Cadth 2015 a4 15.04.04 workshop mike paulden

Transforming the cost-effectiveness threshold into a ‘value threshold’

Initial findings from a simulation modelMike Paulden and Christopher McCabe

Problem• The conventional cost-effectiveness (CE) threshold represents “an

estimate of health forgone as other [services] are displaced to

accommodate the additional costs of new technologies”

(Claxton et al. 2013)

• Plotted as a straight line on the CE plane (Drummond et al. 2005)

• Numerous limitations and assumptions:

• Assumes constant marginal returns and divisibility of technologies

• No account for aspects of ‘value’ beyond those considered by the QALY

• Impact of imperfect information is not explicitly considered, nor the possibility

that new interventions represent net disinvestments

• No account for multiple decision makers with conflicting objectives

• Recently, NICE has applied ‘modifiers’ to its baseline threshold to

account for aspects of ‘value’ beyond the QALY (NICE 2009, 2014)

• Resulted in inconsistencies in NICE’s methodology (Paulden et al. 2014)

Objective

• Our objective is to transform the conventional CE threshold

into a ‘value threshold’ of greater use to decision makers

• In doing so we aim to address the limitations previously

described

• As a first step we have developed a simulation model in order to

understand how a ‘value threshold’ may differ from a CE threshold

• Of key interest are the implications of:

i. Relaxing conventional assumptions such as constant marginal

returns to scale and perfect divisibility of technologies

ii. Incorporating imperfect information and ‘value’ considerations within

a complex health system with multiple decision makers

iii. Extending the threshold so that it may be used for net disinvestments

Pool of initial technologiesThe cost and effectiveness of each

technology is drawn from a distribution

Each technology is randomly assigned a ‘value’ attribute and a specific health production function ‘shape’ (applies

only if marginal returns are diminishing)

Model schematic





Divisibility of technologiesTechnologies in the pool are either

all divisible or all indivisible

Marginal returns to scaleTechnologies in the pool either all have constant marginal returns to

scale or all have diminishing marginal returns to scale

Model schematic





Initial budgetUpon the establishment of the health system, an initial budget

is assigned for purchasing technologies from the pool





Model schematic





Initial allocator

Imperfect informationEach decision maker has one of

four levels of information regarding the effectiveness of technologies:

none, poor, good, or perfect

Other value considerationsEach decision maker assigns one

of four possible weights to ‘value’ considerations beyond the QALY:

none, small, medium, or large



1. The initial allocator purchases technologies from the pool until the

initial budget is exhausted





Model schematic





New interventionEach new intervention represents either a net investment or net disinvestment

Net investments impose costs on the health system, requiring that resources

be released from other technologies

Net disinvestments release resources, allowing these to be spend on other

technologies from the pool

Initial allocator















Model schematic





Initial allocator Agent











Value thresholdUsed by the agent to determine whether or not to recommend

the new intervention

2. The agent recommends the new intervention if its

expected value exceeds the agent’s value threshold





Model schematicNew intervention

Each new intervention represents either a net investment or net disinvestment









Initial allocator Reallocator Agent



















Model schematicNew intervention

Each new intervention represents either a net investment or net disinvestment






















3. If the agent recommends a net investment, the reallocator must contract adopted NE/NW technologies and/or expand non-exhausted SE/SW technologies. Alternatively, if the agent recommends a net disinvestment, the reallocator may

expand non-exhausted NE technologies and/or contract adopted SW technologies





Model schematic





























Agent’s authorityAgent may have mandate to

consider reallocation and/or an alternative to the intervention

Model schematic



























4. Prior to making its recommendation, the agent places its own valuations on both the new intervention and the reallocator’s preferred reallocation. If the agent has the authority to mandate a reallocation and/or propose an alternative to the new intervention then it also places a valuation upon this. The optimal value threshold is that which ensures that a new intervention is only recommended if doing so maximizes the expected value to the agent





Agent’s authorityAgent may have mandate to

consider reallocation and/or an alternative to the intervention

Model schematic










Conventional Assumptions

-$50m

-$40m

-$30m

-$20m

-$10m

$0m

$10m

$20m

$30m

$40m

$50m

-2,000 -1,000 0 1,000 2,000

Expe

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Value of new technology (QALY equivalents)

Lowerbudget

Higherbudget

Lowerbudget

Higherbudget

Threshold'kinks'

All decision makers haveperfect information

All decision makers placeno weight on other

‘value’ considerations

Technologies are divisible

Technologies exhibit constant returns to scale

Agent cannot reallocate

-$50m

-$40m

-$30m

-$20m

-$10m

$0m

$10m

$20m

$30m

$40m

$50m

-2,000 -1,000 0 1,000 2,000

Expe

nditu

re o

n ne

w te

chno

logy


Lowerbudget

Higherbudget

Lowerbudget

Higherbudget





Technologies exhibit diminishing returns to scale


Diminishing Returns to Scale

-$50m

-$40m

-$30m

-$20m

-$10m

$0m

$10m

$20m

$30m

$40m

$50m

-2,000 -1,000 0 1,000 2,000

Expe

nditu

re o

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chno

logy


Lowerbudget

Higherbudget

Lowerbudget

Higherbudget

(overlap)




Technologies are indivisible

Returns to scale irrelevant if technologies are indivisible


Indivisible Technologies

-$50m

-$40m

-$30m

-$20m

-$10m

$0m

$10m

$20m

$30m

$40m

$50m

-2,000 -1,000 0 1,000 2,000

Expe

nditu

re o

n ne

w te

chno

logy


Lowerbudget

Higherbudget

Lowerbudget Higher

budget

Threshold'kinks'

Reallocator and agent haveperfect information

and initial allocator haspoor information

Reallocator and agentplace small weight and initial allocator placeslarge weight on other ‘value’ considerations




Imperfect Information andOther ‘Value’ Considerations

-$50m

-$40m

-$30m

-$20m

-$10m

$0m

$10m

$20m

$30m

$40m

$50m

-2,000 -1,000 0 1,000 2,000

Expe

nditu

re o

n ne

w te

chno

logy


Lowerbudget

Higherbudget

Lowerbudget

Higherbudget

Threshold'kinks'

Initial allocator and agent have perfect information

and reallocator haspoor information

Initial allocator and agentplace small weight and

reallocator placeslarge weight on other ‘value’ considerations




-$50m

-$40m

-$30m

-$20m

-$10m

$0m

$10m

$20m

$30m

$40m

$50m

-2,000 -1,000 0 1,000 2,000

Expe

nditu

re o

n ne

w te

chno

logy


Lowerbudget

Higherbudget

Lowerbudget

Higherbudget

Threshold'kink'

Initial allocator and agent have perfect information

and reallocator haspoor information

Initial allocator and agentplace small weight and

reallocator placeslarge weight on other ‘value’ considerations



Agent can reallocate

Agent Has Authority to Reallocate

Conclusions

• The conventional ‘CE threshold’ model is merely a special case

among many approaches for determining a value threshold

• Departing from this special case allows for consideration of:

• Differences in the information available to, the values held by, and the

objectives pursued by, multiple interacting decision makers

• The specific value characteristics of each technology

• This has potentially significant implications for the appropriate

specification of value thresholds used for decision making

• Our findings provide insights for future theoretical work, as well

as a rich source of potential hypotheses for researchers

conducting empirical research in this area

Questions

1. Why should value considerations be accounted for within the

threshold used for CE analysis? Isn’t it sufficient to simply apply

weights to new technologies or to consider ‘values’ separately?

2. Why might differences in information, values and objectives

across multiple interacting decision makers result in:

a) Different thresholds for net investments and net disinvestments?

b) Thresholds that cross into the SE and NW quadrants of the CE plane?

3. Why is the threshold dependent upon the agent’s authority?

Are there any implications for the recommendations made by

CADTH or for the decisions of Canadian policy makers who

depend upon CADTH’s guidance?

References• Claxton et al. (2013). Methods for the Estimation of the NICE Cost

Effectiveness Threshold. CHE Research Paper 81. York: University of

York.

• Drummond et al. (2005). Methods for the Economic Evaluation of Health

Care Programmes. Third Edition. Oxford: Oxford University Press.

• Sendi et al. (2002). Opportunity costs and uncertainty in the economic

evaluation of health care interventions. Health Economics, 11(1), 23–31.

• National Institute for Health and Care Excellence (2009). Appraising life-

extending, end of life treatments. London: NICE.

• National Institute for Health and Care Excellence (2014). Consultation

Paper: Value Based Assessment of Health Technologies. London: NICE.

• Paulden et al. (2014). Some Inconsistencies in NICE’s Consideration of

Social Values. PharmacoEconomics. November 2014, 32(11), 1043-1053.

Date post:	07-Aug-2015
Category:	Health & Medicine
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Cadth 2015 a4 15.04.04 workshop mike paulden

Health & Medicine