60, Oct. 1, 1978.

Hazell, J., et al., “Intermediate Benefit Analysis

—Spencer’s Dilemma and School Health Services,” Am, J. Public Health 62:560, April 1972.

Heagarty, M., et al., “Some Comparative

Costs in Comprehensive Versus Fragmented

Pediatric Care, ” Pediatrics 46:596, October

1970.

He Hefner, D., A Study 

to Determine the CostEffectiveness of a Restrictive Formulary: The

Louisiana Experience (Washington, D. C.: National Pharmaceutical Council, Inc., 1979).

Hertzman, M., et al., “Cost-Benefit Analysis

and Alcoholism, ” J. Stud. Alcohol 38:1371,

July 1977.

Hessel, S., “Perspectives on Benefit-Cost Analysis in Medical Care, ” editorial, Am. J. Roentgenol. 129:753, October 1977.

Hiatt, H., “Lessons of the Coronary-Bypass

Debate,” N. Eng. J. Med. 297:1462, 1977.

“Protecting the Medical Commons:

Who Is Responsible?, ” N. Eng. J. Med. 293:

235, July 31, 1975.

Hilbert, S., “Prevention,” Am. J. Public Health

67(4):35, April 1977.

Hoffman, K., et al., “The ‘Cost-Effectiveness’

of Sim One, ” J. Med. Educ. 50:1127, December

1975,
265.

266.

267.

268.

269.

270.

271.

272.

273.

274.

275.

276.

277.

278.

Holahan, J., “The Economics of Drug Addiction and Control in Washingtonr D. C.: A

Model for Estimation of Costs and Benefits of

Rehabilitation” (Washington, D. C.: District of

Columbia Department of Corrections, 1970).

“Measuring Benefits From Alternative

Heroin ’Policies, “ in National Conference Methodone Treatment Proceedings 2:1219, 1973.

Holler, A., “Risks Versus Benefits in Breast

Cancer Diagnosis, ” CA-A Cancer J. for Clinicians. 26:63, 1976.

Holtman, A., “Alcoholism and the Economic

Value of a Man, ” Rev, Soc. Eco. 23:143, September 1965.

Hu, T., et al., Pennsylvania State University,

Institute for Policy and Research and Evaluation, “Cost-Effectiveness Study of Drug Prevention Programs, ” June 30, 1978.

Hughes, J., “A Method To Determine the Cost

Effectiveness of Occupational Health Programs, ” J. Occup. Med. 16:156, March 1974.

Hurtado, A., et al., “The Utilization and Cost

of Home Care Facility Services in a Comprehensive, Prepaid Group Practice Program, ”

Med. Care 10:8, January-February 1972.

Ingalls, J., et al., “Attacking the Cost Crisis, ”

Int. Med. J. 153:125, February 1978.

Inman, R., “On the Benefits and Costs of Genetic Screening, ” editorial, Am. J. Hum. Gent.

30:219, March 1978.

Institute for Medical Information Processing, Bestandsanfnahme Gesundheits-Systemforschung, State of the Art Report Health Systems Research, vols. 1 & 2, computerized literature compilation compiled for the Robert

Bosch Foundation, Munich University, West

Germany.

Jackson, M., et al., “Elective Hysterectomy: A

Cost-Benefit Analysis, ” Inquiry 15:275, September 1978.

Jackson, S., and Ward, D., “Prevention of Institutionalization: A Cost-Effectiveness Model

of Community Based Alternatives, ” paper presented at the Annual Meeting of the American

Public Health Association, Miami Beach, Fla.,

Oct. 17-21, 1976.

Jaffe, F., et al., “Short-Term Benefits and Costs

of U.S. Family Planning Programs, 1970-

1975, ” Fam. Plann. Perspect. 9:77, MarchApril 1977.

Jeffers, J., and Johnson, J., “A Cost-Benefit

Analysis of Heroin Abuse Control Programs, ”

Bureau of Business and Economic Research

working paper (Iowa City, Iowa: University of

Iowa, 1973).

279.

280.

281.

282.

283.

284.

285.

286.

287.

288.

289.

290.

291.

292.

293,

294.

Joehnk, M., and McGrail, G., “Benefit-Cost

Ratios for Family Practice Residency Centers, ”

Manage. Account 58:41, February 1977.

Joglekar, P., “Cost-Benefit Studies of Health

Care Programs: Choosing Methods for Desired

Results, ” paper presented at the Joint National

Meeting of TIMS/ORSA, Washington, D. C.,

May 1980.

Johns, M., et al., Benefit-Cost Analysis of Alcoholism Treatment Centers (Rockville, Md.:

National Institute on Alcohol Abuse and Alcoholism, May 1976).

Jonas, A., “Cost-Effectiveness of Developing

Animal Models, ” in Animal Models of Thrombosis and Hemorrhagic Diseases (Bethesda,

Md.: National Institutes of Health, 1976).

Jong, A., and Gluck, G., “Factors Influencing

the Cost-Effectiveness of Community Health

Center Dental Programs in the USA, ” Comm.

Dent. Oral Epidemiol. 2:263, 1974.

Kagan, A., and Skinner, D., “Detection of

Metastatic Disease in the Urologic Patient: An

Opinion on Cost Versus Benefit, ” J. Urol.

120:140, August 1978.

Kane, R., “Societal Values and Modern Medicine: How Do We Measure Costs Benefits?” J.

Comm. Health 4:97, winter 1978.

, et al., “Can Nursing-Home Care Be

Cost-Effective?” J. Am. Geriatr. Soc. 22:265,

June 1974.

, et al., “IS Good Nursing-Home Care

Feasible?” ). A.M.A. 235:516, Feb. 2, 1976.

Kaser, M., “Choice of Technique, ” in The Economics of Health and Medical Care, edited by

M. Perlman (New York, N. Y.: John Wiley and

Sons, 1974).

Keith, L., et al., “Gonorrhea Detection in a

Family Planning Clinic: A Cost-Benefit Analysis of 2,000 Triplicate Cultures, ” Am, J. Obst.

G. 121:399, Feb. 1, 1975.

Kirby, W., “Cost-Benefit Analysis in a Large

Health Care System, “ in Cost-Benefit Analysis,

edited by M. Kendall (New York, N. Y.: American Elsevier, 1971).

Klarman, H. , “Application of Cost-Benefit

Analysis to the Health Services and the Special

Case of Technologic Innovation, ” Int. J. Health

Serv. 4:325, Spring 1974.

“Application of Cost-Benefit Analysis

to Health Systems Technology, ” J. Occup.

Med. 16:172, March 1974.

The Economics of Health (New York,

N. Y.: Columbia University Press, 1965).

, “Observations on Health Care Technology: Measurement, Analysis, and Policy, ”
90 ● Background Paper #1: Methodological Issues and Literature Review

295.

296.

297.

298.

299.

300.

301.

302.

303.

304.

305.

in Medical Technology: The Culprit Behind

Health Care Costs, edited by S. H. Altman and

R. Blandon, proceedings of the 1977 Sun Valley

Forum on National Health, DHEW publication

No. (PHS) 79-3216 (Washington, D. C.: U.S.

Government Printing office, 1979).

, “Present Status of Cost-Benefit Analysis in the Health Field, ” Am. J. Public Health

57:1948, November 1967.

“The Socioeconomic Impact of Heart

Disease, ” in The Second National Conference

on Cardiovascular Disease, the Heart and Circulation (Washington, D. C.: Federation of

American Societies for Experimental Biology,

1965).

, and Guzick, D., “Economics of Influenza, “ in Influenza: Virus, Vaccines, and Strategy, edited by P. Selby (New York, N. Y.: Academic Press, 1976).

, et al., “Cost Effectiveness Analysis Applied to the Treatment of Chronic Renal Disease, ” Med. Care 6:48, January-February 1968.

Knapper, D., and Dungy, C., “Cost-Benefits of

Using Practitioners in a School-Based CHDP

Program, ” paper presented at the Annual

Meeting of the American Public Health Association, Los Angeles, Calif., Oct. 19, 1978.

Knaus, W., and Davis, D., “Utilization and

Cost-Effectiveness of Cranial Computed Tomography at a University Hospital, ” J. Comput. Assist, Tomogr., 1978.

and Wagner, D., “CT Scanning Patients With Severe Headache: A Cost Benefit

Calculation, ” forthcoming.

Knobel, R., and Longest, B., “Problems Associated With the Cost-Benefit Analysis Technique in Voluntary Hospitals, ” Hosp. Admin.

19:42, winter 1974.

Kodlin, D., “A Note on the Cost-Benefit Problem in Screening for Breast Cancer, ” Meth. lnf.

Med. 11, 1972.

Korenbrot, C., Flood, A., Higgins, M., Roos,

N., and Bunker, J., “Elective Hysterectomy:

Costs, Risks, and Benefits, ” in The Implications

of Cost-Effectiveness Analysis of Medical

Technology/Background Paper #2: Case Studies of Medical Technologies, prepared by

OTA, U.S. Congress (Washington, D. C.: in

press, 1980).

Kramer, M., “Ethical Issues in Neonatal Intensive Care: An Economic Perspective, ” in Ethics

of Newborn lntensive Care, edited by A. R.

Joneson and M. Garland (Berkeley, Calif.: Institute of Governmental Studies, 1976).

306.

307.

308.

309.

310.

311.

312.

313.

314.

315.

316.

317.

318.

319.

320,

Krause, B., et al., “Is Coronary Artery Surgery

So Expensive?” N. Z. Med. J. 86:570, Dec. 28,

1977.

Kristein, M., “Cost-Effectiveness Analysis for

HSA Planning, ” paper presented at the Annual

Meeting of the American Public Health Association, New York, N. Y., Nov. 7, 1979.

, “Cost Effectiveness of Various Smoking Cessation Methods” (New York, N. Y.:

American Health Foundation, 1977).

, “Economic Issues in Prevention, ” Prev.

Med. 6:252, 1977.

“The Economics of Screening for ColoRectal Cancer” (Stony Brook, N. Y., American

Health Foundation (unpublished)).

“Economics of Secondary Prevention:

Screening for Disease—An Example From Colorectal Cancer, ” paper presented to the American Society of Preventive Oncology, Washington, D. C., Mar. 9, 1978.

, and Arnold, C., “A Mini Cost-Effectiveness Analysis of Mammography as a Procedure for the Mass Screening of Asymptomatic

Populations, ” paper presented at the Annual

Western Economic Association Conference,

San Diego, Calif., June 17, 1980.

, and Arnold, C., “Mammographic

Screening for Breast Cancer—An Economic

Analysis, ” paper presented at the Annual Meeting of the American Public Health Association,

Los Angeles, Calif., Oct. 17, 1978.

and Jonas, S., “A Cost-Effectiveness

Manual for HSA Planning, ” draft prepared for

the National Center for Health Services Research, Hyattsville, Md., February 1980.

, et al., “Health Economics and Preventive Care, ” Science 195:457, February 1977.

Kuschner, J., “A Benefit-Cost Analysis of

Nurse Practitioner Training, ” Can, J. Public

Health 67:405, September-October 1976.

Laguna, J., et al., “Impact of Computerized Tomography in Medical Practice: Cost-Effectiveness Considerations, ” Ariz. Med. 34:344, May

1977.

Lasdon, G., et al., “Evaluating Cost-Effectiveness Using Episodes of Care, ” Med. Care

15:260, March 1977.

Lashof, J., “Do Benefits Exceed Costs of Alternatives to Institutional Care?” Geriatrics 32:33,

November 1977.

Lave, J., and Lave, L., “Measuring the Effectiveness of Prevention: I,” Milbank Mern.,

spring 1977.
321.

322.

323.

324.

325.

326.

327.

328.

329.

330.

331.

332.

333.

Lavor, J., et al., “Home Health Cost Effectiveness: What Are We Measuring?” Med. Care

14:866, October 1976.

Layde, P., et al., “Maternal Serum Alpha-Fetoprotein Screening: A Cost-Benefit Analysis, ”

Am. J. Public Health 69:566, June 1979.

Ledley, R., et al., “Medical Technology and

Cost Containment: Two Applications of Operations Research, ” Science 202:979, Dec. 1,

1978.

Leitch, I., “Value for Money in Health and

Welfare: A LocaI Study of the Home Help

Service, ” R. Soc. Health J. 88:159, May-June

1968.

LeRoy, L., and Solkowitz, S., “Costs and Effectiveness of Nurse Practitioners, ” in The Imp/ications of Cost-Effectiveness Analysis of Medical Technology/Background Paper #2: Case

Studies of Medical Technologies, prepared by

OTA, U.S. Congress (Washington, D. C.: in

press, 1980).

Leslie, A., “A Benefit/Cost Analysis of New

York City Heroin Addiction Problems and Programs—1971, ” in Analysis of Urban Health

Problems, edited by I. Levinson and D. J.

Weiss) New York, N. Y.: Spectrum Publications, Inc., 1976).

Lesourd, D., et al., Benefit-Cost Analysis of

Kidney Disease Programs, PHS publication

No. 1941, report prepared by the Research Triangle Institute (Washington, D. C.: U.S. Government Printing Office, 1968).

Leveson, I., “Cost-Benefit Analysis and Program Target Populations: The Narcotics Addiction Treatment Case, ” Amer. J. Econ. Soc.

32:129, April 1973.

and Weiss, J., Analysis of Urba n

Health ‘Problems (New York, N. Y.: Spectrum

Publications, Inc., 1976).

Levin, A., “Cost-Effectiveness in Maternal and

Child Health: Implications for Program Planning and Evaluation, ” N. Eng. J. Med. 278:

1041, 1968.

Lewis, D., et al., “Initial Dental Care Time,

Cost and Treatment Requirements Under

Changing Exposure to Fluoride During Tooth

Development, ” J. Can. Dent. Assoc. 38:140,

April 1972.

Litsios, S., “Developing a Cost and Outcome

Evaluation System, ” Int. J. Health Serv. 6:345,

1976.

Longest, B., “An Empirical Analysis of the

Quality/Cost Relationship,” Hosp. Hlth. Serv.

Admin. 23:20, Fall 1978,

334.

335.

336.

337.

338.

339.

340.

341.

342.

343.

344.

345.

346.

347.

348.

Lubeck, D., and Bunker, J., “The Artificial

Heart: Costs, Risks, and Benefits, ” in The Implications of Cost-Effectiveness Analysis o f

Medical Technology/Background Paper #2:

Case Studies of Medica! Technologies, prepared by OTA, U.S. Congress (Washington,

D. C.: in press, 1980).

Luce, B., “Allocating Costs and Benefits in Disease Prevention Programs: An Application to

Cervical Cancer Screening, ” in The Implications of Cost-Effectiveness Analysis of Medical

Technology/Background Paper #2: Case Studies of Medical Technologies, prepared by

OTA, U.S. Congress (Washington, D. C.: in

press, 1980).

Luft, H., “Benefit-Cost Analysis and Public

Policy Implementation: From Normative to

Positive Analysis, ” Pub, Pol. 24:437, Fall 1976.

Macklin, F., “Mainstreaming: The Cost Issue, ”

Am. Ann. Deaf. 121:364, August 1976.

Mandel, M., “Cost Analysis of Regionalized

Versus Decentralized Abortion Programs, ”

Med. Care 13:137, 1975.

Mani, M., et al., “The Economics of Peritoneal

Dialysis: A Cost-Efficiency Study, ” Nephron.

17:130, 1976.

Marram, G., “The Comparative Costs of Operating a Team and Primary Nursing Unit, ” J.

Nurs. Adm. 6:21, May 1976.

, et al., “Comparison of the Cost-Effectiveness of Team and Primary Nursing Care

Modalities” (Boston, Mass,: New England Deaconess Hospital, Nursing Office, July 1975).

Marshall, A., “Cost-Benefit Analysis in

Health” (Santa Monica, Calif,: RAND Corp.,

December 1965).

Martin, G., and Newman, I., “The Costs and

Effects of a Student Health-Aide Program, ” J.

Am. CoIl. Health Assoc. 21:237, February

1973.

Martin, J., “Research Priorities, ” Dimens.

Health Serv. 55:8, October 1978.

Martin, S., et al., “Inputs Into Coronary Care

During 30 Years: A Cost-Effectiveness Study,”

Ann, Inter. Med. 81:289, 1974.

Marty, A., et al., “The Variation in Hospital

Charges: A Problem in Determining Cost/Benefit for Cardiac Surgery, ” Ann. Thorac. Surg.

24:409, November 1977.

Mather, H., “Cost-Effective Patient Care, ” J.

R. Coil, Physicians Lend. 13:93, April 1979.

, et al., “Acute Myocardial Infarction:

Home and Hospital Treatment, ” Br. Med. J.

3:334, 1971.
92 ● Background Paper #l: Methodological Issues and Literature Review

349.

350.

351.

352.

353.

354.

355.

356.

357.

358.

359.

360.

361.

362.

Matlack, D., “Cost-Effectiveness of Spinal

Cord Injury Center Treatment,” Paraplegia

12:222, 1974.

Maturi, V., “An Automated Cost-Effective

HMO,” Public Health Rep. 91:188, 1976.

May, P., “Cost-Effectiveness of Mental Health

Care: Sex as a Parameter of Cost in the Treatment of Schizophrenia, ” Am. J. Public Health,

60:2269, December 1970.

“Cost-Efficiency of Mental Health

Care: Treatment Method as a Parameter of

Cost in the Treatment of Schizophrenia, ” Am.

J. Public Health 61:127, January 1971.

“Cost-Efficiency of Mental Health Delivery System: A Review of the Literature on

Hospital Care,” Am. J. Public Health 60:2060,

November 1970.

“Cost-Efficiency of Treatments for the

Schizophrenic Patient, ” Am. J. Psychiatry 127:

1382, April 1971.

Maynard, A., “Avarice, Inefficiency and Inequality: An International Health Care Tale, ”

Int. J. Health Serv. 7:179, 1977.

McCaffee, K., “The Cost of Mental Health

Care Under Changing Treatment Conditions, ”

in Program Evaluation in the Health Fields,

edited by H. Schulberg, et al. (New York,

N. Y.: Behavioral Publications, 1969).

McGhan, W., et al., “Cost-Benefit and Cost-Effectiveness: Methodologies for Evaluating Innovative Pharmaceutical Services, ” Am. J.

Hosp. Pharm. 35:133, February 1978.

McGlothlin, W., et al., “Alternative A p -

proaches of Opiate Addiction Control: Costs,

Benefits and Potential, ” Bureau of Narcotics

and Dangerous Drugs Report SC1O-TR-7

(Washington, D. C.: U.S. Government Printing

Office, 1972).

McGregor, M., and Pelletier, G., “Planning of

Specialized Health Facilities: Size vs. Cost and

Effectiveness in Heart Surgery, ” N. Eng. J.

Med. 299:179, July 27, 1978.

McNeil, B., “Pitfalls in and Requirements for

Evaluations of Diagnostic Technologies, ” in

Medical Technology, proceedings of the Urban

Institute Conference, National Center for

Health Services Research, West Palm Beach,

Fla., Dec. 10-12, 1978.

“A Summary of Cost-Effectiveness

Calculations in the Diagnosis and Treatment of

Hypertensive Renovascular Disease,” Bull.

N. Y. Acad. Med. 52:680, July-August 1976.

, and Adelstein, S., “Determining the

Value of Diagnostic and Screening Tests,” J.

Nucl. Med. 117:439, 1976.

363.

364,

365.

366.

367.

368.

369.

370,

371.

372.

373.

374.

375.

376.

377.

378.

379.

, and Adelstein, S., “The Value of Case

Finding in Hypertensive Renovascular Disease,” N. Eng. J. Med. 293:221, 1975.

, et al., “Measures of Clinical Efficacy:

Cost-Effectiveness Calculations in the Diagnosis and Treatment of Hypertensive Renovascular Disease,” N. Eng. J. Med. 293:216, July 31,

1975.

, et al., “Measures of Clinical Efficacy:

III—The Value of the Lung Scan in the Evaluation of Young Patients With Pleuritic Chest

Pain,” J. Nucl. Med. 17:163, March 1976.

, et al., “Primer on Certain Elements of

Medical Decision Making,” N. Eng. J. Med.

293:211, July 31, 1975.

Menz, F., “Economics of Disease Prevention:

Infectious Kidney Disease, ” Inquiry 8:3, 1971.

Merck, Sharp, and Dohme, Vaccine Cost-Benefit Analysis Program (West Point, Pa.: MSD,

n.d. ).

Michels, R., et al., “Mental Health Services for

Students: Cost Benefit and Value,” J. Am. CoIl.

Health Assoc. 24:208, April 1976.

Mikkelsen, M., et al., “Cost-Benefit Analysis

of Prevention of Down’s Syndrome, ” in Prenatal Diagnosis, edited by A. Baue (Paris: Institut

National de la Sante et de la Recherche Medicale, 1976).

Miller, M., “The Cost-Effectiveness of Medical

Device Standards, ” Med. Instrum. 10:28, January-February 1976.

Moore, G., et al., “Comparison of Television

and Telephone for Remote Medical Consultation,” N. Eng. J. Med. 92:729, 1975.

Moore, R., and Hoover, A., “NIOSH Interest

in the Cost Effectiveness of Occupational

Health Programs, ” J. Occup. Med. 16:154,

March 1974.

Morrow, J., et al., “U.S. Health Manpower

Policy: Will the Benefits Justify the Costs?” J.

Med. Educ. 51:791, October 1976.

Moskowitz, M., and Fox, S., “Cost Analysis of

Aggressive Breast Cancer Screening, ” Radio.

130:253, January 1979.

, et al., “Breast Cancer Screening: Benefit and Risk for the First Annual Screening, ”

Radio. 120:431, August 1976.

Moulding, T., “Chemoprophylaxis of Tuberculosis: When Is the Benefit Worth the Risk and

Cost?” Ann. Intern. Med. 74:761, May 1971.

Muller, C., et al., “Cost Factors in Urban Telemedicine, ” Med. Care 15:251, March 1977.

Murphy, J., et al., “A Cost-Benefit Analysis

of Community Versus Institutional Living, ”

Hosp. Comm. Psych, 27:165, March 1976,
380.

381.

382.

383.

384,

385.

386.

387.

388.

389.

390.

391.

392.

393.

394.

Mushkin, S., “Evaluation of Health Policies

and Actions, ” Soc. Sci. Med. 11:491, May

1977.

“Health as an Investment, ” J. Pol.

Econ. 70:129, October 1962.

“Knowledge and Choices in Health:

Cost-Benefit Analysis in Health Policy Assessments” (Washington, D. C.: Georgetown University, Public Services Laboratory, 1977).

and Cotton, J., “The Cost of Mental

Health ‘Care Under Changing Treatment Methods: One Criterion Out of Many, ” Int. J.

Psych. 4:162, August 1967.

, and Weisbrod, B., “Investment in

Health—Lifetime Health Expenditures on the

1960 Work Force, ” KYKLOS 16:583, 1963.

, et al., “Returns to Biomedical Research, 1900-1975: An Initial Assessment of Impacts on Health Expenditures” (Washington,

D.C.: Georgetown University, Public Services

Laboratory, December 1977).

Mustard, R., “Major Cardiac Surgery: Are the

Benefits Worth the Cost?” editorial, Ann .

Thorac. Surg. 24:400, November 1977.

Nason, F., and Delbanco, T., “Soft Services—

A Major Cost-Effective Component of Primary

Medical Care,” Soc. Work in Health Care

1:297, spring 1976.

National Institute of Mental Health, “Development and Test of a Cost-Effectiveness Methodology for Community Mental HeaIth Centers”

(Rockville, Md.: NIMH, August 1975).

Neenan, W., “Distribution and Efficiency in

Benefit-Cost Analysis, ” Can. J. Econ. 4:216,

May 1971.

Nelson, W., et al., “Cost-Benefit Analysis of

Fluoridation in Houston, Texas,” J. Public

Health Dent. 36:88, spring 1976.

, “An Economic Evaluation of a Genetic

Screening Program for Tay-Sachs Disease, ”

Am. J.. Hum. Genet. 30:160, March 1978.

Neuhauser, D., “Cost-Effective Clinical Decision-Making, ” Pediatrics 60:756, November

1977.

, “Cost-Effective Clinical Decision-Making: Implications for the Delivery of Health

Services, ” in Costs, Risks, and Benefits of

Surgery, edited by J. P. Bunker, et al. (New

York, N. Y.: Oxford University Press, 1977).

“Elective Inguinal Herniorrhaphy Versus Truss in the Elderly, ” in Costs, Risks, and

Benefits of Surgery, edited by J. P. Bunker, et

al. (New York, N. Y.: Oxford University Press,

1977).

395.

396.

397.

398.

399.

400.

401.

402.

403.

404.

405.

406.

407.

408.

and Halperin, W., “Cost-Effective

Clinical Decision-Making, Parts I and II, ” Ford

Foundation Series on the Delivery of Urban

Health Services (Boston, Mass.: Harvard University, 1973). Available through Abstracts of

Hospital Management Studies (#23030 MD).

, and Lewicki, A., “National Health Insurance and the Sixth Stool Guaiac, ” Pol.

Anal., 1976.

, and Lewicki, A., “What Do We Gain

From the Sixth Stool Guaiac?” N. Eng. J. Med.

293:226, July 31, 1975.

Neutra, R., “Indications for the Surgical Treatment of Suspected Acute Appendicitis: A CostEffectiveness Approach, ” in Costs, Risks, and

Benefits of Surgery, edited by J. P. Bunker, et

al. (New York, N. Y.: Oxford University Press,

1977).

Newhouse, J., “Allocation of Public Sector Resources in Medical Care: An Economist Looks

at Health Planning, ” Econ. Bus. Bull. 23:8,

winter 1971.

Norcross, K., “Society and the Doctor, ” editorial, Am. Heart J. 94:261, August 1977.

Nordgerg, O., et al. (eds. ), Action for Children

(Uppsala, Sweden: Dag Harnmarskjold Foundation).

Norling, R., “Cost and Effectiveness Models

for Hospitals Programs” (Ann Arbor, Mich.:

University Microfilms International, March

1975).

Nyiendo, J., et al., “Cost-Effective Clinical Microbiology, ” Am. J. Med. Technol. 45:393,

May 1979.

“On Cost-Benefit and Cost-Effectiveness Analysis, ” editorial, NIHAE Bull. 9:166, 1976.

Office of Technology Assessment, U.S. Congress, Assessing the Efficacy and Safety o f

Medical Technologies, GPO stock No. 052-

003-00593-O (Washington, D. C.: U.S. Government Printing Office, September 1978).

U.S. Congress, A Review of Selected

Federal Vaccine and Immunization Policies,

GPO stock No. 052-003 -00701-1 (Washington,

D. C.: U.S. Government Printing Office, September 1979).

U.S. Congress, Development of Medical Technologies: Opportunity for Assessment,

GPO stock No. 052-003 -00217-5 (Washington,

D. C.: U.S. Government Printing Office, August 1976) .

U.S. Congress, Policy Implications of

the Computed Tomography (CT) Scanner,

GPO stock No. 052-003 -00565-4 (Washington,
409.

410.

411.

412.

413.

414.

415.

416.

417.

418.

419.

420.

421.

422.

423.

D.C.: U.S. Government Printing Office, August 1978).

U.S. Congress, Policy Implications of

Medical Information Systems, GPO stock No.

052-003-00496-8 (Washington, D.C.: U.S.

Government Printing Office, November 1977).

Olavi, E., “Health and Economic Consequences of Rubella,” Acta Universitatis Tamperensis, Series A.

Osteria, T., “AC Cost-Effectiveness Analysis of

Family Planning Programs in the Philippines,”

Stud. Fam. Plann. .4:191, July 1973.

Packer, A., ’’Applying Cost-Effectiveness Concepts to the Community Health System, ” Oper.

Res. 16:227, March-April 1968.

Pantell, R., “Cost-Effectiveness of Pharyngitis

Management and Prevention of Rheumatic Fever, ” editorial, Ann. Intern. Med. 86:497,

April 1977.

Panzetta, A., “Cost-Benefit Studies in Psychiatry, ” Compr. Psychiatry 14, September-October 1973.

Parker, B., “Quantitative Decision Techniques

for the Health/Public Sector Policy-Maker: An

Analysis and Classification of Resources, ” J.

Health Polit. Policy Law 3:388, spring 1978,

Patiala, H., et al., “Cost-Benefit Analysis of

Synovectomy of the Knee, ” Scand. J. Rheumatol. 5:227, 1976.

Pauker, S., “Coronary Artery Surgery: The

Use of Decision Analysis, ” Ann. Intern. Med.

85:8, 1976.

and Kassirer, J., “Therapeutic Decision-Making: A Cost-Benefit Analysis, ” N.

Eng. J. Med. 293:229, July 31, 1975,

Penner, D., “Cost Effectiveness of the Autopsy

in Maintaining and Improving the Standard of

Patient Care, ” Am. J. Clin. Pathol. 69:250,

February 1978.

Pettingiee, B., “Cost Effectiveness of Hospital

Treatment,” Dimens. Health Serv. 55:19, February 1978.

Phelps, C., “Benefit/Cost Assessment for

Quality Assurance Program,” RAND Corp.

Report R-1954-HEW (Santa Monica, Calif.:

RAND Corp., 1976).

Phillips, C., and Wolfe, J., Clinical Practice

and Economics (London: Pitman Medical,

1977).

Phillips, R., and Hughes, J., “Cost-Benefit

Analysis of the Occupational Health Program:

A Generic Model, ” J. Occup. Med. 16:158,

March 1974.

424.

425,

426.

427.

428,

429.

430.

431.

432,

433.

434,

435.

436,

437.

438.

439.

Piachaud, D., and Weddell, J., “The Economics of Treating Varicose Veins, ” lnt. J. Epi.

1:287, 1972.

Pliskin, J., “The Management of Patients With

End-Stage Renal Failure: A Decision Theoretic

Approach, ” dissertation, Harvard University,

Cambridge, Mass., 1974.

and Beck, C., Jr., “A Health Index for

Patient’ Selection: A Value Function Approach

With Applications to Chronic Renal Failure Patients, ” Manage, Sci. 22:1009, 1976.

Pliskin, N., and Taylor, A., “General Principles: Cost-Benefit and Decision Analysis, ” in

Costs, Risks, and Benefits of Surgery, edited by

J. P. Bunker, et al. (New York, N. Y.: Oxford

University Press, 1977).

Pole, J., “The Cost-Effectiveness of Screening, ”

Proc. R. Soc. Med. 64:1256, December 1971.

“Economic Aspects of Screening for

Disease, “ in Screening in Medical Care, edited

by T. McKeown (London: OUP, 1968).

f “The Economics of Mass Radiography,” in The Economics of Medical Care,

edited by M. Hauser (London: George Allen

and Univin, 1972).

“Mass Radiography: A Cost-Benefit

Approach, “ in Problems and Progress in Medical Care: Essays in Current Research, edited

by G. McLachlan (New York, N. Y.: Oxford

University Press, 1971).

Pomrinse, S., et al., “Cost-Benefit Analysis of

Computer,” Hospitals 46:76, March 1972.

Potchen, E., et al., “Value Measurement of Nuclear Medicine Procedures, ” in Financial Operation and Management Concepts in Nuclear

Medicine, edited by J. Bennington, et al. (Baltimore, Md.: University Park, 1977).

Preston, T., Coronary Artery Surgery: A Critical Review (New York, N. Y,: Raven Press,

1977).

Quilligan, E., and Paul, R., “Fetal Monitoring:

Is It Worth It?” Obstet. Gyn. 45:96, 1975.

Rabello, Y., and Paul, R., “Fetal Monitoring:

What Does It Cost? What Is the Benefit?”

JOGN Nurs. 5:715, September-October 1976.

Radtke, H., “Benefits and Costs of a Physician

to a Community, ” Amer. J. Agr. Econ. 56:586,

August 1974.

Ramaiah, T., “Cost-Effectiveness Analysis of

the Intensified Campaign Against Smallpox in

India,” NIHAE Bull. 9:169, 1976.

Raskin, M., “Quality Assurance and Cost Effectiveness for Prepaid Care, ” N. Y. State Dent,

J. 41:464, October 1975.
440.

441,

442.

443.

444.

445.

446.

447.

448.

449,

450.

451.

452.

Rathbone-McCuan, E., et al., Cost-Effectiveness Evaluation of the Levindale Adult Day

Treatment Center (Baltimore, Md.: Levindale

Geriatric Research Center, 1975).

Rees, P., et al., “Medical Care in a Tropical

National Reference and Teaching Hospital:

Outline Study of Cost-Effectiveness, ” Br. Med.

J. 2:102, Ju]y 8, 1978.

Reid, M., and Morris, J., “Perinatal Care and

Cost Effectiveness: Changes in Health Expenditures and Birth Outcome Following the Establishment of a Nurse-Midwife Program, ” Med.

Care 17:491, May 1979.

Reiff, T., “It Can Happen Here, ” ]. A.M.A.

239:2761, June 30, 1978.

Retka, R., “Cost Accountability in Drug Abuse

Prevention” (RockviIle, Md.: National Institute

on Drug Abuse, Office of Program Development and Analysis, 1977),

Rettig, R., “End-Stage Renal Disease and the

‘Cost’ of Medical Technology, ” in Medical

Technology: The Culprit Behind Health Care

Costs? edited by S. H. Altman and R. Blandon,

proceedings of the 1977 Sun Valley Forum on

National Health, DHEW publication No.

(PHS) 79-3216 (Washington, D. C.: U.S. Government Printing Office, 1979).

“The Policy Debate on Patient Care Financing for Victims of End-Stage Renal Disease, ” Law Conternp. Prob. 40:196, autumn

1976.

“Formal Analysis, Policy Formulation,

and End-Stage Renal Disease, ” in The Implications of Cost-Effectiveness Analysis of Medical

Technology/Background Paper #2: Case Studies of Medical Technologies, prepared by

OTA, U.S. Congress (Washington, D. C.: in

press, 1980).

Reynell, P., and ReynelI, M., “The Cost-Benefit of a Coronary Care Unit, ” Br. Heart Jr.

34:897, September 1972.

Rich, G., et al., “Cost-Effectiveness of Two

Methods of Screening for Asymptomatic Bacteriuria, ” Br. J. Prev. Soc. Med. 30:54, March

1976.

Rios, J., et al., “The Quest for Optimal Electrocardiography: Task Force V—Cost Effectiveness of the Electrocardiogram, ” Am. J. Cardiol.

41:175, January 1978.

Roberts, J., “Economic Evaluation of Health

Care: A Survey, ” Br. J. Prev. Soc. Med. 28:

210, 1974.

Robinson, D., “Cost and Effectiveness of a Program To Prevent Rheumatic Fever, ” HSMHA

Health Rep. 86:385, April 1971.

453.

454.

455.

456,

457.

458,

459,

460.

461.

462.

463.

464.

465,

Romm, J., et al., “Survey and Evaluation of the

Physician Extender Reimbursement Study:

Cost Effectiveness, ” paper presented at the Annual Meeting of the American Public Health

Association, Los Angeles, Calif., Oct. 18,

1978.

Rosenthal, G., “Anticipating the Costs and

Benefits of New Technology: A Typology for

Policy, ” in Medical Technology: The Culprit

Behind Health Care Costs? edited by S. H. Altman and R. Blandon, proceedings of the 1977

Sun Valley Forum on National Health, DHEW

publication No. (PHS) 79-3216 (Washington,

D. C.: U.S. Government Printing Office, 1979).

Rowe D., and Bisbee, J., “Preventive Health

Care in the HMO: Cost-Benefit Issues, ” J. Am.

Coil. Health Assoc. 26(6):298, June 1978.

Ruchlin, H., and Levey, S., “Nursing Home

Cost Analysis: A Case Study, ” Inquiry 9:3,

September 1972.

Russell, R., et al., “Unstable Angina Pectoris:

National Cooperative Study Group to Compare Medical and Surgical Therapy, ” Am. J.

Cardiol. 37:896, 1976.

Sagan, L., “Prevention and Cure: Some

Thoughts on Cost Effectiveness, ” Science,

April 1973.

Salvatierra, O., et al., “Analysis of Cost and

Outcomes of Renal Transplantation at One

Center: Its Implications, ” ]. A.M.A. 241:1469,

April 1979.

Saslaw, M., et al., “Cost of Rheumatic Fever

and Its Prevention, ” Am. J. Public Health

55:429, 1965.

Saunders, J., “Results and Costs of a Computer-Assisted Immunization Scheme, ” Br. J. Prev.

Soc. Med. 24:187, August 1970.

Savas, B., “Simulation and Cost-Effectiveness

Analyis of New York’s Emergency Ambulance

Service,” Mgt. Sci. 15: B608, 1969.

Saxe, L., The Implications of Cost-Effectiveness Analysis of Medical Technology/Background Paper #3: The Efficacy and Cost-Effectiveness of Psychotherapy, prepared by OTA,

U.S. Congress (Washington, D. C.: in press,

1980).

Scanlon, J., “Proceedings: Cost Savings/Benefit Analysis of Drug Abuse Treatment, ” Am.

J. Drug Alcohol Abuse 3:95, 1976.

Schachter, K., and Neuhauser, D., “Surgery

for Breast Cancer, ” in The Implications o f

Cost-Effectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of

Medical Technologies, prepared by OTA, U.S.

Congress (Washington, D. C.: in press, 1980).
96 ● Background Paper #l. Methodological Issues and Literature Review)

466.

467.

468.

469.

470.

471.

472.

473.

474.

475.

476.

477.

478.

479.

Schaefer, M., “Demand Versus Need for Medical Services in a General Cost-Benefit Setting, ”

Am. J. Public Health 65:293, May 1975,

Scheffler, R., “A Methodological Framework

for Cost-Benefit Analysis in Health,” Evaluation in Health Services Delivery, proceedings

of an Engineering Foundation Conference,

South Berwick, Maine, Aug. 19-24, 1973.

and Delaney, M., “Assessing Selected

Respiratory Therapy Modalities: Trends and

Relative Costs in the Washington, D.C. Area, ”

in The Implications of Cost-Effectiveness Analysis of Medical Technology/Background Paper

#2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington,

D. C.: in press, 1980).

, and Rovin, S., “Periodontal Disease:

Assessing the Effectiveness and Costs of the

Keyes Technique, “ in The Implications of CostEffectiveness Analysis of Medical Technology/

Background Paper #2: Case Studies of Medical

Technologies, prepared by OTA, U.S. Congress (Washington, D, C.: in press, 1980).

Schelling, T., “The Life You Save May Be Your

Own,” in Problems in Public Expenditure

Analyses, edited by S. Chase, Jr. (Washington,

D. C.: Brookings Institution, 1968).

Schippers, H., and Kalff, M., “Cost Comparison Hemodialysis and Renal Transplantation, ”

Tissue Antigens 7:86, 1976.

Schoenbaum, S., et al., “Benefit-Cost Analysis

of Rubella Vaccination Policy, ” N. Eng. J.

Med. 294:306, Feb. 5, 1976.

, et al., “The Swine-Influenza Decision, ”

N. Eng. J. Med. 295:759, Sept. 30, 1976.

Schramm, C., “Measuring the Return on Program Costs: Evaluation of a Multi-Employer

Alcoholism Treatment Program, ” Am, J, Public Health 67:50, January 1977.

Schultz, G., “The Logic of Health Care Facility

Planning, “ Socio-Econ. Plan. Sci. 4:383, 1970.

Schultz, P., and McGlone, F., “Primary Health

Care Provided to the Elderly by a Nurse Practitioner/Physician Team: Analysis of Cost-Effectiveness,” J. Am. Geriatr. Soc. 25:443, October

1977.

Schwartz, W., and Joskow, P., “Medical Efficacy Versus Economic Efficiency: A Conflict in

Values,” N. Eng. J. Med. 299:1462, Dec. 28,

1978.

Schweitzer, S., “Cost Effectiveness of Early Detection of Disease, ” Health Serv. Res. 9:22,

spring 1974.

and Luce, B., A Cost-Effective Approach to Cervical Cancer Detection, DHEW

480,

481.

482.

483.

484.

485.

486.

487.

488.

489.

490.

491.

492.

publication No. 79-32371 (Hyattsville, Md.:

National Center for Health Services Research,

January 1979).

, and Scalzi, C., “The Cost-Effectiveness

of Bone Marrow Transplant Therapy and Its

Policy Implications, ” in The Implications of

Cost-Effectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of

Medical Technologies, prepared by OTA, U.S.

Congress (Washington, D. C.: in press, 1980).

, et al., “Social Cost Versus Effectiveness of Bone Marrow Transplant Therapy, ”

UCLA Can, Cent. Bull. 6:3, January-February

1979.

Scriver, C., “PKU and Beyond: When Do

Costs Exceed Benefits?” Pediatrics 54:616, November 1974.

Seidman, H., “Screening for Breast Cancer in

Younger Women: Life Expectancy Gains and

Losses: An Analysis According to Risk Indication Groups, ” CA-A Cancer J. for Clinicians

72:69, March-April 1977.

Sencer, D., and Axnick, N., “Utilization of

Cost/Benefit Analysis in Planning Prevention

Programs,” Acta. Med. Scand. 576:123, 1975.

Shapiro, S., “Measuring the Effectiveness of

Prevention II, ” Milbank Mere., spring 1977.

Sharfstein, S., et al., “Community Care: Costs

and Benefits for a Chronic Patient, ” Hosp.

Comm. Psych. 27:170, March 1976.

Sheehan, D., and Atkinson, J., “Comparative

Costs of State Hospital and Community-Based

Inpatient Care in Texas: Who Benefits Most?”

Hosp. Comm. Psych. 25:242, April 1974.

Shepard, D., “Cost Benefit Analysis in Health:

A Selected Annotated Bibliography” (Boston,

Mass.: Massachusetts Department of Public

Health, Office of State Health Planning, January 1978).

, “The Economics of Prevention: The

Method of Cost-Effectiveness Analysis” (Boston, Mass.: Massachusetts Department of Public Health, Office of State Health Planning, July

1977).

“First Principles of Cost-Effectiveness

Analysis, ” Pub. Health Rep., forthcoming.

, et al., “Cost-Effectiveness of Interventions to Improve Compliance With Anti-Hypertensive Therapy, ” paper presented at the

National Conference on High Blood Pressure

Control, Washington, D. C., Apr. 4-6 (abstract

published in Prev. Med., March 1979).

Showstack, J., and Schroeder, S., “The Costs

and Effectiveness of Upper Gastrointestinal Endoscopy,” in The Implications of Cost-E ffec-
Appendix B–Bibliography on CEA/CBA ● 97

493.

494.

495.

496.

497.

498.

499.

500.

501.

502.

503.

504.

505.

506.

507.

508.

tiveness Analysis of Medical Technology/

Background Paper #2: Case Studies of Medical

Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

Siebert, C., and Azidi, M., “Benefit Cost Analysis in Health Care, ” Biosciences Communications 1:193, 1975.

Silverr E., “The Torrance et al. Cost-Effectiveness-Ranking Algorithm, ” Health Serv. Res.

7:322, winter 1972.

Simmons, H., ‘The Routine Physical Exam: Is

It Worth the Cost?” J. Term. Med. Assoc.

69:183, March 1976.

Sirotnik, K., et al., “A Cost-Benefit Analysis

for a Multimodality Heroin Treatment Project, ” Int. . Addict. 10:443, 1975.

Siu, T., “Cost Effectiveness of Early Detection, ” Health Serv. Res. 11:302, fall 1976.

Skillings, J., et al., “Cost-Effectiveness of Operative Cholangiography, ” Am. J. Surg. 127:26,

1979.

Smith, C., “Cost-Benefit Ratio of Exfoliative

Cytology of the Cervix,” letter, Am. J. Obst.

Gyn. 129:476, Oct. 15, 1977.

Smith, H., “Application of Cost-Effectiveness

Analysis to Patient Record Systems,” J. Am.

Pharm. Assoc., January 1973.

Smith, W., “Cost-Effectiveness and Cost-Benefit Analysis for Public Health Programs, ” Public Health Rep. 83:899, November 1968.

Sonenblum, S., et al., Program Budgeting for

Urban Health and Welfare Service With Special

Reference to Los Angeles (New York, N. Y.:

Praeger Publications, 1974).

Spears, M., “Concepts of Cost Effectiveness:

Accountability for Nutrition, Productivity, ” J.

Am. Diet. Assoc. 68:341, April 1976.

Spector, R., et al., “Medical Care by Nurses in

an Internal Medicine Clinic. Analysis of Quality and Its Cost, ” J.A.M.A. 232:1234, June 23,

1975.

Speight, A., “Cost-Effectiveness and Drug

Therapy,” Trop. Doct. 5:89, April 1975.

Spencer, D., and Axnick, N., “Cost Benefit

Analysis, ” International Symposium on Vaccination Against Communicable Diseases, Monaco, Symp. Series Immunobiol. Standard

22:37, 1973.

Spitzer, W., et al., “Nurse Practitioners in Primary Care: Assessment of Their Deployment

With the Utilization and Financial Index, ” Can.

Med. Assoc. J. 114:1103, June 19, 1976.

, et al., “Nurse Practitioners in Primary

Care: Development of the Utilization and Financial Index To Measure Effects of Their De509.

510.

511.

512.

513.

514.

515.

516.

517.

518.

519.

520.

521.

522.

ployment,” Can. Med. Assoc. J. 114:1099, June

19, 1976.

Spratt, J., Jr., “Cancer: Do Early Diagnosis and

Treatment Really Help? How Do We Relate

Costs to Benefit in Cancer Control?” Oral

Surg. 45:220, February 1978.

, “Cost Effectiveness in the Post-Treatment Follow-Up of Cancer Patients, ” J. Surg.

Oncol. 3:393, 1971.

Stahl, J., “Present State of Cost Benefit Analysis in Medical Evaluation, ” (Lund, Sweden: Department of Economics, Lund University,

n.d. ).

Stanford Research Institute, Feasibility and

Cost-Effectiveness of Alternative Long-Term

Care Settings (Menlo Park, Calif.: SRI International, May 1978).

Stange, P., and Sumner, A., “Predicting Treatment Costs and Life Expectancy for End-Stage

Renal Disease, ” N. Eng. J. Med. 298:372, Feb.

16, 1978.

Starr, J., “Better Answer Alternatives to Institutional Care, ” paper presented at the 25th

Annual Meeting of the National Council on

Aging, Washington, D. C., Sept. 30, 1975.

Stason, W. B., and Fortess, E., “Cardiac Radionuclide Imaging and Cost Effectiveness, ” in

The Implications of Cost-Effectiveness Analysis of Medical Technology/Background Paper

#2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington,

D. C.: in press, 1980).

, and Weinstein, M., “Allocation of Resources To Manage Hypertension, ” N. Eng. J.

Med. 296:732, Mar. 31, 1977.

Steiner, K., and Smith, H., “Application of

Cost Benefit Analysis to a PKU Screening Program, ” Inquiry 10:34, December 1973.

Stephen, K., et al., “Caries Reduction and

Cost-Benefit After 3 Years of Sucking Fluoride

Tablets Daily at School: A Double-Blind Trial, ” Br. Dent. J. 144:202, April 1978.

Stewart, C., “Allocation of Resources to

Health,” J. Hum. Res. 6:104, 1971.

Stewart, J., et al., “The Costs of Domiciliary

Maintenance Haemodialysis: A Comparison

With Alternative Renal Replacement Regimens,” Med. J. Aust. 1:156, Jan. 27, 1973.

Stilwell, J., “Benefits and Costs of the Schools’

BCG Vaccination Programmed,” Br. Med. J.,

Apr. 24, 1976.

Stokes, J., and Carmichael, D., “A Cost-Benefit Analysis of Model Hypertension Control, ”

National Heart and Lung Institute (Bethesda,
523.

524.

525.

526.

527.

528.

529.

530.

531.

532.

533.

534.

535.

536.

537.

538.

Md.: National High Blood Pressure Education

Program, 1975).

Strong, C., “Surgically Correctable Causes of

Hypertension, ” editorial, Mayo Clin. P. 52:

585, September 1977.

Sugar, J., “An Ounce of Prevention Is Worth

It: Benefits and Costs of Family Planning, ” presented at the Annual Meeting of the American

Public Health Association, Los Angeles, Calif.,

Oct. 18, 1978.

Sullivan, W., and Thuesen, G., “Cost Sensitivity Analysis for Radiology Department Planning,” Health Serv. Res. 6:337, winter 1971.

Sussna, B., and Heinemann, H., “The Education of Health Manpower in a Two-Year College: An Evaluation Model,” Socio-Economic

Planning Services 6:21, 1972.

Swartz, R., and Desharnius, S., “Computed

Tomography: The Cost-Benefit Dilemma, ” Radio. 125:251, 1977.

Swint, J., and Nelson, W., Cost-Benefit Analysis in Health Planning (Houston, Tex.: University of Texas, 1975).

, et al., “The Application of Economic

Analysis to Evaluation of Alcoholism Rehabilitation Programs, “ Inquiry 14:63, March 1977.

, et al., “The Economic Returns to Community and Hospital Screening Programs for a

Genetic Disease, ” Prev. Med. 8(4):463, July

1979.

, et al., “The Economic Returns to

Employment-Based Alcoholism Programs: A

Methodology,” J. Stud. Alcohol. 39:1633, September 1978.

, et al., “Prospective Evaluation of Alcoholism Rehabilitation Efforts: The Role of

Cost-Benefit and Cost-Effectiveness Analyses, ”

J. Stud. Alcohol. 38:1386, July 1977.

Taylor, D., Benefits and Risks in Medical Care

(London: Office of Health Economics, 1974),

, “The Costs of Arthritis and the Benefits of Joint Replacement Surgery, ” Proc. R.

Soc. Lend. 192:145, Jan. 20, 1976.

Taylor, F., “Cost and Benefits of Rare Earth

Screens,” letter, Br. J. Radio. 50:294, April

1977.

Taylor, V., “How Much Is Good Health

Worth?” Pol. Sci., spring 1970.

Teeling-Smith, G., “A Cost-Benefit Approach

to Medical Care, ” in The Economics of Medical

Care, edited by M. M. Hauser, et al., London,

1972.

“Cost-Benefit Paralysis, ” Nurs. Times

72:88, Jan. 22, 1976.

539.

540.

541.

542.

543.

544.

545.

546.

547.

548.

549.

550.

551.

r “The Economics of Screening, ” Screening in General Practice, edited by C. Hart

(Edinburgh, Scotland: Churchill Livingstone,

1975).

Terrill, J., Jr., “Cost-Benefit Estimates for the

Major Sources of Radiation Exposure, ” Am, J.

Public Health 62:1008, July 1972.

Thomson, J., “Cost-Effectiveness of an EMI

Brain Scanner. A Review of a 2-Year Experience, ” Health Trends 9:16, 1977.

“Epidemiology and Health Services

Administration: Future Relationships in Practice and Education, ” Milbank Mere. 56:253,

summer 1978.

Thomson, K., et al., “Scope of Interventional

Radiology 1977, ” Applied Radio. 7:73, January-February 1978.

Thorbury, J., et al., “Cost-Benefit Analysis,

Medical Decision Making and the Individual

Radiologist, ” Curr. Probl. Diagn. Radio. 7:1,

March-April 1977.

Thrall, R., “Benefit/Cost Estimation, Alternatives, Requirements, Advantages and Disadvantages, ” in Workshops From the Centennial

Conference on Laryngeal Cancer, edited by P.

Alberti and D. Bryce (New York, N. Y.: Appleton-Century-Crofts, 1976).

, and Cardus, D., “Benefit-Cost and

Cost-Effectiveness Analysis in Rehabilitation

Research Programs, ” Methods Inf. Med. 13:

147, July 1974.

Tompkins, R., et al., “An Analysis of the Cost

Effectiveness of Pharyngitis Management and

Acute Rheumatic Fever Prevention, ” Ann, Intern, Med. 86:481, 1977.

, et al., “The Effectiveness and Costs of

Acute Respiratory Illness Medical Care by

Physicians and Algorithm-Assisted Physicians’

Assistants, ” Med. Care 15:991, Decembe r

1977.

Torrance, G., “Generalized Cost-Effectiveness

Model for the Evaluation of Health Programs, ”

dissertation, McMaster University, Hamilton,

Ontario, February 1971.

, et al., “Utility Maximization Model for

Program Evaluation: A Demonstration Application, ” in Health Status Indexes: Proceedings

of a Conference, edited by R. Berg (Tucson,

Ariz.: Hospital Research and Educational

Trust, 1973).

Tunbridge, R., and Wetherill, J., “Reliability

and Cost of Diabetic Diets, ” Br. Med. J. 2:78,

Apr. 11, 1970.
552.

553.

554,

555.

556.

557.

558.

559.

560.

561.

562.

563.

564.

Utian, W., “Application of Cost-Effectiveness

Analysis to Post-Menopausal Estrogen Therapy, ” Front Horm. Res, 5:26, 1977.

VanPelt, A., and Levy, H., “Cost-Benefit Analysis of Newborn Screening for Metabolic Disorders, ” N. Eng. J. Med. 291:1,414, Dec. 26,

1974.

Vehorn, C., et al., “Biomedical Research and

Its Impact on Personal Health Care Expenditures, 1930-1975" (Washington, D. C.: Georgetown University, Public Services Laboratory,

December 1977).

Waaler, H., “Cost-Benefit Analysis of BCGVaccination Under Various Epidemiological

Situations, ” Bull, Int. Union Tuberc. 41:42,

December 1968.

, and Piot, M., “Use of an Epidemiological Model for Estimating the Effectiveness of

Tuberculosis Control Measures, ” Bull. W.H.0.

43:1, 1970.

Wagner, D., et al., “Gains in Mortality From

Biomedical Research, 1930-1975: A Macro

View” (Washington, D. C.: Georgetown University, Public Services Laboratory, December

1977).

Wagner, J., The Implications of Cost-Effectiveness Analysis of Medical Technology/Background Paper #s: Assessment of Four Common

X-Ray Procedures, prepared by OTA, U.S.

Congress (Washington, D. C.: in press, 1980).

“The Feasibility of Economic Evaluation of ‘Diagnostic Procedures: The Case of CT

Scanning, ” in The implications of Cost-Effectiveness Analysis of Medical Technology/

Background Paper #2; Case Studies of Medical

Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

Walker, G., “Primary Health Care in Botswana: A Study in Cost-Effectiveness, ” Proc. R.

Soc. Med. 69:936, December 1976.

, and Gish, O., “Mobile Health Services: A Study in Cost-Effectiveness, ” Med.

Care 15:267, April 1977.

Walworth, C., et al., “Industrial Hypertension

Program in a Rural State. Efficacy and Cost Effestiveness, ” J, A.M.A. 237:1942, May 2, 1977.

Warden, W., “Assessment of the Benefits,

Risks, and Costs of Medical Programs, ” in Benefits and Risks in Medical Care, edited by D.

Taylor (London: White Crescent Press, Ltd.,

1974).

Warner, K., “The Economic Implications of

Preventive Health Care, ” Soc. Sci. Med.

13 C:227, December 1979.

565.

566.

567.

568.

569.

570,

571.

572.

573.

574.

575.

576.

577.

“Epilogue,” in Medical Technology,

proceedings of the Urban Institute Conference,

National Center for Health Services Research,

West Palm Beach, Fla., Dec. 10-12, 1978.

Watts, C., et al., “Cost Effectiveness Analysis:

Some Problems of Implementation, ” Med.

Care 17:430, April 1979.

Watts, M., “The Dollars for Health, ” West. J.

Med. 125:219, September 1976.

Weiler, P., “Cost-Effective Analysis: A Quandary for Geriatric Health Care Systems, ” Gerontologist 14:414, October 1974.

Weinstein, M., “Economic Evaluation of Medical Procedures and Technologies: Progress,

Problems, and Prospects, ” in Medical Technology, proceedings of the Urban Institute Conference, National Center for Health Services Research, West Palm Beach, Fla., Dec. 10-12,

1978.

and Fineberg, H., “Cost-Effectiveness

Analysis for Medical Practices: Appropriate

Laboratory Utilization, ” in Logic and Economics of Clinical Laboratory Use, edited by E.

Benson and M. Rubin (North-Holland: Elsevier/North Holland Biomedical Press, 1978).

, and Pearlman, L., “Case Study on

Cost-Effectiveness of Automated Multichannel

Chemistry Analyzers, ” in The Implications of

Cost-Effectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of

Medical Technologies, prepared by OTA, U.S.

Congress (Washington, D. C.: in press, 1980).

, and Stason, W., “Allocating Resources: The Case of Hypertension, ” Z-last.

Cent. Rpt. 7(5):24, October 1977.

, and Stason, W., “Economic Considerations in the Management of Mild Hypertension, ” Ann. N. Y. Acad. Sci. 304:424, Mar. 30,

1976.

, and Stason, W., “Foundations of CostEffectiveness Analysis for Health and Medical

Practices,” N. Eng. J. Med. 296:716, Mar. 31,

1977.

and Stason, W., Hypertension: A Policy Perspective (Cambridge, Mass.: Harvard

University Press, 1976).

, et al., “Coronary Artery Bypass Surgery: Decision and Policy Analysis, ” in Costs,

Risks, and Benefits of Surgery, edited by J. P.

Bunker, et al. (New York, N. Y.: Oxford University Press, 1977).

Weisbrod, B., “Costs and Benefits of Medical

Research: A Case Study of Poliomyelitis, ” J.

Polit. Econ. 79:527, May-June 1971,
578.

579.

580.

581.

582.

583.

584.

585.

586.

587.

588.

589.

The Economics of Public Health:

Measuring the Economic Impact of Disease

(Philadelphia, Pa.: University of Pennsylvania

Press, 1961).

“Research in Economics: A Survey, ”

Int. J. Health Serv. 5(4):643, 1975.

, et al., “An Alternative to Mental Hospital Treatment: III. Economic Benefit-Cost

Analysis, ” unpublished paper, Madison, Wis.,

December 1978.

Weiss, W., “Routine Sigmoidoscopy Costs and

Usefulness, ” J. A.M.A. 216:886, May 3, 1971.

Welch, L., “Draft Report on PSRO Effectiveness Stirs Commentary, ” Hospitals 52:44, Jan.

16, 1978.

Welssert, W., et al., Effects and Costs of Day

Care and Homemaker Services for the Chronically 111: A Randomized Experiment, NCHSR

Research Report Series, DHEW publication

No. (PHS) 79-3258 (Washington, D. C.: U.S.

Government Printing Office, 1980).

Werner, M., et al., “Strategy for Cost-Effective

Laboratory Testing, ” Hum. Pathol. 4:17,

March 1973.

White, K., “Planning and Execution, Costs and

Benefits of Cross-National Sociomedical Research, ” in Cross-National Sociomedical Research, edited by M. Pflanz and E. Schach

(Stuttgart, West Germany: Thiemi, 1976).

Willems, J., “Cost-Effectiveness Analysis of

Medical Technologies as an Aid to Policymaking, ” prepared for the Health Care Technology

Evaluation Symposium, Columbia, Me., Nov.

6, 1978.

Williams, A., “The Cost-Benefit Approach, ”

Br. Med. Bull. 30:252, September 1974.

, and Corn, B., “Description Versus Valuation in Long-Term Care Data, ” Med. Care

14:148, May 1976.

Wingert, W., et al., “Effectiveness and Efficiency of Indigenous Health Aides in a Pediatric

Outpatient Department, ” Am. J. Public Health

65:849, August 1975.

590.

591.

592.

593.

594.

595.

596,

597.

598.

599.

600.

601.

Wiseman, J., “Cost-Benefit Analysis and

Health Service Policy, ” Scott, J. Pol. Econ.

10:128, February 1963.

Witte, J., et al., “The Benefits From 10 Years of

Measles Immunization in the United States, ”

Public Health Rep, 90:205, May-June 1975,

Wolfe, H., “Pharmacy: HOW Cost-Effective

Are Generics?” Hospitals 47:100, May 1, 1973.

Wortzman, G., and Holgate, R., “Reappraisal

of the Cost Effectiveness of Computed Tomography in a Government-Sponsored Health Care

System, ” Radio, 130:257, January 1979.

, et al., “Cranial Computed Tomography: An Evaluation of Cost Effectiveness, ”

Radio, 117:75, 1975.

Yates, B., “Cost-Effectiveness Analysis: Using

It For Our Own Good,” SPAA Newsletter

(American psychological Association), 8(4),

May 1977.

“How To Improve, Rather Than Evaluate, Cost-Effectiveness, ” Counseling Psychologist 8(1):72, 1979.

“Improving the Cost-Effectiveness of

Obesity Programs: Three Basic Strategies for

Reducing the Cost Per Pound, ” Int. J. Obes.

2:249, 1978.

“The Theory and Practice of Cost-Utility, Cost-Effectiveness, and Cost-Benefit Analysis in Behavioral Medicine: Toward Delivering More Care for Less Money, ” in A Comprehensive Handbook of Behavioral Medicine,

edited by J. Ferguson and B. Taylor (Englewood Cliffs, N. J.: Spectrum Publications, Inc.,

1979).

Yorio, D., et al., “Cost Comparison of Decentralized Unit Dose and Traditional Pharmacy

Services in a 600-Bed Community Hospital,”

Am. J. Hosp. Pharm. 29:922, November 1972.

Zapka, J., and Averill, B., “Self Care for

Colds: A Cost-Effective Alternative Upper Respiratory Infection Management, ” Am. J. Pub.

Health 69:814, August 1979.

Zeckhauser, R., and Shepard, D., “Where Now

for Saving Lives?” Law & Contemp. Prob.

40(4):5, 1976.
Appendix C.—Abstracts of Selected Entries

From the Bibliography on CEA/CBA

Baker, C., and Way, L., “Clinical Utility of CAT

Body Scans, “ Am. J. Surg. 136:37, July 1978.

This CEA of computed axial tomography (CAT) body

scans employs an efficacy scale which ranges from 1 point

(given when the scan is deemed to have saved a patient’s

life) to 18 points (given when the scan is held to have led to

a patient’s death). In the course of the analysis, the sensitivity, specificity, and accuracy of CAT body scans are

evaluated. The authors note that less expensive tests, most

notably ultrasound, are bypassed or performed simultaneously with CAT scans. Analysis indicated that ultrasound

and CAT scans are of about equal clinical value in any

given situation, but ultrasound costs one-fourth as much as

CAT scanning. The authors observe that clinicians, when

employing CAT scanning, often seem to have no clear expectations that it can affect patient management. They also

note that for most conditions about which CAT body

scans are informative, insufficient information is not the

major factor limiting the success of therapy. Though this

study, limited to hospitalized patients, would have missed

any decreased admissions for diagnostic tests which may

have resulted from the use of CAT body scanning, its authors believe that few savings can be expected from replacing other diagnostic procedures with CAT scans. They recommend that CAT body scans be ordered only if 1) more

information would truly affect patient management, 2)

more cost-effective diagnostic tests have failed, and 3) the

likelihood of disease is high.

The authors caution that their study was done as CAT

technology was rapidly evolving. This evolution has obvious implications, including the likelihood that current use

patterns (frequency and motivation) differ from what they

will become if and when body scanning becomes standard

practice. As such, the study fails to distinguish between

cost effectiveness today and in a steady-state situation in

the future. In addition, the study does not identify potential cost efficacy (i. e., cost effectiveness under optimal conditions). Despite these drawbacks, this study stands out as

one of the very few which have attempted to identify and

quantify patient management and health outcomes.

Barnes, B., “Cost-Benefit Analysis of Surgery: Current Accomplishments and Limitations, ” Am. J.

Surg. 133:438, April 1977.

The general principles of CBA are presented, with a

“good” program described as one in which the net discounted benefits exceed zero. The author says that CBA

was first applied to health care in response to rapidly rising

medical care expenditures. When conflict between individual and societal interests is discerned, the techniques of

CBA must be applied with sensitivity to the individual and

public interests involved. Limitations of CBA in health

care include difficulties in accurately accounting for the numerous complex costs and benefits encountered, in identifying and valuing long-range effects, and in determining a

discount rate when costs and benefits are deferred many

years.

CBA is described as applicable only where effects are

nearly equivalent, so that the analysis becomes, in effect, a

cost comparison. (However, one can also look at different

effects resulting from equivalent costs. ) Three examples of

CBA as applied in health care are presented: 1) consideration of cholecystectomy for silent gallstones, 2) renal transplantation or chronic hemodialysis for end-stage renal dialysis, and 3) intensive care unit support for different illnesses.

The author states that the accomplishments of CBA and

related techniques in health are largely those of more comprehensive understanding of the advantages or disadvantages of a particular therapy or policy. In itself, CBA is seldom definitive, but in conjunction with political and professional judgments, it can improve decisionmaking.

Bartlett, J., et al., “Evaluating Cost Effectiveness of

Diagnostic Equipment: The Brain Scanner Case, ” Br.

Med. J. 2:815, Sept. 16, 1978.

The bulk of this article is devoted to a comparison of the

costs involved in five different options for implementing

CAT scanning in a region of England. The net costs of

CAT scanning are calculated as gross costs (e.g., purchasing, installation, staffing, etc. ) minus savings from the decreased use of conventional neuroradiology and reduced

bed days, presumed to result from the introduction of

CAT. The article also includes a discussion of possible

treatment improvements, unquantified and not included in

the cost of calculations, that may result from the use of

CAT. There is little discussion of the cost effectiveness of

CAT scanning v. conventional neuroradiology, though the

analysis of the five CAT implementation options seems

based on the premise that CAT is more cost effective in certain circumstances. The authors acknowledge the lack of

precision and uncertainty involved in the savings calculations, but contend that some savings do result from the introduction of CAT and must be assessed in any analysis.

Bennett, W., “Cost-Benefit Ratio of Pretransplant Bilateral Nephrectomy, ” ].A.M.A. 235:1703, Apr. 19,

1976.

This paper is an example of how titles can be misleading.

Despite the title, there is not a single cost-benefit ratio in

the entire article. The author compares the posttransplant

course of patients who previously had had their kidneys removed to that of patients who had had no pretransplant

surgery. The latter group experienced fewer rejections and

better survival.

NOTE: Three types of entries are abstracted I) many of the better known studies or methodology articles, 2) several examples of articles of varying technical sophistication (that is, a sample of the general literature) and 3) most of the case studies prepared or supported by OTA as part of the overall assessment

(see app. D) Inclusion here does not imply that any particular study iS one of the "best."

67-774 0- 80 - 8 101
102 • Background Paper #1: Methodological Issues and Literature Review

Bentkover, J. D., and Drew, P. G., “Cost-Effectiveness/Cost-Benefit of Medical Technologies: A Case

Study of Orthopedic Joint Implants, ” in The Implications of Cost-Effectiveness Analysis of Medical

Technology/Background Paper #2; Case Studies of

Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

This study examines the feasibility and potential usefulness of undertaking CEA/CBA of orthopedic joint prostheses. Two specific issues are addressed: 1) whether it is feasible to evaluate carefully and completely the orthopedic

joint implant technology within a CEA/CBA framework;

and 2) how could such an evaluation be useful in formulating public policy.

The authors present a state-of-the-art study of CEA/

CBA as it pertains to this technology. They do not try to

assess the technology. The study includes a description of

the technology (joint implants) based on a review of the

literature, communications with selected medical specialists, and conversations with representatives of the orthopedic prostheses industry. The authors briefly discuss

alternative forms of treatment for arthritis and point out

an important difference between the alternatives (e. g.,

drugs) and joint implants: Most alternatives are only

short-run measures, whereas joint implantation is a longterm measure.

Few data are available regarding the efficacy of joint implants. Data regarding the efficacy of hip replacements are

better than the data for other joint implants or alternative

measures. They may even be acceptable. Efficacy studies

are in progress for some implants. The authors did not explore the possibility of producing the result (successful

joint implantation) in the most efficient manner possible.

Potential benefits were put into two categories: direct

and indirect. Potential direct benefits discussed include relief of pain, improved functional status of joint, measures

included in the “Sickness Impact Profile” (e. g., social interactions, ambulation, sleep, leisure, and emotions), qualityadjusted life years (QALYs), and earnings. Potential indirect benefits include averted expenditures for the caring

for, and treatment of, individuals handicapped with debilitated joints, e.g., those with severe arthritis. These potential benefits were only mentioned; none were quantified or

measured.

Most costs mentioned were not distinguished from

charges, and “avoidable” costs are not specifically identified. Some indirect costs, e.g., loss of productivity when

patient is hospitalized, were identified. The author points

out that both indirect and direct costs of complications

associated with joint implants must be included as well as

the costs of followup care and rehabilitation therapy.

The authors note that all projected benefits and costs

should be discounted, but do not suggest any discount rate

in particular. They do suggest that variables with uncertain values, e.g., discount rates, be subjected to a sensitivity analysis. Equity issues are not considered. The authors

briefly mention some potential public policy implications

of conducting CEA/CBA of orthopedic joint implants but

their study does not contain specific results regarding the

cost effectiveness of orthopedic joint implants.

Budetti, P., McManus, P., Barrand, N., and Heinen,

L. A., “The Costs and Effectiveness of Neonatal Intensive Care, “ in The Implications of Cost-Effectiveness Analysis of Medical Technology/Background

Paper #2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington, D, C.:

in press, 1980).

This paper includes a review of the efficacy and effectiveness literature, as well as the “cost” and costeffectiveness literature, on neonatal intensive care services.

The authors note the rapid progress made in this area in

the last is years, emphasizing the range and sophistication

of care that hospitals can now offer. Their study centers on

an examination of costs, personnel, technologies, and procedures used, and the efficacy and effectiveness of the intensive care services designed to provide advanced care to

severely ill newborns.

Numerous problems involved in analyzing neonatal intensive care services are identified. First, the definitions are

very tenuous. Neonatal services in many hospitals do not

fit into the classifications used. Technological or personnel

capabilities vary considerably in different hospitals, and

regulatory and reimbursement policies create incentives

for hospitals to classify their neonatal units inappropriately. Providers, paying units, and regulators disagree on uniform definitions that should be applied to different levels

of care.

The major focus of the study is on efficacy, effectiveness, and costs of neonatal intensive care. Outcomes are

defined in terms of improved mortality and morbidity

rates and mental and physical development of critically ill

newborns. Costs are distinguished from charges. The

study addresses the average cost per day of caring for the

critically ill newborn and reimbursement policies and procedures. No discount rate is used. Except in a very rough

estimate of high and low figures for use and the cost effectiveness of caring for different birthweight infants, sensitivity analysis is not applied. Equity issues are not addressed.

The authors examine the incidence and severity of prematurity in the United States. They evaluate the social and

biological aspects of prematurity, trends in infant mortality, and the incidence of underweight infants in the last two

decades, and the effect of neonatal intensive care units

(NICUS) on mortality and morbidity of premature infants

at various birthweights. They also examine the use of

NICUS via admission rates, estimated average length of

stay, estimated total patient days, the number of hospitals

with NICUS, and the number of intensive care beds.

Next, the authors examine the costs of neonatal intensive

care, providing a caveat that the data on use and cost are

very rough approximations. The authors derive the cost

and use data from small, restricted population samples

drawn from NICUS that vary in size, shape, and capability. Data were examined from three geographic regions and

five individual centers, along with numerous studies on

neonatal care, Costs associated with varying degrees of

prematurity and severity of illness were examined, as well.

In general, costs are directly related to birthweight and

prematurity—the lower the weight and/or the earlier the
birth, the higher the cost. The average cost per day in the

hospital for critically ill newborns is $267 for an average

stay of 13 days. The average charge per day was about

$394. The study looks at the existing system of reimbursement for the cost of neonatal intensive care in five States

and via five payers: commercial insurance, Blue Cross,

medicaid, self-pay, and private insurance.

NICUS have been shown to reduce mortality rates, and

all indications are that NICUS are cost effective. Nevertheless, more data is needed to determine their full impact.

The authors review studies of the cost effectiveness or benefit of neonatal intensive care. They use a hybrid costeffectiveness and cost-benefit analysis developed by Marcia Kramer to measure marginal costs of providing neonatal intensive care. They also compare methods of care in

Great Britain and France with those in the United States.

The authors suggest that Federal policies need to be

changed to reflect changes that have occurred in neonatal

care. In particular, they suggest, guidelines that establish

maximum numbers of beds per live births and minimum

sizes of neonatal care units need to be revised. Also,

medicaid and Social Security provisions for reimbursement of neonatal care costs need to be reexamined. The

potential ethical implications of neonatal intensive care

need more discussion.

Cretin, S., “Cost-Benefit Analysis of Treatment and

Prevention of Myocardial Infarction, ” Health Serv.

Res. 12:174, summer 1977.

This article, technically a CEA, compares the effects of

three alternative methods for the treatment or prevention

of myocardial infarction: 1) a coronary care unit, 2) a

mobile coronary care unit, and 3) an intervention/prevention program aimed at reducing serum cholesterol levels.

Effects are measured in terms of the total years of life

added as a result of each alternative program. Costs are

classified as direct and indirect. Costs and effects of each

strategy are modeled on the basis of a cohort of 1O-yearolds followed throughout their lifetimes. In addition, the

manner of implementation is varied. Costs and effects are

calculated for each alternative method assuming 1) the

method is newly introduced alone, and 2) it is newly introduced with the other alternatives ongoing. “Costbenefit” ratios are calculated as the dollar cost per added

year of life for each alternative, introduced alone. The

author illustrates changes in the ratios that result from

varying the discount rate (i. e., performs sensitivity

analysis), using rates of O, 5, and 10 percent. She also discusses problems of selecting a discount rate for comparing

alternative programs that incur costs and accrue benefits at

widely separated times. The author finds the results of her

analysis inconclusive. She notes that this and other modeling processes involve many simplifying assumptions and

require that parameter values be estimated even when supporting data is scant.

Doherty, N., et al., “Cost-Effectiveness Analysis and

Alternative Health Care Programs for the Elderly, ”

Health Serv. Res. 12:190, summer 1977.

In this article, the authors discuss the method of CEA in

general, contrast it with CBA, and illustrate it with an example involving alternative programs of health care for the

elderly (e. g., home care, day care, etc. ). They also discuss

the problems of measuring costs by market prices which

may “obscure the real opportunity costs of resource consumption .“ With regard to effectiveness criteria, the

authors note that many can be specified only in terms of

ordinal numbers denoting rank, and they warn against the

temptation “to add the nonadditive and to compare the incomparable. ” Costs in the analysis presented as an example are classified as primary, secondary, and tertiary, denoting program costs, other health-related service costs,

and personal living expenditures, respectively. The authors explain and illustrate the tabular display approach to

presenting data, in which effectiveness criteria are presented in columns and alternative programs are presented

as row headings. It is unlikely, the authors conclude, that

one alternative will emerge as preferred on the basis of all

relevant criteria. In their example, day care is preferred on

the basis of effectiveness criteria, while home care is preferred on the basis of cost criteria.

Eddy, D., “Rationale for the Cancer Screening Benefits Program Screening Policies: Implementation

Plan, Part III, ” report to the National Cancer Institute, Blue Cross Association, Chicago, Ill., 1978.

This report describes the methods used to analyze the

cost effectiveness of alternative cancer screening policy options and the rationale for a recommended insurance benefits program. Five cancer sites—breast, colon, cervix, lung,

and bladder—were selected for full analysis. The model

used translates the problem of screening-program effectiveness, and many variables that contribute to it, into

quantitative terms and logical relationships. Probability

formulas relating to the important variables are derived.

The model, designed to be programed on a computer,

traces the expected fate of a patient under various program

options. It will accept information about patient characteristics (age, relative risk, previous history, incidence rates,

etc. ) and will program options and present information on

the costs and effectiveness of a specified program. Different discount rates can be entered into it.

The author notes that creating a cancer screening program that is both medically effective and low in cost requires that many age, sex, and risk categories be used to

define the optimal services and screening frequencies for

various groups of individuals. Ideally, a program might include several screening protocols, each tailored to different

categories. This is not possible, however, for a prepaid

benefit program that will be purchased by a large heterogeneous population. Thus, one objective is to design a

benefit program in which services do not vary greatly for

those covered. Marginal effectiveness, rather than absolute

effectiveness, was considered the effectiveness criterion,

and on this basis, there is little difference in the cost-effective program for high-risk as compared to average-risk

groups. The benefit program designed includes the following provisions: I) a standard screening program will be

provided every 4 years for persons aged 25 to 45; 2) a

standard screening program will be provided every year

for those over age 45; 3) an impregnated guaiac slide will
be provided every year beginning at age 45; 4) a Pap smear

will be provided to women every 4 years beginning at age

25; 5) a mammography will be provided to women covered

by the high-option benefit every 2 years beginning at age

50; 6) a proctosigmoidoscopy will be provided every 5

years beginning at age 50.

Eddy, D., “Screening for Colon Cancer: A Technology Assessment, ” in The Implications of Cost-Effectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

This study focuses on the techniques that are available to

screen for colon cancer—their development, evaluation,

use, and cost effectiveness.

The author examines the three basic methods of techniques used in the detection of colon cancer: 1) the digital

exam, 2) the sigmoidoscope, and 3) the test for occult

blood in the stool. For each method, the author notes,

there is either some degree of uncertainty regarding the

sensitivity and specificity of the tests, or some degree of

risk to the patient involved.

The study points out that there have been few, if any,

clinical studies of the digital exam. Its effectiveness has

been proven via the “time-honored” method of use and acceptable results at the patient-provider level. The effectiveness of sigmoidoscopes has been examined in a few

clinical studies. The Hemoccult test has been through, and

is going through, a number of large clinical trials to

evaluate its efficacy. To date, the results are inconclusive.

The author discusses the problems that exist in trying to

apply CEA to colon cancer screening programs. He also

examines a number of factors that affect CEA studies in the

health care area in general. One is the need for, but absence

of, information from formal randomized clinical trials

regarding the effect and value of screening techniques. The

information that is available is usually from uncontrolled

studies that are burdened with problems of their own. Factors such as leadtime bias, patient-self-selection bias, and

length-of-study-period bias also present data problems

that must be considered. Another problem for the analyst

are the quantitative aspects of trying to measure the costs,

benefits, risks, or outcomes of the different colon cancer

screening programs.

The author also discusses the special considerations that

colon screening programs present to a CEA. These factors

include patient characteristics and differences (in terms of

effectiveness of screening programs), schedule (or history)

and type of testing procedures used, varying accuracy of

the different procedures, different origins of the cancer that

require separate analysis, order and frequency of testing,

and a host of other variables that must be included in a

thorough evaluation.

Once, or if, these data and methodological problems are

solved, the author feels the central issue can be addressed:

What is the value of screening for colon cancer? The author sets out the basic format for addressing the problems

involved in a CEA approach. An illustrative example is

used to examine the costs and benefits of screening for colon cancer. A screening program for a 50-year-old average

risk woman is evaluated using eight different combinations

and frequencies of screening tests. The relevant factors

(costs, screening regimen, efficacy data, outcome information, etc. ) are examined by the author, using a sensitivity

analysis approach to determine how the different variables

affect the mortality rate and cost of the various screening

programs. The result of the analysis is presented as a comparison between the decreasing probabilities of colon cancer’s occurring with more frequent testing, improved life

expectancy changes, increases in screening costs, and decreases in lost earnings as a result of the different levels of

screening programs.

Fineberg, H. V., and Pearlman, L. A., “Benefit and

Cost Analysis of Medical Interventions: The Case of

Cimetidine and Peptic Ulcer Disease, ” in The Implications of Cost-Effectiveness Analysis of Medical

Technology/Background Paper #2: Case Studies of

Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

The study has two major goals: One is to assess the

available evidence regarding the benefits and costs of

cimetidine in the treatment of peptic ulcer disease; the

other is to develop a widely applicable cost-benefit model

for evaluation of medical technology. The study combines

these two objectives by applying the model to the evaluation of cimetidine and ulcer disease. The authors approach

the analysis in three parts: 1) a development and discussion

of the cost-benefit model that they feel can be applied to

medical interventions in general; 2) an overview of peptic

ulcer disease in the United States; and 3) a discussion of the

development, diffusion, and use of cimetidine to treat

and/or manage peptic ulcer disease.

The foundation of their cost-benefit model is as follows:

1) There are two principal classes of effects—clinical effects

and health system effects—and the specific components of

these effects depend on the population and intervention being examined; 2) an evaluative model must apply to an

identifiable patient population and specific health care interventions; 3) a patient population may be defined in

terms of a diagnostic category, clinical signs or symptoms,

risk factors, or complications of disease; and 4) clinical and

health system effects interact to lead to an outcome (health

status and/or resource costs).

The authors examine a host of studies dealing with the

safety, efficacy, and effectiveness of cimetidine. Among

the short-term clinical effects they assess are healing, pain

relief, safety and adherence to the treatment plan, complications, recurrence, and recommendations for treating

newly diagnosed, uncomplicated ulcers. The long-term

clinical effects they examine are recurrence, safety, and

complications. They also briefly discuss the pending approval by the Food and Drug Administration of cimetidine

for long-term use.

The authors also examine the health system and outcome effects of cimetidine use. Among the variables evaluated are medication, diagnostic tests, physician visits,

mortality, morbidity, and resource costs. These three areas

—clinical effects, health system effects, and outcomes of
cimetidine use—are the primary elements of the CBA they

perform.

The authors also examine and discuss the following findings: Cimetidine promotes healing and provides faster and

more complete pain relief for duodenal ulcers; it may b e

more effective than placebos for patients with gastric

ulcers; when used for up to 2 months, cimetidine appears

to be a relatively safe drug; most known side effects are

minor or reversible; cimetidine plus moderate amounts of

antacid costs no more than a therapeutically equivalent

course of intense antacid therapy; and maintenance treatment with cimetidine for as long as a year significantly

reduced the chance of ulcer recurrence (compared to a placebo) during the period of treatment. Cimetidine, according to a few studies, also appears to have contributed to a

sharp decline in surgery for ulcer disease in 1978, as well as

to have helped patients to lose significantly fewer days of

work than patients given a placebo.

These many findings and conclusions indicate that cimetidine provides a substantial benefit to cost ratio to the

peptic ulcer patient and the health care system. The authors cite the findings of two other studies; one by the

Netherlands Economic Institute in 1977 and the other by

Robinson Associates, Inc., in 1978. The authors conduct

an in-depth review and critique of the Robinson study.

Geiser, E., and Menz, F., “The Effectiveness of Public

Dental Care Programs, ” Med. Care 14:189, March

1976.

This CBA examines the costs and benefits of a public

dental care program designed to “maintain the integrity of

the natural teeth” in school-age children. Benefits are

calculated by estimating the number of teeth “saved” in Isyear-olds that are a result of the program, and then multiplying it by the cost of replacing a natural tooth with an artificial bridge. The current costs of saving a permanent

tooth are used as a cost measure. Data from two actual

public dental care programs are examined. The authors

conclude that public dental care programs must be administered over a relatively long period of time (6 to 7 years)

before net benefits begin to accrue on an annual basis. A n

even longer period of time (11 to 14 years) is required before the programs generate sufficient total benefits to cover

total costs. The discounted present values of the program,

with use of an 8-percent discount rate, were found to be

particularly sensitive to changes in the cost of care and the

value of saving a tooth. Extensive sensitivity analysis is

performed on the variables involved, making this article

an excellent illustration of the use of sensitivity analysis in

handling uncertainty.

Grosse, R., “Cost-Benefit Analysis of Health Services, ” Ann. Am, Acad. Polit. Soc. Sci. 399:89, January 1972.

This article, a general review rather than an analysis,

presents an explanation of the rationale behind the use of

CEA and CBA in the allocation of health resources and describes an application by HEW. Costs are described as forgone benefits: “The cost of saving a human life is not to be

measured in dollars, but rather in terms of alternative lives

to be saved or other social values sacrificed. ” The problem

of incommensurability of benefits is discussed. HEW’s calculations of the cost per death averted and of productivity

and medical treatment savings in various cancer control

programs are presented and compared to other health programs (e.g., motor vehicles safety and arthritis). The article illustrates the changes in program priority that can occur when the criterion is changed from deaths averted to

savings from avoided medical treatment and loss of productivity (measured as discounted lifetime earnings). The

problem of uncertainty is discussed, and a matrix composed of relative payoffs and the certainty of results is presented as one method of handling it. The final section of

the article describes in detail the HEW maternal and child

health program analysis.

Hagard, S., et al., “Preventing the Birth of Infants

With Down’s Syndrome: A Cost-Benefit Analysis, ”

Br. Med. J. 1:753, Mar. 27, 1976.

The costs and benefits of providing routine prenatal diagnosis, with termination of affected pregnancies, are examined. In the event of pregnancy termination, two situations are considered: 1) Termination is followed by a further pregnancy, assumed to be normal (replacement); and

2) termination is not followed by a further pregnancy (no

replacement). Since such prenatal testing could diagnose

fetal myelocele, the costs and benefits involved in preventing this disease are also taken into consideration. For

Down’s syndrome, during the period 1975-94, the following numbers are estimated: 1) the number of births by 5-

year maternal age groups, 2) survival rates and the degree

of handicap of survivors, 3) costs to society of caring for

survivors, 4) characteristics, including the number of affected births prevented, of a prenatal diagnostic program,

and 5) the costs of such a program. The benefit of preventing the birth of infants with Down’s syndrome is calculated

as the cost to the community of their care. In the case of replacement, this is the difference between the cost of caring

for a handicapped person and the cost of caring for a normal person. In the case of no replacement, this is the cost of

caring for a handicapped person. Results of the study indicate that the benefit-cost ratio of prenatal diagnosis is

greater than 1 for women over 40 years old, equal to 1 for

women between 35 and 45 years, and less than 1 for

women under 35 years. The problems associated with different results for different age groups are discussed. A discount rate of 10 percent is used. The authors examine the

changes in the results of the analysis that would occur if,

after genetic counseling, only half of the women accepted

amniocentesis and possible termination of pregnancy.

Harris, G., “Introduction to Cost-Benefit Analysis

Applied to New Health Technologies, ” prepared by

Arthur D. Little, Inc., for Bureau of Health Planning

and Resource Development, Health Resources Administration, Hyattsville, Md., December 1977.

This document describes the steps in CBA as the following: 1) articulation of the problem, 2) enumeration of alternatives to address the problem, 3) identification of their

achievable effects, 4) measurement and valuation of the
achievable effects, and 5) application of the economic decision criteria. Objectives are described as cost reduction

and/or enhancing of benefits. Costs and benefits are classified as direct, indirect, or intangible. The need to focus on

incremental, rather than total, costs and benefits is explained. Discounting to present value and the problem of

choosing a discount rate are discussed. Five criteria of

preferredness are described: 1) net present benefit, 2) internal rate-of-return, 3) benefit-cost ratio, 4) payback period,

and 5) average rate of return. The advantages, disadvantages, and appropriate use of each criterion are presented.

Threshold analysis, sensitivity analysis, and probability/risk analysis are described as methods of dealing with

uncertainty. Common problems encountered in analysis,

such as incomplete data, transitional costs, scope, and externalities, and the issue of equity and distribution are

discussed.

Klarman, H., et al., “Cost-Effectiveness Analysis Applied to the Treatment of Chronic Renal Disease, ”

Med. Care 6:48, January-February 1968.

The authors attempt to determine the best mix of center

dialysis, home dialysis, and kidney transplantation in examining the costs and effects of treating chronic renal disease. A quality-of-life adjustment is made to account for

the differences in lifestyle between patients on dialysis and

those with effective transplants. (The freedom associated

with the latter is valued at 0.25 of a life-y ear.) The calculations in the analysis are based on survivorship tables for

transplant and dialysis cohorts of 1,000 each. The authors

warn that, at the time of the analysis, there had not been

enough experience with any of the three treatment modes

to generate an expected life table with great accuracy. The

discount rate used is net of an anticipated inflation rate, resulting in a discount rate of 4 percent for transplant and

center dialysis and 5 percent for home dialysis. No sensitivity analysis is presented for the discount rate, the anticipated inflation rate, or life expectancy. The authors

conclude that kidney transplantation is more cost effective

than the other two alternatives. Choice of the preferred

treatment modality is independent of the quality-of-life adjustment because transplantation dominates even without

the adjustment.

Korenbrot, C., Flood, A., Higgins, M., Roos, N.,

and Bunker, J., ● “Elective Hysterectomy: Costs,

Risks, and Benefits, ” in The Implications of CostEffectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

This study examines elective hysterectomy as it is used

for sterilization and cancer prevention. The focus of the

study is a review of the literature and the issues surrounding the costs, risks, and benefits of elective hysterectomy.

The study does not attempt to establish the cost effectiveness of hysterectomy. The authors examine the significant

● With the technical assistance of Mitchell LaPlante

side effects of hysterectomy, such as change in medical utilization and psychological effects following surgery.

The authors review selected studies that evaluate the efficiency and cost effectiveness of elective hysterectomies.

Not taking a cost-benefit approach, these studies do not attempt to value the saving of life in monetary terms. The

first two efficiency studies that the authors’ review contrast

the direct costs of hysterectomy with the net lifetime costs

of gynecological care. Future costs are discounted at rates

varying from 3 to 6.5 percent. Another study the authors

review examines the use of hysterectomy as a sterilization

device v. the direct costs of tubal ligation plus the expense

of future gynecological care which would have been

averted by hysterectomy.

The effectiveness of hysterectomies in preventing pregnancy and cancer is not an issue; but the health risks of the

procedure are. Efficacy/effectiveness of alternative means

to accomplish these objectives are assessed, but not in the

cost-effectiveness studies reviewed. Additionally, the costeffectiveness studies which are reviewed do not attempt to

identify, measure, or place a value on the side effects of

surgery.

Costs are distinguished from charges and issues of equity

are discussed. The authors do not employ a sensitivity

analysis. Conclusions are drawn with respect to the cost effectiveness of elective hysterectomies as they are used for

the separate purposes that are examined.

Leroy, L., and Solkowitz, S., “Costs and Effectiveness of Nurse Practitioners, “ in The Implications of

Cost-Effectiveness Analysis of Medical Technology/

Background Paper #2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

This study reviews the literature on the cost effectiveness

of nurse practitioners to provide primary medical care

services. Only limited data are available, and much of the

information deals with other types of physician extenders.

In addition, many of the data have been gathered in the

developmental stage of introducing nurse practitioners; the

relevance of these data for present policy purposes is

unclear.

At least theoretically, nurse practitioners offer the potential to reduce the costs of health care and improve access to the health care system. Nurse practitioners can perform basic and routine medical care tasks, allowing physicians to focus their efforts on serious illness problems.

Training costs and pay are less for nurse practitioners than

for physicians, so costs should be lower for routine care if

nurse practitioners are used. There are a number of problems in directly extrapolating to lower costs, however,

and, depending on the system within which nurse practitioners operate, cost savings may or may not be realized.

A key question examined by this study deals with the

nature of the services nurse practitioners perform and how

they affect costs. In general, they provide complementary

and substitute services, although the nature of these services is difficult to document because data often indicate

only “office visit. ” Complementary services would include
treatment such as “well baby care, ” while substitutive services refers to such treatment as “physicals.”

In terms of quality of care, nurse practitioners appear to

provide care that is of as high quality as that of physicians

(with whom they usually work and are compared). There

is some evidence that nurse practitioners, working in close

conjunction with physicians, provide superior care when

compared to solo practitioners. Productivity is more difficult to assess and depends on how nurse practitioners are

used. There seems to be clear evidence that the use of nurse

practitioners improves physicians’ productivity, but it is

not clear how this improved productivity affects costs. Supervisory time, duplicative work, and the fact that nurse

practitioners spend more time per patient must be considered.

The data needed to conduct a CEA of nurse practitioners

include employment costs, training costs, and medical care

costs. Unfortunately, each of these factors may be subject

to changes as a result of alterations in another part of the

system. The employment costs of nurse practitioners, for

example, is a function (in part) of the demand for their

services. Even more difficult to determine is price. Because

they are most often hired by physicians or health institutions which have already established fee systems, any cost

savings may be absorbed by the physicians or institutions

and may not be reflected in the price of services delivered.

The case concludes by cautioning against the use of current data to determine new policy. Based on changes in the

way nurse practitioners are used, costs could vary widely.

This is a case in which an actual CEA may provide misleading policy advice, although the identification of variables required by the CEA may be very helpful.

Lesourd, D., et al., Benefit-Cost Analysis of Kidney

Disease Programs, PHS publication No. 1941, prepared by the Research Triangle Institute (Washington, D. C.: U.S. Government Printing Office, 1968).

This analysis was one of a series of federally sponsored

efforts to assess the costs and benefits of alternative approaches to the problem of kidney disease. The approaches

included screening, prevention, and three treatment modalities (home dialysis, center dialysis, and transplantation). Employing a variety of assumptions (e. g., risk population for the screening programs, size of treatment facilities), the authors concluded that early detection dramatically dominated the treatment approaches with respect to

economic benefits and costs. Depending on the population

screened, the former had benefit-cost ratios of 30:1 and

greater. By contrast, the treatment alternatives produced

benefit-cost ratios in the vicinity of 1:1. This ratio varied

according to: 1) the treatment method (transplantation

producing the highest ratios); 2) the scale of operation; 3)

the allocation of research costs; and 4) high, low, and best

cost estimates in the two instances of dialysis. To estimate

indirect benefits (i. e., productivity losses avoided), the

authors assumed that 70% percent of the dialysis patients

would be capable of resuming a normal earning capacity;

the remaining 30 percent were assigned half the expected

income of a comparable but healthy individual.

The qualitative findings of this analysis were supported

by other studies undertaken at the same time. Despite the

consensus that prevention and early detection were the

most cost-effective approaches to dealing with the kidney

disease problem, Federal policy was directed toward the

alternative which appeared least economically desirable,

center dialysis.

Lubeck, D. P., and Bunker, J. P., “The Artificial

Heart: Costs, Risks, and Benefits, ” in The Implications of Cost-Effectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress

(Washington, D. C.: in press, 1980).

This study examines the many factors that have played a

role in the development of the artificial heart: factors that

are affected by, and in turn affect, three areas of public

policy—R&D, reimbursement, and regulation.

The authors provide a backdrop of the history of the artificial heart development program. They also examine the

safety and efficacy determinations that have been arrived

at through experiments and clinical trials. The current and

potential technological developments that are or will be,

part of the artificial heart are described, and the numerous

R&D needs that must be met before an artificial heart can

be successfully used are examined.

The authors examine the economic aspects of the artificial heart from the patient’s perspective and from a societal

view, focusing on the costs of diagnosis, implantation, and

postoperative care. These costs are compared to the costs

associated with related procedures: cardiac pacemakers,

aortocoronary bypass surgery, and heart transplants. The

renal dialysis program is used to illustrate the possibility of

the Federal Government’s financing artificial heart procedures and the distribution of services to the population.

The authors also examine four social cost areas: increased social expenditures, potential distributional inequities, effects of nuclear radiation if a nuclear energy source

is used, and the opportunity costs. They also examine the

efficacy, potential benefits and costs, and likelihood of

saving lives by cardiac disease prevention programs.

Quality of life issues are addressed for both the shortand long-term effects. The authors draw on the experiences

of those who have had heart and kidney transplants to illustrate the types of impacts on the patient and the family

that can occur. The potential effects include personal,

marital, family, physical, medical, and psychological

problems that can occur after a person undergoes major

surgery. The authors also discuss the added burdens/impacts that will result if a nuclear-powered energy source is

used.

On the benefits side, although the authors briefly discuss

the technological spinoffs of the artificial heart program,

their primary focus is on two areas: the potential for patients returning to an active life, and the estimated years of

life that may be gained. Morbidity, mortality, and added

years of life are examined and estimated via a best case and

worst case analysis if the artificial heart is implanted.
Luce, B., “Allocating Costs and Benefits in Disease

Prevention Programs: An Application to Cervical

Cancer Screening, ” in The Implications of Cost-Effectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of Medical Technologies, prepared by OTA U.S. Congress (Washington, D. C.: in press, 1980).

This author believes that one important reason for the

reluctance to fund disease prevention/health promotion

programs is that benefits often do not accrue sufficiently to

those who incur the costs. Also, the private sector is expected to fund such programs. Consequently, traditional

CEAs which are performed only from the societal perspective may not be applicable for public policy.

This author performs a CEA of cervical cancer screening

for a given risk group from different perspectives. Screening for cervical cancer is used to demonstrate the cost effectiveness of disease prevention programs. The disease process is modeled by the author using a Markov Chain technique to “age” a simulated population of 30- to 39-year-old

women for 10 years (using disease transition probabilities

reported in the literature). The cost effectiveness of screening is then calculated at different intervals—ranging from

annual screening to no screening for the 10-year period.

The effects are evaluated for: 1) different migration patterns, 2) different risk groups, 3) different modes of administering Pap tests, and 4) joint production considerations.

The author also tests the sensitivity of the results to

various discount rates and to the range of error rates for

Pap tests.

The results indicate that a private party always has a financial incentive to postpone screening, whereas society

finds it more cost effective to screen, but only at infrequent

intervals. In addition, the author notes, the cost effectiveness of screening is markedly affected when a more efficient (i.e., less costly) delivery mode is simulated. Screening is significantly affected when joint production effects

are considered. The cost effectiveness of screening, however, is not very sensitive to small changes in the discount

rate, initially set at 10 percent, nor to varying assumptions

regarding error rates.

The author concludes that if society wants the private

sector to screen for cervical cancer at a socially determined

optimal rate, then society must be willing to subsidize the

cost of the program. The study also concludes that the cost

effectiveness of cervical cancer screening is much more affected by the cost assigned to screening then by different

assumptions of the precise error and discount rates.

The cost effectiveness of screening at each simulated interval was compared to no screening for a 10-year period.

Efficacy information was addressed and different test error

rates were used. The production of the Pap test was simulated, for cost purposes, at two levels: an expensive university hospital clinic using specialists, and an inexpensive

health clinic using licensed nurses. Only lives and years of

life saved were identified as benefits.

Costs were distinguished from charges, marginal costs

were considered, and indirect costs are used. Discounting

of costs and benefits was done (rates tested: O, 5, 8 to 12

percent), and sensitivity analysis was performed; however,

issues of equity were not directly considered in the

analysis.

Luft, H., “Benefit-Cost Analysis and Public Policy

Implementation: From Normative to Positive Analysis, ” Pub. Pol. 24:437, Fall 1976.

The author argues that conventional CBA and CEA

should be extended to include a predictive analysis of the

implementation phase in order to determine whether and

how the project will be done. The predictive analysis involves three steps: 1) a standard CBA to determine whether the project should be undertaken; 2) a CBA from the

perspective of each decisionmaker or interest group capable of influencing the success of the project to determine

the likelihood that the project will be undertaken; 3) a redesign of the project or the development of incentives to

improve the likelihood of success for socially desirable

projects.

In a case study of a surgicenter, it is noted that the resultant shifting of a revenue from one set of providers to

another, though only a pecuniary externality in standard

benefit-cost analysis, has a substantial impact on the likelihood that a surgicenter will actually be implemented. The

importance of identifying decisionmakers and their respective power to influence the success of the project is discussed. The author points out that in the second step of the

analysis (the “interest-group analysis”), transfer payments,

taxes, and pecuniary externalities should be explicitly considered, so that the financial flows as perceived by the relevant interest groups are adequately represented. In addition, it may be appropriate to use substantially different

discount rates for each interest group. The final step in the

interest-group analysis is to estimate each group’s utility

function and the group’s relative power to either promote

or block implementation of the project.

Luft presents an application of predictive analysis to the

use of a work evaluation unit for ascertaining functional

work capacity following a myocardial infarction. The relevant interest groups in this analysis include the patient,

family, physician, employer, insurer, and society. Luft

estimates both the likely net effects on each interest group

of using the work evaluation unit and each group’s relative

weight. The author concludes that this extended, positive

form of benefit-cost analysis can improve the allocation of

resources by helping to promote the implementation of desirable and feasible programs and “to prevent the adoption

and implementation of proposals that appear promising in

theory but are likely to be sabotaged in practice. ”

McNeil, B., et al., “Measures of Clinical Efficacy:

Cost-Effectiveness Calculations in the Diagnosis and

Treatment of Hypertensive Renovascular Disease, ”

N. Eng. J. Med. 293:216, July 31, 1975.

The authors measure the value, in terms of sensitivity

and specificity, of intravenous pyelography and radiohippuran renography as diagnostic screening methods for hypertension caused by renovascular disease. Costs associated with both diagnosis and subsequent surgical treatment are also calculated. Financial costs of the diagnostic

procedures are based on the Massachusetts Relative Value

Scale; hospital and operation costs are based on 1974
charges at Peter Bent Brigham Hospital. Three aspects of

cost-effectiveness in the management of renovascular hypertension are examined: 1) the financial costs of casefinding in relation to the sensitivity and specificity of both

diagnostic procedures; 2) the total dollar cost of screening

the American hypertensive population, of making a definitive diagnosis, and of performing corrective operations;

and 3) the ]ife and dollar cost of each surgical cure. The

cost of case-finding is found to be approximately $2,OOO

per positive diagnosis when only one diagnostic examination is used for screening. This figure rises to $2,600 to

$4,400 when both procedures are employed. The total

costs of screening all patients with hypertension, performing arteriography on those with positive tests, and operating on all patients with renovascular disease amounts to

$10 billion to $13 billion. The authors note that this estimate does not include the costs of initial identification of

all hypertensive Americans. Thus, the authors estimate a

cost of $15,000 to $20,000 per cure, and note that there are

15 deaths for every 100 surgical cures. The cost-effectiveness calculations are not sensitive to varying the assumptions regarding the prevalence of renovascular disease in

hypertension patients from 10 to 5 percent.

Neuhauser, D., “Elective Inguinal Herniorrhaphy

Versus Truss in the Elderly, ” in Cost, Risks, and Benefits of Surgery, edited by J. P. Bunker, et al. (New

York, N. Y.: Oxford University Press, 1977).

This CEA reviews available data in order to see what effect the choice of elective herniorrhaphy v. truss has on the

life expectancy of a 65-year-old person. The analysis includes a calculation of the average effects of 1) having an

immediate elective herniorrhaphy (with its low mortality,

but the risk that the hernia will recur and require additional elective operations); and 2) using a truss (with its attendant risk of obstruction, followed by an emergency operation with a high mortality rate). Using data obtained

from the relevant literature, the author estimates: 1) the

mortality rates associated with (a) elective and (b) emergency surgery, 2) the probability of recurrence of the hernia after an operation, 3) the yearly probability of strangulation, and 4) the life expectancy of the patient. Two sets of

numbers are used in the analysis. The first set of numbers

serves as a conservative test of the hypothesis that the truss

prolongs life, because the values in this set are those which

systematically place the benefit of the doubt in a direction

favorable to the elective operation. The numbers in the second set are based on what seem to be the most reasonable

and reliable data. (The author notes that there are insufficient data to consider a “do nothing” third alternative. )

The model takes the form of a decision tree, which is designed so that the “payoffs” equal the expected value of the

average number of life-years lost. The results of the conservative test (used because it makes the strongest case for

the elective operation, which is standard of surgical practice uniformly proposed by current surgical literature)

indicate that the elective operation has a higher loss of life

associated with it for the 65-year-old than the truss does.

The test using the “most reasonable” estimates indicates

that the elective operation has a mortality rate 5.5 times

greater than the truss. This large relative difference, however, translates into an absolute difference of only 14.29

days. The author notes that in view of this small absolute

difference in mortality, the issue of quality of life becomes

important. The article continues with a discussion of this

type of adjustment, but no quality-of-life adjustments on

the analysis data are attempted. The magnitude of the costs

involved in the elective operation is noted, but a detailed

analysis is not presented. On the basis of this study, the

author observes that medicare funds expended on elective

herniorrhaphy serve, if anything, not to increase life expectancy, but rather to improve the quality of life. He

asks, therefore, if these funds might better serve to improve the quality of life for the elderly in some other way

(such as in reducing subway fares for the elderly).

Neuhauser, D., and Lewicki, A., “What Do We Gain

From the Sixth Stool Guaiac?” N. Eng. J. Med. 293:

226, July 31, 1975.

This article examines the costs and effects of the sixth sequential stool guaiac for screening asymptomatic colonic

cancer. An analysis of the expenditures concludes that

costs rise exponentially, so the marginal cost of the sixth

test may be 20,000 times the average cost. In addition, data

indicate that there is little gain in the true positive rate

from testing beyond the second guaiac examination. Thus,

the cost per true positive becomes gigantic. The marginal

cost is decreased with lower test sensitivity and increased

with lower prevalence of colonic cancer. The authors conclude that defining a high-risk group, which wouId serve to

lower marginal cost, is essential to justify such screening

programs in a world of constrained resources.

Neutra, R., “Indications for the Surgical Treatment

of Suspected Acute Appendicitis: A Cost-Effectiveness Approach, “ in Costs, Risks, and Benefits of Surgery, edited by J. P. Bunker, et al. (New York, N. Y.:

Oxford University Press, 1977).

This article presents a quantitative approach to the costs

and benefits associated with the “interventionist” and

“noninterventionist” management of suspected appendicitis. The assessment considers lives, postoperative disability, and economic costs. Since the author relied on the

rather scanty data from the available literature and on

many simplifying assumptions, however, he cautions that

the analysis should be viewed as “paradigmatic rather than

definitive, ” The analysis addresses the question of when to

operate, not alternative strategies, such as a dietary prevention program or antibiotic therapy.

On the basis of two symptoms (location and severity of

pain) and two signs (presence of right lower quadrant rebound tenderness and rectal tenderness), an “appendicitis

risk score” was developed. Twenty-four symptom combinations were developed and the probability of appendicitis

for each combination was determined and ranked.

For example, the highest rank (24) corresponds to the

combination of right lower quadrant, severe pain with rebound, and rectal tenderness. Assumptions are presented

regarding: 1) the distribution of cases and noncases of appendicitis along the risk scale, 2) the prevalence of cases
and noncases, and 3) the net costs of the false negatives and

false positives in terms of mortality, convalescence, and direct hospital costs. Two analyses are performed, one assuming that 100 percent of the appendicitis patients on

whom surgery is not performed will perforate, the other

assuming that 30 percent will perforate, The results indicate that a surgeon can ensure an acceptable mortality rate

by taking an “interventionist” approach, but only at the

cost of increasing convalescent days and hospital costs. Relaxing the indications for surgery to include patients who

lack the most obvious symptoms saves lives, but at an ever

diminishing rate. The few lives saved by operating on patients with minimal symptoms are purchased at great costs

in convalescence and dollars associated with the removal

of large number of normal appendices. The author suggests a solution to this dilemma—namely, increasing discrimination by using very complete diagnostic information

and careful clinical interpretations. Increased discrimination can reduce the removal rate of normal appendices

without an increase (and possibly with a decrease) in the

rate of perforation. The author estimates the possible savings in lives, convalescence, and money that may result

from an increase in discrimination.

Office of Technology Assessment, U.S. Congress, A

Review of Selected Federal Vaccine and Immunization Policies, GPO stock No. 052-003 -00701-1

(Washington, D. C.: U.S. Government Printing O ffice, September 1979).

This study includes an examination of the cost effectiveness (CE) of applying a primary preventive technology—

vaccination against pneumococcal pneumonia—to different age groups. Medical care costs and health effects

associated with a preventive program are explored from

the perspectives of society and of a third-party payer such

as medicare.

A CEA was used to calculate the expected change in

health effects and medical costs from vaccination against

pneumococcal pneumonia—an alternative compared to

continuing the present situation in which pneumococcal

pneumonia is treated if it occurs. In the analysis, costs

were limited to expenditures and savings within the medical care sector, and changes in health status were expressed

in years of healthy life. Thus, the cost-effectiveness ratio

represented the net medical cost per year of healthy life

that would be gained by a vaccinated person. The calculations were based on a single hypothetical vaccination

program conducted in June 1978. The analysis used a

simulation model to estimate the costs and effects that

would result from 1978 to 2050 for two closed populations,

one vaccinated and the other unvaccinated. Costs and effects were discounted at 5 percent per year. Separate costeffectiveness ratios were calculated for five different ages:

2 to 4 years, 5 to 24 years, 25 to 44 years, 45 to 64 years,

and 65 years and older. The analysis employed a sensitivity analysis to test the effect on the results of varying the

values of several uncertain parameters over reasonable

ranges.

Net health effects were expressed in quality-adjusted life

years (QALYs). Mortality rates for pneumonia as an underlying cause of death provided by the National Center

for Health Statistics (NCHS) formed the basis for estimating 1978 pneumonia mortality among the unvaccinated.

Unpublished age-specific data from the Health Interview

Survey conducted by NCHS was used to estimate the days

of pneumonia morbidity among the unvaccinated.

Medical care costs, expressed in dollars, included additional expenditures for vaccinations and for treatment of

vaccine side effects; reduced expenditures for treating

pneumococcal pneumonia that would be expected to occur

without vaccination; and additional expenditures for other

illness in the extended years of life gained by vaccinees who

avoid death from pneumococcal pneumonia. Unpublished

age-specific data from the Hospital Discharge Survey and

the National Ambulatory Care Survey of NCHS was used

to construct estimates of the costs of treating pneumonia.

The study found that, given the range of factors involved, vaccinations would entail positive medical expenditures for every age group and would be most cost effective

for those 65 years or older. The cost-effectiveness ratio was

about $4,800 per QALY gained for all ages and $1,000 per

QALY for ages 65 and older. The analysis found that vaccination of 21.5 percent of the population 65 years and

older would result in a net cost to society of about $23 million and would yield about 22,000 QALYs over the lifetimes of those vaccinated. The study also concluded that

vaccination for all age groups in the population would

have a net cost of about $150 million for a gain of 31,000

QALYs.

The study also examines policy implications of these

findings, including a possible change in the medicare law

to permit Federal payment for pneumococcal vaccine for

the elderly.

Pauker, S., and Kassirer, J., “Therapeutic DecisionMaking: A Cost-Benefit Analysis, ” N. Eng. J. Med.

293:229, July 31,1975.

In this article, a mathematical relationship is derived between the benefits and costs of a treatment in a given disease and the threshold level of clinical suspicion of the disease. When the probability of a patient’s illness exceeds

this threshold level, the better choice is to administer treatment; when the probability is below the threshold, the better choice is to withhold treatment. The benefit equals the

net benefit of appropriate treatment and is calculated as the

difference between the utility of administering treatment

and the utility of withholding treatment from patients who

could benefit from it. The cost is the net cost of unnecessary therapy and is calculated as the difference between the

utility of avoiding treatment and the utility of administering treatment to those who do not have the disease. Using

probabilities, the authors develop equations expressing the

expected values of treatment and no treatment. The point

of indifference as to course of action is where the expected

value of treatment equals the expected value of no treatment. The probability value at the indifference point is the

threshold level. Using this concept in a clinical setting requires assessing the probability of the disease in a given patient and determining whether it is above or below the

threshold level. A unique threshold value must be calcu-
lated for each disease and its treatment in a given cohort of

patients (defined as having common risk characteristics).

Sensitivity analysis may be employed when significant uncertainty surrounds the probabilities and utilities involved

in the calculations. In addition, if the clinical status of the

patient or if the circumstances of administration of the

therapy differ notably from the typical case, the benefits

and/or costs must be adjusted appropriately.

Rettig, R. A., “Formal Analysis, Policy Formulation,

and End-Stage Renal Disease, ” in The Implications of

Cost-Effectiveness Analysis of Medical Technology/

Background Paper #2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

This paper examines the role of formal analysis in Federal decisionmaking related to end-stage renal disease rather

than that of CEA per se. The study places special emphasis

on institutional factors encouraging or inhibiting the use of

formal analyses. These are defined as “any explicitly analytical means of systematically examining the social costs

and benefits of alternative policies for the purpose of

choosing a preferred alternative in light of an a priori normative decision rule. ” CEA and CBA fit this definition, as

do risk-benefit and cost analyses.

The case study presents information on patients with

end-stage renal disease. The author notes that the proportion of men in the total patient population on dialysis declined between 1970 and 1976. The average age of dialysis

patients increased, and the proportion of home dialysis patients declined from 40 percent in 1972 to 24 percent in

1976. The number of dialysis patients in the medicare program has risen from 14,000 in 1973 to 50,000 in 1978.

The paper deals primarily with the impact of two formal

analyses of end-stage renal disease issued in 1967: 1) the

“Gottschalk report, ” prepared by an expert advisory committee for the Bureau of the Budget; and 2) the “Burton

report, ” prepared by a Public Health Service task force for

the U.S. Surgeon General. (The paper mentions several

other formal analyses but focuses on these two. ) The

author describes policy-related and institutional /bureaucratic factors that led to the conduct of these formal

analyses and that affected the form the analyses took along

with many of their methodological assumptions. The

author also describes and summarizes the results of the

CEA in the Gottschalk report and of the “costs and

benefits” analysis in the Burton report.

The author then addresses the effects of both reports.

The Gottschalk report, for example, led the Bureau of the

Budget to fund a Veterans Administration (VA) administered hemodialysis program that included a substantial

portion of the VA dialysis patients. The Burton report, according to the author, had no direct program effects.

On the whole, this study suggests that formal analysis

“did not affect the fact that the policy choice was a basic

political choice. ” Yet the paper also notes that the analyses

may have raised the consciousness of high level policymakers as to cost implications. The paper also mentions

some of the factors that limit the effect of analysis such as

inadequate data, lack of access of analysts to decisionmakers, and difficulties in making assumptions that frame the

problem.

Saxe, L., The Implications of Cost-Effectiveness

Analysis of Medical Technology/Background Paper

#3: The Efficacy and Cost-Effectiveness of Psychotherapy, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980),

This case study prepared by Leonard Saxe, was based on

a document prepared for OTA by Brian Yates and Frederick Newman. It describes a variety of methodological and

substantive problems that arise in assessing the effects of

mental health treatments. The report both summarizes the

existing literature and attempts to present the divergent

perspectives within the research-policy community concerned with psychotherapy. As described below, it deals

with four issues that are centrally related to the evaluation

of psychotherapy.

Definition, Psychotherapy is not a simple intervention,

and part of the confusion about its effectiveness has to do

with reviewers’ use of different definitions. The present

report uses a relatively broad definition of psychotherapy

in order to best represent current therapy practice. This

definition includes treatments based on Freudian ideas

about psychodynamics, as well as newer therapies based

on theories of learning and cognition. The report also notes

that psychotherapies are not distinguishable only by their

theoretical bases. In addition, patient variables (e.g., intelligence), therapist variables (e.g., empathy), and the

nature of the treatment setting affect the nature of psychotherapy. Although the inclusion of such factors makes the

analysis of psychotherapy more difficult, there seems to be

ample evidence as to the importance of these factors on the

outcome.

Assessibility. Although psychotherapy itself is complex

and there is no clearly agreed upon way of viewing it, the

methods for assessing psychotherapy seem better established. The report describes the variety of experimental

and quasi-experimental designs that have been used in

assessing psychotherapy, along with an analysis of what

types of information can be obtained by application of

these techniques. The report also describes and analyzes

various methodological strategies for measuring the outcomes of psychotherapeutic treatment and the ways in

which the reliability and validity of measures are established. Unfortunately, research practice does not always

meet these standards. Some explanations offered in the report include the difficulties of withholding treatment and

the problems of assessing effects over time. The report also

considers the recent development of systematic procedures

for synthesizing the findings of multiple investigations.

The problems of such techniques, as well as their promise

for detecting valid trends in the research literature, are

analyzed.

Efficacy, The report describes some of the plethora of research which has been conducted on psychotherapy. The

focus of the report’s efficacy analysis is a discussion of six

important earlier reviews of the psychotherapy literature.

In addition, many of the evaluative studies themselves

were reviewed. Despite some fundamental differences,
112 ● Background Paper #1: Methodological Issues and Literature Review

both in the criteria they develop for assessing psychotherapy and the studies they include for review, the reviews all

seem to support the findings that (under specified conditions) there is evidence as to psychotherapy’s effectiveness.

In fact, with the exception of reviews that focus on psychoanalytically oriented therapies, there seems to be little negative evidence as to efficacy of such treatments. Although

it is difficult to make global statements, the evidence seems

more supportive of psychotherapy than of any alternative

hypothesis (spontaneous remission, placebo effects). However, there is a great need for well-conducted research

which evaluates psychotherapy for specific disorders under

specified treatment conditions. This research would need

to be carried out in actual delivery settings.

Cost effectiveness. The application of CEA/CBA to psychotherapy is much more recent, and hence less developed

than efficacy research. Nevertheless, a number of models

are available for conducting such analyses. In general, the

models are based on those used in other applications of

CEA/CBA, and the problems engendered by their use are

similar. A particular concern with such psychotherapy

assessments is whether costs and benefits can be comprehensively measured. Thus, for example, although the

costs of psychotherapy treatment are relatively easy to

measure, it is more difficult to determine and quantify

what type of benefit has been achieved. Much of the

CEA/CBA research to date has involved a comparison of

psychotherapy treatments. Although such research indicates the potential use of CEA/CBA to improve the functioning of clinical settings where psychotherapy is given,

its use for policymaking is less clear. Such work seems possible, however, and may potentially be incorporated as

part of large- scale efficacy assessments.

Schachter, K., and Neuhauser, D., “Surgery for

Breast Cancer, ” in The Implications of Cost-Effectiveness Analysis of Medical Technology\Background Paper #2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

This study is an examination of the scientific and technical issues that are part of the debate over the appropriate

approach to detecting and treating breast cancer. The major focus of the analysis is devoted to the review, discussion, and evaluation of the various types of surgical and

nonsurgical procedures used to treat breast cancer. Costeffectiveness considerations, however, are not totally ignored. The authors note that the resolution of the detection

and treatment issues will have major cost and benefit implications. The authors also perform a hospital cost analysis of two different treatment strategies—inpatient versus

outpatient tissue biopsy.

The background of the study is established by a brief

overview of the extent and effects of breast cancer in

America. A history of cancer of the breast is presented, as

is a description of the development and popularization of

the Halsted method of performing radical mastectomy procedures to treat breast cancer. Developed in the late 1880’s,

the Halsted method remained the generally accepted “treatment of choice” for over 80 years—in 1970, 80 percent of

breast cancer patients in the United States received radical

mastectomies.

Variations of the Halsted method and completely new

approaches to treating breast cancer (both surgically and

nonsurgically or a combination of both techniques) over

the last two decades have challenged the traditional

Halsted technique. In this paper, the authors examine the

evidence regarding the efficacy, safety, mortality, and

morbidity of these new techniques, as well as that for the

Halsted method.

The six treatment procedures they examine are: 1) radical mastectomy, 2) extended radical mastectomy, 3) modified radical mastectomy, 4) simple or total mastectomy,

5) partial mastectomy, and 6) local excision, lumpectomy

(or tylectomy). Special emphasis is placed on reviewing the

status of the nontraditional methods of treating breast

cancer, i.e., those procedures that run contrary to the

Halsted approach (radical mastectomy). Also discussed are

the roles of three American surgeons—Dr. Leslie Wise, Dr.

George Crile, Jr., and Dr. Oliver Cope—who have long

advocated and practiced a more limited surgical approach

to treating breast cancer. Their investigations and results

regarding the success of using non-Halsted procedures to

treat patients are examined.

The authors summarize the debate by discussing the results of the National Cancer Institute’s consensus panel

meeting on the topic of breast cancer treatment held June 5,

1979, at the National Institutes of Health. In essence, the

conclusion was that much work is left to be done in evaluating the various techniques. The conference recognized

the potential of the nontraditional procedures and the

value of the total mastectomy as used in place of the Halsted radical procedure for certain women. More information is needed regarding the efficacy and safety of the alternative procedures; segmental mastectomy, primary radiotherapy, etc. Over the last few years, the modified radical

procedure has become more popular than the Halsted radical technique, but there is still no general consensus on

what procedure(s) should be the treatment of choice.

According to the authors, there is good evidence that

survival rates are no better for the radical procedures than

for the less severe techniques available. Why then is there

still adherence to the more drastic approach? The authors

set out a number of micro and macro issues that may help

explain the continued reliance on the Halsted method: cultural and traditional reasons, economic incentives, individual personalities and reputations, existing logic of

cancer treatment, structure of the medical specialties,

burden of proof requirements on innovators and traditionalists, medical conservatism, and the scaling of evidence.

The authors’ cost analysis, as mentioned above, is a

comparison of the cost differences of inpatient versus outpatient tissue biopsy. The authors consider these alternative strategies in light of the number of cases of breast surgery at Massachusetts General Hospital in 1976 and the

total number of procedures for the United States in 1975.

Their calculations and extrapolations determined that $185

million (excluding radiation therapy) or a 45-percent reduction in total costs would result per year if outpatient biopsies were used uniformly and radical surgery were re-
placed with more limited surgery. However, as the authors

note, the reader must realize the very approximate nature

of cost analysis. Nevertheless, the authors feel that the

magnitude of the cost differences warrant a more complete

investigation.

Scheffler, R. M., and Delaney, M., “Assessing Selected Respiratory Therapy Modalities: Trends and

Relative Costs in the Washington, D.C. Area, ” in

The Implications of Cost-Effectiveness Analysis of

Medical Technology/Background Paper #2: Case

Studies of Medical Technologies, prepared by OTA,

U.S. Congress (Washington, D. C.: in press, 1980).

This study is basically a cost analysis of alternative

methods to deliver respiratory therapy. The authors describe the technology of respiratory therapy, the indications for the use of each type of therapy, and the substitutability of different modalities. The authors also review the

literature on effectiveness and conclude that respiratory

therapy’s efficacy and effectiveness has not been adequately proven and is still in dispute.

The paper describes an empirical survey which the authors undertook in the metropolitan Washington, D. C.,

area. Using data from that survey, the authors chart the

utilization of respiratory therapy techniques by type of

hospital and by number of beds. They also chart the trends

in use from 1976 to 1979, noting a shift from the more expensive high-technology oriented therapy (IPPB) to the less

expensive simpler aerosols and spirometers.

In their cost analysis, the authors compare each type of

therapy with another. Cost savings of the shift in technology are estimated. By focusing on a cost comparison analysis, the authors implicitly assumed that efficacy and effectiveness across therapies are constant. The costs of one

therapy are compared with those of the others.

The adequacy of efficacy and effectiveness information

is addressed (and found to be inadequate). Specific benefits

and effectiveness are not identified, measured, or valued.

Costs are distinguished from charges, and “avoidable,” or

incremental costs are identified. The indirect costs (lost

production) are not identified. Discounting is not used

(costs are incurred in the present, future benefits are not

projected). Sensitivity analysis is not used, and issues of

equity are not addressed. Public policy considerations are

discussed.

Schoenbaum, S., et al., “Benefit-Cost Analysis of

Rubella Vaccination Policy, ” N. Eng. J. Med. 294:

306, Feb. 5, 1976.

The authors estimate the costs and benefits of various

rubella vaccination strategies, each at 100- and 80-percent

compliance. Benefits are the savings that result from the

prevention of both acute rubella and congenital rubella.

The direct costs of rubella (and hence the direct cost savings from prevention) are the costs of medical care, medication or special devices, and special education or rehabilitation. Indirect costs result from temporary disability during acute illness and complications, in addition to deaths

from purpura or encephalitis, and from permanent disability that results from congenital rubella syndrome. The

costs of rubella vaccination were estimated on the basis of

the cost of measles vaccination. Vaccination at ages 10 to

12 appears preferable to vaccination at ages 1 to 3 for two

reasons: 1 ) because the gap between vaccinating and realizing benefits from prevention of congenital rubella is

shorter the closer vaccination is to childbearing; and 2)

because the net benefits of preventing congenital rubella

are greater than those associated with preventing acute

rubella infection. The latter reason was demonstrated by

employing conservative assumptions: Only the most obvious abnormalities associated with congenital rubella

were included in the analysis, and the number of clinical

cases of acute rubella was probably overestimated.

The results indicate that the economic benefits of a

rubella vaccination program, assuming 100-percent compliance, are greater if offered once to females at age 12

rather than to children of both sexes at age 6 or younger. If

compliance is 80-percent instead, the least number of

babies with congenital rubella will be born when vaccination is offered twice, once to children of both sexes at the

age of 2 and again to females at the age of 12. Finally, the

analysis indicates that if the vaccine is to be offered to

children at or before age 2, it is more effective to use combined measles and rubella vaccine.

A 6-percent discount rate is used throughout the analysis, with no sensitivity testing done. It is assumed that

complications of rubella vaccination in the age groups

under consideration are negligible. The frequency of rubella infection was estimated on the basis of two serologic

surveys.

Schoenbaum, S., et al., “The Swine-Influenza Decision,” N. Eng. J. Med. 295: 759, Sept. 30,1976.

This CBA examines alternative strategies for a swine influenza vaccination program. The benefits of a vaccination

program are described as the product of the direct and indirect costs that would be incurred in the event of an

epidemic, the probability of an epidemic, and vaccine efficacy. The costs involved in the program include those

associated with vaccine production and administration,

resultant complications, and intangibles. Both private and

public sector programs are examined. The Delphi method

is used to obtain information regarding the probability of

an epidemic, age-specific morbidity and mortality rates for

both total and high-risk populations, vaccine efficacy and

side effects, and vaccine acceptance rates. The net benefits

for three strategies, which vary by age and risk of the

target population, are calculated. The probability of an

epidemic, vaccine efficacy, and vaccine acceptance rates

are subjected to sensitivity analysis. The three strategies

under consideration were found to be sensitive to acceptance rates. The results of the analysis indicate that expected net benefits are not maximized by the vaccination of

everyone over 5 years of age. A policy of orienting the program toward the general adult population can be justified

with low vaccine-administration costs, high vaccine efficacy, and high acceptance rates (59 percent), assuming further that the flu strain represents a potential pandemic.

Otherwise, only high-risk group vaccination is warranted.
A major feature of this study—both in its design and

achievement—is demonstration that a sound, useful analysis can be initiated and completed in a matter of weeks.

Schweitzer, S. O., and Scalzi, C., “The Cost-Effectiveness of Bone Marrow Transplant Therapy and Its

Policy Implications, ” in The Implications of CostEffectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

The study is a CEA of a highly technical and very costly

emerging medical technology. The cost and effectiveness

(lives and years of life saved) data the authors use were empirically derived from the Bone Marrow Transplant (BMT)

Program at the University of California at Los Angeles.

Much of the effectiveness data had been previously published. Quality of life data was collected by a single

observer, a BMT Program nurse.

Patients with aplastic anemia and leukemia were studied. Since there were insufficient resources to allow all

eligible patients into the BMT Program, patients who received transplants were compared to those who were

judged eligible but not selected. The sample sizes were very

small and survival data was limited to 3 years as a result of

the newness of the technology.

Bone marrow transplant procedures are compared to

conventional therapy, as opposed to no treatment, even

though there is no indication that conventional treatment

is efficacious. The cost of transplant procedures is considered to be the incremental—or avoidable—cost above

that what would have been spent anyway.

Efficacy data is empirically derived from the study of patients admitted to the program, extrapolated to normal life

expectancy for “successful” transplants (defined as those

patients still living after 3 years), and compared to the

group of nonselected patients. The production process described and used in the analysis is the one currently in

place (this is an emerging technology).

A wide range of benefits is identified, and an attempt is

made by the authors to value and combine quality of life

with projected increase in life. Hospital charges are used

for costs, and incremental costs are identified and included

in the analysis. Indirect costs are also calculated. Discounting is not used for future benefit (years of life saved) valuations. All costs were assumed to occur in the present. Sensitivity analysis is not used. Bone marrow transplantation

is still being employed in a research mode, so equity issues

are mainly relevant to the patient selection process; such

issues are not directly addressed in this study.

The results of the analysis are expressed as a cost-effectiveness ratio (cost per year of life saved). The authors do

not qualify these results by discussing the confidence which

the reader can place in them. An extensive discussion on

the relevance this study has to public policy is presented.

The cost-effectiveness ratios developed for bone marrow

transplant procedures are compared to the cost-effectiveness ratios for other life-saving programs.

Showstack, J. A., and Schroeder, S. A., “The Costs

and Effectiveness of Upper Gastrointestinal EndoScopy, “ in The Implications of Cost-Effectiveness

Analysis of Medical Technology/Background Paper

#2: Case Studies of Medical Technologies, prepared

by OTA, U.S. Congress (Washington, D. C.: in

press, 1980).

This report examines the use of the fiberoptic endoscope

to visualize the upper gastrointestinal (UGI) tract from the

esophagus to the upper portion of the small intestine. The

study covers the effectiveness and economic costs of this

common form of endoscopy. Issues related to evaluating

endoscopy’s benefits and costs are discussed, though no

formal comparison of costs and benefits is undertaken.

The authors describe the technique of endoscopy and the

device used—the fiberoptic endoscope. They briefly touch

on training in the technique and identify the common medical indications for endscopy’s use.

The report discusses the clinical effectiveness of UGI endoscopy, which is used to diagnose conditions of the UGI

tract and to obtain specimens of tissue. The medical indications for use are quite broad and inclusive. Studies of the

diagnostic value of the technique suggest that endoscopy

significantly contributes to the amount of diagnostic information. Very often, however, the medical condition being diagnosed is such that the information gained does not

improve morbidity or mortality for the patient(s).

The authors state that the most common dangers associated with endoscopy are perforation (esophagus or stomach), bleeding, cardiopulmonary effects, and infection.

These complications are relatively rare, yet not insignificant given the large number of endoscopies performed nationally (at least .500,000 each year).

The authors distinguish between the cost of performing

the procedure and the charges for it. Using data from California, they provide a median charge of $240, and by extrapolation, a total national expenditure of $122 million.

Using a hypothetical cost analysis, they then estimate that

the average cost to a physician for performing a routine

procedure ranges from $41 to $83.

The study addresses issues in evaluating benefits and

costs of endoscopies. The authors point out the difficulties

of adequately estimating the value of a diagnostic procedure such as endoscopy. They cite the difficulties of conducting a clinical trial ethically when conditions such as

gastric cancer are involved. They also cite other difficulties, such as problems in extrapolating from the results of

clinical trials in the event that such trials were conducted.

The authors maintain that cost-effectiveness studies would

be limited in their usefulness because of these difficulties in

assessing benefits. Though theoretically possible, measurements of costs and benefits are unlikely since such measures cannot realistically be made sensitive enough to provide an accurate and useful assessment for decisionmakers.

The authors also discuss the use of endoscopy and policy

considerations, such as incentives leading to its use and the

regulatory issues involved. Finally, the need for increased

investigation of more narrowly defined indications for use

of endoscopy is discussed.
Stange, P., and Sumner, A., “Predicting Treatment

Costs and Life Expectancy for End-Stage Renal Disease, ” N. Eng. J. Med. 298: 372, Feb. 16, 1978.

The objectives of this analysis are to predict the future

medical care costs and life expectancy of patient cohorts in

facility dialysis, home dialysis, and cadaveric transplantation over the next decade and to estimate the cumulative

effect on costs and life expectancy of successive 1,000-

patient cohorts, changing methods of treatment in each of

the 10 years. Three treatment transition options are evaluated: 1 ) facility dialysis to home dialysis, 2) facility dialysis

to cadaveric transplantation, and 3) home dialysis to cadaveric transplantation. Both costs and life expectancy are

discounted at a rate of 7 percent, which is not subjected to

sensitivity analysis. The 10-year survival and cost estimates are obtained through linear extrapolation of recent

data trends. The experience of the cadaveric-transplantation cohort is predicted for two survival-rate assumptions. The low assumption is based on rates reported in

1976, and the high assumption is an estimate of the average

survival rates that will be experienced nationally over the

next 10 years. The results of the first phase of the analysis

indicate that, over the next decade, each of the dialysis

cohorts is predicted to have more added years of life than

the transplantation group. Though the predicted number

of life-years for both forms of dialysis is approximately

equal over the 10-year period, treatment for the home-dialysis cohort will cost about $43 million less than that for the

facility-dialysis cohort. Transplantation is less costly than

both forms of dialysis.

The second phase of the analysis indicates that undergoing home dialysis instead of facility dialysis (the first option) provides approximately the same life expectancy, but

at 34 percent lower costs. The second option, moving from

facility dialysis to transplantation, also results in a substantial reduction in costs, but there is an accompanying

reduction in life expectancy as well. The third option,

moving from home dialysis to transplantation, has results

similar to those of the second option. The authors conclude

that while it is clear that there are potential savings to

society from public policies that encourage patients who

are able and willing to shift from facility to home dialysis,

an evaluation of the two dialysis-to-transplant options is

ambiguous. Transplantation is less costly than dialysis

over the 10-year period, but attention must also be paid to

the impact of the shift in life expectancy. No cost-effectiveness ratios are presented. The authors caution that the intent of their analysis is not to promote any specific form of

treatment, but rather to provide information, such as the

relative magnitude of the “tradeoffs” between cost reduction and life expectancy in each of the treatment options.

Stason, W. B., and Fortess, E., “Cardiac Radionuclide Imaging and Cost-Effectiveness, ” in ‘The implications of Cost-Effectiveness Analysis of Medical

Technology/Background Paper #2: Case Studies of

Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

The authors of this analysis examine a considerable

range of issues that deal with the recent growth and expanded use of cardiac radionuclide imaging technology in

the health care field. The areas they address are the present

and potential future characteristics of the technology; the

market for and industry involvement in cardiac imaging

innovations; the uses and users of these procedures; the

clinical efficacy and risks associated with the techniques;

the costs and charges of imaging technology use; and the

cost effectiveness of these procedures in different service

delivery situations.

The authors point out that much of the rapid diffusion

and use in this area is taking place without a well-grounded

understanding of the benefits and limitations of the various

scanning techniques. To date, only very selected patient

populations have been evaluated out of a much broader

spectrum of uses and techniques available and in use. Adding to the uncertainty are the rapid technological changes

that are occurring and the poorly defined target population

for cardiac scans.

Using the various suggested clinical indications and uses

as a backdrop, the authors estimate that the potential

target population for cardiac imaging could be 134 million

people per year if all asymptomatic people 20 years old

and over were scanned, 70.8 million people per year if

routine screening were limited to those 40 and over, and

11.7 million people per year if scans were restricted to people with suspected or established coronary heart disease.

The study looked at these direct nonlabor costs (equipment, maintenance, radionuclides, etc.), direct labor costs

(personnel needs, training, support staff), and indirect

costs (overhead) to estimate the financial costs of cardiac

scanning services. The authors estimate the annual fixed

costs of a model radionuclide laboratory to be $112,300 for

the complete service, with the costs of the various individual procedures ranging from $258 to $72 (there are

nine different types of procedures and two different types

of radionuclide testing materials involved in the range of

procedures available). Significant variations exist across

the country regarding the charges for the various procedures. Nomenclature and billing procedures/listings are

not comparable from hospital to hospital. As a result, it is

extremely difficult to determine if there is a relative standard or range of charges for these techniques. The authors

developed a set of suggested fee schedules for these procedures that range from $405 to $155 per scan.

The medical literature is examined to determine if there

is a proper role for scanning techniques. The authors examine extant studies to determine what types of sample

populations have been used, the reference or control

groups used, the technical and medical standards against

which radionuclide procedures were judged, and the clinical settings in which the studies were conducted. In addition, the authors examine the risks associated with these

procedures—both to the health care professionals and the

patients—and assess the value of the diagnostic information that the scans provide to the diagnosis or the understanding of the extent of the disease and its response to

treatment.

The authors fit the many variables into a cost-effectiveness framework to conduct a limited analysis of cardiac

imaging procedures. No discount rate is employed (the

benefit, costs, and risks occur in the present), nor is a sensi-
tivity analysis performed. The conclusion is that “decision

strategies based on threshold cutoff probabilities of a given

disease(s) are cost effective compared to blanket testing

. . . and that use of cardiac imaging appears to identify additional surgical candidates at reasonable cost when compared to exercise tolerance testing, ” The reasonableness of

these additional costs will depend, to a large extent, on the

incremental health benefits achieved by coronary artery

surgery.

The authors identify many of the policy issues raised by

this emerging technology. A few of the areas they discuss

are issues of reimbursement, safety and efficacy determination, disposal of the radionuclide wastes, clinical standards

and indications for use, allocation of resources, and responsibility for regulation and diffusion of these procedures throughout the medical community.

Stason, W., and Weinstein, M., “Allocation of Resources To Manage Hypertension, ” N. Eng. J. Med.

296: 732, Mar. 31, 1977.

CEA is applied to the management of essential hypertension to “determine how resources can be used most efficiently within programs to treat hypertension and to provide a yardstick for comparison with alternative health-related uses of the resources. ” Costs of treatment consist of

the lifetime costs of hypertension treatment, costs of treating diseases that occur during additional years of life

gained by antihypertensive treatment, minus the costs that

would have been incurred for the treatment of cardiovascular morbid events if treatment had not been given. Effectiveness is calculated in terms of increased years of life expectancy from blood-pressure control, adjusted for

changes in the quality of life due to the prevention of morbid events and to the side effects of medication. The analysis is performed under three alternative assumptions concerning the proportional reduction of risk of cardiovascular events and death associated with the reduction of blood

pressure due to treatment: 1) full benefit, 2) half benefit,

and 3) age-varying partial benefit.

One year of life with side effects is taken to be the equivalent of 0.99 quality-adjusted life years. A 5-percent discount rate is used throughout the analysis. Sensitivity

analysis is performed on several critical variables, including the discount rate, medical treatment costs, and the

quality-of-life adjustment. In addition, the effects of incomplete adherence to the treatment regimen are

examined.

The results of the analysis indicate that in no case does

treatment pay for itself. At best, only 22 percent of gross

treatment costs, on average, can be recovered from savings

in the treatment of strokes and heart attacks. However, the

analysis also indicates that, in terms of effectiveness, funds

spent to improve adherence may be a better use of resources than efforts to screen a maximum number of

subjects.

Steiner, K., and Smith, H., “Application of Cost

Benefit Analysis to a PKU Screening Program, ” Inquiry 10:34, December 1973.

The authors compare and contrast the techniques of

CBA and CEA, stating that although equally sound decisions may be reached by either method, one of the two is

usually better suited for a particular problem. The authors

believe that CBA is the best approach for screening programs, and it is this technique that they subsequently use in

evaluating a PKU screening program in Mississippi. (PKU

is a hereditary condition which causes mental retardation

if not detected and treated with a dietary regimen early in

life. )

The costs associated with PKU are classified as direct

and indirect. Direct costs are defined in this study as the actual expenditures for medical and other services attributable to the disease. Indirect costs are defined as a loss of

economic productivity attributable to the disease. These

costs serve to measure the benefits of a successful prevention program. The analysis is performed from both a retrospective and a prospective point of view. The retrospective

approach measures the costs of the current population with

PKU and estimates what the costs of screening, detecting,

and treatment would have been. For this study, the direct

costs associated with PKU are estimated using data from

three mental institutions in Mississippi. Indirect costs are

measured by the loss of income, under the assumptions

that the PKU victim remains incapacitated for life. Detection costs are based on estimates of the incidence of PKU,

The retrospective analysis indicates that the total costs of

institutionalization and lost earnings associated with the

current Mississippi population with PKU (25 patients)

amount to $2,314,595. The costs of detecting and treating

the 25 patients are estimated at $1,392,668, yielding a costto-benefit ratio of 1 to 1.66.

The prospective method calculates the cost of screening

all live births in a given year to treating those found to be

suffering from PKU. In this study, these calculations are

based on the 1967 live births in Mississippi. Testing the

46,714 live births that year would have detected an average of 1.76 PKU cases. The costs associated with these

cases amount to $135,062, if the minimum expected length

of institutionalization (30 years) is assumed, or $256,418,

if institutionalization is assumed to cover the normal life

expectancy of a l-year-old child born in 1967 (70.8 years).

Program costs are estimated at $98,518, yielding cost-benefit ratios of 1 to 1.37 and 1 to 2.6, respectively. The

authors state that in all calculations, the detection costs are

high and the total illness costs (i.e., possible benefit) are

low in order to produce conservative results. A discount

rate of 4 percent is applied to the lost earnings data, but not

to direct or detection costs. Other than varying the length

of institutionalization in calculating the prospective costbenefit ratios, the authors do not perform sensitivity

analysis.

Van Pelt, A., and Levy, H., “Cost-Benefit Analysis

of Newborn Screening for Metabolic Disorders, ” N.

Eng. J. Med. 291:1414, Dec. 26,1974 .

This article examines the costs and benefits of a Massachusetts program designed to detect inborn errors of metabolism and transport in newborn infants. The costs,

based on a survey of all hospitals with obstetric and newborn units in Massachusetts, include those for routine specimen collection, laboratory analysis, the collection of additional specimens, confirmatory testing, and followup care
Appendix C–Abstracts of Selected Entries From the Bibliography on CEA/CBA ● 117

and therapy. For fiscal year 1972-73, these costs amounted

to $460,638. Benefits are calculated as the estimated savings from the prevention of mental retardation and other

complications. For 1972-73, estimated total savings

amounted to $825,300, yielding a net benefit of $364,662

or a benefit-cost ratio of nearly 1.8. Indirect costs of

metabolic disorders (such as reduced economic productivity due to disability and premature mortality), which would

also be averted as a result of a screening program, are not

included in the calculation of benefits. Presumably, the inclusion of the present value of such benefits, when considered along with a similar future stream of the other costs

and benefits (also discounted to present value), would

result in even higher net benefits.

Wagner, J. L., “The Feasibility of Economic Evaluation of Diagnostic Procedures: The Case of CT Scanning, ” in The Implications of Cost-Effectiveness

Analysis of Medical Technology/Background Paper

#2: Case Studies of Medical Technologies, prepared

by OTA, U.S. Congress (Washington, D. C.: in press

1980).

This study examines the appropriate methodology of

CEA/CBA for diagnostic procedures. Following the development of a framework for analysis, the author reviews

the literature of the cost effectiveness of CT scanning,

critically evaluating it in terms of the evaluation model.

The author describes a theoretical “ideal” evaluative

model in which the analysis compares alternative diagnostic pathways, each of which begins with the presentations

of signs and symptoms and ends with patient outcomes.

The purpose of the evaluation is not to examine the technology per se, but rather to evaluate its appropriate use.

The author describes the need for an appropriate means to

1) identify homogeneous patient groups, 2) specify diagnostic pathways, 3) measure diagnostic accuracy, 4) measure diagnostic and therapeutic costs, and 5) specify outcomes of the diagnostic and therapeutic process.

In a review of the literature on the economic impact of

CT scanning, only one study that attempted to specify diagnostic pathways was identified. Most of the other studies

examined the impact CT has on diagnostic costs or examined the cost of case finding.

Efficacy information is addressed both for diagnostic

studies in general and for CT scanners in particular. Comments regarding the potential benefits associated with negative findings are also included.

Costs are distinguished from charges; marginal, or

avoidable, costs are recommended; the difficulty of capturing true costs is discussed extensively. Indirect costs are not

considered. Discounting was not specifically discussed, except within the context of the reviewed case studies; where,

in one, future benefits were discounted. Equity issues were

not addressed.

Despite major limitations in applying principles of economic evaluation to diagnostic procedures, such evaluations are feasible. For CT scanning, when sufficient demand exists to operate a scanner at full capacity, some

specific uses appear to be cost effective.

Weinstein, M., “Economic Evaluation of Medical

Procedures and Technologies: Progress, Problems,

and Prospects, “ in Medical Technology, proceedings

of the Urban Institute Conference, NationaI Center

for Health Services Research, West Palm Beach, Fla.,

Dec. 10-12, 1978.

This paper presents a state-of-the-art assessment of CBA

and CEA of medical procedures. CBA/CEAs are defined

and distinguished from each other. The author advocates

the use of a multiattribute accounting framework, in conjunction with CEA and CBA, in which unquantifiable concerns, such as equity and ethical issues, are considered

along with the traditional, measurable impacts. The basic

methodological principles are reviewed, including estimation of event rates, sensitivity analysis, choosing a discount rate, measurement of costs, and measurement of

benefits. The controversy surrounding the assignment of

monetary value to life saving and health improvement in

CBA is discussed.

A review of selected applications, classified as treatment, secondary prevention, screening, and immunization, is presented. The author states that diagnostic procedures other than screening have not received much attention, in part because of methodologic obstacles. He predicts that technology evaluation will be the area where the

next major advances in CEA and CBA will develop. He

then discusses current methodologic problems, classified as

1) the valuation of multiattributed outcomes, 2) the evaluation of diagnostic tests, 3) the evaluation of multifaceted

technologies, and 4) uncertainty concerning efficacy, costs,

and ultimate uses of evolving technology.

The paper concludes with a generally optimistic assessment of the prospect for CEA and CBA in medical care and

for overcoming the current methodological problems. The

author recommends a multidisciplinary approach to analysis, including the expertise of physicians, engineers, and

economists. He notes that the value of formal economic

analysis lies not so much in the actual results, but rather in

the ability of such analysis to highlight uncertainty and the

most important value tradeoffs involved in alternative

policies.

Weinstein, M. C., and Pearlman, L. A., “Case Study

on Cost-Effectiveness of Automated Multichannel

Chemistry Analyzers, ” in The Implications of CostEffectiveness Analysis of Medical Technology/Background Paper #2: Case Studies of Medical Technologies, prepared by OTA, U.S. Congress (Washington, D. C.: in press, 1980).

This study illustrates the possible techniques for evaluating the cost effectiveness of automated multichannel chemistry analyzers. The authors also examine and discuss the

limitations due to data deficiencies, areas for future research, and influences of clinical practice on the evaluation

of such analyzers.

The case study briefly reviews the history of the multichannel clinical chemistry technology and presents an analytical framework for evaluating the cost effectiveness of

the multichannel analyzer. The authors review the available data concerning the costs of multichannel chemistry

67-774 0 - 80 - 9
analyzers and examine the evidence concerning the cost effectiveness of using the cardiac enzymes and isoenzymes in

the diagnosis of myocardial infarction.

The paper discusses several important issues related to

the clinical efficacy and cost effectiveness of clinical laboratory chemical tests. A prominent example of such an

issue is the potential influences on physicians’ test-ordering

behavior that may be induced by the availability of multichannel analyzers.

Various types of automated multichannel chemistry

analyzers could be compared to one another under specified circumstances. Continuous flow models, for example,

could be compared to discrete sample models and even single channel models to find the most cost-effective method

of running specific cardiac enzyme tests. The study also

discusses the cost effectiveness of using automated multichannel chemistry analyzers to obtain laboratory values as

compared to not obtaining that laboratory value at all.

Further, the authors advocate comparing the efficiency of

using the automated multichannel chemistry analyzers

under varying workloads (i. e., the number of tests performed per unit of time).

The study addresses the adequacy—or inadequacy—of

efficacy information. As usual, such information is not

plentiful; studies designed to produce efficacy data are underway. The authors discuss alternative ways to use the

technology in various forms to produce the greatest degree

of efficiency. The authors also discuss the variability of

benefits resulting from use of automated multichannel

chemistry analyzers. Potential benefits are described from

a societal perspective and include potential reduced costs

from reduced incidence of unnecessary hospitalization resulting from more accurate diagnostic and monitoring testing. Health benefits would be measured in quality-adjusted

life years.

Costs are distinguished from charges, and several direct

costs are identified, including those for nonlabor (e. g.,

equipment, service and maintenance, reagents, and consumables) and labor. Fixed, variable, and induced costs are

all addressed. The authors state that indirect costs have not

been adequately studied and may not be extensively affected by automated analyzers. Discounting would be included in analyses described in this case study, as would

the use of sensitivity analysis. The extent to which sensitivity analysis would be used is not explained explicitly.

Data results are not derived from this case study; however, the many different ways the CEA could be conducted

are discussed. Each different approach would yield results

of a different meaning; hence several caveats would be

needed for each approach and set of results.

The authors discuss the potential public policy implications of this analysis which could affect reimbursement

policies regarding laboratory tests, the use of automated

analyzers by hospitals and physicians, and the design of

equipment by manufacturers. No conclusions regarding

the cost effectiveness of automated multichannel chemistry

analyzers can be drawn from this study. The study was not

designed to be an actual assessment; rather, it was intended to illustrate how a CEA of automated analyzers

could be performed.

Weinstein, M. C., and Stason, W., “Foundations of

Cost-Effectiveness Analysis for Health and Medical

Practices, ” N. Eng. J. Med. 296: 716, Mar. 31, 1977

This article presents principles of CEA as applied to the

allocation of health care resources. The authors caution

that in conducting an analysis, the objectives of the actual

decisionmaker may be more relevant than the societal

point of view. Whenever possible, measures of effectiveness should be expressed in outcome-oriented terms, such

as length of life and quality of life. Tradeoffs between present and future health benefits and costs, and hence the use

of discounting, are discussed. Net health care costs are expressed as the sum of costs associated with treatment, side

effects, and increased longevity less the savings from

decreased morbidity. Net health effectiveness is expressed

as the expected number of quality-adjusted life years

gained, calculated as the expected number of unadjusted

life years, adjusted for improvements in the quality of life

due to the alleviation or prevention of morbidity and side

effects of treatment. Sensitivity analysis is described, and

its use is recommended whenever uncertainty is involved

in the estimation of key variables (e. g., discount rates,

clinical efficacy, prevalence, etc. ). The article ends with a

discussion of the value and application of CEA in health

care and concludes that its principle value is that it forces

one to be explicit about the beliefs and values that underlie

allocation decisions.

Weisbrod, B., “Costs and Benefits of Medical Research: A Case Study of Poliomyelitis, ” J. Polit.

Econ. 79: 527, May-June 1971.

This CBA of poliomyelitis research uses and expands on

the benefit calculations first presented in Weisbrod’s The

Economics of Public Health (578). These calculations comprise savings from avoided premature mortality, morbidity, and treatment and rehabilitation costs. The analysis requires an estimation of 1) the time stream of research expenditures directed toward poliomyelitis, 2) the time

streams of a number of forms of benefits resulting from (or

predicted to result from) the application of the knowledge

generated by the research, and 3) the cost of applying that

knowledge.

Using this information, Weisbrod calculates internal

rates of return on research expenditure. Savings per case

prevented, application costs, the time horizon, and research expenditures are all subjected to sensitivity analysis.

The internal rates of return were found to be sensitive to

application costs, varying from 4 to 14 percent. In approximating present value of expenditures and benefits, Weisbrod uses a discount rate of 10 percent. No sensitivity analysis is performed on this variable. The difficulties encountered in trying to associate specific medical research

expenditures with a particular disease are discussed. These

Include the fact that basic research is often not directed at a

specific disease problem and even disease-specific research

frequently yields knowledge relevant to the prevention or

treatment of other diseases. The data used here are estimates of awards for poliomyelitis research from 1930 to

“1956. Weisbrod stresses the need to include the costs in-
volved in the application of new medical knowledge, as

well as the costs of generating it, when attempting to comprehensively analyze a medical research program.

The article concludes with an interesting discussion of

the impact on private market allocative efficiency when a

collective consumption good (e. g., medical research) requires for its application a procedure such as vaccination

which is provided individually and from which nonpayers

may be excluded. Weisbrod also discusses the effects of externalities on the provision of medical research and its application for contagious diseases. The author concludes

that when collective consumption goods require use of individual consumption goods for their application, and

where these individual goods produce real external economies, neither the nature nor the extent of private market inefficiency is clear.

Witte, J., et al., “The Benefits From 10 Years of

Measles Immunization in the United States, ” Public

Health Rep. 90: 205, May-June 1975.

For the 10-year period 1963-72, the authors estimate the

costs the Nation would have sustained without measles immunization (i. e., the benefits of measles immunization)

and the actual costs of measles during that period in terms

of illness and associated resources consumed. The research

costs of developing and testing the measles vaccine are not

included because of the difficulty in identifying them and

in determining the share applicable to the United States in

the period under consideration.

The benefits associated with the measles immunization

program considered in this analysis include 1 ) savings in

medical care costs for services of physicians and for longterm institutional care for those who would have become

retarded, and 2) avoidance of production losses due to

morbidity and premature mortality. Program costs are

those incurred in vaccine production, distribution, administration, and promotion. The analysis concludes that the

net benefits achieved through immunization in the United

States totaled $1.3 billion for the period 1963-72. A single

discount rate of 4 percent is used. The authors assume that

the national immunization effort had no significant effect

on the demand for medical care or on the size and composition of the labor force.
Appendix D.— Description of

Other Volumes of the Assessment

The overall OTA assessment, The Implications of

Cost-Effectiveness Analysis of Medical Technology,

consists of a main, policy-oriented report plus five

background papers. The present volume, Methodological Issues and Literature Review, is one of the

background papers. The main report and the other

background efforts are briefly described below.

The main report examines three major issues: 1)

the general usefulness of CEA/CBA in decisionmaking regarding medical technology, 2) the methodological strengths and shortcomings of the technique,

and 3) the potential for initiating or expanding the

use of CEA/CBA in six health care programs (reimbursement coverage, health planning, market approval for drugs and medical devices, Professional

Standards Review Organizations, R&D activities,

and health maintenance organizations), and most importantly, the implications of any expanded use.

The prime focus of the report is on the application

of CEA/CBA to medical technology (i. e., the drugs,

devices, and medical and surgical procedures used in

medical care, and the organizational and support systems within which such care is provided). With the

exception of a background paper on psychotherapy,

the report does not address psychosocial medicine,

Other aspects of health, such as the environment, are

not directly covered either. The findings of the assessment, though, might very well apply to health

care resource decisionmaking in general, and with

modification, to other policy areas such as education, the environment, and occupational safety and

health.

The main report contains chapters on methodology, general decisionmaking, each of the six health

programs mentioned above, and the general usefulness of CEA/CBA. It contains appendixes covering a

survey of current and past uses of CEA/CBA by

agencies (primarily Federal), a survey of the resource

costs involved in conducting CEA/CBAs, a discussion of ethical issues and CEA/CBA, and a brief discussion of legal issues.

In order to help examine the applicability of techniques to assess the costs and benefits of medical

technology, 19 case studies were prepared. All 19 are

available individually. In addition, 17 of the cases are

available collectively in a volume entitled Background Paper #2: Case Studies of Medical Technologies. Some of the cases represent formal CEAs (e. g.,

the case on bone marrow transplants), and some represent net cost or “least cost” analysis (e. g., the case

on certain respiratory therapies). Other cases illustrate various issues such as the difficulty of conducting CEA in the absence of adequate efficacy and safety information (e.g., the case on breast cancer surgery), or the role and impact of formal analysis on

policymaking (e.g., the case on end-stage renal disease interventions). The 17 case studies in Background Paper #2 and their authors are:

Artificial Heart

Deborah P. Lubeck

John P. Bunker

Automated Multichannel Chemistry Analyzers

Milton C. Weinstein

Laurie A. Pearlman

Bone Marrow Transplants

Stuart O. Schweitzer

C. C. Scalzi

Breast Cancer Surgery

Karen Schachter

Duncan Neuhauser

Cardiac Radionuclide Imaging

William B. Stason

Eric Fortess

Cervical Cancer Screening

Bryan R. Luce

Cimetidine and Peptic Ulcer Disease

Harvey V. Fineberg

Laurie A. Pearlman

Colon Cancer Screening

David M. Eddy

CT Scanning

Judith L. Wagner

Elective Hysterectomy

Carol Korenbrot

Ann B’. Flood

Michael Higgins

Noralou Roos

John P. Bunker

End-Stage Renal Disease Interventions

Richard A. Rettig

Gastrointestinal t Endoscopy

Jonathan A. Showstack

Steven A. Schroeder

Neonatal Intensive Care

Peter Budetti

Peggy McManus

Nancy Barrand

Lu Ann Heinen

120
Nurse Practitioners

Lauren LeRoy

Orthopedic Joint Prosthetic Implants

Judith D. Bentkover

Philip G. Drew

Periodontal Disease Interventions

Richard M. Scheffler

Sheldon Rovin

Respiratory Therapy

Richard M. Scheffler

Morgan Delaney

The 18th case study is published separately as

Background Paper #3: The Efficacy and Cost-Effectiveness of Psychotherapy. That study assesses methodological and substantive issues relating to the

scope of psychotherapy, the evaluation of psychotherapeutic efficacy, and the applicability of CEA/

CBA in assessing psychotherapy. It was prepared by

Leonard Saxe on the basis of a report prepared for

OTA by Brian Yates and Frederick Newman. The

19th case study was prepared by Judith Wagner and

is published separately as Background Paper #5: Assessment of Four Common X-Ray Procedures.

Background Paper #4: The Management of Health

Care Technology in Ten Countries is an analysis of

the policies, programs, and methods, including costeffectiveness and cost-benefit techniques, that nine

industrialized nations other than the United States

use to manage the effects of medical technology. The

experience of these nine countries in managing medical technology is compared to that of the United

States. The paper on the United States and the comparative analysis were prepared by OTA staff, assisted by Louise Russell. The authors of the papers on

the nine foreign countries are:

United Kingdom

Barbara Stocking

Canada

Jack Needleman

Australia

Sydney Sax

Japan

Joel Broida

France

Rebecca Fuhrer

Germany

Karin A. Dumbaugh

Netherlands

L.M.J. Groot

Iceland

David Gunnarson

Duncan vB. Neuhauser

Sweden

Erik H. G. Gaensler

Egon Jonsson

Duncan vB. Neuhauser

A related report prepared by OTA and reviewed

by the Advisory Panel to the overall assessment is A

Review of Selected Federal Vaccine and Immunization Policies. That study, published in September of

1979, examined vaccine research, development, and

production; vaccine efficacy, safety, and cost-effectiveness; liability issues; and factors affecting the use

of vaccines. Pneumococcal vaccine was used as a

case study, and a CEA/CBA was performed.
Appendix E.— Health Program Advisory Committee,

Authors of Case Studies of Medical Technologies

(Background Papers #2, #3, and #5)

HEALTH PROGRAM ADVISORY COMMITTEE

Frederick C. Robbins, Chairman

Dean, School of Medicine, Case Western Reserve University

Stuart H. Altman

Dean

Florence Heller School

Brandeis University

Robert M. Ball

Senior Scholar

Institute of Medicine

National Academy of Sciences

Lewis H. Butler

Health Policy Program

University of California, San Francisco

Kurt Deuschle

Professor of Community Medicine

Mount Sinai School of Medicine

Zita Fearon

Consumer Commission on the Accreditation of

Health Services, Inc.

Rashi Fein

Professor of the Economics of Medicine

Center for Community Health and Medical Care

Harvard Medical School

Melvin A. Glasser

Director

Social Security Department

United Auto Workers

AUTHORS OF CASE STUDIES OF

Nancy Barrand

Health Policy Program

University of California, San Francisco

Judy Bentkover

Arthur D. Little, Inc.

Peter Budetti

Health Policy Program

University of California, San Francisco

Patricia King

Professor

Georgetown Law Center

Sidney S. Lee

Associate Dean

Community Medicine

McGill University

Mark Lepper

Vice President for Znter-institutional Affairs

Rush-Presbyterian Medical School

St. Lukes Medical Center

Frederick Mosteller

Professor and Chairman

Department of Biostatis tics

Harvard University

Beverlee Myers

Director

Department of Health Services

State of California

Mitchell Rabkin

General Director

Beth Israel Hospital

Kerr L. White

Rockefeller Foundation

MEDICAL TECHNOLOGIES

John P. Bunker

Division of Public Services Research

School of Medicine

Stanford University

Morgan Delaney

School of Medicine

George Washington University

Philip G. Drew

Arthur D. Little, Inc.
David Eddy

Department of Engineering-Economics Systems

Stanford University

Harvey V. Fineberg

School of Public Health

Harvard University

AnnB. Flood

School of Medicine

University Of Illinois

Eric Fortess

School of oPublic Health

Harvard University

Lu Ann Heinen

Health Policy Program

University of California, San Francisco

Michael Higgins

Division of Health Services Research

Stanford University

Carol Korenbrot

Health Policy Program

University of California, San Francisco

Lauren LeRoy

Health Policy Program

University of California, San Francisco

Deborah P. Lubeck

Division of Health Services Research

Stanford University

Bryan R. Luce

Office of Technology Assessment

Congress of the United States

Peggy McManus

Health Policy Program

University of California, San Francisco

Lawrence Miike

Office of Technology Assessment

Congress of the United States

Duncan Neuhauser

School of Medicine

Case Western Reserve University

Frederick Newman

Systems Research Unit

Eastern Pennsylvania Psychiatric institute

Laurie A. Pearlman

School of Public Health

Harvard University

Richard A, Rettig

The RAND Corp.

Noralou Roos

Faculty of Medicine

University of Manitoba

Sheldon Rovin

School of Dental Medicine

University of Pennsylvania

Leonard Saxe

Department of Psychology

Boston University

C. C. Scalzi

School of Public Health

University of California, Los Angeles

Karen Schachter

School of Public Health

Harvard University

Richard M. Scheffler

Department of Economics

George Washington University

Steven A. Schroeder

Health Policy Program

University of California,

Stuart O. Schweitzer

School of Public Health

University of California,

Jonathan A. Showstack

Health Policy Program

University of California,

William B. Stason

School of Public Health

Harvard University

Judith L. Wagner

The Urban Institute

Milton C. Weinstein

School of Public Health

Harvard University

Brian T. Yates

San Francisco

Los Angeles

San Francisco

Department of Psychology

The American University
Other References
Other References

701.

702.

703.

704.

705.

706.

707.

708.

709.

710.

711.

712.

Anderson, J. P., et al., “Performance Versus

Capacity: A Conflict in Classifying Function

for Health Status Measurement, ” paper presented at the Annual Meeting of the American

Public Health Association, Washington, D. C.,

Nov. 2, 1977.

Arthur D. Little, Introduction to Cost-Benefit

Analysis Applied to Health Technologies, I-IRA

230-75-0063 (Hyattsville, Md.: Health Resources Administration, December 1977).

Association of American Medical Colleges,

“Cost Containment Educational Efforts—

United States Medical Schools, ” Washington,

D.C. : AAMC, 1978.

Banta, H. D., “The Diffusion of the Computed

Tomography (CT) Scanner in the United

States, ” Int. J. Health Serv. 10(2):251, 1980.

, and Thacker, S. B., “Policies Toward

Medical Technology: The Case of Electronic

Fetal Monitoring, ” Am. J. Public Health 69(9):

93I, September 1979.

Baumol, W. J., “On the Social Rate of Discount, ” J. Am. Econ.. Assoc. 58(4):788, September 1968.

Bergner, M., et al., “The Sickness Impact Profile: Conceptual Formulation and Methodology

for the Development of a Health Status Measure,” Int. J. of Health Serv. 6:393, 1976.

, et al., “The Sickness Impact Profile:

Validation of a Health Status Measure, ” Med.

Care 14:57, 1976.

Berry, C. C., and Bush, J. W., “Estimating

Prognoses for a Dynamic Health Index, the

Weighted Life Expectancy, Using the Multiple

Logistic With Survey and Mortality Data, ” in

Proceedings of the American Statistical Association, Social Statistics Section, Part 11,

(Washington, D. C.: American Statistical Association, 1978).

Blischke, W. R., et al., “A Successive Intervals

Analysis of Social Preference Measures for a

Health Status Index, ” Health Serv. Res. 10(2):

181, summer 1975.

Brook, R. H., et al., “Overview of Adult

Health Status Measures Fielded in Rand’ s

Health Insurance Study, ” Med. Care, Suppl.

17:7, July 1979.

Bush, J. W., et al., “A General Computer Simulation Model for Disease Histories and

Changes in Health Status, ” in Proceedings of

713.

714.

715.

716.

717.

718.

719.

720.

721.

722.

723.

724.

the San Diego Biomedical Symposium, edited

by R. Yoder (San Diego, Calif: The Symposium, 1972).

, et al., “Analysis of a Tuberculin Testing Program Using a Health Status Index, ”

Socio-Econ. Ping. Sci. 6:49, 1972.

, et al., “Comparison of Methods for

Measuring Social Preferences for a Health

Status Index, ” in Proceedings of the American

Statistical Association, Social Statistics Section, Part 11 (Washington, D. C.: The American

Statistical Association, 1978).

, et al., “Estimating Health Program

Outcomes Using a Markov Equilibrium Analysis of Disease Development, ” Am. J. Publi c

Health 61(12):2362, December 1971.

, et al., “Health Indices, Outcomes, and

Quality of Medical Care,” in Evaluation in

Health Services Delivery, edited by R. Yaffe

and D. Zalkind (New York, N. Y.: Engineering

Foundation, 1975).

Chen, M., et al., “Effectiveness Measures, ” in

Operations Research in Health Care—A Critical Analysis, edited by L. J. Shuman, et al.

(Baltimore, Md.: Johns Hopkins University

Press, 1975).

, et al., “Social Indicators for Health

Planning and Policy Analysis, ” Pol. Sci .

6(1):71, March 1975.

Cohon, J. L., Multiobjective Programming and

Planning (New York, N. Y.: Academic Press,

1978) .

Congressional Budget Office, U.S. Congress,

Expenditures for Health Care: Federal Programs and Their Effects (Washington, D. C.:

U.S. Government Printing Office, 1977).

Cooper, B. S., and Rice, D., “The Economi c

Cost of Illness Revisited, ” Soc. Sec. Bull, February 1976.

Crystal, R. A., and Brewster, A. W., “Cost

Benefit and Cost Effectiveness Analyses in the

Health Field: An Introduction, ” inquiry 3(4):3,

1966.

Donabedian, A., “Evaluating the Quality of

Medical Care, ” in Program Evaluation in the

Health Fields, edited by H. C. Schulberg, et al.

(New York, N. Y.: Behavioral Publications,

Inc., 1969).

Donald, C. A., et al., Conceptualization and

Measurement of Health for Adults in the

(app. B).

127
725.

726.

727.

728.

729.

730.

731.

732.

733.

734.

735.

736.

737.

Health insurance Study: Vol. IV, Social

Health, publication No. R-1987/4-HEW, prepared under contract for the Department of

Health, Education, and Welfare (Washington,

D. C.: RAND Corp., August 1978).

Epstein, K., et al., “The ‘Abnormal’ Screening

Serum Thyroxine (T4): Analysis of Physician

Response, Outcome, Cost and Health Effectiveness” (San Diego, Calif.: University of California, Department of Community Medicine

and Pathology, May 29, 1979).

Fanshel, S., and Bush, J. W., “A Health Status

Index and Its Application to Health Services

Outcomes, ” operations Res. 18(6):1021, November-December 1970.

Gilson, B. S., et al., “Revision and Test of the

Sickness Impact Profile 1973-74, ” Department

of Health Services, School of Public Health and

Community Medicine, University of Washington, Seattle, (mimeo) 1974.

, et al., “The Sickness Impact Profile:

Development of an Outcome Measure of

Health Care, ” Am. J. Public Health 65:1304,

1975.

Gramlich, E., University of Michigan, Ann Arbor, Mich., unpublished manuscript on costbenefit analysis.

Jones-Lee, M. W., The Value of Life: An Economic Analysis (Chicago, 111.: University of

Chicago Press, 1976).

Kaplan, R. M., et al., “Health Status Index:

Category Rating versus Magnitude Estimation

for Measuring Levels of Well-Being, ” Med.

Care, in press, May 1979.

, et al., “Health Status: Types of Validity for an Index of Well-Being, ” Health Serv.

Res. 11(4):478, winter 1976.

, et al., “The Reliability, Stability, and

Generalizability of a Health Status Index, ” in

Proceedings of the American Statistical Association, Social Statistics Section, Part II (Washington, D. C.: American Statistical Association, 1978).

Kavet, J., “A Perspective on the Significance of

Pandemic Influenza, ” Am. J. Public Health

67(11):1063, November 1977.

Krischer, J. P., “An Annotated Bibliography of

Decision Analytic Applications to Health

Care, ” Oper. Res. 28:1, January-February

1980.

McNeil, B. J., et al., “The Fallacy of the Five

Year Survival in Lung Cancer, ” N. Eng. J. Med.

299:1397, 1978.

Mishan, E. J., “Evaluations of Life and Limb, ”

J. Pol. Ec. 79(4):687, 1971.

738.

739.

740.

741,

742.

743.

744.

745.

746.

7478

748.

749.

750.

751.

Murnaghan, J. H., “Health Indicators and Information Systems for the Year 2000,” School

of Hygiene and Public Health, Johns Hopkin

University, (draft), January 1980.

Office of Technology Assessment, U.S. Congress, Cancer Testing Technology and Saccharin, GPO stock No. 052-003 -00471-2 (Washington, D. C.: U.S. Government Printing Office,

October 1977).

U.S. Congress, Selected Topics in Federal Health Statistics, GPO stock No. 052-

003-00683-9 (Washington, D. C.: U.S. Government Printing Office, June 1979).

Patrick, D. L., et al., “Methods for Measuring

Levels of Well-Being for a Health Status Index,” Health Serv. Res. 8(3):228, Fall 1973.

, et al., “Toward an Operational Definition of Health, ” J. Health and Social Behavior

14(1):6, March 1973.

Public Health Service, Office of the Assistant

Secretary for Health and Surgeon General,

Healthy People: The Surgeon General’s Report

on Health Promotion and Disease Prevention,

GPO stock No. 017-001 -00416-2 (Washington,

D. C.: U.S. Government Printing Office, 1979).

Quade, E. S., Analysis for Public Decisions

(New York, N. Y.: American Elsevier Publishing Co., 1975).

Redisch, M., “Hospital Inflationary Mechanisms, ” paper presented at the Meeting of the

Western Economic Association, Las Vegas,

Nev., June 10-12, 1974.

Rice, D. P., Estimating the Cost of Illness, PHS

publication No. 947-6 (Washington, D. C.:

U.S. Government Printing Office, 1966).

Rice, D., et al., “The Current Burden of Illness

in the United States, ” paper presented at the

Annual Meeting of the Institute of Medicine,

Washington, D. C., Oct. 27, 1976.

Rivlin, A., Systematic Thinking for Social Action (Washington, D. C.: Brookings Institution,

1971).

Roemer, M., “Innovative Functions of Health

Personnel in Other Countries: Lessons for U.S.

Planners,” Inquiry 16(3):259, Fall 1979.

Schelling, T. C., “The Life You Save May Be

Your Own,” in Problems in Public Expenditure, edited by S, B. Chase, Jr. (Washington,

D. C.: Brookings Institution, 1968).

Schick, A., “The Trauma of Politics: Public

Administration in the Sixties, ” in American

Public Administrations: Past, Present, Future,

edited by F.C. Mosher (Alabama: University of

Alabama Press, 1975).
Other References ● 129

752,

753,

754,

755.

756,

Scitovsky, A., and McCall, N., “Changes in

the Cost of Treatment of Selected Illnesses,

1951-1964-1971, “ DHEW publication No .

(HRA) 77-361 (Washington, D. C.: National

Center for Health Services Research, 1976).

Steiner, P. O., “Public Expenditure Budgeting, ” in The Economics of Public Finance

(Washington, D. C.: Brookings Institution,

1974) ,

Stewart, A. L., et al., Conceptualization and

Measurement of Health for Adults in a Health

Insurance Study: Vol. II, Physical Health in

Terms of Functioning, publication No. R1987/2-HEW, prepared for the Department of

Health, Education, and Welfare (Washington,

D. C.: RAND Corp., July 1978).

Tversky, A., and Kahneman, D., “Judgment

Under Uncertainty: Heuristics and Biases, ” Science 185:1124, 1974.

Ware, J. E., et al., Conceptualization and

Measurement of Health for Adults in a Health

Insurance Study: Vol. V, General Health Perceptions, publication No. R-1987/5-HEW, pre757.

758.

759.

760.

761.

pared for the Department of Health, Education, and Welfare (Washington, D. C.: RAND

Corp., September 1978).

et al., Conceptualization and Measurement of Health for Adults in the Health insurance Study: Vol. III, Mental Health, publication No, R-1987/3-HEW, prepared under contract for the Department of Health, Education,

and Welfare (Washington, D. C.: RAND

Corp., December 1979).

Warner, K., “The Effects of Hospital Cost Containment on the Development and Use of Medical Technology, ” Milbank Mere. 56:2, spring

1978.

, “The Need for Some Innovative Concepts of Innovation: An Examination of Research on the Diffusion of Innovations, ” Pol.

Sci. 5:433, 1974.

Zeckhauser, R., et al. (eds. ), Benefit-Cost and

Policy Analysis (Chicago, 111.: Aldine Co.,

1975).

“Procedures for Valuing Lives, ” Pub.

Pol. 23;419, Fall 1975.

0