Research Proposal

For

The Comparison Of The Total Alzheimer

Disease Cost Of Living Among 22 Countries

Around The World

By

John Wong

MMI 409 Winter 2012

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Introduction: The year 2011 represents the first batch of the post war baby boomers entering

into a “segment of the life span when Alzheimer’s disease (AD) increases exponentially”

(Trojanowski, 2010). Worldwide, 35.6 million people were estimated to have AD in 2010, with

the cost estimated at US$604 billion in the next 20 years (Handels, 2011). In this proposal, we

want to find out if the total AD cost of living (TADCL) is significantly higher in the USA, in

comparison with other countries in the world.

Background: The first case of “presenile dementia” was described by Alois Alzheimer in 1906.

(Mimica, 2010). The development of AD is thought to be caused by disintegration and structural

dysfunction of the tau protein within the neurofibrillary tangles (Bacher, 2010). The disease is

characterized by a deterioration of cognitive behavioral function, with loss of memory, reasoning

and functional capacity (L’opez-Bastidaa, 2009).

Current Treatment: The drug cost for the treatment of AD, represents a good portion of the

total expense incurred by the patient (Handels, 2011). Donepezil, Galantamine, Rivastigmine

and Memantine are approved by the USA Food and Drug Administration (FDA) (Atri, 2011).

Recently, new and expensive intravenous immunoglobulin (IVIG) injections are also used for the

treatment of patients with AD (Bacher, 2010) (Bayry, 2007). For the four FDA approved drugs,

a 10 mg tablet costs as follows: Donepezil $6.6; Galantamine $3.4; Rivastigmine $3.5;

Memantine $2.9 (Suh, 2009). Donepezil is the preferred medication followed by Galantamine

and Rivastigmine (Hollingworth, 2011). The cost per quality adjusted life year (QALY) of

Donepezil is £80,000 (US$128,000); Galantamine £68,000 (US$108,800); Rivastigmine £57,000

(US$91,200); Memantine £37,000 (US$59,200) (Loveman, 2006). Other analysis shows an

incremental cost-effectiveness ratio of Donepezil to be between US$40,000 / QALY (mild AD)

to US$100,000 / QALY (severe AD) (L’opez-Bastidaa, 2009). Furthermore, studies have shown

that benefits may be greatest when treatment is started while patients are still in the mild stages

of AD (Getsios, 2010). Therefore, a patient’s decision to start AD treatment early during the

onset of the disease can be significantly impacted by the cost of the AD treatment.

Problem Statement: Although various studies (Suh, 2009) (Machado, 2011) provide

comprehensive comparisons of AD drug costs across nations , they do not take into account other

expenditures for a total AD cost of living (TADCL) for AD patients. This proposal seeks to

determine if there is significant differences among the TADCL values in various nations, and

whether the TADCL value in the USA is significantly higher than other nations. A by-product

of this analysis is to explore what options exist for a US AD patient to get affordable treatment

outside of the USA. In addition, we want to derive a linear regression equation to predict the

TADCL value. This may allow us to develop strategies to lower the costs, and thereby may help

us to address the un-affordability problem of drugs around the world (Steinbrook, 2007).

Variables: The dependent variable, the total AD cost of living (TADCL), is computed by

multiplying the total cost of care for the patient with the cost of living index, and dividing by the

quality of life index. The higher the cost of living, the higher is the TADCL, whereas a lower

quality of life index means more hardship, which therefore increases the TADCL.

The list of associated variables and their definitions are summarized in Table 1 of Appendix A.

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For the total cost of care for the patient, we will derive the number by the total expenditure paid

for by the AD patient, that includes the annual cost of the AD medication paid by the patient, the

cost of AD medication paid by insurance, the annual cost per caregiver utilized, and the annual

medical checkup expenditures. All costs will be converted by the International Monetary Fund

(IMF) purchasing power parity (PPP) conversion rates (International Monetary Fund, 2010). For

the quality of life index, we will use the quality of life index as suggested by the Economist in

the 2005 World report (The Economist, 2005) (Numeo, 2011). For the cost of living index, we

will use USA, Washington DC as the base location, with a base index value of 100. The cost of

living index for various locations will be calculated by the COLI calculator from Xpatulator.com

(Xpatulator, 2012).

Formula: TADCL = (Cost of the AD medication paid by the AD patient + Cost of the AD

medication paid by insurance + the annual cost per caregiver utilized + annual medical checkup

expenditures) x Cost of Living Index / Quality of Life index [Formula 1.1].

Constraints: Since countries have different health coverage rules, we cannot take into account

every single cost and reimbursement detail from every country. Therefore, the simplification of

the total cost of care calculation represents a potential weakness of this research study.

Method: For the research, we will work with local Alzheimer Associations in each country.

Participants for the research will be randomly picked from the associations’ registries.

Volunteers will call the potential candidates to obtain the values for the list of variables listed in

Appendix A Table 1. In order to prevent over counting the TADCL due to combination drug

therapies, we will limit our samples to AD patients who are taking one type of medication only.

The volunteers will continue to call until viable data are collected from 200 patients. Collected

information will be entered via secure SSL into an encrypted central database online. To ensure

HIPAA compliance, no identifiable patient information, such as name, id, etc., will be recorded.

The TADCL values will be calculated and presented in a matrix of n=200 subjects by k=22

countries (Appendix A Table 2).

The research will be conducted in 22 countries (Argentina, Australia, Brazil, the Dominican

Republic, France, Hong Kong, India, Japan, Macedonia, Mexico, New Zealand, Nigeria, the

Philippines, Portugal, Serbia, South Korea, Switzerland, Taiwan, Thailand, Uganda, the U.K.,

and the U.S.A.), similar to the ones used in the Suh study for logistic feasibility purpose.

Hypotheses: The hypotheses of the research are as follow:

H0: There is no significant differences in the TADCL among the various countries (i.e.

µ(1) = µ(2) = … = µ(k), where k = number of countries) versus

H1: There is significant differences in the TADCL among the various countries (i.e. µ(1)

≠µ(2) ≠… ≠ µ(k), where k = number of countries).

H2: The TADCL is significantly higher in the USA versus most other countries. (e.g.

µ(USA) > µ(Mexico))

Measures: For the analysis, we will group the 4400 subjects by the AD drugs used. The analysis

will be run using SPSS version 19 (IBM). Since we are comparing more than two sample

means, we will use ANOVA for the analysis (Analyze -> Compare Means -> One Way

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ANOVA). Then, we will use the Tukey procedure to perform post hoc pairwise analysis on the

countries. For the correlations among the various variables, we will use SPSS to perform a

multi-variable linear regression analysis (Analyze -> Regression -> Linear). The linear

regression analysis will tell us the contribution of each factor to the TADCL value.

Analysis: Since we have not conducted the experiment, we will hypothesize an analysis of the

results and the outputs from the experiment:

1) First, we can produce a box plot (simulated in Appendix B Graph 1) from the raw data

collected (Appendix A Table 1). In the simulated graph, we can see that the USA has a

higher median TADCL in comparison with other countries, while Japan, the UK, and

Hong Kong are also high. One would reason that these countries have higher AD drug

costs, and also higher costs of living, which contributes to the higher TADCL.

2) From the linear regression analysis, the R-squared value of 0.486 means that the

regression does a good job of modeling the TADCL, as nearly half of the variation in

TADCL is explained by the model (simulated in Appendix B Table 1). Among the

various variables, gender and quality of life index do not contribute to the model (p value

> 0.05) (simulated in Appendix B Table 2). Furthermore, from the standardized

coefficient column, we can see that $ drug paid by patient and $ medical procedures

contribute more to the model because they have larger absolute standardized coefficients.

3) From the calculated TADCL values (Appendix A Table 2), we can run an ANOVA

analysis (simulated in Appendix B Table 3): With the p value at 0.003, we can reject the

null hypothesis and conclude that there is a significant difference in the TADCL values

for Donepezil across the various countries. The same analysis can be performed for the

other AD drugs.

4) From the post hoc pairwise analysis (simulated in Appendix B Table 4), the simulated

result shows that TADCL level in Group 1 (USA) is significantly different than the

TADCL levels in Group 2, 3, 4, 5, and 20, as the p values are less than 0.05. In addition,

from the mean differences, we can see that the TADCL for the USA is higher than the

TADCLs for Group 2, 3, 4, 5, and 20. On the other hand, there are no significant

differences between the TADCL in the USA, and the TADCLs in Group 6, 7, 21, 22.

Summary: AD is the most common form of dementia among elderly populations and is the

fourth leading cause of death in the developed world (Bacher, 2010). It is estimated that 65

million people worldwide will suffer from some form of dementia by 2030 (Mimica, 2010). As

mentioned in the introduction, the total cost can amount to $604 billion as more baby boomers

reach 65 years old. The purpose of this research was to explore the differences among the Total

Alzheimer Disease Cost of Living in the 22 nations selected. More importantly, we wanted to

find out which countries’ TADCL values are most significantly different from that of the USA.

The result can be used as a possible guidance to patients for potential AD treatments outside of

the USA. And last, from the linear regression equation, we can determine which factors

contributed most to the TADCL value. This may allow us to devise strategies against those

factors to minimize the TADCL for better treatment and affordability of AD drugs around the

world.

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Appendix A: Data

Table 1: Variables Definitions

Variable Type Values Data Source

Age Scale Interview with Patient

Gender Nominal 0 = Male, 1 =

Female

Interview

Severity of AD Ordinal 1 to 5 (Mild to

Severe)

Interview

AD Drug Taken Nominal 1 = Donepezil

2 = Galantamine

3 = Rivastigmine

4 = Memantine

5 = IViG

6 = Other

Interview

Dosage per day Interval e.g. 5 mg, 10 mg,

etc.

Interview

Health Insurance

coverage

Nominal 0 = No, 1 = Yes Interview

$ paid by patient

per year

Scale Interview

$ paid by health

insurance

Scale Interview

$ per caregiver

per year

Scale Interview

$ medical

expenditures per

year (check up,

treatment)

Scale Interview

Cost of Living

Index

Scale Calculated from

Xpatulator.com, using

Washington, DC, USA as the

base location with index value

of 100

Quality of Life

index

Scale Obtained from

nationranking.wordpress.com

PPP Conversion

Rate

Scale Obtained from IMF.gov

Countries Nominal Listed from 1 to n

alphabetically

Interview

TADCL Scale Computed using formula 1.1*

* TADCL = (Annual cost of the AD medication paid by the AD patient + Annual cost of the AD

medication paid by insurance + the annual cost per caregiver utilized + annual medical checkup

expenditures) x Cost of Living Index / Quality of Life index. All costs adjusted by the PPP

conversion rate. [Formula 1.1]

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Table 2: Calculated TADCL table for ANOVA Analysis

US

A

Arg

enti

na

Au

stra

lia

Do

min

ica

n R

ep

ub

lic

Fra

nce

Ho

ng

Ko

ng

Ind

ia

Ja

pa

n

Ma

ced

on

ia

Mex

ico

New

Zea

lan

d

Nig

eria

Ph

ilip

pin

es

Po

rtu

ga

l

Ser

bia

So

uth

Ko

rea

Sw

itzer

lan

d

Ta

iwa

n

Th

ail

an

d

Ug

an

da

UK

TADCL

1.A

TADCL

1.B

… … … … … … … … … … … … … … … … … … TADCL

1.V

TADCL

2.A

TADCL

2.B

… … … … … … … … … … … … … … … … … … TADCL

2.V

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

… … … … … … … … … … … … … … … … … … … … …

TADCL

200.A

TADCL

200.B

… … … … … … … … … … … … … … … … … … TADCL

200.V

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Appendix B: Hypothesized Analysis

Graph 1: Simulated Box Plot

Appendix B: Hypothesized Analysis

Table 1: Simulated Linear Regression Analysis Model Summary

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .697a .486 .449 .98960

a. Predictors: (Constant), Age, Gender, Severity of AD, AD drug taken, $ drug paid by patient, $ paid

by insurance, $ caregiver cost, $ medical procedures, Quality of Life index, insurance coverage,

Cost of living index

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Table 2: Simulated Linear Regression Coefficients

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

Correlations

Collinearity

Statistics

B

Std.

Error Beta

Zero-

order Partial Part Tolerance VIF

1 (Constant) -3.017 2.741 -1.101 .273

Age .883 .331 .293 2.670 .008 .274 .219 .161 .304 3.293

Gender -.046 .013 -.002 -3.596 .611 -.552 -.290 -.217 .187 5.337

Severity of AD .356 .190 .281 1.871 .063 -.135 .156 .113 .162 6.159

AD Drug Taken -.002 .004 -.092 -.509 .021 -.389 -.043 -.031 .112 8.896

$ drug paid by patient .042 .023 .541 1.785 .006 .292 .149 .108 .200 4.997

$ drug paid by insurance .042 .023 .541 1.785 .006 .292 .149 .108 .200 4.997

$ caregiver cost -.028 .042 -.073 -.676 .070 .037 -.057 -.041 .313 3.193

$ medical procedures .015 .014 .448 1.032 .004 .215 .087 .062 .178 5.605

Quality of Life Index .156 .350 .075 .447 .655 -.041 .038 .027 .131 7.644

Insurance Coverage -.057 .047 -.167 -1.203 .031 -.016 -.101 -.073 .189 5.303

Cost of Living Index .081 .040 .262 2.023 .005 .121 .168 .122 .217 4.604

a. Dependent Variable: TADCL

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Table 3: Simulated ANOVA Analysis on TADCL for Donepezil

ANOVA

TADCL For Donepezil

Sum of

Squares df

Mean

Square F Sig.

Between

Groups

198.009 21 9.429 6.729 .003

Within Groups 582.816 416 1.401

Total 780.825 439

Table 4: Simulated Tukey Post Hoc Analysis

Multiple Comparisons

TADCL for Donepezil

Tukey HSD

(I)

Group (J) Group

Mean

Difference

(I-J)

Std.

Error Sig.

95% Confidence Interval

Lower

Bound

Upper

Bound

1 2 2.08333* .68341 .030 -3.9962 -.1705

3 2.25000* .68341 .018 -4.1628 -.3372

4 2.89167* .68341 .002 -4.8045 -.9788

5 2.08333* .68341 .030 .1705 3.9962

6 -.16667 .68341 .995 -2.0795 1.7462

7 -.80833 .68341 .644 -2.7212 1.1045

… 2.25000* .68341 .018 .3372 4.1628

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… .16667 .68341 .995 -1.7462 2.0795

… -.64167 .68341 .785 -2.5545 1.2712

20 2.89167* .68341 .002 .9788 4.8045

21 .80833 .68341 .644 -1.1045 2.7212

22 .64167 .68341 .785 -1.2712 2.5545

*. The mean difference is significant at the 0.05 level.

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