A Microeconomic Model Of Healthcare Systems: From Theoretical To Practical

University of Central Florida University of Central Florida

STARS STARS

Electronic Theses and Dissertations

2007

A Microeconomic Model Of Healthcare Systems: From A Microeconomic Model Of Healthcare Systems: From

Theoretical To Practical Theoretical To Practical

Jesse Helligso

University of Central Florida

Part of the Political Science Commons

Find similar works at: https://stars.library.ucf.edu/etd

University of Central Florida Libraries http://library.ucf.edu

This Masters Thesis (Open Access) is brought to you for free and open access by STARS. It has been accepted for

inclusion in Electronic Theses and Dissertations by an authorized administrator of STARS. For more information,

please contact ST[email protected].

STARS Citation STARS Citation

Helligso, Jesse, "A Microeconomic Model Of Healthcare Systems: From Theoretical To Practical" (2007).

Electronic Theses and Dissertations

. 3198.

https://stars.library.ucf.edu/etd/3198

A MICROECONOMIC MODEL OF HEALTHCARE SYSTEMS:

FROM THEORETICAL TO PRACTICAL

JESSE ANDREW ROBERT HELLIGSO

B.A. Trinity University, 2004

A thesis submitted in partial fulfillment of the requirements

for the degree of Master of Arts

in the Department of Political Science

in the College of Sciences

at the University of Central Florida

Orlando, Florida

Summer Term

2007

ABSTRACT

This thesis is a microeconomic market analysis of healthcare systems. Different

countries use various forms for financing and providing healthcare, and the effects of market

forces on the quality, access and economic efficiency of these divergent healthcare markets is the

primary subject. The purpose of this thesis is to describe the forces working in the healthcare

market. Free-market healthcare systems allow medical providers to become price-setters. Price-

setting by medical providers creates an economically inefficient system which decreases public

access to healthcare but creates a high quality system. Single-payer systems make government

the price-setter which creates a system in which medical providers are price-takers. Government

price-setting guarantees access but quality and economic efficiency vary drastically between

countries. Universal single-payer systems tend to set prices higher than the theoretically

necessary price which creates a high quality, economically inefficient system. Socialized single-

payer systems tend to set prices lower than the theoretically necessary price which creates

government savings, wait-lists and poorer quality. The quality, economic efficiency, and equity

of the healthcare system are determined by the form of the market used in the country.

Ultimately, this market determines price. In a free-market system price is determined by

providers of healthcare, in a socialized market price is determined by government, and in a

universal healthcare system price is negotiated by both healthcare providers and government.

Price negotiation in a universal system creates the greatest access to healthcare, and quality of

healthcare. Socialized systems can be more economically efficient than a universal system, but

quality and access can be limited. Price negotiation in a universal healthcare system fixes the

problems inherent in the healthcare market.

iii

ACKNOWLEDGMENTS

Thank you to my mother, without whom I never would have been driven to attain an

education, or been able to do so. She sacrificed to make sure that I was able to accomplish my

goals and break free from a life of poverty in a small town.

A special thanks to Dr. Kerstin Hamann, who provided guidance throughout this entire

thesis, and Master program. She has kept me focused, and helped me define the issues laid out

in this thesis.

Thank you to the State of Oregon, for stepping in and paying the remainder of my

$65,000 medical bills that my insurance provider would not cover. Oregon was such a great

state before the cutting of the Oregon Health Plan.

TABLE OF CONTENTS

LIST OF FIGURES ...................................................................................................................... vii

LIST OF TABLES......................................................................................................................... ix

CHAPTER 1: INTRODUCTION ................................................................................................... 1

Background......................................................................................................................... 6

Assumptions about Healthcare ......................................................................................... 10

Figures and Tables ............................................................................................................ 12

CHAPTER 2: A MICROECONOMIC MODEL OF HEALTHCARE SYSTEMS..................... 13

Model Assumptions .......................................................................................................... 15

The Free-Market Healthcare Market ................................................................................ 18

The Single-Payer Healthcare Markets .............................................................................. 25

Conclusions....................................................................................................................... 27

Figures and Tables ............................................................................................................ 29

CHAPTER 3: EVALUATING HEALTHCARE SYSTEMS....................................................... 34

Methodology..................................................................................................................... 34

Aggregate Data ................................................................................................................. 36

Conclusions....................................................................................................................... 49

Figures and Tables ............................................................................................................ 51

CHAPTER 4: THE UNITED STATES........................................................................................ 71

Figures and Tables ............................................................................................................ 82

CHAPTER 5: THE UNITED KINGDOM ................................................................................... 89

Figures and Tables ............................................................................................................ 95

CHAPTER 6: GERMANY ........................................................................................................... 99

CHAPTER 7: CONCLUSIONS ................................................................................................. 104

Figures and Tables .......................................................................................................... 108

REFERENCES ........................................................................................................................... 109

LIST OF FIGURES

Figure 1: General Supply and Demand Structure of Healthcare if Healthcare Functioned Like a

Normal Market.............................................................................................................................. 29

Figure 2: Active Physicians by Medical Education...................................................................... 30

Figure 3: Number of Medical Personnel in the United States ...................................................... 31

Figure 4: Provider Price-Setting ................................................................................................... 32

Figure 5: Government Price-Setting/ Da is Obsolete ................................................................... 33

Figure 6: Per Capita Expenditure on Healthcare and Total Life Expectancy............................... 51

Figure 7: Linear and Quadratic Scatter Plot All 30 OECD Countries.......................................... 52

Figure 8: Linear and Quadratic Scatter Plot of Wealthy Countries Only..................................... 53

Figure 9: Life Expectancy and Per Capita Expenditure by System Type..................................... 55

Figure 10: Quadratic Regression by System Type ....................................................................... 56

Figure 11: Quadratic Regression and Market Model Overlay...................................................... 58

Figure 12: Number of High Tech Units Per Million..................................................................... 59

Figure 13: Life Style Factors and Life Expectancy ...................................................................... 60

Figure 14: Life Style Factors as an Explanation for Expenditures ............................................... 61

Figure 15: Linear and Quadratic Scatter plot of Infant Mortality and Per Capita Expenditure.... 62

Figure 16: Complex Disease Deaths and Per Capita Expenditure................................................ 63

Figure 17: Healthcare Professionals and Per Capita Expenditure ................................................ 65

Figure 18: Medical Professionals Quadratic Regression by System Type................................... 66

Figure 19: Number of Healthcare Professionals and Life Expectancy......................................... 68

Figure 20: High Technology and Per Capita Expenditure............................................................ 69

vii

Figure 21: Quadratic Regressions for Medical Professionals and Life Expectancy Overlaid on

Model ............................................................................................................................................ 70

Figure 22: Life Expectancy after Age 65...................................................................................... 82

Figure 23: Distribution of the Uninsured and Total U.S. Population by Age .............................. 83

Figure 24: Healthcare Financing................................................................................................... 84

Figure 25: Hospital Payments by Source of Funding ................................................................... 85

Figure 26: Pharmaceutical Expenditures ...................................................................................... 86

Figure 27: Advertisement Expenditures by Pharmaceutical Companies...................................... 87

Figure 28: Gross Domestic Expenditure on R&D (As a Percentage of GDP, 2005 or Latest

Available Year)............................................................................................................................. 87

Figure 29: The Distribution of the Uninsured and Total U.S. Population by Income.................. 88

Figure 30: Change in Life Expectancy and Per Capita Expenditure on British Healthcare......... 95

Figure 31: Percentage Change in Healthcare Expenditures Overlaid on Life Expectancy .......... 96

Figure 32: Number of Medical Professionals by Year in the UK................................................. 97

Figure 33: Linear Regression for Per Capita Expenditure and Number of Healthcare

Professionals in the UK ................................................................................................................ 98

viii

LIST OF TABLES

Table 1: Interaction Between Healthcare Systems and Indicators................................................ 12

Table 2: Relationship between Expenditures, Life Expectancy and Infant Mortality.................. 51

Table 3: Model Summary for Linear and Quadratic Regression of Per Capita Expenditure and

Life Expectancy ............................................................................................................................ 52

Table 4: Model Summary for Life Expectancy and Per Capita Expenditure (Wealthy Countries

Only) ............................................................................................................................................. 53

Table 5: Predicted Life Expectancy and Type of System............................................................. 54

Table 6: Model Summary for Quadratic Regression by System Type ......................................... 57

Table 7: Summary for Infant Mortality and Per Capita Expenditure Regression......................... 62

Table 8: Model Summary for Cerebrovascular Deaths and Per Capita Expenditure ................... 63

Table 9: Model Summary for Per Capita Expenditure and Healthcare Professionals.................. 64

Table 10: Model Summary for Number of Healthcare Professionals and Life Expectancy ........ 67

Table 11: Life Expectancy and Expenditures ............................................................................. 108

CHAPTER 1: INTRODUCTION

In this thesis I develop two healthcare market models, and tests these two models using

aggregate data from the OECD. The focus of the healthcare market models laid out in this work

is in advanced industrial countries, low income countries will not have the wherewithal to fund

healthcare on the same levels as the wealthier countries, and their supply and demand lines will

diverge greatly from those of an advanced industrial country. This is an original thesis—the

market models do not rely on previous theories or the research of others. I developed them in an

attempt to understand why the healthcare literature contained very divergent views on which

type of healthcare system was functioning best. I use aggregate data provided by the OECD (but

the analysis and statistics derived from the data were completed by me and do not rely on the

research of others). The works of others are only used to describe how the individual countries’

systems are functioning. The term “healthcare system” refers to the type of financing and

provision of healthcare used in a country. The term “healthcare market” refers to the connection

and interaction between the supply and demand of healthcare. Three countries are discussed in

terms of how they relate to these healthcare market models—the United States, the United

Kingdom, and Germany. The market models created in chapter 2 are theoretically driven.

They are not meant to model the real world exactly as it is, as every country has a different form

of healthcare system—they are meant to describe the forces that are taking place in the real

world healthcare markets by using economic terms, such as supplier incentives and motivations.

The models are an abstraction, and as such, no country is perfectly described by them. It is

almost certain that not all healthcare providers are out to make large profits, but they do act in a

profit-seeking manner. Chapter 2 is attempting to describe their motivations and incentives for

profit-seeking. Chapter 3 tests whether or not these theoretical models are actually describing

the processes taking place in the world. Chapters 4, 5 and 6 are used to show how these

theoretical market models are implemented in the three different forms of healthcare systems.

Healthcare is a major concern for every country in the world. It is of particular

importance for the advanced industrialized countries that often control the financing of their

healthcare systems. Advanced industrial countries’ governments are deeply involved in the

funding and running of their healthcare systems, which places healthcare at great importance for

them. Most developed countries use some form of government financed healthcare, and

guarantee access to medical treatment for their entire populations. However, the United States,

as one of the most advanced industrial and economically powerful countries in the world, fails to

provide healthcare for its entire population, and has, according to the OECD, large income

inequalities to access.

The Western World has used the free-market economy to provide

surpluses in every form of goods, from food to automobiles. The ability of a free-market

economy to self-regulate, and create profitable surpluses is cause for excitement. The free-

market is important because of its ability to negotiate a price that is set by supply being equal to

the demand for a good or service. However, often there are problems in a free-market. The free-

market works as a balancing mechanism for the supply and demand of goods. The supply of

goods is based on the price of the good that a provider can earn, and the demand for the good is

based on the cost of that good. As price increases the supply increases due to more firms

entering into the production of that good. And, as price increases the demand for the good

decreases as fewer and fewer consumers can afford to pay for the good. The price of the good is

set by the market through competition at the point where the demand for the good equals the

OECD 2004

supply of the good. But, what happens when the demand for a good is set, and does not fluctuate

with the price? What good is a free-market if it is not negotiating a price where supply meets

demand? Suppliers can earn large profits by merely charging more for their goods instead of

increasing the quantity of goods provided. Demand for healthcare is constant—it does not

fluctuate with price. As price increases fewer people can afford care, but the same number still

require care. The free-market falls short of supplying the full demand for healthcare. The

United States relies on the free-market for its supply of healthcare, and by doing so limits access

to care and increases the costs of care. In a normal market the price of a good is negotiated by

the demand for the good and the supply of the good. But, in the healthcare market there is no

such negotiation of price. In a free-market system price is primarily set by providers, in a

socialized system price is primarily set by the government. It is usually through a universal

healthcare system that price is negotiated between the suppliers of healthcare and the demanders

of healthcare. This negotiation between supply and demand in a universal healthcare system

fixes the problems of price-setting in the healthcare market, and forces the price negotiation that

the free-market is hailed the world over for doing with other goods and services but fails to do in

the healthcare market.

How does healthcare function as a market? What are the market effects from government

intervention into the healthcare system? What indicators should be used in discussion of the

overall functionality of the system? How can access, quality, and economic efficiency be

balanced in a way that reflects the real goals of a population or government? This thesis

analyzes how the market functions in healthcare in three divergent systems; free-market,

socialized and universal. In chapter 2 I develop two models that demonstrate the market forces

as they relate to the provision of healthcare, by examining the price and quantity of services

provided. These models represent the different effects on the market that are caused by the

identity of the price-setter; provider price-setting, and government price-setting. These models

are then examined in terms of aggregate data, in chapter 3, on various healthcare indicators

provided by the OECD. The indicators examined are life expectancy, per capita expenditure,

infant mortality, deaths by disease (respiratory, diabetes, and cerebrovascular), numbers of

practicing physicians and nurses, and life style factors (obesity, overweight population, smoking,

and alcohol consumption). Life expectancy is used as a proxy for quality of care, access to care

and life style choices. However, life style choices are also examined separately in terms of their

effects on life expectancy, and on per capita expenditure. Likewise, the number of medical

professionals is examined both in terms of its effects on life expectancy, but also in terms of its

effect on healthcare expenditure. Three countries are then analyzed in terms of how they

function according to the market models. The United States is discussed in chapter 4 as a model

of a free-market healthcare system. I chose the United States was because it is the prime

example of how free-market healthcare functions (and because it is one of the only free-market

healthcare systems in the industrialized world). Furthermore, the United States also has a

functioning universal healthcare market in the form of Medicare and Medicaid. This second

healthcare market allows for easy comparisons between how a free-market healthcare system and

a universal healthcare system create different health outcomes. Chapter 5 discusses the

healthcare system of the United Kingdom. I chose the U.K. as an example of a socialized

healthcare system because it is often used in arguments against using a socialized healthcare

system due to waitlists and a perceived low quality of care. Socialized healthcare has a wide

range of quality conditioned by the manner in which governments set prices. Some socialized

systems have high life expectancies and others have low life expectancies compared to other

industrialized countries. This wide variation is caused, for the most part, by differences in how

governments go about their price-setting (socialized countries with high expenditures on

healthcare had higher life expectancies than socialized countries with low expenditures, and life

style factors were found to influence life expectancy, but not per capita expenditures on

healthcare, see chapter 3). The more negotiation of price between healthcare providers and

government the higher the quality of care can be achieved in the system. The case of the United

Kingdom is very useful in discussing this variation, because throughout the last ten years it has

been increasing its price negotiation and expenditures which has shown an improvement in life

expectancy and the number of practicing physicians (quality and access). In other words, the

United Kingdom exhibits both low and high access socialized healthcare. Chapter 6 analyzes the

healthcare system of Germany as an example of a universal healthcare system. Germany was

chosen, not because it is the best universal healthcare system in terms of health outcomes, but

because it is the first universal healthcare system, and as such, has served as a model for other

countries to build their own healthcare systems. Much of the German healthcare institution has

been copied by other countries, and thus it demonstrates how most of the universal healthcare

systems function. Chapter 7 provides the conclusions from my analysis.

There are various indicators used when discussing a healthcare system. The three

indicators most widely discussed are access, quality of care and economic efficiency. The

indicator of most importance to the researcher or the government directly determines their views

on the functionality of the system. And, the indicator that researchers are most focused on is

determined by their views on healthcare as a right or a commodity. If healthcare is viewed as a

commodity, then quality and economic efficiency become the most important indicators of

system functionality. If healthcare is viewed as a right, then access and quality become the most

important indicators of the functionality of the system. There is no way to balance economic

efficiency, access and quality in a healthcare market. One, or possibly two of the indicators must

be sacrificed.

The balance of access, quality and economic efficiency in a healthcare system is

determined by the identity and goals of the price-setters. Healthcare does not follow a normal

free-market structure due to quasi-monopolistic competition (and a myriad of principle-agent

dilemmas, which cause imperfect knowledge on the part of medical consumers). In a free-

market this structure allows for healthcare providers to become price-setters, and bypass a

competitive market. When healthcare providers are price-setters, the price will be set high,

which will lower access, create higher quality (due to competition for consumers), and be

economically inefficient. However, if government controls healthcare financing, healthcare

providers either take the price that the government offers or do not receive payment. This allows

government to do the price-setting. When government controls healthcare financing and the

provision of healthcare it will tend to set prices as close to cost as possible. Low price-setting

can lower quality and create waitlists. But if the government only controls healthcare financing

and not the provision of healthcare, the government will tend to set prices higher by forced

negotiations with healthcare providers. High price-setting will increase quality through

competition, ensure access, but the system will be economically inefficient.

Background

Various states use differing methods of funding healthcare. In most advanced

industrialized states the government has taken control over the financing, and/or management of

healthcare (the United States remains an outlier)

. Three different forms of healthcare finance

and management have been distinguished in the literature on healthcare. Differing authors or

organizations use different names for these systems but all have the same three descriptions of

the systems: 1. the entrepreneurial model

(Free-market healthcare, the United States), which is

characterized by private insurance and provision of healthcare, hereafter referred to as free-

market healthcare; 2. the mandated insurance model

(universal healthcare, Germany), which is

characterized by compulsory universal coverage financed through a social security framework,

and/or direct control of the provision of healthcare by government, hereafter referred to as

universal healthcare; and 3. the national health service model

(socialized healthcare, the United

Kingdom), which is characterized by universal coverage for all citizens through general tax

funding, and ownership or direct control of provision of healthcare by government, hereafter

referred to as socialized healthcare. This thesis separates the three forms of healthcare systems

by whether the provision and financing of healthcare is primarily public or private. A free-

market system has private funding and private provision of healthcare. Socialized healthcare has

public funding and public provision of healthcare. Universal healthcare has public funding and

private provision of healthcare. Because some organizations classify the healthcare system only

according to the financing mechanism (direct tax, or insurance pooling systems) and not by the

ownership of medical provisions they may classify a country’s system differently than I do in

this thesis (for example, many classify Canada as a socialized healthcare system, such as Fried

because it uses direct taxation to fund its healthcare system, however, in this thesis I classify

Matcha 2003

Fried 2002, pg 26

Fried 2002, pg 27

Fried 2002, pg 26

Canada as a universal system because financing is public and provision is primarily private).

Provision of healthcare refers to both general practitioners and hospitals. As stated, there are

three important indicators that define a successful healthcare system that must be examined:

First, equity—also referred to as access to medical needs, how easily patients gain access to

medical attention and removal of barriers to access such as low income, or poor status of health:

Second, quality and effectiveness of healthcare services—patient satisfaction and meeting of

patient needs: And third, macroeconomic and microeconomic efficiency—cost effectiveness of

the overall healthcare system.

Currently there is large disagreement among policy makers on how to best fund

healthcare and provide high quality of healthcare; and a disagreement in the academic literature

as to which system functions best. Both the World Health Organization and the OECD rank the

healthcare systems of various states, with the United States ranked relatively low considering its

high expenditures both as percent of GDP and spending per capita, but neither can agree on who

has the best system or how to rank the systems (in fact the World Health Organization uses three

different ways for ranking healthcare systems within their own analyses)

. Many academics

have argued that the U.S. healthcare system is in complete disarray: Mueller

argues that the

system is too costly, and that access is limited; Bartlett and Steele

argue that the healthcare

market in the United States wastes money due to inefficiency, fraud and profits to companies that

deny healthcare to some; Kassirer

and Abramson

have similar arguments and reason that the

problems of the U.S. healthcare system are due to profit seeking by providers who overcharge

World Health Organization 2006

Mueller 2001

Bartlett 2004

Kassirer 2004

Abramson 2005

and give low quality care; Kleinke

blames the fragmented funding sources (differing insurance

programs) of healthcare for the problems of the system. Yet, other authors argue that the market

improves competition and thus quality of the healthcare system, among them Cutler,

Dranove

and Robinson

. Ohsfeldt and Schneider

argue that competition increases the quality of the

healthcare system and that profit seeking by providers does not have adverse effects on the cost

of healthcare, in fact it spurs innovation. Both groups are correct, the system is over-priced as

many have argued, and competition due to profit seeking by healthcare providers does increase

the quality of care.

I develop an economic model that describes the market forces that are occurring in the

healthcare system. This model takes account of quality, equity, and efficiency, in all three forms

of healthcare financing and provision. I show that, surprisingly, whether or not the state owns

and runs the hospitals has less effect on the overall functionality of the system than whether or

not the government directly controls price-setting of medical treatment. However, government

control of medical provision will most likely lead to lower price-setting than free-market

provision of healthcare, which in turn, will cause a decrease in quality of care in the overall

system. Table 1 shows the general differences between the indicators of a successful healthcare

system in relation to the type of system financing.

Kleinke 2001

Cutler 2004

Dranove 2000

Robinson 1999

Ohsfeldt 2006

Assumptions about Healthcare

The study of healthcare contains many nuanced dilemmas. Consumers must rely on

doctors to tell them what their needs (preferences) are. Consumers rarely directly pay for their

own care, and rely on either insurance or government for payment. Pharmaceutical companies

must rely on the medical community as their agents (which cause them to spend billions of

dollars on advertising, see chapter 4). All of these relationships create principle-agent dilemmas;

which lead to a lack of knowledge on the part of one party or the other, and allow them to have

more power when negotiating. Principle-agent dilemmas make it impossible for healthcare

financers to know the real costs of healthcare and thus make it possible for healthcare providers

to increase the total price of healthcare creating artificially increased expenditures. The

provision of healthcare also provides further dilemmas for the study of the healthcare as a

market. In a normal market services are provided for self-interested reasons—to make money,

but many healthcare professionals argue that they enter into practice out of more altruistic

purposes (for examples look at Doctors Without Borders, Mercy Ships, and the myriad of low

income healthcare offices that only cater to low income families). This makes the supply of

doctors difficult to examine as a mere function of price determining quantity. To this end, I

assume that a small number of medical professionals will enter into practice at cost, but to

provide enough medical professionals for an entire population price will play a major role. In

the study of economics, competition is believed to create higher quality goods, and lower price.

In perfect competition firms must compete with each other, which drives price downward in an

attempt to control a larger share of the market, and the quality of goods is increased in the same

attempt to control a larger share of the market. My research assumes that competition does

increase quality—if 300 physicians are competing for one position a more experienced physician

will be chosen than if only 10 physicians are competing for one position. Furthermore,

competition leads employees to try harder to distinguish themselves from other employees,

which can increase experience, education, and gives motivation for improving quality. However,

due to the unique nature of the healthcare system, and all of its asymmetrical information,

competition will not decrease price—this is not an assumption about the system but a conclusion

arrived at by examining the healthcare market, which will be discussed in the next chapter. It is

also assumed that the life expectancy in a given country is a function of the quality of care, the

access to care and life style choices. Life expectancy is increased as quality and access increase.

However, life expectancies also vary depending on diet and other lifestyle factors that are not

easily identified but have an overall effect. The last assumption pertains to demand—there is a

theoretically set demand for any given ailment, the total number of cases of the population that

has this ailment. This demand may or may not be known, but is theoretically immovable at any

given moment. If 100 people have cancer the demand for cancer treatment will be 100 units at

any price. Actual demand for healthcare may never fully meet this theoretical demand, because

of patient preferences—some patients do not seek treatment for various reasons, but the

theoretical demand still exists.

The next chapter lays out the argument for the market models and why and how supply

and demand are meeting in the three forms of healthcare markets. Chapter 3 then tests these

models using aggregate level data from the OECD, and controls for access and life style factors.

Figures and Tables

Table 1: Interaction Between Healthcare Systems and Indicators

Quality Equity Efficiency

Free-Market

High Medⁿ Low

Universal

Low to High Med-High/ High* Inverse to quality^

Socialized

Low to High High* Inverse to quality^

ⁿAccess for the poor extremely low

*May have waitlists despite guaranteed treatment

^Not directly inverse, but as efficiency decreases quality increases, and as efficiency increases quality decreases

CHAPTER 2: A MICROECONOMIC MODEL OF HEALTHCARE SYSTEMS

What does the healthcare market look like? Does it follow a standard microeconomic

model of other normal goods? To answer these questions requires an in-depth analysis of

general markets in comparison to the market of healthcare. Unlike other goods in the

marketplace, healthcare has a somewhat unique position (some authors such as Robert Ohsfeldt

argue that it is not unique, but my model will show why it is in fact unique). Ohsfeldt argues that

competition in the free-market healthcare system spurs an increase in quality and also economic

efficiency in the same manner that the free-market does with other goods.

However, my

models show that economic efficiency is not achieved through a free-market healthcare system,

but increased quality is.

This chapter develops two economic models for healthcare systems, a provider price-

setting model, and a single-payer model. These models are abstractions from the real world

based on logical arguments. Stockman explains that:

When economists think logically about an economic problem, they produce economic

models: An economic model is a description of logical thinking about an economic

issue. It may express its conclusions in words, graphs, or mathematical symbols. Logical

thinking by itself is not sufficient to reach reliable conclusions about economics; logic

needs the support of evidence. Economic evidence is any set of facts that helps convince

economists that some positive statement about the economy is true or false.

Ohsfeldt 2006

Stockman 1999, pg 19

In this thesis I follow this economic modeling format: first, this chapter lays out the logic behind

supplier and consumer motivations in the healthcare market. Chapter 3 tests these logic based

arguments with aggregate data from thirty OECD countries. And chapter 4, 5, and 6 provide an

examination of how three different countries follow the models through policy. The models

developed in this chapter do not fully represent the complexities of the healthcare market:

Models are simpler than the real-life situations they represent. Many real-life situations

are too complicated for the limited abilities of human minds to comprehend.

Consequently, we create models—simplified versions of reality—to help think logically

about real life. A model assumes that features of an issue are important to think about

while other features are unimportant enough to ignore.

Economic models serve three purposes: 1. Understanding. A model simplifies an issue to

help people understand it. 2. Prediction. A model helps people to predict, so they can

answer questions […] [and] to resolve complicated, real-life issues. 3. Interpretation. A

model helps people to interpret data as evidence about positive economic statements.

A “good” model’s predictions will be supported by the data, and a “bad” model will not achieve

the predicted outcomes.

Healthcare systems are extremely complicated, which means that all

variables cannot be discussed. Therefore, I have selected the variables that I feel are most

important to the functioning of the healthcare market. If my models are “good” the aggregate

data should follow the predicted pattern, and the case studies should show that price-setting

within countries is following the predicted form and achieve the predicted outcomes. These

predictions are:

Stockman 1999, pg 21

Stockman 1999, pg 20

1. A country with price-setting by providers will have high expenditures and decreased life

expectancy due to lowered access (usually a free-market system).

2. A country with price-setting by government will have decreased expenditures and a decreased

life expectancy due to waitlists and decreased quality (usually a socialized system).

3. A country in which price is negotiated by providers and financers of healthcare will have

moderately high expenditures and an elevated life expectancy (usually a universal system, and

sometimes a socialized system).

Model Assumptions

In a normal market the price and quantity of a good provided is determined by supply and

demand, and with competition between firms, price is driven down. Demand in the normal

market is determined by consumer tastes and preferences based on resources. And supply is

determined by the costs of production, the quality of the good and the scarcity of resources. The

point at which supply and demand meet determines the price and quantity of the good provided.

A good is considered a normal good, “If a rise in income raises the demand for a good.”

But,

in healthcare a very different relationship exists—there are two different demand curves. The

first demand curve is not determined by consumer preferences or tastes, but is determined by

ailment and remains perfectly inelastic

(as price increases the demand remains the same). The

demand for treatment of any given ailment remains completely unresponsive to fluctuations in

price. If a patient has cancer and needs chemotherapy, he will still demand the chemotherapy at

Stockman 1999, pg 78

Stockman 1999, pg 103-111

any price. Demand is further complicated by a lack of knowledge on the part of the consumer,

who must rely on an agent (doctor) to determine one’s true demand. Patients neither know what

antibiotics to take or the quantity of antibiotics to take for any given infection, which means they

must rely on medical providers to determine these choices for them. However, theoretically

there is a constant number of consumers with any given ailment, and thus there is a set demand

for services (Dt-Theoretical, actual demand based on need, the true number of cases of each

ailment). The second demand curve in the healthcare market is based on the ability of

consumers to pay for services (Da-Demand based on ability to pay). The ability to pay for

medical services interjects another problem of discussing the healthcare system—often

consumers do not pay for medical services directly, and must rely on insurance providers as their

agents (coupled with the principle-agent dilemma of doctors and patients). Insurance providers

as profit-seeking agents attempt to decrease their own costs while maximizing their profits,

which can further decrease access for the overall population. Some authors, such as Kleinke,

have noted this exact problem.

As consumers’ incomes increase the demand for healthcare

only increases to the theoretical demand, and thus the demand for healthcare cannot be

considered a normal good. Furthermore, as price increases the theoretical demand (Dt) for

healthcare remains constant, but the ability demand (Da) decreases (see figure 1). And, as ability

demand moves away from theoretical demand, access becomes limited—patients who require

services due to ailment do not receive treatments that they cannot afford. Demand in a normal

market is only limited by the price of the product, but healthcare demand has a real set value that

remains constant despite all other factors—this represents an obvious divergence from normal

markets. The second demand curve (Da) matches a normal market. So, should a government be

Kleinke 2001

concerned with meeting the theoretical demand, or only providing services for those that can

afford treatment? Which demand curve is most important, the theoretical demand or the ability

demand? These questions can only be answered by a philosophical discussion of whether or not

healthcare is a right or commodity

. I assume that a government or population is concerned

with meeting the theoretical demand, that is, the general consensus in most countries is that

healthcare should be provided for all of those that require care, not only to those that can afford

care (even if this is not the case no politician or government would claim that it was not).

Supply in the healthcare market remains similar to supply in a normal market, with a

couple of exceptions—theoretically there is a constant cost for every procedure (the biopsy of

two moles costs exactly twice as much as the biopsy of one mole) which develops a perfectly

elastic

supply line (Supply at cost, Sc; this supply at cost has no effect on free-market

healthcare, but comes into play when discussing government price-setting). There is also a

second supply based on the entrance of healthcare providers based on the ability to earn money

(Sp-the supply of medical providers), which follows a normal supply concept—as price increases

the number of firms and physicians wanting to enter the medical field increases with a theoretical

minimum of Sc.

If the healthcare market functioned as a normal market in a wealthy, advanced

industrialized state (poorer, pre-industrial states will have extremely diverse supply and demand

curves, and, as stated, will not be discussed in this paper) the price and quantity of services

would be equal to where Da (the demand with the ability to pay) meets Sp (the supply of medical

professionals). Access would be limited to those who can afford treatment and this loss of

Almgren 2007

His book is an analysis of healthcare from a Rawlsian perspective, and offers multiple views of healthcare as both a

right and as a commodity.

Stockman 1999, pg 103-111

access is represented by the difference between Dt and Da where Sp and Da meet. In figure 1

full provision of the theoretical demand and optimal economic efficiency is represented by

P(Dt=Sp). But, the real price (Pn) and quantity (Qn) provided if healthcare functioned like a

normal market would be represented by the point where Da meets Sp, and would not fully meet

the theoretical demand.

Unfortunately this is not what the real healthcare market looks like; it does not function

like a normal market (If it were functioning like this the United States should be spending less

per capita on healthcare than other states that are providing services that meet the theoretical

demand—the U.S. would have price=Pn and quantity=Qn, and other states would have P(Dt=Sp)

and the quantity would equal Dt). Free-market systems would be represented by the blue line

and universal and socialized markets would be represented by the red line in Figure 1. The

United States, according to the OECD, is currently spending twice as much on healthcare per

capita as every other advanced industrial nation, which negates the idea that healthcare is

functioning like a normal competitive market.

The Free-Market Healthcare Market

So, what is really going on in the healthcare market in a free-market system? Why does

the United States pay twice as much per capita on healthcare than other states that actually meet

their theoretical demands?

There are other factors putting pressure on the healthcare market

that a normal competitive market does not contain. Asymmetrical information (patients do not

know what their needs are, and how much they really cost) and the quasi-monopolistic nature of

OECD Health Data Set 2006

healthcare (generally there is only one hospital in any given region, which gives hospitals

regional monopolies) allow providers of healthcare to become price-setters. Hospitals do not

compete directly with one another; consumers simply choose the hospital that is closest to them

or included in their healthcare plan in emergency situations or for routine care. Furthermore,

hospitals and physicians, being self-interested, try to maximize their profits, but there is little

competition in the region to keep prices low. Increasing profits for hospitals can be

accomplished by raising the prices of routine medical treatment (1 Tylenol pill costing $50 at the

hospital) that would be far too inconvenient for consumers to travel to receive (and laws prohibit

them from doing so), or by specializing treatment and technology in certain fields that will attract

consumers from other markets. For example, while hospitalized, a patient is charged the $50 for

one dose of Tylenol which outside of the hospital costs less than a $1. The patient is unable to

leave the hospital to purchase the medication for physical reasons, and laws further prohibit the

patient from doing so, therefore, the hospital is given monopoly control over the price of the

Tylenol (see Chapter 4). Hospitals can further increase their profits by specializing in certain

fields that will attract consumers from other regions—such as a hospital specializing in the

treatment of cancer (see chapter 4). Patients will be willing to travel longer distances to receive

specialized higher quality treatments in non-emergency, complicated situations; which increases

the share of the healthcare market for the hospital in those specialized fields. This second type of

profit seeking leads to competition between hospitals; which increases the ability to receive

higher quality treatment, but drives price upward for a myriad of reasons—because newer

technologies often cost more to purchase and use, and because the demand for one hospital

becomes higher than for another, the hospital with higher demand is able to set prices even

higher (Nike can charge more for their shoes than other shoe companies because the demand for

Nike is higher than other shoe companies’ shoes). Consumers with insurance often do not know,

or even care, about the price of treatment being higher at one hospital than at another, they just

want the best quality treatment available. Insurance companies are actually paying for the

services, but their users are choosing where to receive treatment which decreases the ability of a

higher price from deterring the consumption of the more expensive medical treatments. This

form of competition increases quality, but fails to drive price downward. Many insurance

companies attempt to curb this from happening by requiring patients to go through their primary

care physicians as a gatekeeper to other medical treatment or creating other limits. These limits,

such as co-pays, can help moderate the overall expense for insurance companies, but do not limit

the decisions of medical providers. If an insurance company refuses to pay for treatment at a

certain location, they are likely to lose consumers. For example, if an insurance company refuses

to allow its consumers to use the services of one hospital in a region because it costs more than

another hospital, but another insurance company allows the use of that hospital by its consumers,

there is motivation for consumers to switch insurance companies. Medical providers and

insurance companies are both fully aware of this fact. Therefore, when negotiations take place

between insurance companies and medical providers, the medical providers can always choose to

refuse service to that insurance company if the price offered by the insurance company is lower

than the provider wishes to receive. The insurance company is motivated to offer a higher price,

or face losing consumers. Insurance companies are competing directly with one another; this

direct competition creates motivations for paying higher costs to medical providers than if there

were only one insurance company. However, medical providers must have consumers which

mean that they cannot refuse services to all insurance companies. Insurance companies with

large consumer bases can negotiate lower prices with hospitals than insurance companies with

small consumer bases, because medical providers are more afraid of losing a large consumer

base than a small consumer base. Hospitals do not have to worry what other hospitals are

charging for their services, they only need to focus on the price that they can negotiate from

insurance companies. This gives medical providers a quasi-monopolistic control over the price

of medical treatment. According to Stockman a monopoly is defined as, “A firm is a monopoly

if it (a) faces a downward-sloping demand curve for its product and (b) makes decisions without

considering the reactions of other firms.”

Hospitals easily fit into this category. Decisions

made by hospitals are often not based on competition with other hospitals, but on maximizing

profits while meeting demand in a given region. And, where competition exists between

hospitals (because patients have the ability to choose between two hospitals); price is further

inflated, despite the competition, by specializing in certain types of illnesses. This allows

hospitals to be price-setters. Price-setting allows providers to choose the price they want, and

given their rational self interest price will most likely be placed high. The price chosen will be

made where Da decreases at a faster rate than price increases (or rather where the total revenue

(TR) is maximized, which will be much higher than the cost based on the supply and demand).

If a 1 unit increase in price decreases demand by more than 1 unit the price will be set too high.

For example if price for chemotherapy is increased from $100 per unit to $101 per unit, and

demand with the ability to pay decreases—Da decreases from 100 units to 98 units, the increase

in price will, therefore, not be made (TR=$10,000 ($100*100patients), or TR=$9898

($101*98patients)). But, if the price is increased from $50 per unit with a demand of 150 units,

to a price of $100 a unit with a demand of 100 units the price will be set at the higher TR

(TR=$7,500 ($50*150patients), or TR= $10,000 ($100*100Patients)) (Actual monopoly price-

Stockman 1999, pg 321

setting is slightly more complicated involving the Marginal Cost and Marginal Revenue, but for

simplicity this model can be used by assuming that the cost of producing one more unit increases

identically at every point, marginal cost has the same value at every quantity; the biopsy of one

mole costs $1, the biopsy of 2 moles costs $2, and the biopsy of 10 moles costs $10, which gives

the same marginal cost at every quantity)

. In this second scenario the hospital will set the price

at $100 because its total revenue will be maximized despite serving fewer patients. Thus, the

price will be set artificially high. Furthermore, because of the regional monopoly on healthcare

provision, small populated regions can even further inflated prices. High tech goods such as

MRI machines and CT scanners can cost large amounts of money (I was unable to find actual

prices because companies do not disclose this information to the public), if a low populated

region buys a MRI unit and only performs a small number of scans with the machine each year,

they must charge each patient more for the use of the machine than in a region where the

machine is used more frequently. If ten patients are paying for a machine it will cost more than

if one thousand patients are paying for the machine.

However, this high price of medical care will have a positive side effect; it will stimulate

competition for medical positions. The opportunity to earn substantial amounts of money will

increase the number of physicians, medical technology companies, and pharmaceutical

companies willing to enter into the medical market. Given the limited number of necessary

physicians (the demand with the ability to pay at a given price), medical professionals will

compete with each other for their position, which will allow hospitals to hire better quality and

qualified medical professionals. For example, if a country were to pay physicians only $10 an

hour, the number of physicians willing to work would be low, and there would not be enough

Stockman 1999, pg 321-327

physicians to fill vacancies, which would mean that hospitals would have to hire any willing

physician. But, if a country were to pay $1000 dollars an hour, there would be more than enough

physicians willing to enter into practice. This overabundance of physicians willing to enter the

market would allow hospitals to choose between large quantities of physicians which will allow

them to fill their positions with higher quality physicians. This competition between physicians

for a limited number of medical positions increases the quality of the overall healthcare system.

In the United States this competition also allows medical schools to only take the best and

brightest of upcoming students. If a medical school only has 30 open positions for students and

has 300 applicants, they will be able to get higher quality applicants than if only 60 applicants

were available. This is the reason why medical schools in the United States have a high volume

of applicants, and medical schools can be highly selective. Many people wish to become

medical professionals, but do not get accepted into medical programs. If they were all selected

for medical programs the market would become flooded with physicians. Medical schools

function as a limiting agent and filter on the number of medical professionals entering into the

market.

Figures 2 and 3 show that within the last 15-20 years there have been little changes in the

demographics of healthcare providers. Physician to population ratios have been relatively stable

with an average of 2.26 doctors for every 1000 population in the United States, and a current

ratio of 2.4 doctors through 2003 and 2004.

Likewise, the nurse to population ratio has been

stable with and average of 7.74 nurses for every thousand population, and a current trend since

OECD Health Data Set 2006

1995 of 7.8 nurses per 1000 population (medical professionals are discussed further in chapter

3).

High price-setting increases economic inefficiency (represented by the yellow area on

Figure 4), decreases access (represented by the grey area on figure 4) and creates larger

competition, which can increase the quality of healthcare. The surplus supply of doctors—due to

both lowered access and an increased willingness to enter into the market caused by high

returns—leads to more competition for patients between general practitioners and hospitals

(represented by the combination of the grey area and blue area). These two areas, the grey and

blue, do not represent the total number of medical providers in the market. They represent the

number of medical providers willing to enter the market. Hospitals and doctors must compete

with each other for a “limited” number of patients that can afford treatment; this competition can

drive an increase in quality to persuade consumers to use one service over another. Rather than

reduce prices which would increase demand with the ability to pay, but diminish overall profits,

doctors and hospitals will focus on increasing quality of care to gain consumers, not the

reduction of price. This occurs because, as discussed earlier about hospital profits, a small

decrease in price does not increase the quantity demanded at an equal rate, which means doctors

and hospitals can actually increase profits by serving fewer patients. Individual doctors can

increase their share of the market of patients by increasing their reputations, or by creating deals

with insurance providers, which can have a mild effect on lowering price. Patients rarely know

the cost one physician charges over another because they rely on insurance providers to make the

payments for them, which means that if one physician lowers his or her price consumer demand

will not increase. The only option to increase consumer demand for one physician over another

OECD Health Data Set 2006

is through the quality of care provided. Demand for one physician over another will increase by

insurance providers as price is lowered, which has caused variable pricing to take effect in the

United States. Often, physicians will charge insurance providers less for services than

individuals without insurance (further discussion on variable pricing and insurance will be made

in the section on the U.S. healthcare system). Theoretically, these free-market healthcare

systems lead to high costs, lowered access and high quality of care.

The Single-Payer Healthcare Markets

Single-payer systems (a system in which the government directly controls funding of

healthcare), or government run competitive pooling systems (payroll insurance pooling systems)

remove the ability of providers to become price-setters. Either providers take the price offered

by the single-payer or do not receive compensation—providers then become price-takers, in

place of price-setters. Single payer systems (both universal and socialized healthcare) generally

integrate legal provisions that ensure healthcare for all citizenry, which eliminates the Da

demand curve completely. Single-payer systems allow the government to do the price-setting.

Generally, the form of decision making in the price-setting methods of a government determines

the overall functionality of the system. Governments that run both the provision of healthcare

and the financing of healthcare will tend to set prices as close to the supply at cost (Sc) as

possible. If all decisions are made by the government, without negotiation with healthcare

providers, which is often the case when government runs both the provision of healthcare and the

financing of healthcare for its citizens, then the supply at cost becomes an important variable.

When the government knows the actual cost (Sc) of every procedure the price will be set as close

as possible to that price, despite the supply of doctors being too low to meet the theoretical

demand at that given price. If the government sets price too low, or too close to Sc wait lists will

accrue (QDt – QP-), economic efficiency will increase (and can lead to government savings from

P(Dt=Sp)), but quality will be suspect. As can be seen by the grey area on figure 5, when price

is set closer to Sc, and below Sp, wait lists will accrue due to a lack of medical providers. And,

the green area illustrates the money saved by the government. The United Kingdom gives a

good example of this occurring. Prices were set much lower ten years ago than they are

currently set, and the government has been attempting to introduce more price negotiation into

their healthcare market.

In the cases where medical providers are allowed to negotiate with government for the

setting of price (usually when hospitals are privately owned and operated) prices may be

artificially inflated. When governments do not run the hospitals they are less likely to know Sc,

which requires them to rely on the medical providers for negotiating with the price-setting.

Because of imperfect knowledge on the part of government, healthcare providers can negotiate

higher prices than in systems where government has substantial knowledge about the cost of

healthcare provision. If price is set high (P+) the system will be economically inefficient,

theoretical demand (Dt) will be fully met, and a surplus of provision (and thus higher quality)

can be achieved. The yellow area in Figure 5 shows the amount of money wasted (if the

economically efficient point is P(Dt=Sp)), and the blue area shows the surplus in medical

provision, which increases competition and quality. Theoretically it is possible to set the price

where theoretical demand meets the supply of doctors. If price is set at this point where the

theoretical demand matches the supply of doctors (P(Dt=Sp)) the system will be economically

optimal, fully supply for the theoretical demand, but the quality of healthcare will not be

guaranteed. In theory, if government both funds and operates the provision of healthcare the

price will be set closer to Sc (however, governments are not only concerned with costs of

healthcare, they are also concerned with quality, which has led to many reforms in socialized

healthcare systems to help stimulate quality). But, when government only runs the funding of

healthcare and provision remains private, the price will be set higher than P(Dt=Sp), but still

lower than in a free-market system where price is set by providers.

Conclusions

A free-market healthcare system allows medical providers to become price-setters. Price-

setting allows for high profits which stimulates higher quality of care, but decreases access to

healthcare. This system is characterized by massive amounts of economic inefficiency, high

quality, and decreased access. A socialized healthcare system, because of its knowledge about

the cost (Sc), will set prices as close to Sc as possible, which will decrease quality and create

waitlists. This system is characterized by guaranteed access to medical care; however waitlists

create problems of access to care, increased economic efficiency, and decreased quality. A

universal healthcare system, due to imperfect information of the part of government, will have to

negotiate the price for healthcare which allows medical providers to receive higher payments and

stimulates higher quality of healthcare. This system is characterized by increased quality, full

access with short wait periods, if any exist, and a moderate degree (when compared to free-

market systems) of economic inefficiency. This creates three different forms of price-setting; the

free-market system price is set by medical providers, the socialized system price is set by

government, and the universal system price is negotiated by medical providers and government.

The next chapter analyzes aggregate data on thirty OECD countries in relationship to the market

models created in this chapter, to test whether or not these models provide a real representation

of the market forces that are taking effect on the healthcare systems.

Figures and Tables

Figure 1: General Supply and Demand Structure of Healthcare if Healthcare Functioned

Like a Normal Market

Figure 2: Active Physicians by Medical Education

Source: Blue Cross Blue Shield 2007

Figure 3: Number of Medical Personnel in the United States

Source: OECD Health Data Set 2006

Figure 4: Provider Price-Setting

Figure 5: Government Price-Setting/ Da is Obsolete

CHAPTER 3: EVALUATING HEALTHCARE SYSTEMS

All three factors (access, quality, and economic efficiency) must be discussed when

evaluating any healthcare system. As my models of healthcare systems show there is no way to

balance all three factors perfectly. To guarantee high quality care economic efficiency must be

sacrificed, to guarantee access government must control price-setting and price must be higher

than the cost of the actual services provided. And, economic efficiency and full access cannot be

reached through a free-market even if a high quality system can be maintained. How well a

healthcare system is functioning is largely determined by the viewpoint of the person evaluating

the system. If economic efficiency is most important, then a system that sets price as close to Sc

as possible will be viewed as superior to other systems. If quality is most important, then a free-

market system, or possibly an overpriced single-payer system will be viewed as superior to the

other systems. And, if access is most important, then a single payer system that is economically

inefficient is superior to all other systems. These market models have been tested using various

aggregate variables from thirty OECD countries.

Methodology

The following analyses of the thirty OECD countries’ healthcare systems will use various

forms of aggregate level data to evaluate the quality, economic efficiency, and access in each

system. Life expectancy is both a function of quality of healthcare, and access to healthcare (as

well as various life-style choices). I argue in this analysis that the higher the quality of

healthcare and the higher the access to healthcare the longer the life expectancy, with all other

factors being constant. Thus, aggregate data should show that as per capita expenditure on

healthcare increases life expectancy should increase. However, overpriced healthcare markets

should also have lowered life expectancies due to decreased access. Therefore, there should also

be a decrease in life expectancies in countries’ whose markets are at the highest levels of per

capita expenditure on healthcare. Infant mortality rates should share an inverse relationship to

life expectancy and per capita expenditure. As expenditures increase infant mortality rates

should decrease, but infant mortality rates should again increase once per capita expenditure

becomes too high and lowers access. Spending on healthcare is used to evaluate the economic

efficiency of the system. The OECD Health Data Set 2006 available online at www.OECD.org

contains data on the health systems of thirty different countries. Data for analysis were taken

from the most recent year. If data for an individual country were not available for 2006 the most

recent previous years’ data were used. Per capita expenditure is based on PPP (purchasing

power parity) in U.S. dollars. PPP allows for the values to represent actual costs in each market,

differing currency values have already been accounted for. All bar charts are ranked from

highest overall life expectancy at the top to lowest life expectancy at the bottom. The OECD

Health Data Set 2006 reports healthcare expenditures in only certain areas:

Total expenditure on health is defined as the sum of expenditure on activities that –

through application of medical, paramedical, and nursing knowledge and technology –

has the goals of:

- Promoting health and preventing disease;

- Curing illness and reducing premature mortality;

- Caring for persons affected by chronic illness who require nursing care;

- Caring for persons with health-related impairments, disability, and handicaps who

require nursing care;

- Assisting patients to die with dignity;

- Providing and administering public health;

- Providing and administering health programmes [sic], health insurance and other

funding arrangements.

With this boundary, general public safety measures such as technical standards

monitoring and road safety are not considered as part of expenditure on health.

Activities such as food and hygiene control and health research and development are

considered health-related, but are not included in total health expenditure. Expenditures

on those items are reported separately in the chapter on health-related functions.

Some expenditures not related directly to prolonging life are included in the OECD data, but

others such as elective cosmetic surgery, are not included. This distinction is important lest it be

argued that the United States has high per capita expenditures on healthcare primarily due to

elective non-life prolonging procedures and services, such as increased expenditures on plastic

surgery. Expenditures on healthcare education are also not included in the data set, which

includes the educating and training of healthcare professionals.

Aggregate Data

So, how do the different models of healthcare markets hold up to the aggregate level

data? Life expectancy is the most readily available aggregate level data to judge a healthcare

system; the life expectancy of a country is determined by the quality of healthcare, access to

OECD 2007, Definitions

healthcare and lifestyle choices, but which factors are most important? If quality of healthcare

were determined solely by financial resources, then it would be reasonable to believe that the

more money per capita spent on healthcare should increase the overall quality of the system,

which would increase life expectancy. However, Figure 6 demonstrates that per capita

expenditure does not solely determine life expectancy. The data suggests that life expectancy is

increased to a certain point by expenditure, but that many countries spend more money than is

necessary to increase life expectancy. The examples of Luxembourg and the United States

clearly show that, as far as life expectancy is concerned, there is a large amount of economic

waste. The large per capita expenditures on healthcare in the United States and Luxembourg,

with only moderate total life expectancies demonstrate clearly that these countries are not getting

the outcomes in life expectancy that one would predict given their extremely high expenditures.

According to the above market models of healthcare, a country with a free-market healthcare

system will have high expenditures and a lowered life expectancy due to lowered access (life

style factors will be discussed later). A country with a socialized healthcare system will have

low expenditures, guaranteed access, but will also have a lowered life expectancy due to waitlists

and a decreased quality. And, a country with a universal healthcare system will have increased

per capita expenditures, and an increased life expectancy due to high quality and full access.

This means that, according to the models, countries with low expenditures on healthcare should

have decreased life expectancies due to lowered quality and lowered access, and countries with

high expenditures should have lowered life expectancies due to decreased access, despite high

quality. Countries with expenditures in the middle of the spectrum should have the highest life

expectancies due to full access, and high quality. Table 2 shows the predicted relationship

between per capita expenditures on healthcare and total life expectancy if the market models are

functioning the way predicted. A linear regression analysis and a quadratic regression analysis

were performed for total life expectancy and per capita expenditure. The linear regression was

performed to test whether or not the relationship was linear: as expenditures increase does life

expectancy increase? And, to show that the relationship between per capita expenditure on

healthcare and life expectancy is quadratic and not linear as some have argued (such as Cutler,

Dranove and Robinson). It has been argued that the overall relationship is that as expenditures

increase the quality of healthcare increases, and the United States is merely an outlier that does

not conform to the rest of the world. The quadratic regression was performed, to test whether or

not life expectancy was determined by expenditures in the manner suggested by the healthcare

models; as expenditures increase does life expectancy increase? And, when expenditures reach

the highest spectrum does life expectancy decrease? The relationship between life expectancy

and per capita expenditure is either only linear or it is quadratic and will also show both a

quadratic and a linear relationship. If the relationship is only linear the market models in the last

chapter are incorrect, and the more money spent on healthcare the higher the life expectancy, and

access is not limited by high expenditures on healthcare. But if the relationship is both linear and

quadratic the models are correct in that as expenditures increase life expectancy increases, until

the point where expenditures become too high and start decreasing access and thus overall life

expectancy. SPSS provided the following linear regression analysis for per capita expenditure

and total life expectancy (Table 3). The linear regression for life expectancy and per capita

expenditure appears to hold up well, with an R² of 0.314, and a significance value of 0.001.

However, the linear regression only has a regression coefficient of 0.001—the regression shows

that for every dollar increase in per capita expenditure there is a 0.001 year increase in the total

life expectancy on average. For example the United States, given its per capita expenditure on

healthcare of $6102, would have a life expectancy of 81.497 years. And, a country in the middle

of expenditures, like Germany with expenditures of $3034 per capita, would have a life

expectancy of 78.429 years. The linear regression is only taking account of the increases in

healthcare quality caused by increasing per capita expenditure. According to Pollock:

If the magnitude of the PRE statistic [R²] is less than .1, then the relationship is weak; if it

is greater than .1 but less than .2, then the relationship is moderate; if it is greater than .2

but less than .3, then the relationship is moderately strong; and if the magnitude of the

PRE statistic is greater than .3, than the relationship is strong. […] In the analysis of

social science data, especially survey data, large PRE magnitudes (of say, .5 or above) are

uncommon.

According to Pollock’s assessment the linear relationship between per capita expenditure and life

expectancy is moderately strong. There is support for the fact that as expenditures increase total

life expectancy increases. However, the market models above showed that life expectancy

should decline despite high expenditures if access were lowered. When a quadratic regression is

computed (as my market models suggest that life expectancy at both ends of the expenditure

spectrum will have lowered life expectancies, see table 2) the data seems to be more profound.

The R² of .710 shows that 71 percent of the variation in life expectancy is accounted for by

considering quality (as a function of expenditure) and access (increased access as expenditure

increases to a point where access is then decreased due to high costs), and with significance

values of .000 shows that all variables are statistically significant, and the relationship is far

stronger than the linear relationship—so strong in fact, that this R² magnitude of .71 is very

uncommon. The linear regression is only picking up one aspect of the variation caused by

Pollock 2005, pg 148

increasing expenditures, whereas, the quadratic regression is picking up the variation at both

ends of the healthcare expenditure spectrum. As can be clearly seen on Figure 7 the quadratic

regression is a better fit to the data and offers much greater predictive capabilities. Furthermore,

when the poorer countries (The Czech Republic, Slovak Republic, Poland, Mexico, Turkey,

Hungary, and Korea) are removed from the data set the linear regression only has an R² of only

.009 and a significance value of 0.678. No linear relationship exists once these poorer countries

are removed from the data set. When poor countries that do not spend much on healthcare are

removed from the equation no linear relationship between per capita expenditure and life

expectancy exists, in fact the linear regression shows that as spending increases life expectancy

changes at a rate of 0.000. Whereas, a quadratic relationship still holds true with an R² of .302

and significance values of .014 and .010. Figure 8 visually demonstrates this complete lack of a

linear relationship between per capita expenditure and life expectancy.

This is the quadratic equation for per capita expenditure and life expectancy when all

countries are included:

(1)

Predicted Life Expectancy = 70.775yrs + .005yrs (Per Capita Expenditure) – .00000066yrs (Per

Capita Expenditure)²

Equation 1 shows a base life expectancy in the thirty OECD countries of around 70.8 years and

that for every dollar of per capita expenditure life expectancy is increased by .005 years until the

point where the per capita expenditure squared and multiplied by .00000066 years decreases life

expectancy by becoming larger than the increase in life expectancy caused by the increase in

expenditure. Using equation 1 it is possible to predict the life expectancy of a country based on

its expenditures extremely well. Table 5 shows the per capita expenditures on healthcare, the

predicted life expectancies for all thirty OECD countries based on equation 1, the actual life

expectancies in each country, the difference between the predicted life expectancy and the actual

life expectancy, and the type of system. The mean life expectancy for each system type and the

mean difference in life expectancy from the predicted life expectancy are provided. Universal

healthcare systems have a mean life expectancy of 79.45, socialized healthcare systems have a

mean life expectancy of 77.51, and free-market healthcare systems have a mean life expectancy

of 76.7. A quadratic regression was performed for life expectancy and per capita expenditure on

healthcare for all three system types, and the results are provided in table 6. The regression was

found to be insignificant when dealing with universal healthcare systems, but extremely strong

and significant for socialized and free-market healthcare systems. Examination of the scatter

plot for universal healthcare systems shows an accumulation of countries at around the $3,041

(Netherlands) to $3,159 (France) per capita expenditure point, and a life expectancy range of

78.6 (Germany, second lowest in healthcare expenditures of the six countries) to 80.3 years

(France, highest in expenditures of the six countries). Six of the twelve universal healthcare

systems are all within a $118 range and 1.7 year life expectancy range. This accumulation of

data points around the same values of per capita expenditure and life expectancy has rendered

the regression statistically insignificant. However, this tendency for universal healthcare systems

to converge in similar values is enlightening. It demonstrates that universal healthcare systems

tend to negotiate similar prices for healthcare, and maintain similar outcomes in terms of life

expectancy at these negotiated prices. Figure 9 shows the scatter plots for per capita expenditure

and life expectancy by system type. The average life expectancy for each system type is

represented by the black line and the red lines are the quadratic regressions. Figure 10 separates

the quadratic regression of per capita expenditure on healthcare and life expectancy by the type

of healthcare system. Universal healthcare systems accumulate around the center of the

regression, and free-market and socialized systems are spread out through the regression.

Figure 11 visually shows an overlay of the quadratic regression of per capita expenditure

and life expectancy and the market models (provider price-setting, Figure 4, and single-payer

systems, Figure 5) discussed in the previous section. As per capita expenditure increases life

expectancy increases, but once per capita expenditure reaches around four thousand dollars per

capita, life expectancy begins to decrease. This overlay clearly shows the effects of increasing

expenditure increasing the overall quality and access to healthcare and thus the life expectancy,

and the effects of overly inflated medical costs at the upper spectrum of per capita health

expenditures decreasing access and thus overall life expectancy. Japan remains an outlier with

low expenditures and high life expectancies. According to equation 1, Japan, given its

expenditures on healthcare should have a life expectancy of around 78.68, but in actuality has a

life expectancy of 82.1 years. However, the quadratic regression does not account for life style

factors, and Japan appears to have an increased life expectancy due to these lifestyle factors (diet

and exercise). The life expectancy of Japan should be lower given their per capita expenditures

on healthcare, but some other variable is increasing their life expectancies. In theory, as stated

earlier, life expectancy is a function of quality of care, access to care, and life style choices. The

quadratic regression is a function of quality of care and access to care, the remaining differences

in life expectancy should be due to life style factors. In other words, the quadratic regression

takes account of the effects on life expectancy due to variations in per capita expenditure as a

function of access and quality of care.

The quadratic regression accounts for most of the variation due to quality and access, so

it appears that the life style factors are having a great effect on Japan’s life expectancy. Japan

has a universal healthcare system with guaranteed access to healthcare. The quadratic regression

may not be picking up on the increased quality of care in Japan, as it does in other countries.

Japan has an extremely elevated life expectancy due to the quality of its system despite

expenditures. One reason for this increased quality of care in Japan is that it has the highest

levels of high technology in their healthcare system with the United States coming in second. It

would be reasonably argued that this access to high tech machinery is increasing the quality of

the healthcare system despite any lowered competition from lowered expenditures. Figure 12

suggests that Japan can afford high technology that other countries cannot and that the quality of

healthcare in Japan is higher than other countries with the same expenditures. However, it is not

the purpose of this thesis to explain the variations of life expectancies in every country; it is only

to show that the markets are functioning in the manner laid out by the market models in the

previous chapter. Despite Japan being an outlier, the healthcare market models in the previous

section can explain 71 percent of the variation in life expectancy between countries (with the

remaining 29 percent most likely linked to life style choices, and some other minor differences

between each country’s healthcare market not being accounted for purely as a function of

expenditure.

However, the case of Japan brings up another important variable into the model. It is

necessary to examine the changes in life expectancy based on life style variables. The OECD

health data set contains data on alcohol consumption, the percent of population that is obese, the

percent of the population that is overweight, and tobacco consumption. A linear regression

analysis was performed for all four variables and total life expectancy resulting in none of the

variables being statistically significant. All four life style factors had random effects on the life

expectancy of a given country. However, when poorer countries were removed from the data

set, alcohol consumption, obesity and overweight did become statistically significant. This is

most likely due to these life style factors being linked to wealthier countries. It takes money to

consume alcohol, and large amounts of food. Poorer countries will have decreased life

expectancies due to low quality of care and low access to care, but will not have “wealthy” life

style factors decreasing their life expectancy. In other words, wealthy countries should have

higher rates of obesity, and alcohol consumption due to the ability to purchase alcohol and food

products than poorer countries. Poorer countries will exhibit lowered life expectancies due to

lowered access and quality of care, and wealthier countries should exhibit lowered life

expectancies due to an increased level of obesity and alcohol consumption. These life style

factors are having an effect on the life expectancy when controlling for the wealth of the country.

Next all four variables were used in linear regression analyses with per capita expenditure

to test if their effects were influencing expenditures. In other words, were the effects of these

life style factors influencing the costs of healthcare? If so, could they be causing a spurious

relationship between per capita expenditures on healthcare and total life expectancy? It would be

reasonably predicted that as the number of smokers, alcohol consumption, number of overweight

and number of obese population increased that per capita expenditure on healthcare should

increase to pay for related health services. Countries with high values of these variables should

have increased per capita expenditures. This may be causing the observed relationship between

per capita expenditure on healthcare and life expectancy—poor countries would have decreased

life expectancies due to decreased quality and access to care, and wealthy countries would have

decreased life expectancies due to an increase in negative life style choices that can only be

afforded by the wealthy which would cause an increase in healthcare expenditures. However, no

such relationship exists between countries. None of the variables were statistically significant in

any way even when controlling for the wealth of the country. As the number of smokers, the

number of obese, the number of overweight, and alcohol consumption increased, even when

controlling for the wealth of the country, there was no statistically significant change in the per

capita expenditures for healthcare. In fact, the data showed that as the number of smokers

increased that the per capita expenditure on healthcare decreased (however, it was not

statistically significant). The relationship between per capita expenditures and life expectancy

cannot be viewed as spurious, because even when controlling for the wealth of a country there is

no significant change in per capita expenditures due to increasing values of the life style factors.

Based on these analyses it could be reasonably argued that the effects of life style factors on life

expectancy are accounted for by the remaining 29% variation in life expectancy that is not

accounted for by the quadratic regression of per capita expenditure on healthcare and life

expectancy. Basically the quadratic regression is accounting for the difference in life expectancy

due to the quality and access to healthcare as a function of per capita expenditure on healthcare

(71%), and the remaining variation (29%) is attributed to the difference in life style factors. The

observed relationship between per capita expenditure and life expectancy is not spurious. If the

relationship between life expectancy and per capita expenditure were spurious then the data

would show that the countries spending the most on healthcare per capita would be those with

the highest rates of obesity, overweight population, alcohol consumption, and tobacco

consumption. These high rates of life style factors should increase per capita expenditures and

decrease life expectancies. This is not the case—life expectancy is decreased but per capita

expenditure is not increased. Therefore, obesity, smoking, being overweight, and consuming

alcohol do decrease life expectancy, but are not the cause for increased expenditures on

healthcare. The countries paying the most for healthcare are not the countries with the highest

levels of these negative life style factors, if they were it could be argued that this was the reason

why wealthy countries had decreased life expectancies and increased expenditures. But, this is

not the case, and it is not supported by any of the data.

Furthermore, Figure 15 adds more support for the market models. Low expenditures

yield higher infant mortality rates due to lowered quality and access and high expenditures

increase infant mortality rates due to decreased access (See table 2). The quadratic regression

shows that 49 percent of the variation in infant mortality rates is due to expenditures on

healthcare. This is the quadratic regression equation for infant mortality and per capita

expenditure:

(2)

Predicted Infant Mortality Rate = 16.928deaths - .008deaths*(per capita expenditure) +

.00000103deaths*(per capita expenditure)²

Equation 2 can be used to estimate the number of infant mortalities per 1000 live births. The

relationship, according to Pollock is strong (despite being weaker than that of total life

expectancy), and adds further support that the healthcare market models give an accurate

description of the processes taking effect in healthcare systems. An examination of three causes

of death showed the same relationship with per capita expenditure. However, the diabetes death

rate and respiratory death rate were found to be statistically insignificant. Cerebrovascular death

rates mirrored the predicted outcomes as infant mortality rates. Death rates should be higher for

countries spending too little money due to poor quality and waitlists and should also be higher at

the upper spectrum of per capita expenditure due to decreased access, with the lowest rates in the

middle of the per capita expenditures. Even though diabetes and respiratory disease death rates

were insignificant statistically they also followed the predicted pattern which is seen in figure 16.

The quadratic regression for per capita expenditure and cerebrovascular deaths had an R² of .511

which means that fifty-one percent of the variation can be accounted for as a function of per

capita expenditure on healthcare, which according to Pollock is an extremely strong relationship.

Lastly, it would be predicted that as expenditures increase the total number of physicians

should increase to meet the increased demand for healthcare due to increasing access. And,

when access becomes limited due to high costs the number of physicians should begin to

decrease again to match the demand. The number of practicing healthcare professionals can be

used as a gauge for the levels of access to healthcare. If access to healthcare is being increased

through laws and funding, then the number of practicing healthcare professionals should increase

as the number of healthcare consumers increase. And, if access is being limited by the price

becoming too high, then the number of practicing healthcare professionals should decrease to

meet the demand with the ability to pay for services as it decreases (Da). Figure 16 shows that

this relationship holds true.

The quadratic regression for total number of physicians and nurses and per capita

expenditure has an R² value of .415, which shows that forty-two percent of the variation in the

number of healthcare professionals per 1000 population is due to per capita expenditures on

healthcare. The R² for physicians is .257, and for nurses .493. Once again, according to

Pollock’s assessment these would be extremely strong relationships.

[Figure 18]

Figure 18 breaks down the quadratic regression of medical providers and per capita expenditure

on healthcare by the type of system. Once, again universal healthcare systems show up

predominately toward the middle of the regression in terms of the number of healthcare

professionals, and free-market and socialized systems are interspersed throughout the regression.

If life expectancy is partially determined by access to healthcare then there should be a

linear relationship between the number of medical professionals and life expectancy. Figure 19

clearly supports this assumption. The number of physicians has an R² of .111, but it only has a

significance value of .072 which is right on the cusp of being significant. The number of nurses

has an R² of .253 and is significant. The number of physicians and nurses combined (total

number of healthcare professionals) has an R² of .283, and is also significant. There is definitely

a causal relationship between life expectancy and the number of healthcare professionals. And,

there is a causal relationship between per capita expenditures and the number of healthcare

professionals. Therefore, the quadratic regression for per capita expenditure on healthcare and

life expectancy is a good proxy for the access and quality in the system.

Furthermore, the quantity of high technology goods should increase as profits for these

goods increases. However, unlike with physicians there should not be a decrease in the number

of high technology goods due to decreased access, because as discussed in chapter 2 hospitals

without a population large enough to support the use of these goods will still purchase them and

then pass the extra expense onto the local population that uses them. Figure 18 shows that this

assumption from the model in chapter 2 is also correct. The levels of healthcare professionals

show an increase as per capita expenditures increase and then a decrease when expenditures

become too high. These levels are following exactly the predicted pattern of increasing and

decreasing access from the models in chapter 2. And, the levels of high technology goods are

also following the predicted pattern. Figure 21 is an overlay of both the quadratic regression for

per capita expenditure on healthcare and life expectancy, and the quadratic regression for per

capita expenditure and the number of practicing healthcare professionals per 1000 population.

As can be seen from the figure, the models from chapter 2 are accounting for both the changes in

quality of care and the changes in access to care. The quadratic regression for per capita

expenditure on healthcare and life expectancy is not due in any way to life style factors, and can

be considered a good measure of the quality of care and access to care in a healthcare system.

Conclusions

The market models from chapter 2 hold up extremely well under the examination of the

aggregate data. The aggregate data are nearly irrefutable—the quadratic regressions of life

expectancy, infant mortality rates, and rates of deaths by certain diseases fully support the

hypothesis that as spending on healthcare increases life expectancy will increase and infant

mortality and deaths by disease rates will decrease. And, when spending becomes too high,

access will become limited and life expectancy will decrease and infant mortality and deaths by

disease will increase. Life style factors do affect life expectancy, but do not affect per capita

expenditures, thus ruling out any spurious relationship (the countries spending the most on

healthcare are not those with the highest levels of smoking, obesity, overweight population, or

alcohol consumption). The number of practicing physicians exactly mirrors the predicted pattern

and can be used as an overall proxy for access to healthcare—it also shows that the use of total

life expectancy is a good proxy for the combination of quality of care and access to care.

Furthermore, universal healthcare systems tend to accumulate toward the center of the

regressions, suggesting that negotiations are causing them to balance supply and demand.

Whereas, socialized systems are more interspersed throughout the regressions suggesting that

price setting is taking place in a haphazard manner. And, free-market systems are placed at the

extremes of the regressions. Given this information, it is clear that healthcare cannot be

considered a normal good, and the market cannot cause supply to meet the theoretical demand

and set an appropriate price for healthcare. If the market cannot settle an appropriate price that

causes supply to meet the theoretical demand, which it cannot, then forced negotiations of price

is the next best system of price-setting. The following three sections turn to an examination of

three countries with divergent healthcare markets. The United States is discussed because it is

the prime example of a free-market healthcare system (and one of the only examples in the

developed world). The United Kingdom was chosen because it is often used as a case against

government financing of healthcare due to waitlists and poor customer service. The purpose of

choosing the United Kingdom is because of these perceived problems, which many consider a

fault of government intervention into the free-market. But, as the aggregate data have shown, the

perceived problems in the British system are actually caused by a lack of negotiation between

providers and consumers of healthcare. Surprisingly, the United Kingdom fares well when

discussing life expectancies. Lastly, Germany is discussed, not because it is the “best” system of

healthcare, but because it is the first universal healthcare system, and as such, has been a model

on how to run and finance healthcare that has been emulated the world over. If one were to

choose the best universal system for discussion based purely on the best fit for the universal

healthcare model Switzerland would be the obvious choice with healthcare expenditures of

$4077 per capita and a life expectancy of 81.2 years.

Figures and Tables

Figure 6: Per Capita Expenditure on Healthcare and Total Life Expectancy

Source: OECD Health Data Set 2006

Table 2: Relationship between Expenditures, Life Expectancy and Infant Mortality

Expenditures

High Middle Low

Life Expectancy

Middle Highest Lowest

Infant Mortality

Middle Lowest Highest

Table 3: Model Summary for Linear and Quadratic Regression of Per Capita Expenditure

and Life Expectancy

Model Summary and Parameter Estimates

Dependent Variable: Life Expectancy total population

.314 12.800 1 28 .001 75.395 .001

.710 33.132 2 27 .000 70.775 .005 -6.6E-007

Equation

Linear

Quadratic

R Square F df1 df2 Sig.

Model Summary

Constant b1 b2

Parameter Estimates

The independent variable is $ Per Capita.

Figure 7: Linear and Quadratic Scatter Plot All 30 OECD Countries

Source: OECD Health Data Set 2006

Table 4: Model Summary for Life Expectancy and Per Capita Expenditure (Wealthy

Countries Only)

Model Summary and Parameter Estimates

Dependent Variable: Life Expectancy total population

.009 .178 1 20 .678 79.598 .000

.304 4.150 2 19 .032 73.739 .003 -4.5E-007

Equation

Linear

Quadratic

R Square F df1 df2 Sig.

Model Summary

Constant b1 b2

Parameter Estimates

The independent variable is $ Per Capita.

Figure 8: Linear and Quadratic Scatter Plot of Wealthy Countries Only

Source: OECD Health Data Set 2006

Table 5: Predicted Life Expectancy and Type of System

Source: OECD Health Data Set 2006, and Calculations from Equation 1

Country

Per Capita

Expenditure

Predicted

Life

Expectancy

Life

Expectancy Difference Health System

Mean Life

Expectancy

Japan 2249 78.68 82.1 3.42 Universal

Switzerland 4077 80.19 81.2 1.01 Universal

Universal

Iceland 3331 80.11 81 0.89 Socialized 79.45

Australia 3120 79.95 80.6 0.65 Socialized

Sweden 2825 79.63 80.6 0.97 Socialized

Socialized

Spain 2094 78.35 80.5 2.15 Universal 77.51

France 3159 79.98 80.3 0.32 Universal

Canada 3165 79.99 79.9 -0.09 Universal

Free-Market

Norway 3966 80.22 79.9 -0.32 Socialized 76.7

Italy 2467 79.09 79.7 0.61 Universal

Austria 3124 79.95 79.3 -0.65 Universal

Mean

Netherlands 3041 79.88 79.2 -0.68 Universal

Difference

New Zealand 2083 78.33 79.2 0.87

Greece 2162 78.50 79 0.50 Socialized

Universal

Belgium 3044 79.88 78.8 -1.08 Universal 0.17

Finland 2235 78.65 78.8 0.15 Socialized

Germany 3043 79.88 78.6 -1.28 Universal

Socialized

United Kingdom 2508 79.16 78.5 -0.66 Socialized -0.43

Ireland 2596 79.31 78.3 -1.01 Socialized

Luxembourg 5089 79.13 78 -1.13 Universal

Free-Market

Denmark 2881 79.70 77.6 -2.10 Socialized 1.32

United States 6102 76.71 77.5 0.79 Free-market

Korea 1149 75.65 77.4 1.75 Free-market

Portugal 1824 77.70 77.4 -0.30 Socialized

Czech Republic 1361 76.36 75.8 -0.56 Universal

Mexico 662 73.80 75.2 1.40 Free-market

Poland 805 74.37 75.1 0.73 Socialized

Slovak R 777 74.26 74.1 -0.16 Socialized

Hungary 1276 76.08 72.8 -3.28 Socialized

Turkey 580 73.45 71.4 -2.05 Socialized

Figure 9: Life Expectancy and Per Capita Expenditure by System Type

Source: OECD Health Data Set 2006

Figure 10: Quadratic Regression by System Type

Source: OECD Health Data Set 2006

Table 6: Model Summary for Quadratic Regression by System Type

Figure 11: Quadratic Regression and Market Model Overlay

Source: OECD Health Data Set 2006 (For the Quadratic Regression)

Figure 12: Number of High Tech Units Per Million

Source: OECD Health Data Set 2006 (Some Data Missing from OECD Data Set)

Figure 13: Life Style Factors and Life Expectancy

Source: OECD Health Data Set 2006 (Minus Poorest OECD Countries)

Figure 14: Life Style Factors as an Explanation for Expenditures

Source: OECD Health Data Set 2006 (Wealthy Countries Only, No Variables Significant)

Table 7: Summary for Infant Mortality and Per Capita Expenditure Regression

Model Summary and Parameter Estimates

Dependent Variable: Infant mortality per 1000 births

.198 6.908 1 28 .014 9.747 -.002

.496 13.265 2 27 .000 16.928 -.008 1.03E-006

Equation

Linear

Quadratic

R Square F df1 df2 Sig.

Model Summary

Constant b1 b2

Parameter Estimates

The independent variable is $ Per Capita.

Figure 15: Linear and Quadratic Scatter plot of Infant Mortality and Per Capita

Expenditure

Source: OECD Health Data Set 2006

Table 8: Model Summary for Cerebrovascular Deaths and Per Capita Expenditure

Model Summary and Parameter Estimates

Dependent Variable: Total Cerebrovascular deaths per 100,000

.511 8.876 2 17 .002 182.905 -.068 7.67E-006

Equation

Quadratic

R Square F df1 df2 Sig.

Model Summary

Constant b1 b2

Parameter Estimates

The independent variable is $ Per Capita.

Figure 16: Complex Disease Deaths and Per Capita Expenditure

Source: OECD Health Data Set 2006

Table 9: Model Summary for Per Capita Expenditure and Healthcare Professionals

Model Summary and Parameter Estimates

Dependent Variable: Physicians per 1000

.257 4.666 2 27 .018 1.498 .001 -1.5E-007

Equation

Quadratic

R Square F df1 df2 Sig.

Model Summary

Constant b1 b2

Parameter Estimates

The independent variable is $ Per Capita.

Model Summary and Parameter Estimates

Dependent Variable: Nurses per 1000

.493 13.151 2 27 .000 -.037 .005 -5.6E-007

Equation

Quadratic

R Square F df1 df2 Sig.

Model Summary

Constant b1 b2

Parameter Estimates

The independent variable is $ Per Capita.

Model Summary and Parameter Estimates

Dependent Variable: Total # of doctors and nurses per 1000

.415 7.101 2 20 .005 -6.561 .010 -1.2E-006

Equation

Quadratic

R Square F df1 df2 Sig.

Model Summary

Constant b1 b2

Parameter Estimates

The independent variable is $ Per Capita.

Figure 17: Healthcare Professionals and Per Capita Expenditure

Source: OECD Health Data Set 2006

Figure 18: Medical Professionals Quadratic Regression by System Type

Source: OECD Health Data Set 2006

Table 10: Model Summary for Number of Healthcare Professionals and Life Expectancy

Model Summary and Parameter Estimates

Dependent Variable: Life Expectancy total population

.111 3.496 1 28 .072 75.231 1.017

Equation

Linear

R Square F df1 df2 Sig.

Model Summary

Constant b1

Parameter Estimates

The independent variable is Physicians per 1000.

Model Summary and Parameter Estimates

Dependent Variable: Life Expectancy total population

.253 9.483 1 28 .005 75.370 .348

Equation

Linear

R Square F df1 df2 Sig.

Model Summary

Constant b1

Parameter Estimates

The independent variable is Nurses per 1000.

Model Summary and Parameter Estimates

Dependent Variable: Life Expectancy total population

.283 10.673 1 27 .003 74.391 .338

Equation

Linear

R Square F df1 df2 Sig.

Model Summary

Constant b1

Parameter Estimates

The independent variable is Total # of doctors and nurses per 1000.

Figure 19: Number of Healthcare Professionals and Life Expectancy

Source: OECD Health Data Set 2006

Figure 20: High Technology and Per Capita Expenditure

Source: OECD Health Data Set 2006

Figure 21: Quadratic Regressions for Medical Professionals and Life Expectancy Overlaid

on Model

Source: OECD Health Data Set (For Quadratic Regressions Only)

CHAPTER 4: THE UNITED STATES

The difference between the United States and the rest of the developed world is in the

identity of the price-setters. Because the United States uses the free-market to provide for most

aspects of its healthcare system price controls cannot be managed on a system wide level. The

United States remains an outlier only in how it chooses to finance healthcare, the actual market

forces taking place on the U.S. healthcare system are the same as those in every other developed

healthcare system.

Private insurance, usually provided by employers, is the main financing mechanism for

healthcare in the United States:

In 2001, 65 percent of employers offered health insurance benefits to their employees. Of

Americans with employer-based health insurance in 2001, the majority (48 percent) are

insured through preferred-provider organizations. Preferred-provider organizations are a

type of managed care in which incentives (e.g., lower copayments) to individuals who

use these providers. […] Twenty-three percent of Americans are enrolled in health

maintenance organizations (HMOs). Individuals enrolled in HMOs pay a monthly

premium and a small coypayment, usually around $10, for each visit and prescription.

Most HMOs provide members a wide range of preventative and primary healthcare

services that emphasize behaviors and services that will reduce disease and disability and

avoid more costly care. Point-of-service plans allow a person to choose to receive

services from participating of nonparticipating providers, but benefits are usually more

limited if a nonparticipating provider is used. Of those employer-based health insurance,

22 percent had point-of-service plans in 2001. Only 7 percent of Americans with

employer-based health insurance had conventional health insurance plans, known as fee-

for-service or indemnity plans, in 2001.

However, the U.S. government does not rely solely on private methods for financing healthcare.

The U.S. has various forms of public financing of healthcare, the most commonly known of

which provides healthcare for the elderly population through the government called Medicare.

The other systems are Medicaid, Veterans Health Administration and worker’s compensation.

This creates two different healthcare markets in the United States. The Medicare program

functions similarly to a single-payer market, because it is a single-payer system. The life

expectancy of the elderly (those above age 65) in the United States for males is 16.8 years and

19.8 years for females. The average life expectancy for males in the advanced industrial

countries of the OECD is 16.67 years and for females 20.11 years. In other words, once the

United States government finances healthcare for the entire elderly population the life

expectancy mirrors that of every other single-payer healthcare system. The United States has

two healthcare markets, a free-market for the majority of the population and a single-payer

system for the elderly. The population in the United States has high life expectancies after the

age of 65, due to the guaranteed access to healthcare provided by Medicare. Figure 20 shows the

life expectancies after age 65 in order of total life expectancy.

The U.S. is lower on the chart which shows that it has a lower total life expectancy, but at

the same time its life expectancy for the elderly is much higher than its neighboring countries

with lower total life expectancies. Total life expectancy for the United States is one of the lowest

of all the industrialized OECD countries, but the life expectancy for those above the age of 65 is

Fried 2002, pg 74

Fried 2002, pg 72

almost exactly on average with all the OECD countries. This difference (the lower than OECD

average total life expectancy compared to matching the average OECD life expectancy for the

elderly) demonstrates the issue of access effecting life expectancy in the United States. Once

U.S. citizens reach the age of 65 they are guaranteed access, and with a high quality system their

life expectancies are increased. Total life expectancy in the United States is low, but the life

expectancy for the elderly in the United States is high when compared to the rest of the OECD

countries. The only factor that changed on a system wide level was the guaranteed access to

healthcare by the elderly (if life style factors are held constant for both the entire U.S. population

and the elderly population). Life style factors should remain constant in a given population (the

overall U.S. population is overweight; therefore the elderly population in the U.S. is probably

also overweight: Americans eat fatty foods; therefore, it is likely that elderly Americans eat fatty

foods). It is not likely that the increase in life expectancy is due to changing life style factors

(otherwise that would mean that a large number of the population on their 65 birthday happens to

decide to change their diet, exercise routines, and lose weight). It would be reasonable to assume

then, that the increase in life expectancy exhibited by the elderly in the United States is linked to

the biggest change that occurred in the overall system from the age of 64 to 65, namely

guaranteed access to healthcare. Figure 23 shows the uninsured in the United States by age

group. The effects of the market forces on the two separate American healthcare systems match

my market models if life style factors are held constant for the elderly population within the

United States. The United States is not an outlier and the market is functioning in the same

manner that it functions in every country, the difference is in the identity of the price-setter.

An examination of healthcare financing reveals the true nature of the inadequacies of

free-market financing of healthcare in the United States compared to the other OECD countries.

The red area on Figure 24 represents the amount of money spent annually by the government in

each country per capita, the blue area represents private expenditures which includes private

insurance, co pays, and charitable monies. The U.S. government currently spends annually

$2728 per capita on healthcare, and privately $3374 is spent annually per capita. The average

spent annually by public expenditure in all thirty OECD countries is $1862.90, and $2226.17

annually per capita when examining only the advanced industrial countries. The United States

government is currently spending more money per capita on healthcare than the average OECD

country—in fact, it is fourth highest for public expenditures per capita in the OECD. And, it is

currently spending more money per capita than the average of the advanced industrial countries

that provide healthcare for their entire populations. These data suggests that given current

expenditures in the United States, the government should be providing healthcare for the entire

population not just the elderly. It also means that if the government were to take over price-

setting in the medical system by creating a single-payer system additional expenditures would

not be necessary and the system currently has the funding, without raising taxes, to provide

healthcare for the entire population. The predicted life expectancy in the United States

according to equation 1 is 76.71 years and the actual life expectancy is 77.5 years. If the United

States, given current public expenditures of $2728 per capita on healthcare, were to take control

of financing of healthcare by instituting a universal healthcare system and continue spending the

same amount per capita on healthcare the predicted life expectancy for the country would be 79.5

years; a difference of two years. By changing how healthcare is financed, the United States

could theoretically increase the overall life expectancy of the entire country by two years. To put

this into context, Truth (a nonprofit organization against smoking, located online at

www.whudafxup.com) claims that 5.6 million years of potential life is lost each year in the

United States due to smoking.

With a population of 300 million, that amounts to .02 years off

the life expectancy of every American. If no one in the country smoked tobacco the life

expectancy of the U.S. population would only be increased by .02 years, but changing the

financing of healthcare would increase the life expectancy by 2 full years.

How is it possible that the U.S. government is already spending enough per capita to

provide healthcare for the entire population, but only actually be providing healthcare for the

elderly? The Medicare program (prior to the partial privatization of the program under the Bush

administration—which, according to my model, there is little wonder why the latest reports show

that the privatization of Medicare has actually increased costs) was able to price-set. Medicare

offered the same amount of money statewide for medical procedures, which was able to keep

costs lower than private insurance. However, due to the free-market system Medicare is still

being charged more than necessary if the government were to control the funding of the entire

medical system in the United States. For example, whereas insurance providers are charged $10

for a dose of Tylenol which actually only costs $1, Medicare is only charged $5 (not actual

amounts, values are created for demonstrative purposes only). Medicare is able to keep prices

lower than private insurance companies, by setting standard prices for all medical providers that

receive Medicare payments. A recent study by the state of Pennsylvania showed this exact

fact

. Medicare was charged a flat rate across the state, whereas insurance providers were

charged variable prices. The New York Times notes that:

The report by the Pennsylvania Health Care Cost Containment Council, a state agency,

provides a rare glimpse of such detailed information about hospital payments and patient

Truth 2007

New York Times June 14, 2007

outcomes. And the seemingly random nature of payments is striking. Although Federal

Medicare payments are largely fixed, they varied somewhat among Pennsylvania

hospitals surveyed. The far greater disparity involved commercial insurers, which must

negotiate their rates hospital by hospital.

Variable pricing occurs, because, as the New York Times notes, insurance providers are not given

information on what hospitals are charging other insurers. Every insurance company must

negotiate individually with hospitals for prices. Given their lack of information they are unable

to gain control over price in any reasonable manner. This lack of price negotiation by insurance

providers creates, which is seen in Figure 25, even more waste in the U.S. healthcare market, and

it further decreases access. Figure 25 shows the difference that private insurers are charged over

what the government insurers are charged. According to Blue Cross Blue Shield there were

2,984 non-profit hospitals operating in the United States in 2003, 790 for-profit hospitals and

1121 state and government hospitals.

The majority of hospitals in the United States are either

non-profit or government owned. No matter if a hospital is non-profit or for-profit hospitals are

charging more for services from private insurers than from government insurers in both

situations. The Pennsylvania Health Care Cost Containment Council (PHC4) stated in its report

on healthcare in the State of Pennsylvania that:

All but 22 of the 174 GAC [General Acute Care] hospitals [in the State of Pennsylvania]

functioned solely as non-profit organizations. All income or ‘profit’ from their

operations is retained within the organization. The primary uses of income are to fund

New York Times June 14, 2007, pg C4

Blue Cross Blue Shield 2007, pg 33

capital improvements, retire outstanding debt, and to provide a reserve in the event

revenues do not cover expenses in the future.

Whether hospitals are using profits to return to shareholders, or to fund capital improvements

and build reserves, they are still attempting to gain profits. Even non-profit hospitals are acting

in a profit-seeking manner. The PHC4 reports that private insurance paid an average of $10,306

per patient at inpatient discharge, and Medicare paid an average of $9,361 per patient at inpatient

discharge, for a difference of $945 per patient.

The PHC4 reports that, in 2006, 538,700

inpatients with private insurance were discharged.

The $945 payments per patient by private

insurance above Medicare payments multiplied by the number of privately insured discharges

shows that $509,071,500 was paid by private insurers over the costs that Medicare would have

paid. This $509 million came from the State of Pennsylvania alone. Medicare could have been

able to negotiate a difference of $509 million less than private insurance was able to do. The

United States spends $6102 per capita on healthcare, with a population of around 300 million,

which amounts to a total of $1.8 trillion dollars being spent on healthcare. If all 50 of the U.S.

states could each save the same amount that the State of Pennsylvania could have on inpatient

care alone, it would equal $25.45 billion in savings from current expenditure levels on inpatient

hospitalizations. $25.45 billion is 1.4 percent of the $1.8 trillion spent on healthcare in the

United Sates. Clearly price negotiations through government have the ability to decrease costs.

Thirty percent of U.S. healthcare expenditures went to hospital care.

The PHC4 reports that

62% of the money taken in by hospitals came from inpatient care.

Sixty-two percent of the

Pennsylvania Health Care Cost Containment Council 2007, pg 1

Pennsylvania Health Care Cost Containment Council 2007, pg 12

Blue Cross Blue Shield 2007, pg 37

Pennsylvania Health Care Cost Containment Council 2007, pg 7

30% equals 18.6% of the $1.8 trillion, leaving 81.4% of the money spent on healthcare in the

United States coming from areas other than inpatient care. If 1.4% can be saved in a sector of

the healthcare system that accounts for less than a fifth of overall expenditures, it is reasonable to

believe that the other four fifths could have similar savings, for a total savings of 7% just by

restructuring insurance to be provided by the government.

Private insurance companies cannot negotiate the lowered prices that the government

Medicare program negotiates. Private insurance companies wishing to make a profit, and

having little control over price, must create profits by denying claims, restricting the use of

expensive procedures and pharmaceuticals (variable co-pays on prescriptions are a primary

example), and flat out denying access to health insurance for those living with costly illnesses,

such as HIV, Juvenile Diabetes, and other long term illnesses. All these methods of profit

seeking by private insurance further decrease access, and, unfortunately, this decreased access is

usually felt most by those who need medical care the most (those with long term illnesses). The

free-market also gives incentives for medical providers to work primarily in the areas that can

earn the most money. Primary care physicians are actually in short supply:

Although certain specialties have an oversupply of physicians, many parts of the United

States are classified as ‘medically underserved areas.’ In fact, more than 46 million

people live in areas with shortages of primary health professionals, and 25 million live in

areas with shortages of dental health professionals.

Fried 2002, pg 77

These shortages in routine care further decrease access to healthcare and lower the total life

expectancy. Blue Cross Blue Shield notes that primary care physicians as a percentage of all

physicians is down to 58.5% in 2003 from 63.6% in 1990 and 66.2% in 1980.

Often the pharmaceutical industry is discussed when speaking of the U.S. healthcare

system. It has been argued that healthcare in the United States is more expensive because it is

subsidizing the healthcare systems of the rest of the world by paying for pharmaceutical

research.

Figure 26 shows that there may be some credibility to this argument. It is true that

the United States does pay more for pharmaceuticals than other OECD countries (OECD average

is $396, and the United States pays $751). Those costs account for a relatively large part of the

over expenditure on medical care in the United States. The U.S. is paying almost twice as much

as the OECD average, but the extra $355 per capita spent by the U.S. on pharmaceuticals only

accounts for about twelve percent of the total waste in the U.S. healthcare market (the U.S., as

stated earlier, pays roughly $3,000 more than the OECD average on healthcare, and pays $355

more on pharmaceuticals than the OECD average, the $355 amounts to 11.8% of the $3,000

being spent on healthcare over the OECD average). However, an examination of the

pharmaceutical industry shows that U.S. $31.477 billion was spent on research

and U.S.

$11.443 billion was spent on advertising.

To put this into context, if the U.S. population is 300

million and each person is paying $751 on pharmaceuticals yearly, then the total spent on

pharmaceuticals in the United States is $225.3 billion. The 11 billion dollars spent on

advertising represents 5 percent of the money spent on pharmaceuticals and the 31 billion dollars

spent on research and development represents 13.9 percent and cannot account for the high U.S.

Blue Cross Blue Shield 2007, pg 38

Schweitzer 1997

National Science Foundation, online at http://nsf.gov

Blue Cross Blue Shield 2007, pg 44

expenditures on healthcare. Obviously pharmaceutical research costs are not the reason for an

over-priced U.S. healthcare system, and the United States is not subsidizing the healthcare

systems of other countries. Figure 28 further shows the research and development expenditures

of all the OECD countries, which further demonstrates that the United States is not leading the

world in research and development costs.

In the end, the United States remains an outlier compared to other OECD countries

because of its absence of using government-run healthcare insurance, not because the market

forces are any different from the rest of the developed world. It is true, that if one has enough

money, the United States has one of the best quality healthcare systems in the world and access

is not limited. However, if one does not have the financial backing or insurance, the United

States may as well not even have a healthcare system. The wealthy countries of the OECD have

an average life expectancy of 79.39 years. The United States has an average life expectancy of

77.5 years. Most likely, (according to all the aggregate data in chapter 3) the decreased access to

healthcare in the United States is costing the entire population almost two years off of their total

life expectancy. Those 46,000,000 uninsured Americans (usually from the poorer classes in

society)

are most likely decreasing the total life expectancy of the entire country. The OECD

report on Income Inequality and Health states that:

With respect to physician utilization, need is more concentrated among the worse off, but

after ‘standardizing out’ these need differences, significant horizontal inequity favoring

the better off is found in about half of the countries, both for the probability and the total

United States Department of Health and Human Services

number of visits. The degree of pro-rich inequity in doctor use is highest in the US,

followed by Mexico, Finland, Portugal and Sweden.

These data seems to suggest one simple fact—the United States should restructure the financing

of healthcare, and by doing so, force negotiations between healthcare providers and healthcare

financers. Costs could be contained and reduced, and life expectancy could be increased by

increasing access to medical care. If a universal healthcare financing system were to be

implemented, overall costs should be reduced rapidly by removing variable pricing, decreasing

over-pricing in the system, and removing incentives for regional hospitals to buy expensive

equipment that it does not have the population to support (government can control the purchasing

of equipment on a population basis). If the Pennsylvania study holds true for the rest of the

country, then government should be able to decrease expenditures on healthcare by 7%, or $427

per capita overnight, and if it could also reduce the pharmaceutical costs to match those of the

rest of the OECD it could reduce per capita expenditure by another $355, for a total savings of

$782 per capita. Per capita expenditure could be reduced to $5320, which should also increase

access according to the market models in chapter 2, and the quadratic regression. Equation 1

predicts that the life expectancy of the United States with expenditures at $5320 would be 78.69

years, an increase of one year. However, such a policy would receive, and has received, great

resistance by healthcare providers, insurance providers, and high tech companies such as

pharmaceuticals. Profits would be reduced for all of those involved in the healthcare system,

access would be increased, and the quality (given that the United States government is already

paying the fourth highest in per capita public expenditures for healthcare) should remain very

high.

OECD 2004, pg 6

Figures and Tables

Figure 22: Life Expectancy after Age 65

Source: OECD Health Data Set 2006

Figure 23: Distribution of the Uninsured and Total U.S. Population by Age

Source: The United States Department of Health and Human Services

Figure 24: Healthcare Financing

Source: OECD Health Data Set 2006

Figure 25: Hospital Payments by Source of Funding

Source: Blue Cross Blue Shield 2007

Figure 26: Pharmaceutical Expenditures

Source: OECD Health Data Set 2006

Figure 27: Advertisement Expenditures by Pharmaceutical Companies

Source: Blue Cross Blue Shield 2007

Figure 28: Gross Domestic Expenditure on R&D (As a Percentage of GDP, 2005 or Latest

Available Year)

Source: OECD Factbook 2007

Figure 29: The Distribution of the Uninsured and Total U.S. Population by Income

Source: The United States Department of Health and Human Services (FPL= Federal Poverty Line)

CHAPTER 5: THE UNITED KINGDOM

The United Kingdom primarily provides healthcare through its National Health Service.

However, private insurance can be purchased. The NHS was created in 1948 to provide for all

of the health needs of the population.

The healthcare system in the United Kingdom is often

used as an argument against socialized healthcare. Originally the system was completely run by

the NHS, which set all prices and ran all hospitals. Previously the system followed the market

model on single-payer systems, which shows that governments that run both the funding of

healthcare and the provision of healthcare will set prices low, which will create waitlists and

lowered quality. Funding for the healthcare system has been based on general taxation since its

inception in 1948. Both parties within the British government have found problems with the

NHS system. The British NHS has gone through many changes in the last fifteen years, and the

Labour party has been behind the most recent changes. Fried notes that:

In an effort to make the NHS more efficient, it underwent a critical structural reform

during the 1990s, which included the introduction of market forces. The key change of

the reform was to separate ‘purchasing’ and ‘providing’ (or ‘buying’ and ‘selling’). In

accordance with this change, two major divisions of the NHS emerged: purchasers, made

up primarily of the District Health Authorities and the GP (general practitioner) fund

holders, and providers, which were mostly self-managed NHS hospital and community

trusts and GPs. A competitive ‘internal market’ was introduced that required providers to

specify quality and price levels; they are awarded contracts by purchasers on the basis of

these. Thus, providers now had to compete with both quality and cost to attract

Fried 2002, pg 272

purchasers, who are now free to maintain contracts with providers located outside their

traditional geographic boundaries.

These changes did not meet the intentions of the government. According to the market models

in chapter 2 this separation of purchasers and providers should help stimulate price negotiation,

which should increase costs and quality. However, after the separation of purchasers and

providers of healthcare in the United Kingdom’s healthcare system, price was still only set by the

financers of healthcare. Costs were only moderately kept under control, and quality of care was

not increased. This makes sense according to the models in chapter 2; if healthcare providers are

not allowed to negotiate the price, price will remain low. This low price will not stimulate

increased quality. Furthermore, competition between healthcare providers for contracts will

cause them to try and reduce their costs, to maintain profits. The easiest way to reduce costs is to

reduce the quality of care. This competition actually leads to a lower quality system, not higher

quality. When the Labour party came into power it had its own views on how to increase quality

in the healthcare system:

In 2000, another major change in the NHS resulted from the new Labour government’s

intention to reduce much of the competition injected into the system by the previous

government. The document, The New NHS: Modern, Dependable, outlines the

government’s vision for a healthcare system built on collaboration and partnerships.

Among the changes instituted were the dissolution of GP fund holding with primary care

groups and the development of interagency collaboration between primary care groups

and local social services departments. The Labour reforms further included the creation

of primary care groups, primary care trusts, the Commission for Health Improvement, the

National Institute for Clinical Excellence, and the Clinical Governance program.

The plan calls for more private ownership of medical provision, and bringing in private entities

to govern publicly owned facilities. Rowland noted that:

In keeping with its belief that direct state ownership of public facilities is inefficient, the

Labour Party is seeking greater involvement of the for-profit sector in both the ownership

and the operation of publicly funded healthcare facilities. To this end the Blair

government has signaled that NHS bodies must make use of the for-profit sector when

commissioning healthcare services.

Rowland believed that interjecting private provision of healthcare into the British system would

increase costs and decrease the quality of the system. However, the market models in chapter 2

suggest that the costs will increase through private provision of healthcare, but that the quality

will also increase.

The aggregate data on the United Kingdom supports the Labour Party’s belief that private

provision of healthcare is necessary. Figure 28 shows the life expectancy from birth of the

British population in years overlaid on the per capita expenditures. Using the data provided by

the OECD the average increases in life expectancy and per capita expenditure were computed.

Between 1980 and 1989 the life expectancy increased an average of .24 years per year, and per

capita expenditures increased and an average of $50.56 per year. Between 1990 and 2000 the

life expectancy increased by .20 years and per capita expenditure increased by $77.8 per year.

Fried 2002, pg 272

Rowland 2001, pg 403

Between 2000 and 2004 the life expectancy increased by .275 years and the per capita

expenditure increased $159 per year.

The percentage increase in expenditure between 1980 and 1989 was 7.63%, 5.86%

between 1990 and 1999, and 7.32% between 2000 and 2004. The policies pursued in the 1990s

did manage to decrease the percent increase in per capita expenditure in the United Kingdom by

about 2%, however, it also decreased the rate at which life expectancy increased. Figure 30 also

shows two points between 1990 and 2000 (1993 and 1995) in which life expectancy actually

decreased. The form of competition introduced during the 1990s did curb spending, but it also

curbed the increases in life expectancy, and at two points actually decreased the life expectancy.

Figure 31 shows the overlay of the percentage changes in per capita expenditure and total life

expectancy. It clearly shows that throughout the 1990s the percentage changes in per capita

expenditure were decreased, and that these decreases coincided with the decreases in life

expectancy. The steps taken in the 1990s to separate the financers and providers of healthcare in

the United Kingdom were needed, however the two groups need to negotiate the price rather than

have the financers continue to set the price. The Labour plan seems to be working toward its

projected goals of, “More power and information for patients, more hospitals and beds, more

doctors and nurses, much shorter waiting times for hospital and doctor appointments.”

The

Labour government actually argued for increasing per capita expenditures to match those of the

European average, as a method of increasing the quality of care and decreasing wait periods.

With an annual growth rate on expenditures in the United Kingdom from 2000 to 2004 of 7.32%

and a rate of 7.63% before the separation of purchasing and financing in the 199s, and a rate of

Fried 2002, pg 277

Fried 2002, pg 273

5.86% during the 1990s, it is clear that introducing more private ownership and operation of

healthcare provision did not drastically increase prices. In fact the growth rate is slightly lower

during the more recent period than before the reforms took place by both the governments during

the 1990s and the Labour government. And, the increase in life expectancy from 2000 to 2004

of 0.275 is higher than the growth rates for life expectancy in the previous two decades. The

Labour reforms have not increased the expenditure growth rates, which are actually lower than

before the reforms of the 1990s, and have managed to slightly increase life expectancy growth

rates. Rowland’s assessment that introducing private provision of healthcare would decrease the

quality of care and increase the costs of care are unfounded.

As expenditures have increased in the United Kingdom the life expectancy has also

increased. Equation 1 shows a predicted life expectancy in the United Kingdom, given its

current per capita expenditures of $2508, of 79.16 years. The actual life expectancy in the

United Kingdom is 78.5 years. According to the equation, the United Kingdom should have a

higher life expectancy, but only by 0.6 years. Equation 1 predicts the life expectancy in the

United Kingdom fairly well. Given the Labour government’s argument for increasing

expenditures on healthcare, and entering more private provision of healthcare into the system,

there should be an increase in the life expectancy of the British people over the next few years

that coincide with these increases in expenditures and private provisions. The advanced

industrial countries of the OECD have an average life expectancy of 79.39 years and an average

per capita expenditure of $2226.17. The Labour government has achieved its goal of matching

the expenditures and life expectancy equivalents of the rest of the developed OECD countries.

The United Kingdom, like the United States, offers two examples of two different

healthcare markets which has made it useful for study. Fifteen years ago the British system of

healthcare was much different than it is now. The previous system showed an incredible ability

to keep costs low, but there were complaints of long waits and poor quality, which are reflected

in the drops in life expectancy.

The new system has not drastically increased costs, but has increased access (Figures 32

and 33) and increased the overall quality of the system. As per capita expenditures on healthcare

have increased so have life expectancy and the number of practicing physicians. The market

models laid out in chapter 2 are fully supported by the effects that the policy changes have made

on quality, access and costs in the United Kingdom.

Figures and Tables

Figure 30: Change in Life Expectancy and Per Capita Expenditure on British Healthcare

Source: OECD Health Data Set 2006

Figure 31: Percentage Change in Healthcare Expenditures Overlaid on Life Expectancy

Source: OECD Health Data Set 2006

Figure 32: Number of Medical Professionals by Year in the UK

Source: OECD Health Data Set 2006

Figure 33: Linear Regression for Per Capita Expenditure and Number of Healthcare

Professionals in the UK

Source: OECD Health Data Set 2006

CHAPTER 6: GERMANY

When Otto von Bismarck imposed compulsory health insurance in Germany some 115

years ago and mandated its support through separate, primarily occupation-based funds

known as ‘sickness funds,’ under the joint control of employers and employees, he

created what would eventually become the most widely emulated medical delivery

system in the world. Indeed, Germany was the first nation to adopt a national healthcare

program. This system has greatly influenced Eastern European countries, which are

currently importing selected features of the German system into their own health systems.

Long admired by policy experts, the German system has undoubtedly contributed to good

industrial relations in the health sector of the economy through a decentralized structure

that has served to integrate numerous groups into administration and policymaking.

The German Constitution guarantees healthcare to its citizens, through sickness funds that are

paid for and administered by employers and employees.

Germany uses a social corporatist

model for the running of both its provision of healthcare and financing of healthcare (meaning

that interest groups are organized into hierarchies and these groups are then brought into

government policy making decisions). Medical associations and hospital associations are

organized into regional medical associations. Sickness pools have little influence over the

operations of medical provision, and are primarily responsible for the collection and paying of

funds for healthcare. The government controls budgets and costs of healthcare through laws and

regulations:

Fried 2002, pg 121

Fried 2002, pg 124

The present federal system was originally based on the principles of subsidization and

self-administration, which granted considerable fiscal and administrative independence to

the sickness funds, the hospital association, the medical profession, state governments,

and other suppliers of services. However, the macroeconomic objective to keep health

spending under close control has, in reality, resulted in a system that has grown away

from local autonomy and pluralism. The government increasingly defines health finance

matters through laws and regulations, although details of the content continue to be

delegated to healthcare providers.

What this amounts to in the German healthcare market is the private provision of healthcare,

public financing of healthcare through insurance pools, and government regulation of costs.

Medical providers are forced into regional groups and insurance is forced into pools.

Government then meets with insurance pools to discuss financing of healthcare and available

funding. Government also meets with medical associations to discuss their needs and budgets.

After receiving information from both the financers of healthcare and medical associations the

government determines budgets and operating expenses for healthcare provision. Healthcare

providers are then free to spend their budgets where necessary.

Hospital operating costs and capital costs are paid through separate mechanisms, and

funding comes from different sources. Hospital capital is supplied by area government

funds out of general taxation. Hospital operating budgets are negotiated at the regional

level, hospital by hospital, with sickness funds. The sickness funds are obligated to meet

hospitals’ historic operating costs, and, in turn, hospitals are obligated to provide

necessary economical services. Payments to hospitals are based on a prospective budget

Fried 2002, pg 125

100

negotiated between each hospital and the sickness funds; the Lander then approves all

hospital budgets.

This forced negotiation between healthcare financers and healthcare providers through

government regulation allows the German healthcare system to achieve high quality, high access,

and regulate economic efficiency. The quality of care in the German system is not altered by

hospitals attempting to be within their budgets. Hospitals, outside of normal operating costs, can

charge per case, per procedure, or per diem.

If individual cases cost more than originally

budgeted for the hospital can apply for (Fallpauschalen) reimbursement of its costs, or if an

individual procedure ended up being more expensive than budgeted for the hospital can apply for

(Sonderentgelte) reimbursement, and if an individual needs more time in the hospital for care

than originally budgeted for the hospital can apply for per diem reimbursement.

These

reimbursement programs allow hospitals to treat patients individually without worrying about

going over their budget, but at the same time routine procedures are kept at a constant price

rate—a rate that guarantees that hospitals will receive their historical payments, which gives

medical providers incentive to enter into the medical field.

General practitioners are funded differently than hospitals—they are given budgets for

care for a given region. General practitioners are forced into regional chambers of physicians.

These regional associations then disburse funding:

A sickness-fund physician’s income is derived from the number of services rendered

annually and the level of reimbursement for each service. Reimbursement is determined

by the Uniform Evaluation Standard fee schedule, which defines charges for about 2,000

Fried 2002, pg 127

Fried 2002, pg 128-129

101

items and determines their relative point value to one another. Along with the

physician’s own payment, each fee item includes the overhead costs of supporting a

practice, costs for single-use items like gloves and syringes, and costs incurred when

equipment is used during procedures.

Patients are given free choice on which physician’s office they choose to use. Wait-lists do not

exist and physicians compete with each other for patients, but this competition does not affect

price it only affects the quality of care. All practicing physicians and hospitals are guaranteed to

make a profit by serving the public through the various financing schedules. If the physician is

seeing patients, they are making money. Physicians do not rely on pure number of patients for

making money, and can see fewer patients depending on the type of ailment. Not only are there

no wait-lists for services, Germans have a wide variety of benefits through their healthcare

system, Fried explains that:

Germans have one of the most comprehensive health insurance benefits programs in the

world. According to the health insurance law, sickness-fund benefits include ambulatory,

hospital, and preventative care and screening programs; physiotherapeutic, maternity, and

preventative care; drugs prescribed by physicians; family planning; rehabilitation;

eyeglasses; medical appliances; and dental care, including prostheses.

All of these services are provided on a budget of $3043 per capita yearly (however some extra

benefits are now being cut in the German healthcare system like eyeglasses). The advanced

industrial OECD average is $2226.17 per capita on healthcare expenditure. The German system

pays higher prices than the average OECD country. The average life expectancy in Germany is

Fried 2002, pg 130

Fried 2002, pg 131

102

78.6 years, and the advanced industrial OECD average is 79.39 years. The life expectancy of

Germany is slightly lower than the OECD average. Given its expenditures Germany should have

a higher life expectancy—equation 1 shows that the predicted life expectancy of Germany is

79.88 years. It appears that life style factors may be decreasing the German life expectancy, or

that there is economic waste in the system, or perhaps benefits such as eyeglasses, prostheses,

and dental care that do not increase life expectancy are the reasons for the slightly elevated

expenditures. Most likely it is a combination of all three factors. However, the importance of

discussing the overall German system of healthcare is in how it negotiates price. Germany, as

stated earlier is the model by which many other countries use to build their healthcare systems,

and for this purpose it was chosen for analysis over other universal healthcare systems that have

higher predicted life expectancies.

The German healthcare system represents the prime example of forced price negotiation

between medical providers and medical financers. The market appears to be functioning exactly

as predicted by the universal healthcare market model (figure 3). There is little wonder why so

many countries look to Germany on how to provide medical care. It has a high quality system

that guarantees payment for physicians and provides full access, not to mention many extra

benefits like dental and optical care that do not increase life expectancy but do increase the

quality of life.

103

CHAPTER 7: CONCLUSIONS

I came into this project with the bias and assumption that socialized healthcare was the

best way to run a healthcare system. I was shocked to discover that my bias was incorrect.

Universal coverage with private provision of healthcare appears to offer the most benefit to a

society. These systems provide access for their entire populations, create high quality, but over-

pay for medical services. However, socialized healthcare can have the same outcomes as

universal healthcare when there is the same degree of price negotiation between medical

providers and medical financiers. In the end, it appears that it is best to over-pay the medical

community, because it appears that you actually do get what you pay for when full access to

healthcare is guaranteed. Over-payment creates quality producing profit incentives, and

guarantees that enough medical professionals will enter into the healthcare market. I followed a

microeconomic method for creating the models in this thesis that began with discussing the

underlying motivations of suppliers and consumers in the healthcare market, and how the market

was affecting their behavior. I then tested this model against the real-world data, and found the

evidence largely in support of the model. In fact, I failed to find any way in which the

assumptions in chapter 2 were incorrect when looking at the aggregate data and case studies. It

is very likely and almost certain that some of the assumptions from chapter 2 are incorrect (or

only partially correct) because they are an abstraction from the real-world. However, the model

derived from these assumptions is supported by all the data. The free-market appears to be

unable to force a price that causes the supply of medical provisions to meet the theoretical

demand for healthcare. It creates a massively overpriced healthcare system and decreases access

as discussed in chapter 4, on the United States healthcare system. A universal healthcare system,

104

by its nature of private provision of healthcare and public funding of healthcare, forces price

negotiation, as shown in chapter 6. The price negotiation creates a high quality system that does

not limit access. A socialized healthcare system has a tendency to set prices too low, but can

balance the supply and demand for healthcare when price negotiation is entered into the system,

as shown in chapter 5. Ultimately, the difference between a universal healthcare system and a

socialized healthcare makes little difference to the life expectancy if both systems have forced

price negotiation which is seen in the reforms taking place in the United Kingdom. Table 11

summarizes the findings on life expectancy and per capita expenditure. It also shows the

predicted life expectancy in the United States if it had a single-payer system based on its current

public expenditures, and its predicted reduction in expenditures if the government ran all

healthcare financing.

Free-market capitalism works well in balancing the supply and demand of goods, and

setting a price that creates surpluses. However, it fails to make supply and demand meet in the

healthcare market. A free-market forces a negotiation between consumers and producers in the

marketplace of normal goods, but fails to force these same negotiations in the healthcare

marketplace. To replicate the negotiations (supply meeting demand) of a normal market, in the

healthcare market there must be one consumer of healthcare to balance out the monopolistic

characteristics of healthcare provision. Negotiations between the provision of healthcare and the

consumption of healthcare must be artificially introduced. When the U.S. system artificially

introduces price negotiation through Medicare massive savings can be seen over private

insurance, and the system manages to guarantee access. When more private provision of

healthcare was introduced into the British healthcare system life expectancies and access

increased. The German system shows a model of how price negotiation should take place within

105

the healthcare system. This thesis has developed two market models of healthcare based on

economic inquiries. The models remain theoretical, but the aggregate data and the case studies

fully support them.

Further studies using the models developed in this thesis could be done of any country’s

healthcare system. This thesis also implies that a government should be concerned with

introducing the market structure of price negotiation into its healthcare system, and that market

structures such as hospitals competing directly with each other for funding will have negative

implications to the quality of healthcare. These models also suggest a way to evaluate how well

a healthcare system is functioning. By using equation 1 it is possible to gauge how expenditures

and life expectancies should match up. If a country wants to increase the life expectancy of its

population it can locate itself with the quadratic regression and make adjustments where

necessary to per capita expenditures and price negotiations.

The main implication of this thesis is that healthcare financing should be largely public,

whether through direct taxation or employer insurance pooling, and that healthcare provision

should be largely private (whether for profit or non-profit). Free-market healthcare systems like

the United States should work toward government funded healthcare, and socialized healthcare

systems like the United Kingdom should work toward increasing private provision of healthcare.

There is much concern currently about the funding of healthcare due to changing demographics

(a smaller working population will soon be supporting a larger unemployed population). This

thesis offers no method for containing these concerns, governments must find their own way to

deal with the upcoming problems of financing healthcare with smaller working populations.

Relying on the free-market to provide healthcare once the demographic changes happen will not

increase the quality, access, or economic efficiency of healthcare. The upcoming demographic

106

problem is of raising enough money to cover healthcare expenditures, not in trying to cut costs

per capita in the healthcare system. Furthermore, equation 1 shows that life expectancies in all

countries paying less than $4,000 per capita on healthcare can increase their life expectancies by

increasing funding to around $3,900 per capita, which would yield a predicted life expectancy of

81.15 years. I have no suggestion how to raise the necessary funds to maintain this level of per

capita expenditure, but governments should be working toward this goal. This also means that if

the United States had guaranteed access to healthcare and was able to reduce its expenditures

through price negotiations closer to the $4,000 per capita level that the life expectancy of the

entire population would be increased. This would require a 33% reduction in current

expenditures which is not completely unreasonable given the probable 7% reduction in

healthcare expenditures merely by government financing the healthcare system over private

insurance financing the healthcare system. Not to mention the theoretical 11.8% reduction in

healthcare expenditures when coupled with a reduction in pharmaceutical costs. Corporations in

America should be backing such policies as it would decrease their healthcare expenditures

(rather than paying for higher priced private health insurance due to its inability to negotiate

lower costs, corporations could pay for government healthcare at an overall lower cost and cut

their healthcare expenditures). Theoretically, if the government began financing healthcare by

taking in corporate money that is currently going to fund private health insurance in the form of a

healthcare tax, there would be an 11.8% reduction in healthcare expenditures—which, would

yield a life expectancy of 78.69 years according to equation 1, and reduce corporate healthcare

expenses by the 11.8%.

107

Figures and Tables

Table 11: Life Expectancy and Expenditures

Source: OECD Health Data Set 2006, and Calculations from Equation 1

United States United Kingdom Germany

Per Capita Expenditure $6102 / $2728 (Public Exp)

$5320 (Reduction by Gov’t)

$2508 $3043

Actual Life Expectancy 77.5 78.5 78.6

Predicted Life Expectancy 76.71 / 79.5 (Public Exp)

78.69 (Reduction by Gov’t)

79.16 79.88

108

REFERENCES

Abramson, J. Overdosed America: The Broken Promise of American Medicine: How the

Pharmaceutical Companies are Corrupting Science, Misleading Doctors, and

Threatening Your Health. New York: Harper, 2005.

Almgren, Gunnar. Health Care Politics, Policy, and Services: A Social Justice Analysis. New

York: Springer Publishing Company, 2007.

Bartlett, D. L., and J. B. Steele. Critical Condition: How Health Care in America Became Big

Business—and Bad Medicine. New York: Doubleday, 2004.

Blue Cross Blue Shield. 2007 Medical Cost Reference Guide: Facts and Trends to Support

Knowledge-Driven Solutions. Blue Cross Blue Shield Association, 2007.

Cutler, D. M. Your Money or Your Life: Strong Medicine for America’s Health Care System.

New York: Oxford University Press, 2004.

Dranove, D. The Economic Evolution of American Health Care: From Marcus Welby to

Managed Care. Princeton, N.J.: Princeton University Press, 2000.

Fried, Bruce and Laura Gaydos. World Health Systems: Challenges and Perspectives. Chicago:

Health Administration Press, 2002.

Kassirer, J. P. On the Take: How Medicine’s Complicity with Big Business Can Endanger Your

Health. New York: Oxford University Press, 2004.

Kleinke, J. D. Oxymorons: The Myth of a U.S. Health Care System. San Francisco: Jossey-

Bass, 2001.

Matcha, Duane. Health Care Systems of the Developed World: How the United States Remains

an Outlier. Westport: Praeger, 2003.

Mueller, R. M. As Sick as It Gets: The Shocking Reality of America’s Healthcare. Dunkirk,

N.Y.: Olin Frederick, 2001.

OECD. OECD Health Data Set 2006. 2007. Database on-line. Available from OECD

http://www.oecd.org/document/30/0,3343,en_2825_495642_12968734_1_1_1_1,00.html

OECD. OECD Factbook 2007. 2007. Database on-line. Available from OECD

http://masetto.sourceoecd.org/vl=35587766/cl=24/nw=1/rpsv/factbook/

109

OECD. Income-Related Inequality in the Use of Medical Care in 21 OECD Countries. Paris:

2004. Database on-line. Available from OECD

http://www.oecd.org/dataoecd/14/0/31743034.pdf

Ohsfeldt, Robert and John Schneider. The Business of Health: The Role of Competition,

Markets, and Regulation. Washington D.C.: AEI Press, 2006.

Pennsylvania Health Care Cost Containment Council. Financial Analysis 2006: Volume One

General Acute Care Hospitals. Pennsylvania Health Care Cost Containment Council,

2007. Article on-line. Available from Pennsylvania Health Care Cost Containment

Council http://www.phc4.org/reports/fin/06/docs/fin2006report_volumeone.pdf

Rowland, David, Allyson M. Pollock, and Neil Vickers. “The British Labour Government’s

Reform of the National Health Service.” Journal of Public Health Policy. Vol. 22, No. 4.

(2001): 403-414.

The New York Times (New York). Thursday June 14, 2007.

Schweitzer, Stuart. Pharmaceutical Economics and Policy. New York: Oxford University

Press, 1997.

Stockman, Alan. Introduction to Microeconomics: 2

Edition. New York: The Dryden Press,

1999.

The United States Department of Health and Human Services. Overview of the Uninsured in the

United States: An Analysis of the 2005 Current Population Survey. Database on-line.

Available from the United States Department of Health and Human Services

http://aspe.hhs.gov/health/reports/05/uninsured-cps/index.htm#income

110