Additional knowledge Flashcards
Torpedo diagram (sensitivity)
Low to high
Shows variation towards initial nominal values
Shows correlation
Wide bars need more attention
Welfare theory approach
Objective: Maximize individual utility/health
Marginal rate for substition (health for money)
Should be measured in population
Assumes: Perfect divisibility/independence/no uncertainty
Resource allocation (RA)
Allocate scarce resources
Threshold is the shadowprice of budget constraints
Assumes: All can be combined, perfectly divisible, constant return.
Not always possible due to constraints.
Decision rule: CE-rate < lambda, but lambda can change due to budget variation. So in practice, sort by ICER and add new ones till budget is gone.
Knapsack problem
Individual interventions with fixed size which can be combined
No longer a simple optimim
Advice in NL
Use the CE as a starting point for negotiations, so it has X% probability to be CE, thus price drops required of Y%.
–> Appropriate scope needed and dealing with uncertainty
Average CE
Comparing slope i to threshold (care as usual)
Incremental CE
Comparing slope between 2 treatments to the threshold
Extended dominance
Combination of two might still be preferred over third option (easier to leave the third one out by the reimbursement officer)
Rate
Potential for occurance of event (added/substracted)
Rate to probability = 1 - EXP(value)
Probabilities
Likelihood for event to happen (0-1)
EQ5D
5 subjects, few options
Answers have weight
Optimal health (1) - ….
Standard gamble (decision tree)
Seen as timeless (1 healthy, 0 death)
Others assume tradeoff between quality and time.
Look at scenario A and then fillin the utility preferred over A
(40% probon death over A)
Time trade-off
Example; 15 years in A or 12 years full health = 12/15 = 0.8 Strong assumptions 1. Linear life duration 2. No loss aversion 3. No scale comparability Upwards bias
VAS
Rating scales with intervals. Critics:
1. Achors not well defined
2. Biases
3. Results differ towards utility measure (SG)
Too much aversion towards extreme when using scales.
Paired Comparison (Thurstone)
Compairing entities in pairs. Assumes:
- Posses varying attributes
- Preference exists
- Unidimensional quality
- Normal distribution
The greater the preference/likelihood, the bigger the weight