The Role of Cost-Effectiveness Analysis in Healthcare Decision-Making

In today's world, where resources are limited and the needs of the population are constantly growing, making informed and effective decisions in healthcare becomes particularly relevant. One of the key tools that help to evaluate the rationality and effectiveness of various medical interventions is cost-effectiveness analysis (CEA) in healthcare.

The purpose of this article is to explore the important role of cost-effectiveness analysis in the healthcare decision-making process. We will look at what factors are considered when conducting CEA, what methods are used to evaluate the effectiveness of medical interventions, and review case studies that demonstrate the impact of CEA on healthcare decision-making.

Cost-effectiveness analysis - definition and scope

Cost-effectiveness analysis is a method of examining both the costs and health outcomes associated with one or more health interventions. It makes comparisons between these interventions (or compares them to the current state) by estimating how much cost is required to achieve a particular outcome, such as gaining a year of life or preventing death.

The main indicators and methodologies that CEA uses are:

1. Cost-effectiveness ratio (ICER). It is calculated by dividing the difference in costs by the difference in outcomes achieved between two comparable health interventions. For example, ICER will show how much it costs to gain one additional year of life or one additional healthy year (QALY) due to a particular medical intervention compared to an alternative.

2. Quality-adjusted life years (QALYs). This indicator combines the number of quality-adjusted life years lived. Thus, QALY takes into account not only the length of life, but also the patient's level of health and well-being during this period. It allows comparing medical interventions with different degrees of impact on patients' quality of life.

3. Dynamic cost-effectiveness analysis. This method takes into account changes over time when evaluating the effectiveness of a medical intervention. It takes into account long-term consequences, possible prospects for the development of medical technology and improvements in therapeutic approaches.

4. Sensitivity assessment, which allows you to analyze which factors may have the greatest impact on the results of CEA. It helps to assess the degree of uncertainty in the data and provides information on how changes in parameters may affect conclusions and recommendations.

5. Decision Modeling. Decision modeling in CEA is a methodology that uses computer models to analyze the long-term effects of medical decisions and technologies. This approach can predict outcomes and costs over years or decades, which is particularly useful for evaluating chronic diseases or long-term therapies.

6. Systematic reviews are a method of analyzing the literature that integrates the results of multiple studies on a particular topic. In the context of CEA, they are used to collect and analyze data on the cost and effectiveness of medical interventions. Systematic reviews allow for generalizable findings and more reliable estimates of health care effectiveness and costs.

In contrast to cost-benefit analysis, cost-effectiveness analysis provides a more comprehensive and informative picture, taking into account both the cost of health interventions and their actual impact on patient health (more on this in the article on cost-effectiveness analysis vs cost-benefit analysis). This approach enables informed decision-making and optimized allocation of health care resources aimed at achieving the best results for society and the health of the population.

Informing health care decision-making

CEA is used to compare alternative treatments or to compare the current condition (status quo) with a new treatment option. It considers both costs and health outcomes. Costs include both direct costs, such as the cost of drugs and services, and indirect costs, such as lost productivity and loss of quality of life. Health outcomes include the number of cases, the number of deaths, and the quality of life of patients.

CEA can be used to make decisions about which treatment method is best for a patient. It can also be used to make decisions about whether a new treatment should be introduced into the health care system.

One example of the use of CEA is the economic evaluation of a routine childhood immunization program in the United States (2009). It showed that implementing this program among members of the birth cohort in the country would prevent approximately 42,000 premature deaths and 20 million cases of disease. This would result in net savings of $13.5 billion in direct costs and $68.8 billion in total social costs. The ratios of direct costs to social benefits for routine immunization of children with these 9 vaccines were 3.0 and 10.1, respectively. Findings from the analysis indicate that, from both direct cost and societal perspectives, routine vaccination of children as recommended results in significant resource savings.

Value-based healthcare and CEA

Value-based healthcare strives to provide the best outcomes for patients based on their needs and preferences. CEA plays an important role in promoting this approach as it allows:

1. Compare different healthcare interventions and assess their cost and effectiveness. This helps to identify which interventions provide the greatest value to patients and society as a whole.

2. Take into account individual patient characteristics, needs and preferences when assessing the effectiveness of interventions. This facilitates the formation of personalized and more effective treatment and care plans.

3. Obtain information on the cost and effectiveness of different interventions, allowing patients and physicians to make decisions together based on objective data. In this way, CEA promotes shared decision-making in which patients and medical staff work together to determine the best course of treatment.

In this way, CEA is an important tool to support value-based healthcare and promotes improved quality of care by considering patients' needs, preferences, and objective data on the cost and outcomes of medical interventions.

Conclusion

Cost-effectiveness analysis (CEA) plays a key role in making informed decisions in healthcare. CEA identifies the most effective and cost-effective medical interventions, promoting patient-centered care and shared decision making. Thorough and transparent CEA evaluation is necessary to ensure accuracy and validity of results, helping to improve the healthcare system.