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
2
Authors: Éva Orosz, Zoltán Kaló and Balázs Nagy Supervised by Éva Orosz
June 2011
Week 13
Applicability of economic evaluation in the allocation of health care reseources and
health policy decisions
Authors: Zoltán Kaló and Balázs Nagy Supervised by Éva Orosz
Budget Impact Analysis
• BIA: an essential part of a comprehensive economic assessment of a health-care technology:
• Increasingly required, along with cost-effectiveness analysis (CEA), before formulary approval or reimbursement.
• Purpose: to estimate the financial consequences of adoption and diffusion of a new health-care intervention within a specific health-care setting or system context given inevitable resource constraints.
• BIA predicts how a change in the mix of drugs and other therapies used to treat a particular health condition will impact the trajectory of spending on that condition.
3
• Can be used for budget planning, forecasting and for computing the impact of health technology changes on premiums, financing methods and incentives in health insurance schemes.
Budget Impact Analysis Task Force Report, Value Health, 2007
Structure of BIA report
• Report introduction
– Epidemiology and treatment – Clinical impact
– Economic impact
• Technology
• Objectives
Budget Impact Analysis Task Force Report, Value Health, 2007
• Study design and methods – patient population – technology mix – time horizon
– perspective & target audience – model description
– input data – data sources.
– data collection – analyses
• Results
• Sensitivity analysis
• Conclusion
4
Budget Impact Analysis methodology
Budget Impact Analysis Task Force Report, Value Health, 2007
5 Ref: Marshall et al: Pharmacoeconomics 2008; 26 (6): 477-495
6
Market size
BIA modelling
• Static model
– Simple calculation of cost impact from changing one or two factors, holding everything else constant
– May be sufficient if the alternative and reference scenarios are quite similar and probabilities are well known
• Dynamic model
– Captures uncertainty: probability of clinical outcomes
– Captures indirect consequences: more attention on diagnosing patients, shift in resource utilisation, different copayment of patients
– More difficult to understand
7
BIA perspective
Provider/payer’s perspective.
• Excludes patient-incurred costs.
• BIA should reflect impacts on enrollment and retention that could result from affecting patients.
• Ignoring patient and societal costs: many interventions appear less expensive in BIA than in CEA.
• No need to survey patient.
BIA time horizon
Short horizon (max 3–5 years)
• Long-term modeling of costs and clinical outcomes is unnecessary.
• Costs are not usually adjusted for inflation or discounting.
• Reductions in health costs in far future cannot offset initial costs.
BIA necessary conclusions
• The number of the patients with respect to the treatment, including the method of calculation
• Calculation of daily treatment cost and the expected dosage according to the expected therapeutic practice in the given indication
• Risk of using the reimbursed technology outside of the reimbursed indication mentioned? (i.e. the possibility of ‘off-label’ use from a financial perspective)
• Expected sales of the investigated technology
• Net budget impact of the public financing
• The location and time horizon of the budget impact and the potential savings?
8
• If the study mentions savings, will they be realisable in practice from the payers’
aspect?
• If the study mentions savings, will they be realisable in practice from the aspect of the health care provider?
• Sensitivity analysis for the budget impact (number of patients, dose, length of treatment, market penetration, etc.)
• (Will the reimbursement result in additional direct costs or financial burden for the patient?)
Major question of BIA: decision rule
• New technologies usually increase health gain at incremental costs.
• Cost drivers
– increased utilization: extended life (oncology), improved compliance (side- effect profile)
– higher price: improved QoL
– potential reduction of other health care services: smaller impact than in Western Europe
• Can we expect cost-savings? Probably not.
• If not, what is the criteria for BIA? Especially if cost-effectiveness of the new technology is not known?
Application of economic evaluation:
Exercise
9
Why do we need the assessment of cost- effectiveness to reimbursement decisions?
• Assessment of health benefits is not sufficient, as it does not include financial implications (value for money, budget impact).
• Budget impact analysis: may result in false conclusion without assessment of the economic value of new technologies.
Conditions of mandatory economic evaluation in reimbursement decisions
• Human resources (including training)
• Financial resources
• Data availability
• Academic, public institutes
• Political support (willingness to transparency, consistency)
• Collaboration
Introduction the fourth hurdle: necessary steps
• Methodological guidelines – how to conduct economic evaluations
• Decision rules – willingness to pay for a quality adjusted life years gain
• Legislation: incorporation of cost-effectiveness evidence into the reimbursement process
10
• Public budget and organisation for health technology assessment
• Training
– decision-makers – appraisal committee – future trainers
– (undergraduate training)
• Revision of first 20-30 cases iteration and correction
• Critical appraisal checklist
Central Eastern European status
• Compared to Western Europe – worse health status
– even more limited health care resources
– strategic pricing of new health care technologies is adjusted to large Western European countries
• Minimal prospective health economic data collection
• Few trained health economists
• Low public budget for health technology assessment
• No excuse: must improve the appropriateness of reimbursement decisions
Cost effectiveness results
cost QALY
old therapy 12,000 € 0.6 improved therapy 24,000 € 1.5
Cost effectiveness threshold: 30,000 €
11
ICER
Results ICER
Comparator dcost/dQALY improved therapy old therapy 13,333 €
0 € 5 000 € 10 000 € 15 000 € 20 000 € 25 000 € 30 000 € 35 000 € 40 000 €
0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4
incremental cost
QALY gain
12
Cost effectiveness results
Cost effectiveness threshold: 30,000 €
ICER
cost QALY
old therapy 12,000 € 0.6 standard
therapy 24,000 € 1.5 new therapy 36,000 € 1.8
Results ICER
Comparator ∆cost/∆QALY
standard therapy old therapy 13,333 €
new therapy standard therapy 40,000 €
13
Results ICER
Comparator ∆cost/∆QALY
standard therapy old therapy 13,333 €
new therapy standard therapy 40,000 €
new therapy old therapy 20,000 €
14
Optimisation cost-effectiveness to local needs
• Reduce price
– confidential rebate/discount
– financial risk-sharing (price volume agreement, etc) – volume related rebate
• Narrow target patient groups
– risk status: only high-risk patients – positioning: only third-line therapy
– selection of potential responders (e.g. genetic test)
• Guarantee outcomes – pay for performance
– outcomes based risk-sharing
Ref: Sullivan S, ISPOR Paris, 2009
15
ELTE Faculty of Social Sciences, Department of Economics
Thank You for using this teaching material. We welcome any questions, critical notes or comments we can use to improve it.
Comments are to be sent to our email address listed at our homepage,
