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Health outcome valuation study in Thailand

Health outcome valuation study in Thailand. Sirinart Tongsiri Research degree student Health Services Research Unit, Public Health & Policy Department LSHTM Supervisor: Professor John Cairns. 17 November 2006. Outline. Introduction Research question Objectives Methods

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Health outcome valuation study in Thailand

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  1. Health outcome valuation study in Thailand Sirinart Tongsiri Research degree student Health Services Research Unit, Public Health & Policy Department LSHTM Supervisor: Professor John Cairns 17 November 2006

  2. Outline • Introduction • Research question • Objectives • Methods • Budget & Timetable • Conclusion

  3. Introduction • Resources are limited • Market failures in Health • Economic Evaluation ICER = Cost Outcome

  4. 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

  5. Quality-Adjusted Life Year (QALY) Quality of life (QoL) 1 Before treatment Q1 After treatment Q0 Health interventions 0 life expectancy T1 T0 QALY gain = Q1T1 – Q0T0

  6. 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

  7. A national tariff for preference-based health measure: Why? UK = -0.098 Denmark = 0.101 Zimbabwe = 0.400 Japan = 0.031 Thailand ?

  8. Research question: A tariff for health outcomes from the Thai perspective

  9. How to elicit preferences over health states? Torrance (1986) • Prepare health state descriptions • Selection of subjects • Use a utility measurement instrument

  10. 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

  11. The EQ-5D 5 Dimensions - Mobility - Self-care - Usual activities - Pain and Discomfort - Anxiety and Depression 3 Levels - No problem - Some problems - Severe problems

  12. 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

  13. 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

  14. Problem 1: • Is the EQ-5D an appropriate tool to capture a concept of “health” in the Thai population?

  15. Preference, Utility, Value • What different between these terms? • Different methods to derive preferences, e.g. VAS, SG and TTO • Different methods give different values

  16. 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

  17. 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)

  18. How to “quantify” preference? • Health states ranking, the VAS and the TTO methods will be used to elicit preferences of respondents in the study

  19. Whose preferences should be elicited? Patients or Population Population • Aim to use in decision making at the societal perspective • Generalizability

  20. Debates • Whose values should be counted? • Preferences are “elicited” or “constructed”? • Preferences are “labile”. • Simple Heuristics • Framing and labelling effects

  21. Lenert et al. 2000

  22. Problem 2: • Do the elicitation methods appropriate for the Thai population?

  23. Pre-pilot study in London

  24. Pre-pilot study in London

  25. Cognitive burden • How to minimize cognitive burden of Thai respondents?

  26. Respondents can value not more than 13 health states • How all 243 health states will be scored?

  27. 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?

  28. 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?

  29. Are Buddhism beliefs influence preferences on health of the Thai general population ? • The study by Chirawatkul (2005)

  30. Objectives • Elicit preferences on health states from a Thai general population • Identify appropriate statistical models to explain respondents’ preferences over health states • Whether the Thai EQ-5D adequate to capture health concept of the Thai general population

  31. Methods Objective 1: • Health states ranking • Visual Analog Scale • Time trade-off Pre-testing and piloting the survey questionnaire and process

  32. Pre-testing the questionnaire • What, from Thais, are “usual activities”, “self-care”?

  33. Pilot interview • To test the interview procedure • Cognitive burden

  34. 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

  35. 1 region (Central region) 5 provinces: Ratchaburi, Phetchaburi, Nakorn-Nayok, Nakorn-Pathom and Prachuab Kirikhan Multi-stage sampling Sample size = 1,000

  36. Interview procedure • Replicate from the Measurement and Valuation of Health (MVH) study in the UK (Dolan et al 1995)

  37. 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

  38. Thai EQ-5D questionnaire Mobility Self-care Usual activities Pain/Discomfort Anxiety/Depression

  39. The best health imagination Thermometer scale Your health today The worst health imagination

  40. Example of health state card ข้าพเจ้า ไม่สามารถไปไหนได้และจำเป็นต้องอยู่บนเตียง มีปัญหาในการอาบน้ำหรือการแต่งตัวบ้าง ไม่สามารถทำกิจกรรมที่ทำเป็นประจำได้ ไม่มีอาการเจ็บปวดหรืออาการไม่สุขสบาย รู้สึกวิตกกังวลหรือซึมเศร้ามากที่สุด Moderate 32313 ข้าพเจ้า มีปัญหาในการเดินบ้าง ไม่สามารถอาบน้ำหรือแต่งตัวด้วยตนเองได้ มีปัญหาในการทำกิจกรรมที่ทำเป็นประจำอยู่บ้าง มีอาการเจ็บปวดหรืออาการไม่สุขสบายมากที่สุด รู้สึกวิตกกังวลหรือซึมเศร้าปานกลาง Severe 23232

  41. Health states ranking 11111 - anchor 11213 11233 11323 11213 12213 22231 22133 33211 32231 32331 33333 - anchor 11111 21212 32331 11213 33333 Bisection method 33211 12213 22231 22133 11233 11323 22333 13131

  42. 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)

  43. Time trade-off score transformation Health status 1 Preference = x 10 X 0 Duration of life (yrs) 10 Better than death

  44. Time trade-off score transformation Health status 1 Value of health state: -x (10-x) 0 10 X Duration of life (years) Worse than death

  45. 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

  46. 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

  47. Example of models Dolan 1997 R2 = 0.46 Mean absolute difference = 0.46 Dolan et al 2002 R2 = 0.55 Mean absolute difference = 0.03

  48. Estimate preference from health states ranking Salomon (2003) Parameters are predicted using the conditional logit regression model

  49. Timetable

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