What positive impact does health economic modelling have on health care decision-making?

Health care economic modeling is a methodology that is used to examine and economically evaluate various aspects of health care, including the financing, structure, and organization of the healthcare system, as well as the efficiency and effectiveness of health care technologies, programs, and interventions. Modeling is often used in health care decision-making, particularly in situations where the relative value of different options for health care interventions must be assessed. The use of this methodology contributes to more equitable and economically sound health care decision-making.

 

Types of economic modeling of health care

Economic modeling can be applied to analyze a variety of issues, such as:

• Determining the optimal allocation of resources in the healthcare system, given budgetary constraints and population needs;
• assessing the economic efficiency of new medical technologies and medicines;
• studying the impact of various factors on public health and the economy;
• development of payment models for medical services and evaluation of their effectiveness;
• forecasting changes in the health care system in the future.

Various methods are used for economic modeling, such as mathematical modeling, statistical analysis, economic analysis, etc.

The types of economic evaluation most often used for analysis are:

Economic Efficiency Analysis (CEA)

Cost-effectiveness analysis is a methodology that compares the cost and outcomes of different treatments or disease prevention methods to determine which method is most cost-effective.

CEA compares various parameters such as treatment costs, number of years of life, quality of life gains, number of years without disability, etc. After the analysis, the relative costs of different treatments are calculated to determine which method provides the best cost-benefit ratio.

CEA is an important and the most common tool in healthcare decision-making because it allows the selection of the most cost-effective treatments and the use of resources. It also helps set priorities for allocating funds to health care.

 

Cost-Utility Analysis (CUA)

Cost-utility analysis is based on measuring quantitative measures of health, such as quality of life, life expectancy, or the number of years of life gained through treatment.

CUA measures treatment costs and treatment outcomes in units of utility, such as years of life in good health, or years of life saved through treatment. The cost-benefit ratio is then calculated to determine how effective the treatment is in monetary terms.

However, the CUA has its limitations. First, it can be limited to measuring only those health outcomes that can be quantified. Second, this method does not account for individual differences in patient preferences and values, which can influence treatment decisions. Third, CUA results may depend on the observation period chosen and the model used to estimate utility.

 

Budget Impact Analysis (BIA)

Budget impact analysis is a method of estimating the financial impact of introducing a new medical technology or drug in health care. BIA estimates the changes in health care costs associated with the use of a new technology or drug and compares them to current health care costs without the technology or drug.

The BIA considers the following factors:

• The cost of care, including the cost of the new technology or drug, the cost of diagnosing and treating complications, and the cost of treating side effects;
• The number of patients likely to receive the new technology or drug and their characteristics, such as age, gender, diagnosis;
• the time period for which the analysis is conducted, as costs may vary from one period to the next;
• the economic impact on health care and society as a whole, including the economic benefits and losses associated with increased life expectancy, reduced morbidity and mortality, and reduced costs of treating complications.

The BIA can help health care providers and insurers make informed decisions about the introduction of new medical technologies and drugs, considering their impact on budgets. However, the BIA does not take into account all of the factors associated with the use of a new technology or drug and is not a tool for evaluating their effectiveness.

If you are interested in this topic, we recommend reading more about it here. 

 

Other types of modeling

Other types of modeling are also used to make informed decisions in health care:

• Markov modeling — a method of modeling dynamic processes based on Markov process theory;
• Cost-benefit-based decision modeling — an analysis that evaluates medical interventions based on their economic benefits to society as a whole, such as reducing the cost of treating complications or increasing the length of time patients are able to work;
• Сost- and probability-based decision modeling — an analysis that evaluates the probability of certain events occurring and their costs to determine the best risk management strategy.

To learn more about the types of modeling that are used in health care, follow this link.

 

Benefits of Healthcare Economic Modeling

Healthcare economic modeling is an important tool for evaluating various medical interventions. Its benefits include:

1. Determining cost-effective interventions.

Economic modeling allows you to assess whether a medical intervention is cost-effective. That is, whether the intervention is worth the investment, and whether it will be beneficial to patients and the healthcare system as a whole.

2. Helping decision-makers allocate resources efficiently.

Using models can help determine which medical procedures or treatments are more effective and how to allocate limited resources among them. This, in turn, can help improve healthcare quality, reduce costs, and increase patient satisfaction. In addition, economic modeling can help determine the optimal balance between health care quality and costs. For example, economic modeling can help determine which medical procedures can be adjusted to reduce costs without compromising health care quality.

3. Consideration of long-term costs and benefits.

The development of new drugs and technologies requires a significant investment in research and development, but in the long run can yield significant returns. Economic modeling can estimate long-term costs and benefits and compare them to short-term costs and benefits. For example, economic modeling can help determine how much should be invested in research and development of new drugs or technologies to maximize profits in the long run.

In addition, economic modeling allows you to consider not only direct costs and benefits but also indirect and implicit costs. For example, such as savings on future treatments or improved quality of life for patients.

4. Informing policy decisions.

Economic modeling can be used to assess the impact of regulatory changes on the cost of care and the availability of health services. Such changes can include health care reforms, changes in payment structures.

Economic modeling can also be used to predict future trends in health care and determine the most effective strategies to manage them. For example, modeling can be used to assess what steps can be taken to reduce health care costs and improve the quality of health care services.

5. Facilitate communication and collaboration among stakeholders.

Economic models can help identify the best conditions for collaboration among different parties, help improve decision-making processes, and achieve more effective outcomes for business, government, and other activities.

 

Limitations of health care economic modeling

There are certain limitations to consider when using economic models in health care:

1. Lack of data. Economic modeling requires a lot of data that can be used to create accurate and reliable models. In health care, there is often insufficient data, which can lead to inaccurate modeling and errors in decision making.
   
   
2. Modeling complexity. Health care is a complex system that includes many factors such as demographics, medical technology, health care costs, etc. Given all of these factors, the process of creating a model can be difficult and the model may not be accurate enough.
   
   
3. Uncertainty. In health care, many factors such as morbidity, mortality, etc., can be unpredictable and unstable. As a consequence, economic models may not account for all factors affecting outcomes.
   
   
4. Difficulties in estimating outcomes. In health care, it can be difficult to identify specific indicators that can be used to measure the success of an economic model.
   
   
5. Social and ethical issues. For example, issues of fairness, accessibility, and equity may be important to society but are not always addressed in economic models.

Overall, economic modeling is a useful tool for health care analysis, but its use must be complemented by other methods and consider the limitations described.

 

Future Directions for Economic Modeling of Health Care

Health economic modeling has enormous potential and will continue to be an important tool for health care decision-making in the future. The main directions for the development and application of economic modeling in health care are:

1. Integrating real data and personalized medicine into models to improve the accuracy and predictive capabilities of the models. This will allow for more diverse factors such as age, gender, genetics, and patient health status, which in turn will help develop more accurate and effective treatment strategies.
2. Development of more sophisticated modeling methods. A variety of health care modeling techniques are currently being used, but the future may be in developing more sophisticated methods, such as stochastic modeling, artificial intelligence, and machine learning, which will allow more complex variables to be considered and improve the predictive capabilities of the models.
3. Ensuring transparency and reproducibility in model research. This will involve developing standards and methods for assessing the quality of models, as well as publicly available databases and codes that can be used by other researchers to replicate results.
4. Consideration of socio-economic aspects, such as accessibility of treatment for different populations, health care inequalities, cost-effectiveness of treatment, etc.
5. Developing more detailed studies of the cost of disease. The cost of illness is an economic estimate of the cost of treatment and the loss of income associated with illness. More detailed studies of the cost of disease can help assess the economic contribution of different treatment modalities and help make decisions about the allocation of resources in health care.
6. Research on the impact of technological innovation. Advances in health care technology, such as telemedicine, medical robotics, and artificial intelligence, can significantly affect health care and the economy. Economic modeling can help assess the impact of these technologies on health care and determine their effectiveness and economic value.
7. Research on global health issues such as the spread of infectious diseases, evaluating the effectiveness of vaccinations, etc. This research can help make decisions at the global level and improve the availability and effectiveness of health care worldwide.

 

Conclusion

The development of economic modeling of health care plays a key role in improving the efficiency of health care and improving the quality of patient care. In the future, with the use of new technologies and real-world data integration, economic modeling will become even more accurate and personalized to improve healthcare decision-making and improve the quality of care for patients.

Investing in health care economic modeling can lead to significant improvements in health care, such as reduced treatment costs, improved quality of life for patients, and increased overall health care efficiency. In addition, the development of economic modeling can contribute to more accurate prediction of health care needs and optimize the use of resources.

In other words, the development of economic modeling of health care is an important step toward a more efficient and sustainable health care system.