8.3 Interpreting and presenting results
4 min read•august 16, 2024
is crucial for evaluating interventions in healthcare and public policy. It uses ratios and net present values to compare costs and outcomes, helping decision-makers allocate resources efficiently.
Interpreting results involves comparing to benchmarks, assessing , and conducting sensitivity analyses. Effective communication through visuals and clear writing is key to informing policy decisions and balancing efficiency with ethical considerations.
Cost-Effectiveness Ratios and Net Present Values
Measuring Cost-Effectiveness
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- (CERs) quantify cost per unit of outcome achieved by an intervention (typically cost per quality-adjusted life year (QALY) gained)
- (ICER) compares difference in costs between two interventions relative to difference in effectiveness
- Calculated as:
- (NPV) calculates present value of all future cash flows over entire life of investment or project
- Incorporates time value of money concept using discount rate to adjust future costs/benefits
- Positive NPV indicates financially viable project
Interpreting Cost-Effectiveness Results
- Compare CERs and NPVs to predetermined thresholds or benchmarks
- for ICERs (e.g. $50,000 per QALY)
- Positive NPV for cost-benefit analyses
- Evaluate dominance and
- Dominant intervention less costly and more effective than alternatives
- Extended dominance occurs when combination of other options more efficient
- Consider of resource allocation decisions
- Assess uncertainty through sensitivity analyses (covered in next section)
Sensitivity Analysis of Cost-Effectiveness Results
Types of Sensitivity Analyses
- varies single parameter while holding others constant
- Identifies parameters with greatest impact on results
- Often visualized using
- (PSA) uses
- Simultaneously varies multiple parameters based on probability distributions
- Generates and of results
- examines impact of different combinations of assumptions
- Tests "best case" and "worst case" scenarios
- Evaluates alternative policy or implementation approaches
- determines parameter value that changes overall conclusion
- Identifies "" for key variables
- Informs focus of future research or data collection efforts
Visualizing Sensitivity Analysis Results
- Tornado diagrams display results of one-way sensitivity analyses
- Horizontal bars show range of outcomes for each varied parameter
- Parameters ordered by magnitude of impact on results
- (CEACs) show probability of cost-effectiveness
- X-axis willingness-to-pay threshold, Y-axis probability
- Useful for communicating uncertainty to decision-makers
- Scatter plots of PSA results on cost-effectiveness plane
- Visualizes joint distribution of incremental costs and effects
- Quadrants indicate dominance or trade-offs between alternatives
Communicating Cost-Effectiveness Analysis Results
Visual Presentation Techniques
- graph costs vs. effects
- Quadrants indicate dominance or trade-offs between interventions
- Confidence ellipses show uncertainty in estimates
- Cost-effectiveness acceptability curves (CEACs) display probability of cost-effectiveness
- X-axis willingness-to-pay threshold, Y-axis probability of being cost-effective
- Multiple curves can compare different interventions
- Tornado diagrams summarize one-way sensitivity analyses
- Horizontal bars show range of outcomes for varied parameters
- Helps identify most influential factors on results
- Infographics and dashboards convey complex information to non-technical audiences
- Use icons, color-coding, and simplified graphics
- Focus on key takeaways and policy implications
Effective Written Communication
- Clear highlight key findings and implications
- Concise overview of methods, results, and recommendations
- Tailored to decision-maker needs and time constraints
- Detailed tables present numerical results
- Base case analyses and sensitivity analyses
- Clearly labeled with units and definitions
- of methods, assumptions, and limitations
- Builds credibility and facilitates informed decision-making
- Acknowledges areas of uncertainty or potential bias
- provide additional details for interested readers
- Full model specifications and data sources
- Supplementary analyses and scenario results
Implications of Cost-Effectiveness Analysis for Policy
Informing Resource Allocation Decisions
- guides healthcare and public policy spending
- Enables comparison of interventions across diverse areas (healthcare, education, infrastructure)
- Supports setting priorities and justifying funding decisions
- Identify "" or most efficient use of limited resources
- Highlight interventions with greatest potential impact
- Incorporates opportunity cost concept in decision-making
- Resources allocated to one intervention unavailable for alternatives
- Encourages consideration of forgone benefits
Balancing Efficiency and Other Considerations
- Ethical considerations complement economic efficiency
- and fairness in resource distribution
- Prioritizing vulnerable populations or rare diseases
- of results across contexts
- Consider demographic, geographic, or health system differences
- Adapt findings to local circumstances when applying to policy
- Acknowledge limitations of analyses in policy discussions
- Uncertainty in long-term outcomes or hard-to-monetize benefits
- Potential for unintended consequences or implementation challenges
- Integrate cost-effectiveness with other forms of evidence
- Clinical effectiveness, budget impact, feasibility
- Stakeholder perspectives and public values
Key Terms to Review (27)
Best Buys: Best buys refer to the most cost-effective interventions or programs that yield the highest benefits relative to their costs. In the context of evaluating different strategies, these are the options that provide the greatest impact for the least amount of resources, making them a focal point for decision-makers who aim to maximize efficiency and effectiveness.
Confidence Intervals: Confidence intervals are a statistical tool used to estimate the range within which a population parameter, such as a mean or proportion, is likely to fall. They provide an upper and lower limit, giving a sense of the uncertainty around an estimate and how much it might vary due to sampling. This concept is crucial for interpreting results from analyses, especially when assessing the impact of interventions or treatments.
Cost-effectiveness acceptability curves: Cost-effectiveness acceptability curves (CEACs) are graphical representations used in economic evaluations to show the probability that a health intervention is cost-effective compared to alternatives at different willingness-to-pay thresholds. They help decision-makers visualize uncertainty in economic evaluations, allowing them to see how likely it is that an intervention will provide value for money as costs and effectiveness vary.
Cost-effectiveness analysis: Cost-effectiveness analysis (CEA) is a method used to compare the relative costs and outcomes (effects) of different courses of action, helping decision-makers allocate resources efficiently. This approach emphasizes the ratio of costs to health or social outcomes, allowing comparisons across diverse programs or interventions to determine which options provide the best value for money.
Cost-effectiveness ratios: Cost-effectiveness ratios are quantitative measures used to assess the relative costs and outcomes of different interventions or programs, helping to determine which option provides the best value for resources invested. These ratios allow decision-makers to compare the economic efficiency of various strategies, particularly in healthcare and social programs, by calculating the cost per unit of outcome achieved, such as cost per life saved or cost per quality-adjusted life year (QALY).
Dominance: Dominance refers to a situation where one option or intervention outperforms others in a given context, making it the preferred choice. In evaluating outcomes, this concept helps researchers and decision-makers identify which alternatives yield superior results, thereby guiding effective policy and program decisions based on comparative effectiveness.
Equity: Equity refers to the concept of fairness and justice in the distribution of resources, opportunities, and outcomes among individuals and groups. It emphasizes that different people may require different levels of support or resources to achieve similar outcomes, recognizing systemic inequalities that affect various populations. In the context of interpreting and presenting results, equity involves understanding and addressing disparities in how different groups are impacted by programs or policies.
Executive Summaries: An executive summary is a concise overview of a larger document or report, highlighting the main points and recommendations in a clear and accessible format. It serves as a tool for decision-makers to quickly understand the key findings and implications without having to read the entire document. By presenting essential information succinctly, it plays a critical role in interpreting results and communicating impact evaluation findings effectively.
Extended dominance: Extended dominance is a concept in decision theory and health economics that refers to a situation where one option is preferred over another across a range of outcomes, even when accounting for varying levels of risk. This principle is crucial for understanding how interventions or treatment options can be evaluated against each other, particularly when considering cost-effectiveness and patient outcomes.
Generalizability: Generalizability refers to the extent to which findings from a study can be applied or transferred to settings, populations, or times beyond the specific context in which the research was conducted. This concept is crucial as it allows researchers and policymakers to draw broader conclusions and make informed decisions based on specific study results.
Incremental Cost-Effectiveness Planes: Incremental cost-effectiveness planes are graphical representations used in health economics to visualize the trade-offs between the additional costs and the additional health outcomes of a new intervention compared to an existing one. These planes help in understanding how different interventions can be assessed relative to their cost-effectiveness, making it easier to interpret results and inform decision-making about resource allocation in healthcare.
Incremental cost-effectiveness ratio: The incremental cost-effectiveness ratio (ICER) is a measure used in health economics to assess the cost-effectiveness of a health intervention compared to an alternative. It is calculated by taking the difference in costs between two interventions and dividing it by the difference in their effectiveness, usually measured in terms of quality-adjusted life years (QALYs) or life years gained. This ratio helps decision-makers evaluate whether the additional benefits of a new treatment justify its extra costs.
Monte Carlo Simulation: Monte Carlo Simulation is a statistical technique that uses random sampling and repeated simulations to model and understand the impact of risk and uncertainty in prediction and forecasting models. This method allows researchers to generate a range of possible outcomes for a given scenario, which is particularly useful in evaluating complex systems where many variables interact.
Net Present Value: Net Present Value (NPV) is a financial metric that calculates the value of a stream of cash flows over time, adjusted for the time value of money. It helps determine the profitability of an investment by comparing the present value of cash inflows to the present value of cash outflows. This concept is critical in evaluating projects through cost-benefit and cost-effectiveness analysis, enabling decision-makers to assess whether an investment will generate more wealth than it costs.
One-way sensitivity analysis: One-way sensitivity analysis is a method used to evaluate how changes in a single variable can affect the outcome of a model or analysis while keeping other variables constant. This approach is crucial for identifying which inputs have the most significant impact on results and helps in interpreting and presenting findings more effectively. By isolating one variable at a time, this analysis aids in understanding the robustness of conclusions drawn from data.
Opportunity Costs: Opportunity costs refer to the value of the next best alternative that must be forgone when making a decision. This concept emphasizes that every choice has a cost, not just in terms of money but also in terms of time, resources, and potential benefits that are sacrificed. Understanding opportunity costs is crucial in evaluating decisions, especially when interpreting and presenting results, as it highlights the trade-offs involved in any given scenario.
Probabilistic Sensitivity Analysis: Probabilistic sensitivity analysis is a technique used to evaluate how uncertainty in the input variables of a model affects the output results. By incorporating probability distributions for uncertain parameters, this analysis helps in understanding the range of possible outcomes and their likelihood, which is crucial for decision-making in impact evaluations. It enhances the interpretation and presentation of results by providing a more comprehensive view of uncertainty and risk associated with the findings.
Quantitative evidence: Quantitative evidence refers to data that can be quantified and expressed numerically, allowing for statistical analysis and objective comparison. It is crucial in evaluating the effectiveness of programs or interventions, as it provides measurable outcomes that can inform decision-making and policy development.
Scatter plots: A scatter plot is a graphical representation of two variables plotted along two axes, showing the relationship between them. This type of plot is useful for identifying trends, patterns, and correlations in data, as well as highlighting outliers. By visually displaying the data points, scatter plots help to present results in a clear and concise manner, making it easier to interpret the relationships among variables.
Scenario Analysis: Scenario analysis is a strategic planning method that organizations use to evaluate and prepare for various potential future events by examining different possible outcomes and their implications. This technique helps in interpreting and presenting results by providing a structured approach to understand uncertainties and risks, allowing decision-makers to visualize how changes in key variables could affect outcomes.
Sensitivity Analysis: Sensitivity analysis is a method used to determine how the different values of an independent variable impact a particular dependent variable under a given set of assumptions. This technique helps assess the robustness of results, especially when evaluating models, making it crucial for understanding the reliability of findings in various contexts, including statistical matching methods, cost-benefit assessments, and the interpretation of analytical outcomes.
Technical appendices: Technical appendices are supplementary materials that provide detailed information, methodologies, data analyses, and additional context related to a primary report or document. They serve to enhance understanding by allowing readers to access the intricate details without overwhelming the main content, making it easier to interpret and present results effectively.
Threshold analysis: Threshold analysis is a method used in impact evaluation that helps to identify the point at which a variable or intervention leads to a significant change in outcomes. This technique is particularly useful for determining the minimum level of input, resource, or effort required for an intervention to be effective, and it helps in understanding how different factors interact to influence results.
Tipping points: Tipping points are critical moments or thresholds at which a significant change occurs in a system, leading to a dramatic shift in its state or behavior. These points can represent the moment when small changes can lead to larger consequences, often impacting outcomes in various fields such as social sciences, economics, and environmental studies. Recognizing and understanding tipping points is essential for interpreting and presenting results effectively, as they often highlight key insights and implications of data.
Tornado Diagrams: Tornado diagrams are a visual representation used to display the sensitivity of various inputs on a given outcome in decision-making and risk analysis. These diagrams help to identify which variables have the most significant impact on the result, allowing stakeholders to prioritize their focus on the most critical factors influencing outcomes. This visualization aids in interpreting complex data and effectively presenting results, particularly in applied impact evaluation scenarios.
Transparent reporting: Transparent reporting refers to the clear, honest, and comprehensive presentation of research findings and methodologies, ensuring that all relevant information is available for scrutiny and understanding. This practice fosters trust and accountability in the evaluation process, allowing stakeholders to critically assess the results and implications of the findings.
Willingness-to-pay thresholds: Willingness-to-pay thresholds refer to the maximum amount an individual or society is willing to pay for a particular good, service, or intervention, particularly in health economics and policy analysis. This concept is essential in assessing the value of health interventions and determining whether they should be implemented based on their cost-effectiveness relative to established thresholds.