8 Questions
What is the primary purpose of decision modelling in economic evaluation?
To allow for the variability and uncertainty associated with decisions
How is the likelihood of each consequence expressed in a decision analytic model?
In terms of probabilities
What does the expected cost for a given option represent?
The weighted sum of the costs of each consequence by the probability of that consequence
Which of the following best represents variability in decision modelling?
Response rates among patients
In decision analytic models, how is the uncertainty of a parameter best addressed?
Using sensitivity analysis
What type of events might be modeled as dichotomous in decision analysis?
Response and no-response to treatment
In the context of economic evaluation, what does the 'decision' typically relate to?
Resource allocation questions
What does the estimation of parameters in decision models require?
Sensitivity analysis to account for uncertainty
Study Notes
Decision Modelling
- Decision modelling is a systematic approach to decision making under uncertainty, used in economic evaluation to evaluate alternative options.
Decision Analytic Model
- A decision analytic model uses mathematical relationships to define a series of possible consequences that would flow from a set of alternative options being evaluated.
- Each consequence has a cost and an outcome, and the likelihood of each consequence is expressed in terms of probabilities.
- The model calculates the expected cost and expected outcome of each option under evaluation.
Expected Cost and Outcome
- The expected cost (outcome) is the sum of the costs (outcomes) of each consequence weighted by the probability of that consequence.
Variability and Uncertainty
- A key purpose of decision modelling is to allow for the variability and uncertainty associated with all decisions.
- The model reflects the fact that the consequences of options are variable, and that there is uncertainty in estimating parameters.
Structuring the Model
- The model is structured to reflect the variability and uncertainty of consequences, using probability parameters to express the likelihood of outcomes.
- Sensitivity analysis is used to account for the uncertainty in estimating these parameters.
Applications of Decision Modelling
- Decision modelling is used to inform resource allocation decisions in healthcare, such as:
- Should a collectively-funded health system fund a new drug for Alzheimer's disease?
- What is the most cost-effective diagnostic strategy for suspected urinary tract infection in children?
Learn about decision modelling, a systematic approach to decision making under uncertainty, and its application in economic evaluation. Understand how decision analytic models use mathematical relationships to define consequences and outcomes.
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