Measuring health state utilities for cost utility analysis

MEASURING HEALTH-STATE UTILITIES FOR COST-UTILITY ANALYSIS WANG PEI (B.SC., M.SC.) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY SAW SWEE HOCK SCHOOL OF PUBLIC HEALTH NATIONAL UNIVERSITY OF SINGAPORE 2013 DECLARATION I hereby declare that this thesis is my original work and it has been written by me in its entirety I have duly acknowledged all the sources of information which have been used in the thesis This thesis has also not been submitted for any degree in any university previously Wang Pei August, 2013 ii ACKONWLEDGEMENTS First, I would like to thank the National University of Singapore for providing a generous scholarship during my years‟ candidature I would like to express my sincerest gratitude to my supervisor, Dr Luo Nan, for his direction, patience and high standards in research He has taught me a lot about how to research and write academic papers He also spent many hours reviewing my original manuscripts, gave valuable suggestions and made detailed editions His support has been invaluable for me to complete this thesis I am also grateful to my supervisor, Prof Julian Thumboo, and Prof Lee Hin Peng who is my PhD committee chair, for their continuous support, suggestions to accomplish my work My sincere thanks also go to Assoc Prof Tai E Shyong, who provided research subjects for me I am also thankful to Prof Cheung Yin Bun for his instructions on statistical methods I would like to thank Dr Wee Hwee Lin for giving my opportunities to participant in pharmacy journal club My thanks are also due to Dr Wong Kin-Yoke for her help in questionnaire design I would also like to thank Saw Swee Hock School of Public Health for giving me the student travel grants and providing me research facilities Thanks are also due to all staffs at the School of Public Health for their support and kindness Many thanks go to my colleagues and office-mates, Yang Fan, Wang Xing Zhi, iii Zhou Hui Jun, Chen Zhao Jin, Vivian, Pan Chen Wei, Jiang Jun Dong and Zhou Xin for their help and a source of inspiration Finally, I would like to deeply thank my family for their wholehearted support and continuous encouragement iv TABLE OF CONTENTS Acknowledgements iii Table of contents v Summary viii List of tables x List of figures xii List of Publications xiii Chapter One - Introduction 1 How to Define Health States How to Measure HSU values 2.1The Direct Methods 2.1.1 Standard Gamble 2.1.2 Time Trade-Off 2.1.3 More on Standard Gamble and Time Trade-Off 2.1.4 Discrete Choice Experiments 10 2.2 The Indirect Method 11 2.2.1 EQ-5D 12 2.2.2 SF-6D 12 2.2.3 HUI 13 2.3 Mapping Health Profiles to Health-state Utilities 17 2.3.1 Model Specification 18 v 2.3.2 Model Estimation 18 2.3.3 Model Performance 19 Whose Health-state Utilities Should Be Used? 21 3.1 General Population Health-state Utilities 22 3.2 Patient Health-state Utilities 23 Research Objectives 24 Summary of Studies 26 Chapter Two – Do Asians have similar health-state preference? A comparison of mainland Chinese and Singaporean Chinese 28 Introduction 28 Methods 30 Results 36 Discussion 42 Chapter Three – The impact of diabetes on health-state utilities 46 Introduction 46 Methods 48 Results 52 Discussion 55 Chapter Four – Valuation of EQ-5D-3L health states in Singapore 57 vi Introduction 57 Methods 59 Results 67 Discussion 76 Chapter Five – Predicting preference-based SF-6D index scores from the SF-8 health survey 85 Introduction 85 Methods 87 Results 92 Discussion 100 Chapter Six – Preference-based SF-6D scores derived from the SF-36 and SF-12 have different discriminative power in a population health survey 105 Introduction 105 Methods 106 Results 110 Discussion 117 Chapter Seven – Conclusions 121 Bibliography 125 vii SUMMARY Given that no country can afford the costs of all health-care programs which claim to have some benefits, cost-utility analysis (CUA) which compares the costs of an intervention with its benefits, is increasingly used for setting priorities In CUA, the benefits are measured as quality-adjusted life-years (QALYs), which combines quantity of life with health-related quality-of-life (HRQoL) into a single measure To calculate QALY values, health-state utilities (HSU) need to be used as HRQoL weights Several research questions on HSU measurement are addressed First, we compared the preference values of EQ-5D-5L health states between mainland Chinese and Singaporean Chinese We found that Singaporean Chinese valued EQ-5D-5L health states with severe or extreme problems as much more undesirable than mainland Chinese Second, we investigated whether the values of the EQ-5D-3L health states are the same to the general population and the patients of interest For this purpose, we compared the TTO values of EQ-5D-3L health states directly elicited from patients with type diabetes mellitus (T2DM) and the general population in Singapore We found that the values of EQ-5D-3L states with mild health problems to T2DM patients were higher than to the general population, although these two populations valued the EQ-5D-3L states with severe health problems as similarly undesirable Third, we developed an EQ-5D-3L value set using time trade-off (TTO) values directly measured from the general Singaporean population because there was viii no local HSU value sets Fourth, we developed functions to predict the SF-6D36 index score from the SF-8 health survey Fifth, we compared the discriminative power of the SF-6D index score derived from the SF-36 and SF-12 We found the SF-36 provides a more discriminative preference-based health index than the SF-12 These studies have generated new knowledge on measuring HSUs and provided health service researchers with useful tools and guidance for obtaining HSU values First, the much greater health benefit gained from a transition from a severe health state to a mild health to Singaporean Chinese than to mainland Chinese supports the practice of developing local EQ-5D-5L value sets Second, the values of mild EQ-5D-3L health states are higher to T2DM patients than to the general population indicates that the EQ-5D-3L values based on the general population‟s preferences could be insensitive to the benefits of and underestimate the effectiveness of health inventions for T2DM Hence, it may be worthwhile to determine the values of the EQ-5D-3L health states to patients with a certain condition Third, the established EQ-5D-3L value set provides health services researchers in Singapore a useful tool to appraise the cost-effectiveness of health programs and technologies Fourth, the functions developed for predicting the preference-based SF-6D36 index score from the psychometric instrument SF-8 enable the SF-8 data to be used in CUA Fifth, the finding that the SF-6D derived from the SF-36 is more sensitive than that derived from the SF-12 supports the usage of the SF-6D index score derived from the SF-36 when a preference-based index is needed ix LIST OF TABLES Table 1.1 Characteristics of the generic preference-based instruments 15 Table 2.1 Characteristics of participants 38 Table 2.2 Comparison of TTO values between Mainland Chinese and Singaporean Chinese 40 Table 3.1 Characteristics of participants 53 Table 3.2 TTO values between T2DM patients and the general population 54 Table 4.1 Health states valued in the study 64 Table 4.2 Socio-demographic statistics of full sample and valuation sample compared with Singapore population 69 Table 4.3 Parameter estimates and goodness-of-fitness statistics at individual level using Fixed effect (FE) and random effect (RE) regression 73 Table 4.4 Parameter estimates and goodness-of-fitness statistics at aggregated level using OLS regression 75 Table 5.1 Socio-demographic characteristics and health status of the study sample (N=7529) 93 Table 5.2 Goodness of fit of the tested OLS models in the modeling dataset 95 Table 5.3 Goodness of fit of tested OLS models in the validation dataset 96 Table 5.4 The parameters of the OLS models estimated using the entire dataset (N=7529) 99 Table 6.1 Characteristics of the preference-based instruments 106 Table 6.2 Demographic characteristics of the study sample 112 Table 6.3 The SF-6D36 and SF-6D12 scores for respondents with and without a chronic condition 114 x Chapter Conclusions Wang, Pei simpler and its values are less likely to be affected by factors other than preferences for health states It is a promising tool in health-state valuation The EQ-5D-5L is a new version of the EQ-5D-3L, which has the same domains as the EQ-5D-3L, but comprises functional levels including no problem (level 1), slight problems (level 2), moderate problems (level 3), severe problems (level 4), and extreme problems (level 5) Currently, the EQ-5D-5L index score can be obtained by applying the indirect mapping method from the EQ-5D-3L to the EQ-5D-5L Future studies need to develop EQ-5D-5L value sets based on directly measured EQ-5D-5L health states 124 BIBLIOGRAPHY Abdin E, 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