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Published byOscar Wells Modified over 8 years ago
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1 EQ-5D, HUI and SF-36 Of the shelf instruments….
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2 Direct valuation
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3 …or use 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
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4 Validated questionnaires
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The Rosser & Kind Index 5
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The Rosser & Kind index One of the oldest valuation 1978: Magnitude estimation Magnitude estimation PTO / VAS N = 70 Doctors, nurses, patients and general public 1982: Transformation to “utilities” On a 0.00 to 1.00 scale Could be used for QALYs 6
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1985: High impact article 7
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Survey at the celebration of 25 years of health economics in the UK (HESG): chosen most influential article on health economics 9
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Criticism on the Matrix Sensitivity only 30 health states The unclear meaning of “distress” The involvement of medical personnel No clear way how to classify the patients into the matrix Only British values The compression of states in the high values 10
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Value compression 11
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New initiatives Higher sensitivity (more then 30 states) More and better defined dimensions Other valuation techniques Standard Gamble, Time Trade-Off, Visual Analogue Scale Values of the general public A questionnaire… to allow patients to ‘self classify’ themselves An international standard to allow international comparisons That is at that time “Europe” 12
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13 Validated questionnaires
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14 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)
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15 Statistically inferred strategies Value a sample of states empirically Extrapolation Statistical methods, like linear regression 11111 = 1.00 11113 =.70 11112 = ?
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16 Statistically inferred strategies EuroQol EQ-5D: 5 dimensions of health 245 health states Quality of Well-Being scale (QWB) 4 dimensions of health 2200 health states plus 22 additional symptoms SF-36 SF-6D: 6 dimensions of health 18.000 health states
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17 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% 21111 = 1 - (0.20 x (1.00 - 0.80)) = 0.96
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18 Explicitly Decomposed Methods Combine values of dimensions and levels with specific assumptions Multi Attribute Utility Theory (MAUT) Mutual utility independence Structural independence
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19 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)
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20 Exercise EuroQol EQ-5D (3 level) SF-6D
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21 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 Now development of 5 Level EQ-5D-5L No consensus in EuroQoL that more levels is always better…
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EQ-5D-3L versus EQ-5D-5l
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23 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?
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24 5Lmore sensitive than 3L
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25 More health states, more assumptions General public values at the most 50 states The ratios empirical (50) versus extrapolated Rosser & Kind1:1 EuroQol EQ-5D-3L1:5 QWB1:44 EQ-5D-5L1:63 SF-361:180 HUI (Mark III)1:19,400 15D1:610,000,000 What is the critical ratio for a valid validation?
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26 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
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27 Collapsing levels SF-6D Many levels are taken together If PF=2decrement: - 0.056 If PF=3decrement: - 0.056 If RL=2decrement: - 0.073 If RL=3 *decrement: - 0.073 If RL=4 *decrement: - 0.073
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28 SF-6D loses a lot of levels Levels in system and actual levels PF6 5 RL 42 SF 55 PN 65 MH 54 VI 53 Levels in system: 18.000 6x4x5x6x5x5 Actual levels: 480 5x2x5x5x4x3
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Conflicting evidence sensitivity SF-36 Liver transplantation, Longworth et al., 2001
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30 EQ-5D-3L Strong punts Very sensitive in the low Measures subjective burden (inside the skin) Low administrative burden Many translations Cheap Most used QALY questionnaire Most international validations Weak points Only there levels per dimensions Insensitive in the high regions
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31 EQ-5D-5L Strong punts Very sensitive in the low Measures subjective burden (inside the skin) Low administrative burden Many translations Cheap Weak points No scorings algorithm yet Might still not be as sensitive in the high regions
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32 HUI Strong punts Sensitive Measures objective burden (outside the skin) Well developed proxy versions Well developed child versions Weak points Expensive
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33 SF-6D Strong punts Probably sensitive in the high regions Often already include in trials (SF-36) Cheap …. Many translations Weak points Insensitive in the low regions Only one validation study Changed Standard Gamble Upwards shift of values
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EQ-5D-Y No scoring algorithm
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35 Conclusions More states better sensitivity The three leading questionnaires have different strong and weak points
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