1

Health Economics

Comparing different allocations Should we spent our money on

• Wheel chairs

• Screening for cancer

Comparing costs

Comparing outcome

Outcomes must be comparable Make a generic outcome measure

2

Outcomes in health economics

Specific outcome are incompatible Allow only for comparisons within the specific field

• Clinical successes: successful operation, total cure

• Clinical failures: “events”

Generic outcome are compatible Allow for comparisons between fields

• Life years

• Quality of life

Most generic outcome Quality adjusted life year (QALY)

3

Quality Adjusted Life Years (QALY)

Multiply life years with quality index Quality of life index

1.0 = normal health

0.0 = death (extremely bad health)

Example Losing sense of sight

Quality of life index is 0.5

Life = 80 years

0.5 x 80 = 40 QALYs

4

A new wheelchair for elderly (iBOT) Special post natal care

Which health care program is the most cost-effective?

5

A new wheelchair for elderly (iBOT) Increases quality of life = 0.1

10 years benefit

Extra costs: $ 3,000 per life year

QALY = Y x V(Q) = 10 x 0.1 = 1 QALY

Costs are 10 x $3,000 = $30,000

Cost/QALY = 30,000/QALY

Special post natal care Quality of life = 0.8

35 year

Costs are $250,000

QALY = 35 x 0.8 = 28 QALY

Cost/QALY = 8,929/QALY

Which health care program is the most cost-effective?

6

QALY league table

Intervention $ / QALYGM-CSF in elderly with leukemia 235,958

EPO in dialysis patients 139,623

Lung transplantation 100,957

End stage renal disease management 53,513

Heart transplantation 46,775

Didronel in osteoporosis 32,047

PTA with Stent 17,889

Breast cancer screening 5,147

Viagra 5,097

Treatment of congenital anorectal malformations 2,778

7

1.0

0.0A B C

Uti

lity

of

Hea

lth

Egalitarian Concerns:Burden of disease

8

CE-ratio by equity

9

Burden as criteria

0

5

10

15

20

25

30

Accepted Rejected

High burden Low burden

Pronk & Bonsel, Eur J Health Econom 2004, 5: 274-277

10

Choice

First strongly preferred to second

First slightly

preferred to second

Unable to

choose

Second slightly

preferred to first

Second strongly preferred

to first

5 year old 70 year old 57 23 14 5 2

35 year old 60 year old 29 42 27 1 0

2 year old 8 year old 4 5 70 16 5

Single Married 3 3 69 20 5

Smoker Non-Smoker 6 8 43 30 12 Heavy drinker

Light drinker 5 6 25 41 23

Woman Man 4 4 90 1 0

Unemployed Employed 3 3 81 10 2

Director Unskilled 5 8 83 3 0

Lorry driver Teacher 2 2 86 8 3

With children No children 27 38 31 3 1

What form of equity?

11

3500 Citations in PubMed

1980[pdat] AND (QALY or QALYs)

050

100150200250300350400450500

1980 1985 1990 1995 2000 2005 2010

Pu

bli

cati

on

s

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Top 6 journals Cost Utility Analysis

0 10 20 30 40 50

Pharmacoeconomics

Ann Intern Med

JAMA

Int J Technol Assess

Med Decis Making

Am J Med

# publications 1976 - 2003

www.tufts-nemc.org/cearegistry

13

Most debate about the QoL estimates

Unidimensional QoL In QALY we need a unidimensional assessment of Quality of life

Rules out multidimensional questionnaires SF-36, NHP, WHOQOL

0

10

20

30

40

50

60

70

80

90

100

Physic

al fu

nctio

ning

Social

Functio

ning

Role P

hysi

cal

Role e

motio

nal

Men

tal h

ealth

Vitalit

y

Bodily p

ain

Genera

l Hea

lth

Sc

ore

s o

n S

F-3

6

General pop.

Diabetes II

Growth hormon def.

Depression

14

Utility assessment

Unidimensional QoL Often called ‘utility’

15

Who to ask?

The patient, of course!

16

The clinical perspective

Quality of life is subjective….. “Given its inherently subjective nature, consensus was quickly

reached that quality of life ratings should, whenever possible, be elicited directly from patients themselves. “

• (Niel Aaronson, in B. Spilker: Quality of life and Pharmacoeconomics in Clinical Trails, 1996, page 180)

…therefore ask the patient!

17

Patient values count….

[…] the best way to do this, the technology, is a patient-based assessment. They report, they evaluate, they tell you in a highly standardized way, and that information is used with the clinical data and the economic data to get the best value for the health care dollar.”

John Ware

18

A problem in the patient perspective….

Stensman Scan J Rehab Med

1985;17:87-99.

Scores on a visual analogue scale 36 subjects in a

wheelchair

36 normal matched controls

Mean score Wheelchair: 8.0

Health controls: 8.3

Healthy

Death

19

The economic perspective

In a normal market: the consumer values count

The patient seems to be the consumer Thus the values of the patients….

If indeed health care is a normal market… But is it….?

20

Health care is not a normal market

Supply induced demands Government control

Financial support (egalitarian structure)

Patient Consumer The patient does not pay

Consumer = General public Potential patients are paying

Health care is an insurance market A compulsory insurance market

21

Health care is an insurance market

Values of benefit in health care have to be judged from a insurance perspective

Who values should be used the insurance perspective?

22

Who determines the payments of unemployment insurance?

Civil servant Knowledge: professional

But suspected for strategical answers

• more money, less problems

• identify with unemployed persons

The unemployed persons themselves Knowledge: specific

But suspected for strategical answers

General public (politicians) Knowledge: experience

Payers

23

Who’s values (of quality of life) should count in the health insurance?

Doctors Knowledge: professional

But suspected for strategical answers

• See only selection of patient

• Identification with own patient

Patients Knowledge: disease specific

But suspected for strategical answers

But coping

General public Knowledge: experience

Payers

Like costs: the societal perspective

24

Validated questionnaires

MOBILITY I have no problems in walking about I have some problems in walking about I am confined to bed

SELF-CARE I have no problems with self-care I have some problems washing or dressing myself I am unable to wash or dress myself

USUAL ACTIVITIES (e.g. work, study, housework family or leisure activities)

I have no problems with performing my usual activities I have some problems with performing my usual activities I am unable to perform my usual activities

PAIN/DISCOMFORT I have no pain or discomfort I have moderate pain or discomfort I have extreme pain or discomfort

ANXIETY/DEPRESSION I am not anxious or depressed I am moderately anxious or depressed I am extremely anxious or depressed

25

Validated Questionnaires

Describe health states Have values from the general public

Rosser Matrix

QWB

15D

HUI Mark 2

HUI Mark 3

EuroQol EQ-5D

26

EQ-5D, HUI and SF-36

Of the shelf instruments….

27

Validated questionnaires

Rosser

EuroQol EQ-5D www.euroqol.org

QWB

SF-36 (SF-6D) www.sf-36.org

HUI Mark 2

HUI Mark 3

15D www.15d-instrument.net

28

The Rosser & Kind Index

29

The Rosser & Kind index

One of the oldest valuation 1978: Magnitude estimation

Magnitude estimation PTO

N = 70: Doctors, nurses, patients and general public

1982: Transformation to “utilities” 1985: High impact article

Williams A. For Debate... Economics of Coronary Artery Bypass Grafting. British Medical Journal 291: 326-28, 1985.

Survey at the celebration of 25 years of health economics: chosen most influential article on health economics

30

More health states

Criticism on the Rosser & Kind index Sensitivity (only 30 health states)

The unclear meaning of “distress”

The compression of states in the high values

The involvement of medical personnel

New initiatives Higher sensitivity (more then 30 states)

More and better defined dimensions

Other valuation techniques

• Standard Gamble, Time Trade-Off

Values of the general public

31

Validated questionnaires

Questionnaire Number of health state

Rosser 30

EuroQol EQ-5D 245

QWB 2,200

SF-36 (SF-6D) 9,000

HUI Mark 2 24,000

HUI Mark 3 972,000

15D 3,052,000,000

32

No longer value all states

Impossible to value all health states If one uses more than 30 health states

Estimated the value of the other health states with statistical techniques Statistically inferred strategies

• Regression techniques

• EuroQol, Quality of Well-Being Scale (QWB)

Explicitly decomposed methods

• Multi Attribute Utility Theory (MAUT)

• Health Utility Index (HUI)

33

Statistically inferred strategies

Value a sample of states empirically Extrapolation

Statistical methods, like linear regression

11111 = 1.00

11113 = .70

11112 = ?

34

Explicitly Decomposed Methods

Value dimensions separately Between the dimensions What is the relative value of:

• Mobility…... 20%• Mood…….. 15%• Self care.… 24%.

Value the levels Within the dimensions What is the relative value of

• Some problems with walking…… 80%• Much problems with walking…... 50%• Unable to walk…………………….10%

35

Explicitly Decomposed Methods

Combine values of dimensions and levels with specific assumptions Multi Attribute Utility Theory (MAUT)

• Mutual utility independence

• Structural independence

36

Explicitly Decomposed Methods

Health Utilities Index (Mark 2 & 3) Torrance at McMaster

8 dimensions

Mark 2: 24.000 health states

Mark 3: 972.000 health states

The 15-D Sintonen H.

15 dimensions

3,052,000,000 health states (3 billion)

37

More health states, higher sensitivity ? (1)

EuroQol criticised for low sensitivity Low number of dimensions

• Development of EQ-5D plus cognitive dimension

Low number of levels (3)

• Gab between best and in-between level

38

More health states, higher sensitivity ? (2)

Little published evidence Sensitivity EQ-5D < SF-36

• Compared as profile, not as utility measure

Sensitivity EQ-5D HUI

Sensitivity the number of health states How well maps the classification system the illness?

How valid is the modelling?

How valid is the valuation?

39

More health states, more assumptions

General public values at the most 50 states The ratios empirical (50) versus extrapolated

Rosser & Kind 1:1

EuroQol 1:5

QWB 1:44

SF-36 1:180

HUI (Mark III) 1:19,400

15D 1:610,000,000

What is the critical ratio for a valid validation?

40

SF-36 as utility instrument

Transformed into SF6D SG N = 610 Inconsistencies in model

18.000 health states

regression technique stressed to the edge

Floor effect in SF6D

41

Conflicting evidence sensitivity SF-36

Liver transplantation, Longworth et al., 2001

42

Conclusions

More states better sensitivity The three leading questionnaires

have different strong and weak points

43

Value a health state

Wheelchair Some problems in walking about

Some problems washing or dressing

Some problems with performing usual activities

Some pain or discomfort

No psychosocial problems

44

Uni-dimensional value

Like the IQ-test measures intelligence Ratio or interval scale

Difference 0.00 and 0.80 must be 8 time higher than 0.10

Three popular methods have these pretensions Visual analog scale

Time trade-off

Standard gamble

45

Visual Analogue Scale

VAS Also called “category scaling”

From psychological research

“How is your quality of life?” “X” marks the spot

Rescale to [0..1]

Different anchor point possible: Normal health (1.0) versus dead (0.0)

Best imaginable health versusworse imaginable health

Dead

Normal health

X

46

Time Trade-Off

TTO Wheelchair

With a life expectancy: 50 years

How many years would you trade-off for a cure? Max. trade-off is 10 years

QALY(wheel) = QALY(healthy) Y * V(wheel) = Y * V(healthy)

50 V(wheel) = 40 * 1

V(wheel) = .8

47

Standard Gamble

SG Wheelchair Life expectancy is not important here How much are risk on death are you prepared

to take for a cure? Max. risk is 20%

wheels = (100%-20%) life on feet

V(Wheels) = 80% or .8

48

Consistent picture of difference

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

EQ-5D health states

Uti

liti

es

SG

TTOVAS

103 students

49

Health economics prefer TTO/SG

Visual analogue scale Easy

No trade-off: no relation to QALY

• No interval proportions

Standard Gamble / Time trade-Off Less easy

Trade-off: clear relation to QALY

• Interval proportions

Little difference between SG and TTO

50

Little difference between Cost/Life Year and Cost/QALY

Richard Chapman et al, 2004, Health Economics

51

Difference in QALYs makes little difference in outcome

Richard Chapman et al, 2004 “In a sizable fraction of cost-utility analyses,

quality adjusting did not substantially alter the estimated cost-effectiveness of an intervention, suggesting that sensitivity analyses using ad hoc adjustments or 'off-the-shelf' utility weights may be sufficient for many analyses.”

“The collection of preference weight data should […] should only be under-taken if the value of this information is likely to be greater than the cost of obtaining it.”

52

QALYs make a difference when:

Chronic disease Palliative Long term negative consequences

53

Conclusions

SG/TTO are preferred in Health economics Reproducible results

Problems in QALYs are overestimated Difference in QALYs makes little difference in outcome

• Compared to cost per life year

• With exception of chronic illness