Questionnaire

Thank you for taking the time to fill in this questionnaire.

The first part of the questionnaire contains publication specificquestions concerning the challenges that you may have experienced during the development of the model where the publication is based on. The second part of the questionnaire contains general questions concerning challenges that you may have experienced during the modelling process of any cardiovascular diseaseintervention.

General information:

Selected corresponding author:

Selected publication:

Part 1

This part of the questionnaire focusses on the challenges that arose while creating the model where the selected publication is based on.

General questions

Q1:Please confirm the details on the interventionsof your publication provided in Table 1 below. Please correct if the details are incorrect

Table 1: Interventions
Short description of the interventions / Type of intervention / Correct?(Q1)
1 / Choose an item. /
2 / Choose an item. /
3 / Choose an item. /
4 / Choose an item. /

Q2: Please confirm the details on the comparators of your publication provided in Table 2 below. Please correct if the details are incorrect

Table 2: Comparators
Short description of the comparators / Type of intervention / Correct?(Q2)
1 / Choose an item. /
2 / Choose an item. /
3 / Choose an item. /
4 / Choose an item. /

Challenges data requirements -solved

Q3:Describe a maximum of 5 major solved challenges concerning data requirements that arose while creating the economic model. Please provide the short descriptionsin Table 3

Q4: Please indicate in Table 3how important the challengeis; i.e. the impact of the challenge on the ICER

Table 3: Solved challenges - Data requirement
Short description(Q3) / Importance (Q4): impact on the ICER
No impact: 0 / 1 / 2 / 3 / Strong impact:
4
1 / / / / /
2 / / / / /
3 / / / / /
4 / / / / /
5 / / / / /

Q5: Please provide the details concerning the solutions for the data requirement challenges that were solved. Please do this in Table 4

Q6:Please provide in Table 4the sources(if available) that were used to solve the challenges

Table 4: Solved challenges- Data requirement
Challenge / Solution to solved challenges (Q5) / Reference or inspiration (Q6)
1
2
3
4
5

Challenges data requirements -unsolved

Q7:Describe a maximum of 5 major unsolved challenges concerning data requirementthat arose while creating the economic model. Unsolved challenges imply also the use of assumptions that were necessary to evaluate the intervention. Please provide the short descriptions in Table 5

Q8: Please indicate in Table 5how important the challenge is; i.e. the impact of the challenge on the ICER

Table 5: Unsolved challenges - Data requirement
Description(Q7) / Importance (Q8): impact on the ICER
No impact: 0 / 1 / 2 / 3 / Strong impact:
4
1 / / / / /
2 / / / / /
3 / / / / /
4 / / / / /
5 / / / / /

Q9: Please provide reasons why the challenges wereunsolved. Please do this in Table 6

Table 6: Unsolved challenges- Data requirement
Challenge / Reason for not solving challenge (Q9)
1
2
3
4
5

Challenges modelling methods - solved

Q10: Please describe a maximum of 5 major solved challenges concerning modelling (e.g. structure or extrapolation) that arose while creating the economic model.Please provide the short descriptions in Table 7

Q11: Please indicate in Table 7 how important the challenge is;i.e. the impact of the challenge on the ICER.

Table 7: Solved challenges - Modelling
Description (Q10) / Importance (Q11): impact on the ICER
No impact: 0 / 1 / 2 / 3 / Strong impact:
4
1 / / / / /
2 / / / / /
3 / / / / /
4 / / / / /
5 / / / / /

Q12:Please provide inTable 8the details concerning the solutions for the modelling challenges that weresolved

Q13: Please provide in Table 8the sourcesif available where the solutions of the challenges are based on

Table 8: Solved challenges- Modelling
Challenge / Solution to solved challenges (Q12) / Reference or inspiration (Q13)
1
2
3
4
5

Challenges modelling methods - unsolved

Q14: Describe max 5 major unsolved challenges concerning modelling that arose while creating the economic model. Unsolved challenges imply also the use of assumptions that were necessary to evaluate the intervention. Please provide the short descriptions in Table 9

Q15: Please indicate in Table 9how important the challenge is; i.e. the impact of the challenge on the ICER.

Table 9: Unsolved challenges - Modelling
Description (Q14) / Importance (Q15): impact on the ICER
No impact: 0 / 1 / 2 / 3 / Strong impact:
4
1 / / / / /
2 / / / / /
3 / / / / /
4 / / / / /
5 / / / / /

Q16: Please provide in Table 10reasons why the challenges were unsolved.

Table 10: Unsolved challenges- Modelling
Challenge / Reason for not solving challenge (Q16)
1
2
3
4
5

Part 2

This part focusses on the challenges that you may have experienced during any cardiovascular disease intervention modelling study.Thus this includes both the selected study and other modelling studies estimating the cost-effectiveness of cardiovascular disease interventions.

Challenges regarding data requirements

Q17:Table 11shows a list of data requirement challenges(solved or unsolved) which were identified by other authors with experience in modelling cardiovascular disease interventions. Please indicate how frequent a challenge is in that specific category (type of intervention). If you have never performed analyses for a specific type of intervention please use the “not applicable” option. Furthermore, if you find that certain challenges are not included in this list,please add them at the bottom of this list and briefly describe them.

Q18: Please rank in Table 11the challenges that were presentin order of importance; i.e. the impact of the challenge on the ICER and the frequency.

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Table 11: Challenges - Data requirements
Subject / Description / Q17:Frequency (% of performed studies) / Q18
NA / 0-10% / 11-30% / 31-70% / 70-100% / Rank
Estimating a sufficiently valid, precise and accurate estimate of cost-effectiveness was a challenge ………
All types of interventions
1 / Lack of data (efficacy) / …. sincea limited amount of treatment effectiveness data were available. / / / / /
2 / Lack of data (quality of life) / …. sincea limited amount of quality of life data were available. / / / / /
3 / Lack of data (adverse events) / …. sincea limited amount of adverse events data were available. / / / / /
4 / Lack of data (unit costs) / …. sincea limited amount of unit cost data were available. / / / / /
5 / Lack of data (resource use) / …. since a limited amount of resource use data were available. / / / / /
6 / Lack of data (indirect costs) / …. since a limited amount of e.g. productivity data were available. / / / / /
7 / Missing values / …. because of missing values of important input parameters. / / / / /
8 / Input parameters distributions / …. since distributions of input parameters could not be estimated / / / / /
9 / Combining literature / …. since it was difficult to combine literature that is conflicting or is based on different populations / / / / /
Other data requirement challenges?

Challenges modelling

Q19:Table 12shows a list of modelling challenges(solved or unsolved) which were identified by other authors with experience in modelling cardiovascular disease interventions. Please indicate how frequent a challenge is in that specific category (type of intervention). If you have never performed analyses for a specific type of intervention please use the “not applicable” option. Furthermore, if you find that certain challenges are not included in this list,please add them at the bottom of this list and briefly describe them

Q20: Please rank in Table 12the challenges that were presentin order of importance; i.e. the impact of the challenge on the ICER and frequency

Table 12: Challenges - Modelling
Subject / Description / Q19:Frequency (% of performed studies) / Q20
NA / 0-10% / 11-30% / 31-70% / 70-100% / Rank
Estimating a sufficiently valid, precise and accurate estimate of cost-effectiveness was a challenge ………
All interventions
1 / Model structure / …. because it was difficult to determine the right model structure to incorporate all differences in costs and effects between interventions. E.g. unclear disease framework / / / / /
2 / Time horizon / …. because it was difficult to determine the right length of the time horizon (and in case of e.g. Markov modelling the cycle length) to incorporate all differences in costs and effects between interventions / / / / /
3 / Care pathway / …. because it was difficult to model the care pathway appropriately due to e.g. treatment variation between countries/physicians / / / / /
4 / Comparators / …. because it was difficult to include all possible comparators since the data did not include all treatment options (e.g. RCT intervention vs. placebo) / / / / /
5 / Population / …. because it was difficult to incorporate heterogeneity into the model / / / / /
6 / History / …. because it was difficult to build a model that incorporates memory/history (e.g. screening history or experienced event) / / / / /
7 / Extrapolation short term results / …. because it was difficult to extrapolate RCT results into long term outcomes / / / / /
8 / Competing risks / …. because it was difficult to estimate valid transition probabilities due to competing risks (patients are at risk of more than one mutually exclusive events) / / / / /
9 / Use of existing models / …. because it was difficult to use an existing model or combine(several) existing models developed for another decision problem / / / / /
10 / (probabilistic) Sensitivity analysis / --- because it was difficult to determine how many inner/outer loops for patient level simulation models are necessary / / / / /
Subject / Description / Q19: Frequency (% of performed studies) / Q20
NA / 0-10% / 11-30% / 31-70% / 70-100% / Rank
Estimating a sufficiently valid, precise and accurate estimate of cost-effectiveness was a challenge ………
11 / Interacting clinical outcomes / …. because it was difficult to model the cost-effectiveness of an intervention that has an effect on two different clinical outcomes that also interact with each other / / / / /
12 / Scenario analyses / … since it was difficult to decide which scenario analyses need to be performed / / / / /
13 / Productivity costs / …. because it was difficult to incorporate productivity costs into the model / / / / /
Test interventions
9 / Extrapolation intermediate outcomes / …. because it was difficult to extrapolate intermediate outcomes such as test results (sensitivity, specificity) into long term outcomes (QALYs) / / / / /
10 / Multiple testing / …. because it was difficult to model strategies involving a combination of tests or dynamic strategies (repeated testing) / / / / /
11 / Lead time bias / …. because it was difficult to incorporate lead time bias (early diagnosis falsely appears to prolong survival) / / / / /
12 / Length time bias / …. because it was difficult to incorporate length time bias (screening preferentially identifies slowlyprogressingdisease) / / / / /
Tests & non-drug interventions
13 / Waittime and capacity constraints / …. because it was difficult to include waittime or capacity constraints of an intervention into the model / / / / /
14 / Learning curve / ….because it was difficult to incorporate learning curves (patients and/or physicians) for procedures or devices / / / / /
15 / Reusability / …. because it was difficult to model reusability of interventions (CT, MRI, cardiac monitoring). Thus interventions can be used in more than one patient / / / / /
Subject / Description / Q19: Frequency (% of performed studies) / Q20
NA / 0-10% / 11-30% / 31-70% / 70-100% / Rank
Estimating a sufficiently valid, precise and accurate estimate of cost-effectiveness was a challenge ………
Non-drug intervention
16 / Relevance of process utilities / …. because it was difficult to include ease, comfort of use or the unpleasantness of an device or invasive procedure / / / / /
Tests, drug interventions & non-drug intervention
17 / Multiple indications / …. because it was difficult to evaluate an intervention for all indications since it can be used for multiple indications (e.g. CT scanner used for CVD or lung diseases) / / / / /
Drug interventions & disease management programs
17 / Compliance / …. because it was difficult to incorporate compliance into the model / / / / /
Disease management programs
18 / Intervention effectiveness / …. because it was difficult to combine the individual effectiveness of several interventions as a whole / / / / /
Other modelling challenges?

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Thanks for your participation!

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