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HEALTH ECONOMICS

Sponsored by a Grant TÁMOP-4.1.2-08/2/A/KMR-2009-0041 Course Material Developed by Department of Economics,

Faculty of Social Sciences, Eötvös Loránd University Budapest (ELTE) Department of Economics, Eötvös Loránd University Budapest

Institute of Economics, Hungarian Academy of Sciences Balassi Kiadó, Budapest

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Authors: Éva Orosz, Zoltán Kaló and Balázs Nagy Supervised by Éva Orosz

June 2011

Week 10

Cost-effectiveness and cost-utility analyses

Authors: Zoltán Kaló and Balázs Nagy Supervised by Éva Orosz

Full economic evaluation

(comparative assessment of both costs and consequences of two or more alternative health care interventions)

Type of analysis Abbr. Unit of inputs (costs)

Unit of outputs (consequences)

cost-minimisation CMA money identical cost-

effectiveness CEA money natural unit (e.g. Hgmm, life years)

cost-utility CUA money quality adjusted life years (e.g.

QALY)

cost-benefit CBA money money

Drummond et. al. (1987)

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Cost-effectiveness analysis

• Costs and savings are assessed in monetary values

• Health benefit is expressed in natural units

– intermediate outcomes (Hgmm blood pressure, mmol/L cholesterol reduction) – hard endpoints (life years gained, disease free days, screened cases)

• Health benefits captures only one dimension

• Decision-making based on ratio

• Applicability: reimbursement decision, is the new health care technology more cost- effective than the current standard

Categories of health outcomes

Natural units

• Hgmm blood pressure reduction

• mmol/L cholesterol reduction

• disease (ulcer) free days

• symptom free days

• avoided amputation

• life years gained

• …

D = Drug cost

C = Other treatment cost E = Effectiveness

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Surrogate (intermediate) outcomes vs hard end-points

RCT results

(1000 patients) Placebo Clofibrat Relative risk reduction

Serum cholesterol

reduction +1% –9%

Non-fatal myocardial

infarct 7.2 5.8 –19%

Fatal and non-fatal

myocardial infarct 8.9 7.4 –17%

Total mortality 5.2 6.2 19%

Source: Sackett et al. – Clinical Epidemiology, 1995

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Incremental cost per life years gained

in US dollars (USD) in terms of fees valid in 1997 Source: Kalo, Járay, Nagy – Progress in Transplantation (2001)

Critical factors of cost-effectiveness analyses

• Surrogate outcome vs. real health gain (hard endpoints)

• Solution: Validation of surrogate outcomes in clinical trials and observational studies

• Health status changes outside the scope of the selected naturalistic endpoint (e.g.

side-effect).

• Solution: inclusion of consequences of these parameters into costs Health care service Haemodialysis (waiting listed) Transplantation

Transplantation 11,444

Dialysis 31,654 4,411

Transport for dialysis 6,049 650

Outpatient care 537 353

Inpatient care 809 886

Medication 5,798 8,813

Total per one life-year

gained 44,846 26,557

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Cost-effectiveness analysis

Applicability:

• Allocative efficiency (with limitations)

• To compare two alternative health technologies, if health outcomes – can be measured by the same health dimension

– are unequal

• Can be used to support reimbursement decisions (ranking between old vs. new technology)

Cost-utility analysis

• Costs and savings are assessed in monetary values

• Health benefit is expressed in quality adjusted life years

QALY, HYE, DALY

• Applicable for all health care interventions

• Decision-making based on ratio

• Applicability: reimbursement decision or revision of insurance package

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Visual analogue scale

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Standard gamble

Time Trade-Off

Torrance GW. J Health Econ 1986.

Torrance GW. J Health Econ 1986.

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Dilemma of establishing utility values

Whom should we ask about the relative utility of each health status?

• patients?

• general population?

• medical workers?

EQ-5D questionnaire

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EQ-5D tariffs (Dolan N3)

Alternatives of QALY measurement in clinical trials

• Direct method: eliciting utility values by applying PROs with related utility values (EQ5D, SF36, QWB)

• Indirect method

• applying HRQoL instruments in clinical trials

• mapping HRQoL and utility values in an independent cross-sectional survey dimension coefficient

constant 0,081

mobility 1. 2. level 2. 3. level

0,069 0,314

self-care 1. 2. level 2. 3. level

0,104 0,214

Usual activities 1. 2. level 2. 3. level

0,036 0,094

pain / discomfortt 1. 2. level 2. 3. level

0,123 0,386

anxiety / depression 1. 2. level 2. 3. level

0,071 0,236

N3 (3. level in any dimension)

0,269

unconscious -0,402

Health Status: 11223 calculated utility:

1 – 0,081 – 0,036 – 0,123 – 0,236 – 0,269 =

0,255

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QALY League Table

Cost/QALY (£ 1990) Cholesterol testing and diet therapy only (all adults, aged 40-69) 220

Neurosurgical intervention for head injury 240

GP advice to stop smoking 270

Neurosurgical intervention for subarachnoid haemorrhage 490 Anti-hypertensive therapy to prevent stroke (ages 45-64) 940

Pacemaker implantation 1,100

Hip replacement 1,180

Valve replacement for aortic stenosis 1,140

Cholesterol testing and treatment 1,480

CABG (left main vessel disease, severe angina) 2,090

Kidney transplant 4,710

Breast cancer screening 5,780

Heart transplantation 7,840

Cholesterol testing and treatment (incrementally) of all adults aged 25-39 years

14,150

Home haemodialysis 17,260

CABG1 (1 vessel disease, moderate angina) 18,830

CAPD2 19,870

Hospital haemodialysis 21,970

Erythropoietin treatment for anaemia in dialysis patients (assuming a 10% reduction in mortality)

54,380

Neurosurgical intervention for malignant intracranial tumour 107,780

Erythropoietin treatment for anaemia in dialysis patients (assuming no increase in survival)

126,290

Source: Maynard A.K. (1991): Developing the health care market.

Economic Journal, 101, 1277-1286.

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Applicability of cost-utility analysis

• To improve the allocative efficiency in health care financing

• To compare any alternative health technologies with different health gain, even if health outcomes are measured in different dimensions

• Examples:

– reimbursement decisions (ranking between old vs. new technology)

– exclusion of therapies from reimbursement (e.g. technologies with huge budget impact)

– development of financing protocols based on existing therapeutic guidelines – comparison of all medical technologies (e.g. to define insurance package)

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