Zeynep Ozdemir - CEU Assignment

8/2/2019 Zeynep Ozdemir - CEU Assignment

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Zeynep OZDEMIR SDA Bocconi - MIHMEP13 12.03.2012

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ECONOMIC EVALUATION - INDIVIDUAL ASSIGNMENT

Q1. Using the available data, calculate the Incremental Cost Effectiveness Ratio (ICER-

incremental cost per life year gained) and Incremental Cost Utility Ratio (ICUR- incremental

cost per QALY) of ICDs vs. conventional therapy in both primary and secondary prevention.

Discuss your results. What would you suggest to the Regional Health Authority?

The ICER & ICUR of ICDs vs CT are calculated based on the given data set. For the relevant

cost, life years gained and QALY calculations please see appendix.

For the ICER, the change in costs ( COSTS) are divided by the life years gained (LYG) for

secondary and primary care preventions:

Table 1. Incremental Cost-Effectiveness Ratios for Secondary and Primary Preventions

It would cost 43.787 / LYG if the ICD implantation is performed for secondaryprevention. If for primary prevention, this intervention would cost a higher amount,

58.215 / LYG. The ICERs are significantly high for both types of preventions, primary prevention

being more costly: Based on these ICER calculations, and assuming the data are

reliable and unbiased, an ICD intervention seems to be more cost-effective for

secondary than primary prevention.

However, to be able to make a proper and accurate decision, ICERs should beinterpreted with some other parameters, such as a threshold ICER accepted by the

authorities or a budget impact approach results; because this single ratio does not

mean a lot only by itself.

For example, assuming the threshold is 50.000/LYG (referring to the optionalquestion as an example), then we can claim that the ICD implementation should becovered only for the patients with a history of major cardiac event, aka secondary

recommendation, since primary preventions ICER is above the threshold meaning it

is not considered as cost effective.

For the ICUR, the change in costs ( COSTS) are divided by the change in QALYs ( QALYs) for

secondary and primary care preventions:


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Table 2. Incremental Cost-Utility Ratios for Secondary and Primary Preventions

The ICUR results are different from ICER results: It would cost 49.855 / QALY if theICD implantation is performed for secondary care prevention. If for primary care

prevention, this intervention would cost a higher amount, 57.005 / QALY.

The difference between the two analyses is because of the difference in LYG andQALYs, as the nominator, COSTS, is the same for both ratios.

For secondary care prevention, the ICUR is higher than ICER while for primary careprevention cost utility analysis provides a slightly lower ratio. The ICURs are significantly high for both types of preventions, primary care

prevention being more costly, as the ICERs.

Same with ICER interpretations, ICURs should be considered with other parametersas they do not provide any basis for decision making.

Assuming the same threshold for this analysis (50.000/QALY), as well, theconclusion will not change: The ICD implementation should be covered only for

secondary prevention purposes, its ICUR being slightly below the limit.

Q2. Show how the ICER and the ICUR vary in different patient groups defined by level of

risk (ejection fraction). Discuss your results.

Initially both ICER and ICURs are provided for the secondary and the overall primary

prevention, without considering the risk level of the patients who are undergoing the ICD

operation for primary prevention purposes. When these two groups are taken as crude, ICDs

are found to be cost effective only for secondary prevention purposes, according to the

threshold taken. However, when the sample of primary prevention interventions is stratified

according to the risk (Ejection Fraction-EF), the results vary significantly among different risk

groups.

Table 3. Incremental Cost-Effectiveness Ratios for Secondary and Primary Preventions; Primary Prevention is stratified by

the risk level of the patients


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As can be seen from the Table 3, primary prevention for high-risk patients (EF


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The two economic evaluation methods seem to be quite similar CUA is a special case of

CEA which uses QALYs in the denominator instead of LYG. Without stratification, the results

do not vary a lot. Nevertheless, when the stratification is performed, the difference between

ICERs and ICURs for medium- and low-risk patients within the primary prevention group is

remarkable: the medium-risk groups ICER is 1,37 times its ICUR, and low-risk groups ICER is2,5 times its ICUR (Table 3 & Table 4). The only difference in the calculations of these ratios

is the denominator: For ICER life years gained, for ICUR QALYs are used; meaning that

the different ratios are caused by the spread of LYG and QALYs.

As for this case, the method and the parameters used to provide information to

policymakers is important for every decision-making process. Different analyses delivering

different results may affect the whole interpretation and the decision made about the issue

that is being considered.

The alternative economic evaluation method to CEA/CUA is the Cost-Benefit Analysis (CBA),in which the outcomes are not measured by LYG or QALYs but in monetary terms as the

costs. In fact, CBA is theoretically more sophisticated and more comprehensive economic

evaluation method with its roots to welfare economics. For measuring benefits in terms of

prices in healthcare, willingness-to-pay approach has to be followed. By this approach,

non-health related benefits, such as the opportunity cost of waiting to see a doctor, can also

be addressed in CBA where CUA do not capture. On the other hand, there are some debates,

at policy making level, on how to measure health in monetary terms going on and there is a

lack of trust in CBA and willingness-to-pay approach, mainly due to the lack of understanding

the method itself and so the lack of trust on it.

For CUA, there are debates on the measurement of the quality of life, in other words

QALYs, since it is a very subjective measure. Moreover, it is already mentioned above that

CUA is less comprehensive than the other full-economic analysis, CBA, as it is incapable of

accounting non-health related benefits of the treatments. However, CUA has become the

golden standard in economic evaluation of health technology assessments recently due to

the fact that it takes not only quantity but also the quality of life into account (despite the

arguments on how quality is measured). CUA is further simple but not without

qualifications- and easy to grasp and apply. It enables the decision-makers to compare the

results with many other interventions as the unit of measure is standard and in QALYs for all

cases. It also avoids the income bias that CBA is claimed to be prone to.

In a nutshell, there are many pros and cons of both analyses. However, there are decisions

have to be made and a method should be agreed on for delivering results to the decision-

makers. For the sake of practicality and simplicity, cost-utility criterion is better. However, it

should be kept in mind that CBA is a more comprehensive analysis and if there is a way to

overcome the practical hurdles can be figured out, it might provide another basis for

decision making i.e. maybe with less emphasize in quality but capturing other non-health

related aspects of the intervention in question.


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4. Assume that implicit cost-effectiveness ratio limit accepted by Regional Health Authority

50.000 per QALY. What is the maximum price for which ICD would be considered cost-

effective in secondary prevention? In primary prevention?

In order to calculate the price limit for of the ICDs, the ICER formula should be solved for

ICD-implantation costs:

ICER = 50.000 =

Implant Price = (50.000 x QALYs) (Incremental Lifetime costs + Followup Costs)

The prices for each intervention category are calculated in the same way. The results are shown in

Table 5 below:

Table 5 Maximum price for ICDs, cost-effectiveness threshold given as 50.000

The prices of ICDs for medium- and low-risk patient groups are calculated asnegative, because they are highly above the cost-effectiveness threshold as alreadydiscussed in the previous questions.


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APPENDIX

1) Cost Calculations:I. ICD Implantation: This cost is relevant for the patients who had an ICD operation. The

calculations are done by simply multiplying each cost component with its price and

summing up the item costs:Table A6. ICD Implantation Costs

Since the patients treated with the conventional drug therapy are not subject to any

operation costs, it is taken as zero (0).

Thus, the incremental implantation cost equals the cost of operation itself;29.039,22/patient.

Note: This amount is quite similar to the amount that was assumed (30.000/patient)

during the pre-assessment talks by the Regional Health Authorities, meaning the

assumptions they made on this cost item was fairly reasonable.

II. Follow-up Costs: The general procedure of calculating the follow-up costs is the sameas of implantation costs: multiplying the number of services/products used by their

unit costs.

For daily costs, i.e. ICU days, ward days and nursing home days, the

calculations are slightly different. The cost of, for instance staying at the ICU is

calculated by the multiplication of the number of re-hospitalizations, days spend in


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ICU and the unit cost of a day in ICU. Same approach is followed for the ward days

and nursing home days cost:

Table A2. 1-year Follow-up Costs for ICD and CT patients

The incremental cost, in this case, is a negative number; meaning that ICD

implantation provides 2.439,56 of savings in the 1-year follow-up period per

patient.

III. Lifetime Costs: They are already given in the data set for each type of patients. Inorder to get the incremental lifetime costs, the difference between two therapies

cost is taken:

Table A3. Lifetime Costs for ICD and CT patients


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2) Life years gained: Already given in the data set (Life Years Added (LYA) by ICD):Table A4. Life Years Added (LYA) by ICD Implantation

3) QALYs:Table A5. Health Related Quality of Life Scores (EQ-5D)

For the CT, QALYs are calculated by multiplying the life expectancy (4,95 years for secondary

care prevention & 8,54 years for primary care prevention) and the corresponding health

related quality of life, HRQL score (0,73), which are given in the data set.

For the ICD implementation patients, the calculation has to be done in two steps: (1)

Temporary reduction in quality of life due to the post-operational adaptation period, which

is given as 2 months (aka 0,16 years) and (2) The lifetime quality of life after the adaptation

period.

For the first step, the temporary HRQL score is multiplied with the correspondingperiod:

0,68*0,16 years = 0,1088

For the second step, the lifetime HRQL score is multiplied with the remaining life-time:

For secondary care prevention; 0,77*(6,64-0,16) years = 4,99

For primary care prevention; 0,77*(9,84-0,16) years = 7,45

Then, the results are summed up.The final calculations are given in the table below, with the incremental QALYs on the

bottom row:

Table A6. QALYs

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