INTRODUCTION
Economic evaluation is a crucial methodology in healthcare, designed to assess the economic efficiency of various medical interventions, ranging from pharmaceuticals to complex medical procedures and diagnostic tools. It provides a structured approach to compare and analyze the costs and outcomes of different healthcare alternatives, ultimately informing decisions about resource allocation within a constrained budget.
Since the introduction of the positive listing system for pharmaceuticals in Korea in 2006, economic evaluations have become increasingly important, especially for new drugs seeking National Health Insurance (NHI) benefits [1]. However, the scope has broadened significantly beyond pharmaceuticals to encompass a wide array of healthcare interventions, including new items for national programs like immunization and health screening. As evidence-based medicine gains prominence, the demand for rigorous and objective economic evaluations to guide healthcare policy and clinical practice is continuously rising.
While guidelines for economic evaluations exist, such as the Health Insurance Review and Assessment Service (HIRA) guidelines revised in 2021, they are often specific to pharmaceutical appraisals for NHI registration and may lack broader applicability [2]. To address this gap, manuals have been developed to provide practical techniques for economic evaluations across diverse healthcare fields, including diagnosis, procedures, vaccination, and screening. This article aims to introduce the core processes and key concepts of economic evaluation in healthcare, drawing on these resources and illustrating them with examples to enhance understanding for an English-speaking audience interested in health economics and policy. We will explore the steps involved in conducting an economic evaluation and provide Examples Of Economic Tools And Concepts In Health Care to demonstrate their practical application.
THE PROCESS FOR CONDUCTING AN ECONOMIC EVALUATION
The economic evaluation process is systematic, typically involving several key stages: planning, outcome and cost calculation, modeling, cost-effectiveness results, uncertainty analysis, and decision-making. These stages are often iterative, especially outcome and cost calculations, which may require refinement as the evaluation progresses. Let’s examine each step in detail and provide examples of economic tools and concepts in health care.
Planning an Economic Evaluation
Effective planning is the cornerstone of any robust economic evaluation. Before embarking on a new study, reviewing existing literature with similar objectives or within the same clinical area is highly recommended. Key elements of planning include defining the study population, interventions, comparators, perspective, time horizon, discount rates, and the type of economic evaluation.
Study Population
Defining the study population is critical as the cost-effectiveness of interventions can vary significantly based on patient characteristics. The population is usually defined by epidemiological factors such as age, sex, comorbidities, or risk factors associated with the disease under study.
Example: Consider a study evaluating the cost-effectiveness of a new screening test for colorectal cancer. The target population could be defined as adults aged 50-75 years (general population screening) or individuals with a family history of colorectal cancer (high-risk population screening). The cost-effectiveness of the screening program might differ significantly between these two populations due to varying baseline risks and disease prevalence.
Target Intervention and Comparator
Clearly defining the target intervention and comparator is essential for a focused and relevant evaluation. The target intervention is the medical technology or strategy whose cost-effectiveness is being assessed. The comparator is the alternative intervention against which the target intervention is being compared. Typically, for a new intervention, the comparator is the current standard of care or most widely used treatment. However, when evaluating existing technologies already within a healthcare system, the distinction might be less clear-cut.
Example: Evaluating a new drug for type 2 diabetes. The target intervention is the new drug, and the comparator could be the standard first-line treatment, such as metformin, or another commonly used second-line drug if the new drug is intended for later-stage treatment.
Study Perspective
The study perspective dictates which costs and outcomes are considered in the analysis. Common perspectives include the payer, healthcare system, and societal perspectives. The perspective chosen significantly impacts the scope of the evaluation and, consequently, the results.
- Payer Perspective: Focuses solely on costs borne by the payer, such as an insurance company or health service.
- Healthcare System Perspective: Includes costs incurred within the healthcare system, such as hospital costs, physician fees, and drug costs.
- Societal Perspective: The broadest perspective, encompassing all costs and outcomes relevant to society, including medical costs, non-medical costs (e.g., transportation, informal care), and productivity costs (e.g., lost workdays).
Example: Analyzing the cost-effectiveness of a new surgical procedure for hip replacement. From a healthcare system perspective, costs would include hospital stay, surgery costs, and follow-up care within the hospital. From a societal perspective, additional costs like patient’s travel to the hospital, time off work for both the patient and caregiver, and potential long-term productivity changes would also be included.
Time Horizon and Discounting
The time horizon should be sufficiently long to capture all relevant clinical outcomes, considering the disease epidemiology and the study population. For acute conditions, a shorter time horizon might suffice, whereas chronic diseases often require longer time horizons to capture long-term effects and costs.
Discounting is crucial when dealing with long time horizons. It is the process of converting future costs and benefits to their present values to reflect time preference – the idea that people generally prefer benefits sooner rather than later and costs later rather than sooner. A discount rate is applied to future costs and outcomes.
Example: Evaluating a preventative intervention like childhood vaccination against measles, mumps, and rubella (MMR). The time horizon needs to be long enough to capture not only the immediate costs of vaccination but also the long-term benefits of preventing measles outbreaks and related complications over a lifetime. Discounting would be applied to future healthcare cost savings and quality of life gains resulting from disease prevention.
Types of Economic Evaluation
Economic evaluations are broadly categorized based on how they compare costs and outcomes. The main types are cost-minimization analysis, cost-effectiveness analysis, cost-utility analysis, and cost-benefit analysis.
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Cost-Minimization Analysis (CMA): Used when comparing interventions with equivalent outcomes. The analysis focuses on identifying the least costly option.
Example: Comparing two generic drugs with proven bioequivalence for treating hypertension. If their clinical effectiveness is deemed the same, CMA would focus on comparing their costs to identify the cheaper option. -
Cost-Effectiveness Analysis (CEA): Compares interventions with varying outcomes using a natural unit of effectiveness, such as life years gained, cases of infection prevented, or reduction in blood pressure. Results are expressed as a cost-effectiveness ratio (e.g., cost per life year gained).
Example: Comparing two different treatments for breast cancer: chemotherapy regimen A versus chemotherapy regimen B. CEA would compare the cost per additional year of life gained with regimen A compared to regimen B. -
Cost-Utility Analysis (CUA): A type of CEA where outcomes are measured in terms of quality-adjusted life years (QALYs) or other utility measures that incorporate both the length and quality of life. CUA is particularly useful for comparing interventions across different disease areas because QALYs provide a common metric for health outcomes.
Example: Comparing a new palliative care program for end-stage heart failure patients versus standard care. CUA would assess the cost per QALY gained with the palliative care program, considering both the impact on survival and quality of life. -
Cost-Benefit Analysis (CBA): Measures both costs and outcomes in monetary terms. Benefits are converted into monetary values, allowing for a direct comparison of total costs and total benefits. While less common in healthcare due to ethical concerns about monetizing health outcomes, CBA can be used for evaluating broad public health programs.
Example: Evaluating a national smoking cessation program. CBA would attempt to quantify both the costs of implementing the program (e.g., advertising campaigns, counseling services) and the monetary benefits, such as healthcare cost savings from reduced smoking-related diseases and increased productivity due to improved population health.
Calculating Outcomes
Measuring and valuing health outcomes is central to economic evaluation. Outcomes can be intermediate (e.g., changes in biomarkers) or final (e.g., mortality, life years, QALYs). Final outcomes are generally preferred as they reflect the ultimate health impact of interventions.
Outcome Indicators
Appropriate outcome indicators are essential for capturing the health improvements resulting from medical interventions. Final outcomes such as changes in mortality rate, survival rate, life years gained, and QALYs are commonly used in healthcare economic evaluations.
Quality-Adjusted Life Years (QALYs)
QALYs are a widely used outcome measure in CUA. They integrate both the length of life and the quality of life into a single metric. A QALY represents one year of life in perfect health. Health states are assigned a quality weight, ranging from 1 (perfect health) to 0 (death), allowing for the valuation of different health states.
Example: A treatment that extends life by 2 years but reduces quality of life to a health state with a quality weight of 0.5 would result in 2 years 0.5 QALYs/year = 1 QALY gained. In contrast, a treatment that extends life by 1 year with no reduction in quality of life would result in 1 year 1 QALY/year = 1 QALY gained.
Measuring Quality Weights
Various methods exist to estimate quality weights for health states, including direct measurement (e.g., standard gamble, time trade-off, visual analog scale) and indirect measurement using preference-based health-related quality of life (HRQoL) questionnaires. Indirect measurement, particularly using tools like EQ-5D-3L or EQ-5D-5L, is often recommended for healthcare economic evaluations because they provide a comprehensive assessment of health status and are preference-based.
Example: Using the EQ-5D questionnaire to assess the health-related quality of life of patients undergoing treatment for chronic pain. The EQ-5D measures health across five dimensions (mobility, self-care, usual activities, pain/discomfort, anxiety/depression). Responses are then converted into a single utility score, representing the quality weight for that health state.
Calculating Costs
Comprehensive cost calculation is crucial for accurate economic evaluations. Healthcare costs are typically categorized into medical, non-medical, and productivity costs. The specific cost items included depend on the chosen study perspective.
Cost Items
- Medical Costs: Direct costs associated with healthcare services, including hospitalizations, physician visits, drugs, medical procedures, and tests.
- Non-Medical Costs: Costs indirectly related to healthcare, such as transportation to medical appointments, caregiver costs, and long-term care services.
- Productivity Costs: Costs associated with lost productivity due to illness or premature death, including lost wages and reduced economic output.
Example: Evaluating the costs associated with managing patients with severe asthma. Medical costs would include asthma medications, emergency room visits, and hospitalizations for asthma exacerbations. Non-medical costs might include transportation to doctor’s appointments and caregiver time for children with asthma. Productivity costs would include lost workdays for adults with asthma or parents of children with asthma.
Table 1. Cost item by analysis perspective
| Cost item | Payer perspective | Healthcare system perspective | Societal perspective |
|---|---|---|---|
| Medical costs | Formal medical costs | Included (excluding non-benefit out-of-pocket expenses) | Included (including non-benefit out-of-pocket expenses) |
| Informal medical expenses | Included | Included | Included |
| Non-medical costs | Included | ||
| Transportation costs | Included | Included | |
| Caregiving costs | Included | Included | |
| Long-term care service costs | Included if necessary1 | Included | Included |
| Productivity costs | Included2 | ||
| Morbidity costs | Included | Included | |
| Premature death costs | Included | Included |
1In Korea, the National Health Insurance Service is both the insurer of health insurance and long-term care insurance for the elderly; therefore, long-term care costs can be included in the payer’s perspective depending on a study’s purpose.
2Among the morbidity costs, patient’s time costs with relatively clear data sources can be separately included and calculated.
Calculating Medical Costs
Medical costs can be calculated using micro-costing or gross costing methods. Micro-costing involves detailed enumeration and costing of all resources used, while gross costing uses aggregate cost data. The choice of method depends on the required precision, data availability, and study scope.
Example (Micro-costing): Calculating the cost of an appendectomy. Micro-costing would involve identifying all resources used: operating room time, surgeon’s time, nursing time, anesthesia, medications, supplies, and length of hospital stay. Each resource would be quantified and assigned a unit cost to calculate the total cost per appendectomy.
Example (Gross costing): Estimating the average annual medical cost for patients with heart failure. Gross costing might use claims data or hospital billing data to determine the average total medical expenditure per patient with heart failure over a year.
Figure 1. Composition of formal medical costs. NHI, National Health Insurance; NHIS, National Health Insurance Service.
Modeling
Modeling is often necessary in economic evaluations, especially when clinical trials do not capture the full time horizon or all relevant outcomes. Decision-analytic models, such as decision trees and Markov models, are commonly used to synthesize evidence from various sources and extrapolate outcomes over time.
Types of Models
Economic evaluations can be trial-based (using data directly from clinical trials) or model-based (using decision-analytic models). Model-based evaluations are further classified based on whether they are static or dynamic, and population-level or individual-level.
Table 2. Types of simulation-based decision analytic models used for economic evaluation
| Criteria | Static | Dynamic
