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Health outcome valuation study in Thailand

Sirinart TongsiriResearch degree studentHealth Services Research Unit, Public Health & Policy DepartmentLSHTM

Supervisor: Professor John Cairns

17 November 2006

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Outline

Introduction Research question Objectives Methods Budget & Timetable Conclusion

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Introduction

Resources are limited Market failures in Health Economic Evaluation

ICER = Cost Outcome

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Cost-utility analysis (CUA)

Outcome in CUA Quality-adjusted Life Year Impact on health: Quality of life &

Quantity of life Compare across different health

interventions

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Quality-Adjusted Life Year (QALY)

Quality of life (QoL)

life expectancy

Before treatment

After treatment

Health interventions

0

1

Q0

Q1

T0 T1

QALY gain = Q1T1 – Q0T0

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Recommendations from the NICE and the US Panel on Cost-Effectiveness in Health and Medicine

A tariff estimated from the general population

No tariff estimated from the Thai general population

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A national tariff for preference-based health measure: Why?

UK = -0.098Denmark = 0.101Zimbabwe = 0.400Japan = 0.031Thailand ?

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Research question:

A tariff for health outcomes from the Thai perspective

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How to elicit preferences over health states?

Torrance (1986) Prepare health state descriptions Selection of subjects Use a utility measurement

instrument

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Health

Complex Encompass many dimensions Individuals perceive differently A number of generic health

descriptive systems, e.g. the EQ-5D, the SF-36 and the HUI

The EQ-5D will be used in the research

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The EQ-5D

5 Dimensions - Mobility - Self-care - Usual activities - Pain and Discomfort - Anxiety and Depression

3 Levels - No problem - Some problems - Severe problems

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The EQ-5D

5 Dimensions - Mobility - Self-care - Usual activities - Pain and Discomfort - Anxiety and Depression

3 Levels - No problem - Some problems - Severe problems

11223

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The EQ-5D

5 Dimensions - Mobility - Self-care - Usual activities - Pain and Discomfort - Anxiety and Depression

3 Levels - No problem - Some problems - Severe problems

243 health states

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Problem 1:

Is the EQ-5D an appropriate tool to capture a concept of “health” in the Thai population?

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Preference, Utility, Value

What different between these terms?

Different methods to derive preferences, e.g. VAS, SG and TTO

Different methods give different values

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Assumption

A fully informed rational person is the best judge of one’s own welfare

Individual utility can be aggregated and comparable.

An interval scale is needed

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An interval scale

The difference between score 20 and 10 (10) is equal to the difference between 30 and 20 (10).

The difference between the state with score 0.4 and 0.3 (0.1) is equal to the difference between the state 0.6 and 0.5 (0.1)

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How to “quantify” preference?

Health states ranking, the VAS and the TTO methods will be used to elicit preferences of respondents in the study

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Whose preferences should be elicited? Patients or Population

Population Aim to use in decision making at the

societal perspective Generalizability

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Debates

Whose values should be counted? Preferences are “elicited” or

“constructed”? Preferences are “labile”. Simple Heuristics Framing and labelling effects

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UtilityPerceived Risk attitudestate attributes Time preference

Health state Health preferences

Description Cognition

Elicitation Utility procedure measurement

Emotions and prejudices NumeracyRandom errorLogical errorCross method inconsistencyAnchoring on single values

How individuals respond to the preference elicitation methods

Lenert et al. 2000

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Problem 2:

Do the elicitation methods appropriate for the Thai population?

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Pre-pilot study in London

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Pre-pilot study in London

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Cognitive burden

How to minimize cognitive burden of Thai respondents?

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Respondents can value not more than 13 health states

How all 243 health states will be scored?

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Problem 3:

Existing statistical models from various countries

Do these models fit with preferences observed from the Thai population?

What is an appropriate model for the Thai population?

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Thailand

A majority of population is Buddhist

Religious belief 1 : the perfect health in this life guarantee the perfect health in next life

Religious belief 2: inferior health results from bad kamma from previous life (no preferences on different inferior health)

Does these beliefs influence TTO?

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Are Buddhism beliefs influence preferences on health of the Thai general population ?

The study by Chirawatkul (2005)

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Bad Kamma

GermsDrunkeness

Poisoning Carelessness

Aging Disease Congenital AccidentBad luck

Supernatuaral factors

Disability

Mild Moderate Severe

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Objectives

1. Elicit preferences on health states from a Thai general population

2. Identify appropriate statistical models to explain respondents’ preferences over health states

3. Whether the Thai EQ-5D adequate to capture health concept of the Thai general population

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Methods

Objective 1:- Health states ranking- Visual Analog Scale- Time trade-off

Pre-testing and piloting the survey questionnaire and process

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Pre-testing the questionnaire

What, from Thais, are “usual activities”, “self-care”?

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Pilot interview

To test the interview procedure Cognitive burden

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Sample

Randomly selected from the Thai general population

Household registration database The National Statistical Office,

Thailand Health Welfare Survey (addresses

and maps are included) Regional level: 5 provinces in the

central region

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1 region (Central region)

5 provinces: Ratchaburi, Phetchaburi, Nakorn-Nayok,Nakorn-Pathom andPrachuab Kirikhan Multi-stage sampling

Sample size = 1,000

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Interview procedure

Replicate from the Measurement and Valuation of Health (MVH) study in the UK (Dolan et al 1995)

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Interview procedure

Complete the EQ-5D with own health Ranking own health Ranking 15 different health states Score each state using the VAS Score each state using the TTO Personal details: age, gender, education

and socioeconomic status

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Thai EQ-5D questionnaire

Mobility

Self-care

Usual activities

Pain/Discomfort

Anxiety/Depression

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Thermometer scale

The best health imagination

The worst health imagination

Your health today

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Example of health state card

ข้�าพเจ้�า ไม่สาม่ารถไปไหนได้�และจ้�าเป�นต้�องอยู่�บนเต้�ยู่ง ม่�ป�ญหาในการอาบน�!าหร"อการแต้งต้#วบ�าง ไม่สาม่ารถทำ�าก&จ้กรรม่ทำ�'ทำ�าเป�นประจ้�าได้� ไม่ม่�อาการเจ้(บปวด้หร"ออาการไม่ส)ข้สบายู่ ร� �ส*กว&ต้กก#งวลหร"อซึ*ม่เศร�าม่ากทำ�'ส)ด้

Moderate32313ข้�าพเจ้�า ม่�ป�ญหาในการเด้&นบ�าง ไม่สาม่ารถอาบน�!าหร"อแต้งต้#วด้�วยู่ต้นเองได้� ม่�ป�ญหาในการทำ�าก&จ้กรรม่ทำ�'ทำ�าเป�นประจ้�าอยู่�บ�าง ม่�อาการเจ้(บปวด้หร"ออาการไม่ส)ข้สบายู่ม่ากทำ�'ส)ด้ ร� �ส*กว&ต้กก#งวลหร"อซึ*ม่เศร�าปานกลาง

Severe23232

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Health states ranking

11111

3333332331

1221322231

11213

22133

33211

1123311323

22333

13131

21212

11111 - anchor

11213

11233

11323

11213

12213

22231

22133

33211

32231

32331

33333 - anchor

Bisection method

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Time trade-off question

1. Imagine that you live in a state for 10 years and die

2. If you can choose to live in healthy life and die sooner than 10 years, how many years you would sacrifice?

Preference is subjective. To compare preference between states,Years of life in perfect health will be compared

The shorter duration in perfect health, the less preferred state(use years of life to “buy” a better state)

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Time trade-off score transformation

Duration of life (yrs)

Health status

1

0

10

X

Preference = x 10

Better than death

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Time trade-off score transformation

Duration of life (years)

Health status

10X

1

0

Value of health state:

-x (10-x)

Worse than death

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Statistical Modelling

To estimate preferences for 243 health states from the observational data of 42 health states

Econometrics methods Use existing models to fit new data STATA 9

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Estimate preference from TTO

Better health states have higher preferences

11211 is “better” than 11222

Overall preference is the result of the addition of sub-preference in each dimension

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Example of models

Dolan 1997

322222 11109876

54321

NAPUSM

ADPDUASCMOy

R2 = 0.46Mean absolute difference = 0.46

Dolan et al 2002

ijijijijij ANYxxcy 1321 '2

'1

R2 = 0.55Mean absolute difference = 0.03

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Estimate preference from health states ranking

Salomon (2003)

^'jxij

Parameters are predicted using the conditional logit regression model

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Timetable

Activities When?1. Proposal, budget and questionnaire preparation

November 2006 – January 2007

2. Preference elicitation interview

February – June 2007

3. Identify appropriate modelling to predict preferences from TTO and VAS

July - August 2007

4. Qualitative survey September – December 2007

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Budget

Preparation 10,000 baht Preference interview 737,000 baht Qualitative survey 18,400 baht

Total: 765,400 baht

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Potential funding organizations

The International Health Policy and Programs, Thailand

The Health promotion for the Disabled project, Thailand

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Conclusion

Can the EQ-5D health description system capture the concept of health in Thais?

A tariff of the Thai EQ-5D to be used in the economic evaluation in Thailand

How existing models can fit the new data

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How Buddhist beliefs influence preference on health states

Contribution of preference scores to a new version of the EQ-5D

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Acknowledgement

Prof. John Cairns Louise Longworth Dr.Viroj Tangcharoensathien Dr.Wachara Riewpaiboon My fellow PhD students My family