11.2 Cost-Effectiveness Analysis Methodology
3 min read•july 22, 2024
Cost- analysis helps healthcare decision-makers compare treatments based on costs and health outcomes. It involves defining the question, measuring costs and outcomes, developing models, and calculating incremental cost-effectiveness ratios (ICERs).
Key steps include identifying relevant costs and health outcomes, creating decision models, and conducting sensitivity analyses. Understanding ICERs, dominance concepts, and sensitivity analyses is crucial for interpreting results and making informed healthcare resource allocation decisions.
Cost-Effectiveness Analysis Methodology
Steps of cost-effectiveness analysis
Top images from around the web for Steps of cost-effectiveness analysis
Extended Cost-Effectiveness Analysis for Health Policy Assessment: A Tutorial | PharmacoEconomics View original
Is this image relevant?
Cost assessment of health interventions and diseases | RMD Open View original
Is this image relevant?
A cost-effectiveness analysis model of Preventicus atrial fibrillation screening from the point ... View original
Is this image relevant?
Extended Cost-Effectiveness Analysis for Health Policy Assessment: A Tutorial | PharmacoEconomics View original
Is this image relevant?
Cost assessment of health interventions and diseases | RMD Open View original
Is this image relevant?
1 of 3
Top images from around the web for Steps of cost-effectiveness analysis
Extended Cost-Effectiveness Analysis for Health Policy Assessment: A Tutorial | PharmacoEconomics View original
Is this image relevant?
Cost assessment of health interventions and diseases | RMD Open View original
Is this image relevant?
A cost-effectiveness analysis model of Preventicus atrial fibrillation screening from the point ... View original
Is this image relevant?
Extended Cost-Effectiveness Analysis for Health Policy Assessment: A Tutorial | PharmacoEconomics View original
Is this image relevant?
Cost assessment of health interventions and diseases | RMD Open View original
Is this image relevant?
1 of 3
- Define the research question and perspective
- Specify the interventions being compared (drug A vs. drug B)
- Identify the target population (patients with type 2 diabetes)
- Determine the time horizon (lifetime) and discount rate (3% per year)
- Identify and measure relevant costs
- Direct medical costs include medications (insulin), procedures (blood tests), and hospitalizations (due to complications)
- Direct non-medical costs include transportation (to doctor's appointments) and caregiving (by family members)
- Indirect costs include productivity losses (due to missed work days)
- Identify and measure relevant health outcomes
- Quality-adjusted life years (QALYs) combine quality of life and life expectancy
- Disability-adjusted life years (DALYs) measure years of life lost due to disability or premature death
- Life years gained (LYG) represent the additional years of life expectancy
- Develop a decision-analytic model
- Decision tree models short-term outcomes and probabilities
- simulates long-term outcomes and transitions between health states
- Microsimulation model tracks individual patient characteristics and outcomes
- Estimate incremental costs and health outcomes by calculating the difference in costs and health outcomes between interventions (drug A vs. drug B)
- Calculate and interpret incremental cost-effectiveness ratios (ICERs)
- Conduct sensitivity analyses
- One-way varies one parameter at a time (drug cost)
- Probabilistic sensitivity analysis varies multiple parameters simultaneously (drug cost and effectiveness)
- Present and interpret results using a (to plot incremental costs and effects) and cost-effectiveness acceptability curves (to show the probability of cost-effectiveness at different willingness-to-pay thresholds)
Calculation of ICERs
- ICER is the ratio of the difference in costs to the difference in health outcomes between two interventions
- Example: 50,000 - 10,000 per QALY gained$
- Interpretation of ICERs
- Lower ICERs indicate better cost-effectiveness (more health benefits per dollar spent)
- ICERs are compared to a willingness-to-pay threshold (e.g., $50,000 per QALY) to determine if an intervention is cost-effective
- Limitations of ICERs
- Sensitive to the choice of comparator (comparing drug A to placebo vs. existing treatment)
- Do not provide information on the absolute costs or health outcomes of interventions
Concepts in cost-effectiveness comparisons
- Dominance
- An intervention is dominated if it is more costly and less effective than another intervention (drug A costs more and provides fewer QALYs than drug B)
- Dominated interventions are excluded from further analysis
- Extended dominance
- An intervention is extendedly dominated if it has a higher ICER than a more effective intervention (drug A has a higher ICER than drug C, which provides more QALYs)
- Extendedly dominated interventions are excluded from the cost-effectiveness frontier
- Cost-effectiveness acceptability curves (CEACs)
- Graphical representation of the probability that an intervention is cost-effective at different willingness-to-pay thresholds (probability that drug A is cost-effective at $50,000 per QALY)
- Derived from probabilistic sensitivity analysis results
Sensitivity analyses for uncertainty
- Types of uncertainty in cost-effectiveness models
- Parameter uncertainty (costs, health outcomes, probabilities)
- Structural uncertainty (model assumptions, time horizon)
- Methodological uncertainty (discount rate, perspective)
- One-way sensitivity analysis
- Varies one parameter at a time to assess its impact on the ICER (varying drug cost from 200)
- Helps identify the most influential parameters
- Probabilistic sensitivity analysis (PSA)
- Simultaneously varies multiple parameters based on their probability distributions (drug cost and effectiveness)
- Generates a distribution of ICERs and cost-effectiveness acceptability curves
- Importance of sensitivity analyses
- Assess the robustness of the results to changes in key parameters and assumptions
- Identify areas of uncertainty that may require further research (long-term effectiveness data)
- Inform decision-making by providing a range of plausible cost-effectiveness estimates
Key Terms to Review (17)
Cost-benefit analysis: Cost-benefit analysis is a systematic process used to evaluate the financial implications of different healthcare interventions by comparing the expected costs with the anticipated benefits. This method allows healthcare organizations to assess the economic feasibility and overall impact of services and programs, guiding decision-making in resource allocation and investment.
Cost-effectiveness plane: The cost-effectiveness plane is a graphical representation used in health economics to evaluate the trade-offs between the costs and health outcomes of different interventions. It helps to categorize interventions based on their cost-effectiveness ratios, showing whether they provide more health benefits for lower costs, which can guide decision-makers in selecting the most efficient healthcare options.
Cost-utility analysis: Cost-utility analysis is a method used in healthcare economics to evaluate the cost-effectiveness of medical interventions by comparing their costs to the health outcomes they produce, often measured in quality-adjusted life years (QALYs). This analysis helps decision-makers allocate resources efficiently by determining the best value for money when considering treatments or interventions.
Decision Tree Analysis: Decision tree analysis is a graphical decision-making tool that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. This method helps in visualizing the different paths one can take when making decisions in uncertain environments, especially in fields like healthcare for assessing various treatment options and outcomes.
Discounting: Discounting is a financial process used to determine the present value of future cash flows by applying a specific discount rate. This concept is vital in cost-effectiveness analysis as it helps compare the value of costs and benefits that occur at different times, allowing for more accurate economic evaluations of healthcare interventions and policies.
Effectiveness: Effectiveness refers to the degree to which a healthcare intervention or program achieves its intended outcomes in a real-world setting. It is crucial for assessing how well an intervention works in practice, often evaluated through metrics such as health improvements, quality of life enhancements, or reductions in disease incidence. Understanding effectiveness helps inform decisions about resource allocation and prioritization of healthcare strategies.
Efficiency: Efficiency in healthcare refers to the optimal use of resources to achieve the best possible health outcomes. It emphasizes maximizing the value of healthcare services while minimizing waste, costs, and time. Understanding efficiency is crucial for evaluating various payment models, care delivery methods, and resource allocation strategies within the healthcare system.
Health Outcome Measurement: Health outcome measurement refers to the process of quantifying the effects of healthcare interventions on patient health and overall wellbeing. This involves collecting data on various health outcomes to assess the effectiveness, efficiency, and quality of healthcare delivery. It plays a crucial role in informing decision-making and resource allocation in healthcare systems, particularly within cost-effectiveness analysis methodologies.
Healthcare budget impact: Healthcare budget impact refers to the financial effect of implementing a new healthcare intervention or technology on an organization's overall budget. This concept is crucial as it helps organizations evaluate how a proposed change in treatment or service delivery can affect their existing financial resources, affecting both immediate costs and long-term sustainability.
Incremental Cost-Effectiveness Ratio: The incremental cost-effectiveness ratio (ICER) is a measure used to compare the cost-effectiveness of different healthcare interventions by calculating the additional cost per additional unit of effect, usually in terms of health outcomes like life years gained or quality-adjusted life years (QALYs). It provides a way to assess whether the extra costs of a new intervention are justified by its additional health benefits, playing a crucial role in health technology assessments, economic evaluations, and resource allocation in healthcare.
Markov Model: A Markov Model is a statistical model that represents systems where the future state depends only on the current state and not on the sequence of events that preceded it. This model is essential for predicting health outcomes and costs in various scenarios, particularly in healthcare, where it helps to understand patient transitions through different health states over time.
Net monetary benefit: Net monetary benefit refers to the difference between the monetary value of health outcomes gained from an intervention and the costs incurred in delivering that intervention. This measure helps determine the overall economic value of a healthcare intervention by comparing the benefits it produces to its costs, providing insights into whether an intervention is worth pursuing from a financial perspective.
Pharmaceutical pricing: Pharmaceutical pricing refers to the strategies and mechanisms used by companies to set the prices for their drugs and medications. This process involves considering various factors such as research and development costs, competition, market demand, and the perceived value of the drug to patients and healthcare systems. Understanding pharmaceutical pricing is crucial for evaluating the cost-effectiveness of medications and their impact on healthcare delivery.
Quality-adjusted life year (QALY): A quality-adjusted life year (QALY) is a measure used to evaluate the value of medical interventions by assessing both the quantity and quality of life generated by healthcare services. It quantifies the health benefits of treatments in terms of years of life adjusted for the quality of those years, allowing for comparisons across different health interventions and conditions. This metric is vital for informing resource allocation decisions in healthcare systems.
Resource utilization: Resource utilization refers to the efficient and effective use of healthcare resources, including personnel, equipment, and facilities, to provide quality care while minimizing waste. This concept is crucial in managing healthcare delivery systems, as it helps balance the demand for services with the available supply, ultimately influencing cost, access, and quality of care.
Sensitivity analysis: Sensitivity analysis is a method used to determine how different values of an independent variable will impact a particular dependent variable under a given set of assumptions. This technique is especially relevant in economic evaluations where it helps assess the robustness of results by exploring how changes in key parameters influence cost-effectiveness outcomes and decision-making.
Value-Based Care: Value-based care is a healthcare delivery model that prioritizes patient outcomes and the quality of care over the volume of services provided. This approach aims to incentivize providers to deliver high-quality care efficiently while reducing costs, ultimately improving patient satisfaction and health outcomes.