Identify theoretical and methodological differences between different economic evaluation techniques
Grasp the foundations of cost-effectiveness analysis
Describe the steps of valuing costs in economic evaluations & identify ways to curate cost parameters
We’ve touched on the basic framework for decision analysis, focusing on:
Decision trees & probabilities
Bayes theorem & probability revision
Constructing decision trees using Amua
Relevant when decision alternatives have different costs and health consequences.
We want to measure the relative value of one strategy in comparison to others.
This can help us make resource allocation decisions in the face of constraints (e.g., budget).
Type of study | Measurement/valuation of costs | Identification of consequences | Measurement / valuation of consequences |
---|---|---|---|
Cost analysis | Monetary units | None | None |
Source: [@drummond2015a]
Only looks at healthcare costs
Relevant when alternative options are equally effective (provide equal benefits)
Costs are valued in monetary terms (e.g., U.S. dollars)
Decision criterion: often to minimize cost
Type of study | Measurement/Valuation of costs | Identification of consequences | Measurement / valuation of consequences |
---|---|---|---|
Cost analysis | Monetary units | None | None |
Cost-effectiveness analysis | Monetary units | Single effect of interest, common to both alternatives, but achieved to different degrees. | Natural units (e.g., life-years gained, disability days saved, points of blood pressure reduction, etc.) |
Source: [@drummond2015a]
Most useful when decision makers consider multiple options within a budget, and the relevant outcome is common across strategies
Suppose we are interested in the prolongation of life after an intervention.
Outcome of interest: life-years gained.
The outcome is common to alternative strategies; they differ only in the magnitude of life-years gained.
We can report results in terms of $/Life-years gained
Type of study | Measurement/Valuation of costs both alternative | Identification of consequences | Measurement / valuation of consequences |
---|---|---|---|
Cost analysis | Monetary units | None | None |
Cost-effectiveness analysis | Monetary units | Single effect of interest, common to both alternatives, but achieved to different degrees. | Natural units (e.g., life-years gained, disability days saved, points of blood pressure reduction, etc.) |
Cost-utility analysis | Monetary units | Single or multiple effects, not necessarily common to both alternatives. | Healthy years (typically measured as quality-adjusted life-years) |
Source: [@drummond2015a]
Type of study | Measurement/Valuation of costs both alternative | Identification of consequences | Measurement / valuation of consequences |
---|---|---|---|
Cost analysis | Monetary units | None | None |
Cost-effectiveness analysis | Monetary units | Single effect of interest, common to both alternatives, but achieved to different degrees. | Natural units (e.g., life-years gained, disability days saved, points of blood pressure reduction, etc.) |
Cost-utility analysis | Monetary units | Single or multiple effects, not necessarily common to both alternatives. | Healthy years (typically measured as quality-adjusted life-years) |
Cost-benefit analysis | Monetary units | Single or multiple effects, not necessarily common to both alternatives | Monetary units |
\frac{\text{Cost (Intervention A) - Cost (Intervention B)}}{\text{Benefit (A) - Benefit (B)}}
Health Technology Advisory Committees
NICE (The National Institute for Health and Care Excellence, UK)
Canada’s Drug and Health Technology Agency
PBAC (Pharmaceutical Benefits Advisory Committee in Australia)
Brazil’s health technology assessment institute
Groups developing clinical guidelines
WHO
CDC
Disease-specific organizations: American Cancer Society; American Heart Association; European Stroke Organisation
Regulatory agencies:
FDA (U.S. Food and Drug Administration)
EPA (U.S. Environmental Protection Agency)
Decision modeling / economic evaluation requires identifying strategies or alternative courses of action.
These alternatives could include different therapies / policies / technologies.
Or, our alternatives could capture different combinations or sequences of treatment (e.g., what dose? what age to start?)
Once we have identified the alternatives, we’ll want to quantify their associated consequences in terms of:
Health outcomes
Costs
\frac{\text{Cost (Intervention A) - Cost (Intervention B)}}{\text{Benefit (A) - Benefit (B)}}
Source: Gold 1996, Drummond 2015, Gray 2012)
Identify – Estimate the different categories of resources likely to be required (e.g., surgical staff, medical equipment, surgical complications, re-admissions)
Measure – Estimate how much of each resource category is required (e.g. type of staff performing the surgery and time involved, post-surgery length of stay, re-admission rates)
Value – Apply unit costs to each resource category (e.g., salary scales from the relevant hospital or national wage rates for staff inputs, cost per inpatient day for the post-surgery hospital stay)
Direct Health Care Costs
Hospital, office, home, facilities
Medications, procedures, tests, professional fees
Direct Non-Health Care Costs
Time Costs
Productivity costs (‘indirect costs’)
impaired ability to work due to morbidity?
lost economic productivity due to death?
Unrelated healthcare costs
In practice, we count what is likely to matter
Any exclusion must be noted & possible bias examined
We are constrained by what data are available
Micro-costing (bottom-up)
Gross-costing (top-down)
Ingredients-based approach (P x Q x C)
Probability of occurrence (P)
Quantity (Q)
Unit costs (C)
PERSPECTIVE MATTERS –
Formal Healthcare Sector: Medical costs borne by third-party payers & paid for out-of-pocket by patients. Should include current + future costs, related & unrelated to the condition under consideration
Societal perspective: Represents the wider “public interest” & inter-sectoral distribution of resources that are important to consider - reflects costs on all affected parties
Healthcare sector perspective
MAMMOGRAPHY (Healthcare Sector):
Costs associated with the screening itself [mammogram procedure + physician time]
Costs of follow-up tests for both false-positive & true positive results
Downstream costs (or savings) associated with cases of breast cancer, such as: Hospitalization + treatment costs
Costs unrelated to medical intervention/disease; of living longer due to mammography
Societal perspective
MAMMOGRAPHY (Societal perspective):
Costs associated with the screening itself [mammogram procedure + physician time]
Costs of follow-up tests for both false-positive & true positive results
Downstream costs (or savings) associated with cases of breast cancer, such as: Hospitalization + treatment costs
Costs unrelated to medical intervention/disease; of living longer due to mammography
Patient productivity losses associated with the screening or cancer treatment
Childcare/transportation costs
(1) Alongside clinical trials
(2) Using secondary data
International versus US will have different approaches
https://cevr.tuftsmedicalcenter.org/databases/cea-registry
http://ghcearegistry.org/ghcearegistry/
Adjusting for currency and currency year
Discounting
$100 in 2000 is not equivalent to $100 in 2020
Important to adjust for the price difference over time, especially when working with cost sources from multiple years
Choose a reference year (usually the current year of analysis)
Convert all costs to the reference year
Converting cost in Year X to Year Y (reference year):
\textbf{Cost(Year Y)} = \textbf{Cost(Year X)} \times \frac{\textbf{Price index(Year Y)}}{\textbf{Price index(Year X)}}
Cost of hospitalization for mild stroke in the US was ~15,000 USD in 2016. What if we want to convert this number to 2020 USD?
PCE (Personal Consumption Expenditure Health Price Index) in 2016: 105.430 (second column of Table 3 (PCE, health)
PCE in 2020: 112.978
\textbf{Cost(2020)} = \textbf{Cost(2016)} \times \frac{\textbf{PCE(2020)}}{\textbf{PCE(2016)}} \\ = 15,000 \times \frac{112.978}{105.430} \\ = 16,674 \ (\text{2020 USD})
Isn’t required for CEA but may be useful in some situations:
How do we convert 1,000 Turkish Liras to USD?
Current exchange rate in 2024: 1 Turkish Lira = ~0.029 USD
1,000 Liras = 29 USD
Adjust costs at social discount rate to reflect social “rate of time preference”
Pure time preference (“inpatience”)
Potential catastrophic risk in the future
Economic growth/return
Inflation: We convert PAST cost to present-day values
Discounting: We convert FUTURE costs to present-day values
Present value: PV = FV/(1+r)^t
FV = future value, the nominal cost incurred in the future
r = annual discount rate (analogous to interest rate)
t = number of years in future when cost is incurred
Reasonable consensus around 3% per year
May vary according to country guidelines
Adjust for inflation and currency first, then discount
r = 0.03
Recall that PV = FV/(1+r)^t, and we’re at Year 0:
$1 in Year 0 is valued as 1/1.03^0 = \$ 1
$1 in Year 1 is valued as 1/1.03^1 = \$0.97
$1 in Year 2 is valued as 1/1.03^2 = \$0.94
$1 in Year 3 is valued as 1/1.03^3 = \$0.92
…
In other words, we are converting what a $1 would be in Year 2, for example, to the PRESENT VALUE of today. Today, it will be 0.94.