1 Value of Information in relation to risk management Prof. Dr. Jan J.V. Busschbach.
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Transcript of 1 Value of Information in relation to risk management Prof. Dr. Jan J.V. Busschbach.
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Value of Information in relation to risk management
Prof. Dr. Jan J.V. Busschbach
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Change in policy
Now: evaluate all new medication Future: only when risk are high
When is an economic evaluation useful? When there is doubt about cost effectiveness
Low on information about cost effectivenesss
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The 3 meanings of doubt
1. The cost effectiveness might be invalid Methodologically unsound
The CFH judges the validity using guidelines
2. The cost effectiveness might be to high To high = bad
The ACP values the height of cost effectiveness
The CFH has no judgment
3. The cost effectiveness might be uncertain Much error variance
Unclear who is dealing with this….ACP? CFH?
Room for more risk management
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Uncertainty is linked to CE-ratio
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Interested in both costs and effect
Less effective More effective
Low costs (savings)
High costs
Not cost effective
cost effective
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Sensitivity analysis
Less effective More effective
Low costs (savings)
High costs
Superb!
Forget it!
Difficult…
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Good
Better
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Cost-effectiveness plane
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Not cost effective
Cost effective
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Cost Effectiveness Acceptability Curve (CEAC)
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Risk management
We can judge if we are in need of more information
Value of Information analysis
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Value of Information (VoI)
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Low VoI
High VoI
Low VoILow reduction of risk
Low reduction of risk
High reduction of risk
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Risk management
Make prototype cost effectiveness analysis Do a value of information analysis Triage:
Unconditional reimbursement:
• If CE-ratio is far much below threshold
• Value of information is (most likely) low
Conditional reimbursement
• If CE-ratio is close to threshold
• Value of information is high
Unconditional reject of reimbursement
• Value of information is low
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Arguments not to do so…
We should reimburse all effective drugs We should evaluate all (new) effective drug
Assumes that we have the resources to do so
We do not have a threshold We can not make acceptable prototypes
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We have an indication of a threshold…
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Wetenschappelijke Raad voor het Regeringsbeleid, 2006
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Example prototype model: Lucentis evaluated in the ACP
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Patel et al, 2010
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Avastin versus Lucentis
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Conclusion
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Risk management relates to value of information
Conditional reimbursement can be done on prototype cost effectiveness analysis
Only invest in (cost-) effectiveness, if Risks are high
Value of Information is high
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CFH procedure
Standard procedure Test of the validity of the cost effectiveness analysis
Using the guidelines
Orphan and expensive hospital drugs Conditional reimbursement
Approval of a four year data collection
• To arrive ad a valid cost effectiveness analysis
After 4 years
• Test of the validly of the cost effectiveness analysis
Using guidelines
Valuing cost effectiveness = other committee Advies Commissie Pakket (ACP)
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Uncertainty relates to threshold
If: CE-ratio = € 15.000 per QALY Threshold = € 25.000 per QALY Then intervention is cost effective
But what if CE-ratio is an interval: Threshold = € 25.000 per QALY CE-ratio = € 10.000 till € 30.000 per QALY Then intervention might be cost effective
If: Threshold = € 11.000 Then intervention most likely not cost effective
If: Threshold = € 29.000 Then intervention is most likely cost effective
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65 Citations in PubMed
1997 [pdat] AND "value of information analysis"
0
2
4
6
8
10
12
1996 1998 2000 2002 2004 2006 2008 2010 2012
Pu
bli
cati
on
s
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Why is evidence valuable?
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How things could turn out
Net Health Benefit Best we could do if we knewTreatment A Treatment B Best choice
Possibility 1 8 12 B 12
Possibility 2 16 8 A 16
Possibility 3 9 14 B 14
Possibility 4 12 10 A 12
Possibility 5 10 16 B 16
Average 11 12 14
How much evidence?
What’s the best we can do now? Could we do better?
Maximum value of more evidence is 2 QALYs per patient
Choose B Expect 12 QALYs, gain 1 QALY
But uncertain Wrong decision 2/5 times
If we knew Expect 14 QALYs
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Methods
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Treatment A
QALY Cost
Clinical effect
Disease Progression
QALY
Costs
Rand
om
s
ampl
ing Asymptomatic Progressive
Dead
Treatment A
Asymptomatic Progressive
Dead
Treatment B
Model Structure
Treatment B
QALY Cost
1 £10,000
2 £30,000
0 £ 5,000
3 £20,000
2 £15,000
4 £40,000
1 £10,000
3 £30,000
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Is the evidence sufficient?
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How things could turn out
Net Health Benefit Best we could do if we knewTreatment A Treatment B Best choice
Possibility 1 9 12 B 12
Possibility 2 12 10 A 12
Possibility 3 14 17 B 17
Possibility 4 11 10 A 11
Possibility 5 14 16 B 16
Average 12 13 13.6
Would more evidence improve health?
What’s the best we can do now? Could we do better?Choose B, expect additional net benefit of 1 QALY Get an extra 0.6 QALY
Maximum benefit of more evidence is0.6 QALYs or £12,000 per patient
Right decision 3/5 times (p = 0.6)
Wrong decision 2/5 times (1-p = 0.4)
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How uncertain is the decision?
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0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
£0 £10,000 £20,000 £30,000 £40,000 £50,000 £60,000
Cost-effectiveness threshold
Pro
ba
bili
ty c
ost
-effe
ctiv
e
B
A
C
Choose A Choose B
ICER = £25,000 per QALY
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Do we need more evidence?
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£0
£5,000,000
£10,000,000
£15,000,000
£20,000,000
£25,000,000
£0 £10,000 £20,000 £30,000 £40,000 £50,000 £60,000
Cost-effectiveness threshold
Ma
xiu
m b
en
efit
of
evi
de
nce
.
Choose A Choose B
Cost of research
Cost of research
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Alan Williams
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