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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
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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)
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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
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4 A new wheelchair for elderly (iBOT) Special post natal care Which health care program is the most cost-effective?
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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?
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6 QALY league table
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7 1.0 0.0 ABC Utility of Health Egalitarian Concerns: Burden of disease
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8 CE-ratio by equity
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9 Burden as criteria Pronk & Bonsel, Eur J Health Econom 2004, 5: 274-277
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10 What form of equity?
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11 3500 Citations in PubMed
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12 Top 6 journals Cost Utility Analysis www.tufts-nemc.org/cearegistry
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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
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14 Utility assessment Unidimensional QoL Often called ‘utility’
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15 Who to ask? The patient, of course!
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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!
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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
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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
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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….?
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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
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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?
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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
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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
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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
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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
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26 EQ-5D, HUI and SF-36 Of the shelf instruments….
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27 Validated questionnaires
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28 The Rosser & Kind Index
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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
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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
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31 Validated questionnaires
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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)
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33 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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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%
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35 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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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)
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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
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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?
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39 More health states, more assumptions General public values at the most 50 states The ratios empirical (50) versus extrapolated Rosser & Kind1:1 EuroQol1:5 QWB1:44 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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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
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41 Conflicting evidence sensitivity SF-36 Liver transplantation, Longworth et al., 2001
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42 Conclusions More states better sensitivity The three leading questionnaires have different strong and weak points
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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
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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
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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 versus worse imaginable health Dead Normal health X
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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
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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
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48 Consistent picture of difference 103 students
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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
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50 Little difference between Cost/Life Year and Cost/QALY Richard Chapman et al, 2004, Health Economics
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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.”
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52 QALYs make a difference when: Chronic disease Palliative Long term negative consequences
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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
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