Decision Analysis and Economic Evaluation

A Gentle Re-Introduction

Welcome to Nashville!

Orientation Info

Welcome & Introductions
Fellowship Goals and Overview
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Amua
Volunteers for Presenting Today

Example Patient

Lisa is a 45 year old woman with obesity (BMI 32) who has struggled with weight management.
She does not have diabetes but is concerned about her risk for cardiovascular disease due to weight, family Hx of heart disease, and elevated cholesterol levels.
Lisa heard from a friend about Wegovy, and would like her national health program to cover it for her.

Example Patient

Lisa works as a nurse for an Ascension hospital, which recently dropped coverage of weight-loss medications due to concerns over “long-term outcomes, national coverage benchmarks, and cost-effectiveness.”
Lisa’s predicament is not uncommon …

Example Patient

If Wegovy is not covered by the National Health Programme, it will cost Lisa $1,349 per month.
More broadly, how can we reconcile the health benefits of semaglutdie against the access and affordability challenges patients now face?

Decision Trees

What outcomes might Lisa experience?

What alternative to Semaglutide might she also consider?

Let’s now quantify the possible health and cost outcomes in different states of the world …

Health Outcome

Cost Outcome

Let’s now summarize the overall health and cost outcomes

We can now map (average) health and cost outcomes to a plot

The Cost-Effectiveness Plane

The Efficiency Frontier

Efficiency Frontier

A key mechanism for decisions over how to efficiently allocate scarce resources.
Allows us to identify the set of potentially cost-effective treatments.
Strategies off the frontier cannot provide the same health benefits at equal or lower cost.

Opportunity Costs

Under a constrained budget we’d have to divert resources from other worthy activities (e.g., education services, income assistance programs, other medical treatments) to cover a treatment that achieves, at best, the same health outcome.
If we select a strategy off the frontier, there is an opportunity cost and a potential loss in social welfare.

Cost-Effectiveness Analysis

Quantifies how to maximize the quality & quantity of life from among competing alternatives, given restricted resources.
It’s an explicit measure of value for money.
A POPULATION-LEVEL decision-making tool.

Cost-Effectiveness Analysis IS NOT

Indiscriminate cost-cutting
Downsizing
Intended to override individual-level decision-making.
The only tool for decision-making

Cost-Effectiveness Analysis

Cost of Intervention

Cost of Alternative

Benefit of Intervention

Benefit of Alternative

Cost-Effectiveness Analysis

Cost of Intervention

Cost of Alternative

Benefit of Intervention

Benefit of Alternative

Cost-Effectiveness Ratio

Cost of Intervention

\quad - \quad

Cost of Alternative

\frac{\quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad}{\quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad}

Benefit of Intervention

\quad - \quad

Benefit of Alternative

Cost-Effectiveness Ratio

C_1

\quad - \quad

C_0

\frac{\quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad}{\quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad}

E_1

\quad - \quad

E_0

Cost-Effectiveness Ratio

\Delta C

\frac{\quad \quad \quad \quad }{\quad \quad \quad \quad \quad }

\Delta E

Incremental Cost-Effectiveness Ratio

Most often used, since for most conditions there is already some available treatment.

C_1: net present value of total lifetime costs of new treatment
C_0: net present value of total lifetime costs of default treatment
E_1: effectiveness of new treatment, measured in expected life expectancy, quality-adjusted life years (QALYs) or disability-adjusted life years (DALYs), or some decision-relevant health outcome.
E_0: effectiveness of default treatment

\frac{C_1 - C_0 \quad (\Delta C)}{E_1 - E_0 \quad (\Delta E)}

Conducting a CEA

Neurologic Disease Decision Tree

Outcomes

C_{treat} = expected cost of treat everyone strategy.
C_{no treat} = expected cost of treat no one strategy.
C_{biopsy} = expected cost of biopsy strategy.

Outcomes

C_{treat} = expected cost of treat everyone strategy.
C_{no treat} = expected cost of treat no one strategy.
C_{biopsy} = expected cost of biopsy strategy.
E_{treat} = expected life expectancy of treat everyone strategy.
E_{no treat} = expected expectancy of treat no one strategy.
E_{biopsy} = expected expectancy of biopsy strategy.

Treat All vs. Treat None

Strategy: Treat No One

Treat All vs. Treat None

Strategy: Treat All

Key Takeaways (For Now)

Treatment yields higher life expectancy for those with disease, but comes at a cost.
Treatment yields lower life expectancy for those without the disease, and also comes at a cost.
Biopsy can help balance these two outcomes by better targeting treatment, but also comes with risks and costs.
Incremental CEA provides a transparent framework for quantifying and weighing these considerations.

Average Cost-Effectiveness Ratio

Special case where C_0 and E_0 are assumed to be zero.

C_1: net present value of total lifetime costs of new treatment
C_0: Assumed zero
E_1: effectiveness of new treatment, measured in expected life expectancy, quality-adjusted life years (QALYs) or disability-adjusted life years (DALYs), or some decision-relevant health outcome.
E_0: Assumed zero

\begin{aligned} ICER &= \frac{C_1 - 0}{E_1 - 0} \\ &= \frac{C_1}{E_1 } \end{aligned}

Non-Competing vs. Competing CEAs

Use of CEA in two situations

Shopping Spree: Decision problem has non-competing programs/interventions.

Each program is compared to a null alternative; therefore, you’re calculating an “average” cost-effectiveness ratio.

Use of CEA in two situations

Competing Choice: Decision problem has competing programs/interventions for the same purpose; these choices are mutually exclusive.

Two or more active alternatives in addition to the null option.
You need to calculate an “incremental cost- effectiveness ratio”, which gives us the added cost per unit of added benefit of an option, relative to the next less expensive choice

Non-Competing (Shopping Spree) Decision Problem

How can we measure the relative priority of various health programs that compete for limited resources?

Cardiovascular disease program
Safe motherhood program
HIV prevention initiative
Child vaccination
Depression screening

Assumptions

Program alternatives are assumed to be independent
Budget constraint is only limitation
Neither the net cost nor the net effectiveness depend on what other programs are selected
Programs are assumed to be divisible [programs can be partially implemented]

Objectives: Shopping Spree Problem

Maximize the total net effectiveness (health benefit) of the programs selected.

Stay within budget.

Shopping Spree Problem

Step 1: - Rule out programs that cost $ but have negative health effects
- Dominated by alternative of “no program”

Shopping Spree Problem

Step 2:
- Select programs that are cost-saving & offer benefit; net savings can also be added to budget
- Cost-saving compared to alternative of no program

Shopping Spree Problem

Step 3:
- Rank other programs in ascending order by their cost-effectiveness ratio (lowest to highest)
- Programs are then selected from the LEAST to the MOST expensive until the budget is expended
- Final array of programs selected will depend on the budget constraint

Shopping Spree Problem

Steps 1 & 2: Rule out dominated options & select cost-saving interventions

Program	Cost	QALYs	Status
A	27	30
B	30	20
C	56	70
D	20	40
E	30	50
F	50	75
G	40	-30	Ruled Out
H	-20	20	Adopted

Shopping Spree Problem

Initial budget: $80
Budget savings: $20.
Total budget: $80 + $20 = $100

Program	Cost	QALYs	Status
A	27	30
B	30	20
C	56	70
D	20	40
E	30	50
F	50	75
G	40	-30	Ruled Out
H	-20	20	Adopted

Shopping Spree Problem

Calculate average cost-effectiveness ratio.

Program	Cost	QALYs	C/E
A	27	30	0.90
B	30	20	1.50
C	56	70	0.80
D	20	40	0.50
E	30	50	0.60
F	50	75	0.67

Shopping Spree Problem

Calculate average cost-effectiveness ratio.
Sort (by C/E) in ascending order .

Program	Cost	QALYs	C/E
D	20	40	0.50
E	30	50	0.60
F	50	75	0.67
C	56	70	0.80
A	27	30	0.90
B	30	20	1.50

Shopping Spree Problem

Calculate cumulative costs
Determine what is adoptable based on global budget constraint ($100)
Calculate cumulative effects (QALYs)

Shopping Spree Problem

Budget: $100

Program	Cost	QALYs	C/E	Cumulative Cost	Cumulative QALYs
D	20	40	0.50	20	40
E	30	50	0.60	50	90
F	50	75	0.67	100	165
C	56	70	0.80	156	235
A	27	30	0.90	183	265
B	30	20	1.50	213	285

Shopping Spree Problem

Budget: $100

Program	Cost	QALYs	C/E	Cumulative Cost	Cumulative QALYs
D	20	40	0.50	20	40
E	30	50	0.60	50	90
F	50	75	0.67	100	165
C	56	70	0.80	156	235
A	27	30	0.90	183	265
B	30	20	1.50	213	285

Budget	Adopted	Effect	Threshold
100	D, E, F, H	165	0.67

Shopping Spree Problem

Budget: $150

Program	Cost	QALYs	C/E	Cumulative Cost	Cumulative QALYs
D	20	40	0.50	20	40
E	30	50	0.60	50	90
F	50	75	0.67	100	165
C	56	70	0.80	156	235
A	27	30	0.90	183	265
B	30	20	1.50	213	285

Budget	Adopted	Cost	Effect	Threshold	Remaining
150	D, E, F, H	100	165	0.67	50

Shopping Spree Problem

Budget: $150

Program	Cost	QALYs	C/E	Cumulative Cost	Cumulative QALYs
D	20	40	0.50	20	40
E	30	50	0.60	50	90
F	50	75	0.67	100	165
C	56	70	0.80	156	235
A	27	30	0.90	183	265
B	30	20	1.50	213	285

Budget	Adopted	Cost	Effect	Threshold	Remaining
150	D, E, F, H	100	165	0.67	50

Shopping Spree Problem

Budget: $150

Program	Cost	QALYs	C/E	Cumulative Cost	Cumulative QALYs
D	20	40	0.50	20	40
E	30	50	0.60	50	90
F	50	75	0.67	100	165
C (89.3%)	56	70	0.80	156	235
A	27	30	0.90	183	265
B	30	20	1.50	213	285

Budget	Adopted	Cost	Effect	Threshold	Remaining
150	D, E, F, C (89.3%), H	150	226.6	0.8	0

$50 left but program C costs $56 (50/56 = 0.89)
0.89*70 QALYs of program C = 62.3 QALYs

Summary: Shopping Spree Problem

Maximize the total net effectiveness (health benefit)

Stay within budget

Can do the same with other objectives (e.g., Minimize costs, subject decision to ‘minimum benefit’ constraint, etc.)

Use of CEA in two situations

Shopping Spree: Decision problem has non-competing programs/interventions.

Use of CEA in two situations

Competing Choice: Decision problem has competing programs/interventions for the same purpose; these choices are mutually exclusive.

Objectives: Competing Choice Problem

Cannot implement more than one strategy at a time.

Incremental cost-effectiveness ratio is below a pre-specified adoption threshold.

What’s different?

Shopping Spree

Can select multiple programs
Different costs & effects associated with each
Requires calculation of an Average Cost-Effectiveness Ratio

Competing Choice

Programs are mutually exclusive.
Different costs & effects associated with each.
Requires calculation of an Incremental Cost-Effectiveness Ratio (ICER)

(1) Opioid pharmacotherapy is the recommended treatment for OUD in pregnancy, as we know that medication reduces the risk of overdose and relapse, improves overall retention to care, and improves pregnancy & fetal outcomes.

There are three classes of medications approved by the FDA – & there are several sub-modalities that are not listed here that we are modeling – such as injectable formulations versus monotherapy / etc.
But overall – there are options like Methadone that are full “agonists” – where the effects of the treatment increase as the dose increases
Buprenorphine which is a partial agonist – in other words, buprenorphine has a “ceiling effect”, so its effects can only be felt up to a certain point & then plateaus thereafter
And Naltrexone, which is an “antagonist” and works by blocking opioid receptors & reduces & suppresses opioid cravings
The difficult tradeoffs of these therapies, include:

Access challenges & delays in care – for instance, there’s a limited # of methadone clinics across the US – there are only 3 methadone clinics in Nashville (22 total in the state) & 5 total in neighboring Mississippi
& while buprenorphine & naltrexone, for example, can be administered in any office-based setting, methadone can only be dispensed in these specialty OTP clinics that I had mentioned earlier
For opioid recurrence or disengagement from treatment rates, Methadone may have better outcomes BUT methadone also poses a significant risk of mortality from opioid overdose due to respiratory depression during treatment induction
Regarding infant outcomes, buprenorphine has performed better than methadone when it comes to outcomes like preterm birth, neonatal withdrawal syndrome, & length of hospital stay, but infants exposed to Naltrexone have the least severe withdrawal overall & lowest hospital length of stay
There are also different tradeoffs associated with treatment modalities such as tablets, film, injectables
And then there’s many other things to consider such as inpatient versus outpatient induction periods versus continuation of care AND outcomes associated with injection versus non-injection users

While individuals can switch back & forth between these medications, they can only be on ONE medication at a time & we have to decide what is the best option for pregnant invidivudals with OUD given all of the tradeoffs just mentioned

Incremental CEA

1. Incremental CEA in Pictures

1. Calculate incremental costs and effects

Often, a strategy capturing current practice (‘status-quo’, ‘do nothing’, ‘natural history’) is defined.
Costs and effects are then calculated for each strategy relative to the status-quo.
Plot the difference in costs and effects with health effects on x-axis and cost effects on y-axis.

1. Calculate cost and effects

Identify Dominated Strategies

We can rule out any strategies that result in less health at higher cost.
There is an opportunity cost to selecting these strategies.
The resources (budget, staff) used in the provision of a service could have been used to provide a less resource-intensive strategy that yields the same (or higher) health outcome.

Identify Dominated Strategies

We can also rule out strategies where some other competing strategy results in more (or equal) health at lower (or equal) cost.
This is known as “strong” dominance.

Identify Dominated Strategies

What about strategy B?

Hybrid Strategies

Suppose it is feasible to partially implement strategies A and D.
- For example, we could implement A for 90% of the population and D for 10% of the population, or vice versa.

90% A, 10% D

10% A, 90% D

50% A, 50% D

Can we make any statements about B now?

Extended (Weak) Dominance

B is ruled out by extended (“weak”) dominance.

Extended (Weak) Dominance

Efficiency Frontier

The efficiency frontier is the set of non-dominated strategies.

Efficiency Frontier

A key initial mechanism for decisions over how to efficiently allocate scarce resources.
Allows us to identify the set of potentially cost-effective treatments.
Strategies off the frontier cannot provide the same health benefits at equal or lower cost.

Efficiency Frontier and ICERs

Just because something is potentially cost-effective does not mean we should adopt it.
Adoption depends on social value judgements on what we’re willing to pay to improve health in a population.
Depending on the context, we can use an incremental cost-effectiveness ratio as an input into determinations on whether adoption is “worth it.”

ICERs

The slope of a line connecting two points is the incremental cost-effectiveness ratio comparing those strategies. More on this later!

2. Incremental CEA in Tables

Incremental CEA

Please note that the following example uses different strategies and values than the example used in the previous pictures!

Incremental CEA

Calculate costs and effects for each strategy.
Sort table by costs in ascending order.¹
Calculate ICER based on difference in costs and effects.
Determine dominated strategies (ICER<0).
Re-calculate ICERs after eliminating dominated strategies.
Determine strategies ruled out by extended dominance.
Re-calculate ICERs after ruling out all dominated strategies.
Repeat 5-7 as needed.

Incremental CEA

1. Calculate costs and effects for each strategy.

Strategy	Cost	QALYs
A	16,454	17.33
D	24,504	17.49
C	33,443	17.58
B	21,457	17.41
E	43,332	17.49

Incremental CEA

Calculate costs and effects for each strategy.

2. Sort table by costs in ascending order.¹

Strategy	Cost	QALYs
A	16,454	17.332
B	21,457	17.409
D	24,504	17.491
C	33,443	17.580
E	43,332	17.491

Incremental CEA

Calculate costs and effects for each strategy.
Sort table by costs in ascending order.¹

3. Calculate ICER based on difference in costs and effects.

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
B	21,457	5,003	17.409	0.077	64,895
D	24,504	3,048	17.491	0.082	36,989
C	33,443	8,939	17.580	0.088	101,292
E	43,332	9,888	17.491	-0.088	-112,048

Incremental CEA

Calculate costs and effects for each strategy.
Sort table by costs in ascending order.¹
Calculate ICER based on difference in costs and effects.

4. Determine dominated strategies (ICER<0)

Determining Dominated Strategies

Let’s take a look at our table.
Notice that strategy E has a negative ICER. Why is this?
Strategy E raises costs but lowers QALYs.
Therefore, we’d be better off by selecting strategy C (we would get more health gain for less money…)

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
B	21,457	5,003	17.409	0.077	64,895
D	24,504	3,048	17.491	0.082	36,989
C	33,443	8,939	17.580	0.088	101,292
E	43,332	9,888	17.491	-0.088	-112,048

Determining Dominated Strategies

Strong dominance refers to situations where one strategy is preferred over another on both costs and health effects (e.g., QALYs).
When we identify a strongly dominated option, we remove it from the table and re-calculate ICERS based on the remaining strategies.

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
B	21,457	5,003	17.409	0.077	64,895
D	24,504	3,048	17.491	0.082	36,989
C	33,443	8,939	17.580	0.088	101,292
E	43,332	9,888	17.491	-0.088	-112,048	Dominated

A Brief Aside on Negative ICERs

We want to rule out strategies that cost more but result in less health.
- This implies a negative ICER.
But what other scenario would result in a negative ICER?
- Strategy adds health but reduces costs.
- This is a great strategy!

Both Strategies Have a Negative ICER

A Brief Aside on Negative ICERs

For this reason, it is poor practice to report negative ICERs.
Be careful when deleting a strategy becuase it has a negative ICER!
- It may be a great strategy!

Incremental CEA

Calculate costs and effects for each strategy.
Sort table by costs in ascending order.¹
Calculate ICER based on difference in costs and effects.

4. Determine dominated strategies (ICER<0)

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
B	21,457	5,003	17.409	0.077	64,895
D	24,504	3,048	17.491	0.082	36,989
C	33,443	8,939	17.580	0.088	101,292
E	43,332	9,888	17.491	-0.088	-112,048	Dominated

Incremental CEA

Calculate costs and effects for each strategy.
Sort table by costs in ascending order.¹
Calculate ICER based on difference in costs and effects.

Determine dominated strategies (ICER<0).

5. Re-calculate ICERs after eliminating dominated strategies.

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
B	21,457	5,003	17.409	0.077	64,895
D	24,504	3,048	17.491	0.082	36,989
C	33,443	8,939	17.580	0.088	101,292
E	43,332		17.491		-112,048	Dominated

Incremental CEA

Calculate costs and effects for each strategy.
Sort table by costs in ascending order.¹
Calculate ICER based on difference in costs and effects.

Determine dominated strategies (ICER<0).
Re-calculate ICERs after eliminating dominated strategies.

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
B	21,457	5,003	17.409	0.077	64,895
D	24,504	3,048	17.491	0.082	36,989
C	33,443	8,939	17.580	0.088	101,292
E	43,332		17.491

Determining Dominated Strategies

We’re not quite done yet
Notice something odd about strategy B?
Its ICER is higher than the next most costly alternative (strategy D)

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
B	21,457	5,003	17.409	0.077	64,895
D	24,504	3,048	17.491	0.082	36,989
C	33,443	8,939	17.580	0.088	101,292
E	43,332		17.491

Determining Dominated Strategies

A telltale sign of extended dominance in a (sorted) CEA table is a strategy with a higher ICER than the next most expensive option.

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
B	21,457	5,003	17.409	0.077	64,895	Dominated (Extended)
D	24,504	3,048	17.491	0.082	36,989
C	33,443	8,939	17.580	0.088	101,292
E	43,332		17.491			Dominated

Determining Dominated Strategies

You can see this in the pictures as well ….

Incremental CEA

Calculate costs and effects for each strategy.
Sort table by costs in ascending order.¹
Calculate ICER based on difference in costs and effects.

Determine dominated strategies (ICER<0).
Re-calculate ICERs after eliminating dominated strategies.

6. Determine strategies ruled out by extended dominance.

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
B	21,457	5,003	17.409	0.077	64,895	Dominated (Extended)
D	24,504	3,048	17.491	0.082	36,989
C	33,443	8,939	17.580	0.088	101,292
E	43,332		17.491			Dominated

Incremental CEA

7. Re-calculate ICERs after ruling out all dominated strategies.

Strategy	Cost	dCost	QALYs	dQALYs	ICER
A	16,454		17.332
D	24,504	8,050	17.491	0.159	50,478
C	33,443	8,939	17.580	0.088	101,292
E	43,332		17.491			Dominated
B	21,457		17.409			Dominated (Extended)

Strategy D is more expensive than Strategy B, but Strategy D is gaining health MORE EFFICIENTLY than Strategy B

Practice: Weight-Loss Medication

The Institute for Clinical and Economic Review (ICER) is a non-profit organization that evaluates the cost-effectiveness of new drugs and therapies.
- Reports are used by payers to inform coverage decisions.
- Reports are also used by manufacturers to inform pricing decisions.
Next slides summarizes ICERs findings on weight loss therapies.

Practice: Weight-Loss Medication

Five different therapeutic and lifestyle strategies to reduce weight.

Strategy	Cost	QALY
Semaglutide (Wegovy)	392,100	17.83
Liraglutide (Saxenda)	277,000	17.34
Phentermine/Topiramate (Qsymia)	182,600	17.38
Bupropion/Naltrexone (Contrave)	207,300	17.16
Lifestyle Modification	179,200	16.93

Calculate Incremental Costs and QALY

Strategy	Cost	Incremental Cost	QALYs	Incremental QALYs
Lifestyle Modification	179,200	0	16.93	0.00
Phentermine/Topiramate (Qsymia)	182,600	3,400	17.38	0.45
Bupropion/Naltrexone (Contrave)	207,300	24,700	17.16	-0.22
Liraglutide (Saxenda)	277,000	69,700	17.34	0.18
Semaglutide (Wegovy)	392,100	115,100	17.83	0.49

Calculate incremental costs per QALY

Strategy	Incremental Cost	Incremental QALYs	Incremental Cost per QALY
Lifestyle Modification	0	0.00
Phentermine/Topiramate (Qsymia)	3,400	0.45	7,556
Bupropion/Naltrexone (Contrave)	24,700	-0.22	-112,273
Liraglutide (Saxenda)	69,700	0.18	387,222
Semaglutide (Wegovy)	115,100	0.49	234,898

Determine dominated strategies

Strategy	Incremental Cost	Incremental QALYs	Incremental Cost per QALY	Status
Lifestyle Modification	0	0.00
Phentermine/Topiramate (Qsymia)	3,400	0.45	7,556
Bupropion/Naltrexone (Contrave)	24,700	-0.22	-112,273	Dominated (Strong)
Liraglutide (Saxenda)	69,700	0.18	387,222
Semaglutide (Wegovy)	115,100	0.49	234,898

Remove dominated strategies and recalculate

Determine dominated strategies

Strategy	Cost	Incremental Cost	QALYs	Incremental QALYs
Lifestyle Modification	179,200	0	16.93	0.00
Phentermine/Topiramate (Qsymia)	182,600	3,400	17.38	0.45
Liraglutide (Saxenda)	277,000	94,400	17.34	-0.04
Semaglutide (Wegovy)	392,100	115,100	17.83	0.49

Determine dominated strategies

Strategy	Incremental Cost	Incremental QALYs	Incremental Cost per QALY	Status
Lifestyle Modification	0	0.00	0
Phentermine/Topiramate (Qsymia)	3,400	0.45	7,556
Liraglutide (Saxenda)	94,400	-0.04	-2,360,000	Dominated (Strong)
Semaglutide (Wegovy)	115,100	0.49	234,898

Remove dominated strategies and recalculate

Determine dominated strategies

Strategy	Cost	Incremental Cost	QALYs	Incremental QALYs
Lifestyle Modification	179,200	0	16.93	0.00
Phentermine/Topiramate (Qsymia)	182,600	3,400	17.38	0.45
Semaglutide (Wegovy)	392,100	209,500	17.83	0.45

Determine dominated strategies

Strategy	Incremental Cost	Incremental QALYs	Incremental Cost per QALY
Lifestyle Modification	0	0.00	0
Phentermine/Topiramate (Qsymia)	3,400	0.45	7,556
Semaglutide (Wegovy)	209,500	0.45	465,556

Final Table

Strategy	Incremental Cost	Incremental QALYs	Incremental Cost per QALY	Status
Lifestyle Modification	0	0.00	0
Phentermine/Topiramate (Qsymia)	3,400	0.45	7,556
Semaglutide (Wegovy)	209,500	0.45	465,556
Bupropion/Naltrexone (Contrave)	24,700	-0.22	-112,273	Dominated (Strong)
Liraglutide (Saxenda)	94,400	-0.04	-2,360,000	Dominated (Strong)

Where to draw the line?

CEA Thresholds

So now we have our ICERs, but how do we make a decision?
We must define a threshold (\lambda), or an ICER value that determines whether or not we implement a given strategy.
- Also known as “willingness-to-pay” (WTP) threshold.

CEA Thresholds

What are common thresholds and how are they determined?

In high income countries, common thresholds are $50,000/QALY, $100,000/QALY, and $150,000/QALY.
In LMICs, 0.5-3x per capita gross domestic product (GDP) per DALY averted.
More on this in a few minutes.

How do CEA Thresholds Guide Decisionmaking?

CEA Thresholds

Different ways thresholds have been estimated:

“Supply-side” (UK & Europe)
“Demand-side” (US) - per capita consumption (US/LMICs)

There are different ways to determine a cost-effective threshold & it’s done a bit differently around the world, which we talk about in a recent paper I collaborated with UK colleagues on, which discusses the evolution of these thresholds.
Some countries like the UK, use what has been referred to as a “supply-side threshold” – which represents the notion of opportunity cost – whether the health generated from an adopted intervention from NICE, for instance, is greater than the health that could have been generated if the money had been spent on something else - Under a fixed budget.
Another way that countries like the US have defined CE thresholds is by what’s called a “demand-side” perspective, or society’s “willingness to pay” for health gains. There’s still an opportunity cost associated with this but it’s from the perspective of the goods & services we would be willing to forego for these additional health gains.
Similarly, another way that countries have looked at the threshold is in terms of per capita consumption - consistent with the idea that people living in countries with higher incomes are able and willing to pay more for health - which makes intuitive sense

Opportunity cost (“supply-side”)

Decision should be informed by the value of what will be given up as a consequence of those costs.
If resources are committed to the funding of one intervention, then they are not available to fund and deliver others (shopping spree concept)
The opportunity cost of a commitment of resources is the health forgone because these “other” interventions that are available to the health system cannot be delivered.

Opportunity cost (“supply-side”)

This is the closest to a “supply-side” CEA estimate that the US has approached
This simulation looked at the Opportunity Cost attributed to persons dropping health insurance due to health insurance premium increases (which often happens when intervention costs are very high – it’s often the consumers that bear the burden)
The authors found that the threshold should be around $100,000/QALY gained (which is typically
But UK academics would argue that this isn’t a true opportunity cost estimate because it doesn’t evaluate the opportunity cost of displacing interventions for other more effective (but often more costly) alternatives –

either within the health care sector or displacing other programs in other sectors because of how much we spend on health care
& there’s many other things to consider such as effect of increasing healthcare costs on patient copays, wait times, generosity of employer plans, or on public insurance

Opportunity cost (“supply-side”)

If you don’t consider the budget under which you are operating, then some medications could take up half the budget.
This would displace interventions that produce significant health gain OR in the US, could increase premiums or take away $ from other sectors

Opportunity cost (“supply-side”)

Some have argued that the threshold should be lower/on the more conservative end for higher priced therapies.
- NICE (UK) uses a budget impact threshold of 20,000 GBP/QALY for these higher priced therapies as opposed to 30,000 GBP/QALY for others.

Willingness to pay (“demand-side”)

Given that we don’t have “fixed” budget, per se, the US has largely defined thresholds based on what is often referred to as “demand-side” or “willingness-to-pay” criteria.
Intuition: willingness to forego other types of consumption to improve one’s health.
This willingness to pay has been derived through surveys & also what Medicare has been willing to pay for interventions (e.g., ESRD)

Given that our health system is more complicated & we don’t necessarily have a “fixed” budget, per se, the US has largely defined thresholds based on what is often referred to as “demand-side” or “willingness-to-pay” criteria, which can also be represented as the willingness to forego other types of consumption to improve one’s health.
This willingness to pay has been derived through surveys & also what Medicare has been willing to pay for interventions
Some have argued that understanding a population’s willingness to pay is important, especially in a single-payer system that is funded through social insurance – ensuring that individuals have a role in decision-making
But there is huge variation in willingness to pay studies - varied substantially by condition, especially those for extending or saving life (higher WTP).
This very short perspective piece gives an overview of the thresholds we have used in the US in the past & what they are largely based on (has largely been arbitrary) – it’s 2 pages & would recommend reading

Back to the Wegovy Example

Weight Loss Coverage in the UK (\lambda)

England’s National Health Service is most likely to pay for drugs that cost £20,000, or about $25,000 per QALY.

Strategy	Cost	QALY	ICER	Status
Lifestyle Modification	179,200	16.93
Phentermine/Topiramate (Qysmia)	182,600	17.38	7,556
Semaglutide (Wegovy)	392,100	17.83	465,556
Bupropion/Naltrexone (Contrave)	207,300	17.16		Dominated (Strong)
Liraglutide (Saxenda)	277,000	17.34		Dominated (Strong)

Would our example patient have access to Wegovy in the UK?

Patient Heterogeneity

Returns to treatment may vary by relevent patient subgroups.
“Heterogeneity” refers to the extent to which between-patient variability can be explained by patients’ characteristics.

Patient Heterogeneity

Clinically-relevant heterogeneity suggests identification of subgroups for whom separate cost-effectiveness analyses should be undertaken.
Such analyses may inform alternative decisions regarding the service provision to each subgroup, or contribute to a weighted analysis of the aggregate group

Would our example patient have access to Wegovy in the UK?

Availability and Access to Wegovy

Country	Would National Health Program Cover?
US ($1,349)	No and Yes (with PA)
UK ($378)	No
France [not yet avail.]	No
Germany ($328)	No
Spain [not avail.]	No
Netherlands ($296)	No

CEA Thresholds in LMICs

Thresholds in low and middle income countries (LMICs) often based on 1-3X per capita Gross Domestic Product (GDP)
Roughly corresponds to what has become convention for high-income countries (1X per capita GDP in the US is around $60,000.