Expected Value of Perfect Information (EVPI)

In decision theory, the expected value of perfect information (EVPI) is the price that a decision-maker would be willing to pay to gain access to perfect information regarding all factors that influence which treatment choice is preferred as the result of a cost-effectiveness analysis (CEA). It is the value, in monetary terms, of removing all uncertainty from such an analysis.

Uncertainty in Decision-Making

When making decisions, there is always some degree of uncertainty. EVPI analysis aims to measure the expected cost of this uncertainty. It quantifies the value of having perfect information to eliminate the possibility of making the wrong decision.

Payoff Matrix

EVPI analysis involves modeling the decision problem with a payoff matrix. The matrix describes the potential outcomes and payoffs associated with different choices and states of nature. For instance, in a CEA, the rows of the payoff matrix could represent different treatment options, while the columns could represent different health outcomes. The payoffs could be the associated costs and benefits of each treatment-outcome combination.

Expected Monetary Value (EMV)

EMV is a key component in EVPI analysis. It represents the expected payoff for each choice, considering the probabilities of different states of nature. The best choice is the one that maximizes the EMV. In the context of a CEA, the EMV of a treatment option is the weighted average of its costs and benefits, where the weights are the probabilities of the different health outcomes.

Expected Value given Perfect Information (EV|PI)

EV|PI represents the expected payoff when perfect information is available. It considers the best choice for each state of nature. In a CEA, the EV|PI is the sum of the products of the probabilities of each health outcome and the maximum payoff (i.e., the payoff associated with the best treatment option) for that outcome.

Calculation of EVPI

EVPI is the difference between EV|PI and EMV. It represents the expected value that can be obtained by knowing the perfect information and making the best choice accordingly, compared to making a choice without perfect information. In other words, EVPI is the expected gain from having perfect information.

Conclusion

EVPI is a useful concept in decision theory, particularly in fields like health economics, where decisions are often made under uncertainty. It provides a framework for quantifying the value of perfect information and helps decision-makers assess the potential benefits of investing in information acquisition.

References:

1. Claxton, K., Sculpher, M., & Drummond, M. (2002). A rational framework for decision making by the National Institute for Clinical Excellence (NICE). Lancet, 360(9334), 711–715. https://doi.org/10.1016/S0140-6736(02)09832-X
2. Expected Value of Perfect Information (EVPI) – YHEC – York Health Economics Consortium. (2016). YHEC. https://yhec.co.uk/glossary/expected-value-of-perfect-information-evpi/
3. Expected value of information — EVI, EVPI, and ESVI – Analytica Docs. (n.d.). Analytica. https://docs.analytica.com/index.php/Expected_value_of_information_–_EVI,_EVPI,_and_ESVI
4. Hubbard, D. (2007). How to Measure Anything: Finding the Value of Intangibles in Business. John Wiley & Sons.

FAQs

What is EVPI?

EVPI stands for Expected Value of Perfect Information. It is the price that a decision-maker would be willing to pay to gain access to perfect information regarding all factors that influence a decision.

Why is EVPI important?

EVPI is important because it helps decision-makers quantify the value of perfect information and assess the potential benefits of investing in information acquisition.

How is EVPI calculated?

EVPI is calculated as the difference between the Expected Value given Perfect Information (EV|PI) and the Expected Monetary Value (EMV). EV|PI is the expected payoff when perfect information is available, while EMV is the expected payoff when decisions are made without perfect information.

What are some applications of EVPI?

EVPI is used in a variety of fields, including healthcare, business, and finance. In healthcare, EVPI is used to assess the value of new treatments and interventions. In business, EVPI is used to evaluate the potential benefits of market research and other information-gathering activities. In finance, EVPI is used to assess the value of financial information, such as stock market data.

What are some factors that affect EVPI?

The factors that affect EVPI include the degree of uncertainty in the decision, the potential costs and benefits of the decision, and the availability and cost of information.

What are some limitations of EVPI?

EVPI can be difficult to calculate, especially when the decision problem is complex and there is a high degree of uncertainty. Additionally, EVPI assumes that the decision-maker will be able to use the perfect information to make the best possible decision.

How can EVPI be used to improve decision-making?

EVPI can be used to improve decision-making by helping decision-makers identify the areas where they have the most uncertainty and where additional information would be most valuable. EVPI can also be used to justify the cost of information acquisition.

What are some examples of how EVPI has been used in practice?

EVPI has been used in a variety of practical applications, including the evaluation of new medical treatments, the design of marketing campaigns, and the assessment of investment opportunities.