The Challenge of Conditional Reimbursement: Stopping Reimbursement Can Be More Difficult Than Not Starting in the First Place!
Open accessAbstract
Background Conditional reimbursement of new health technologies is increasingly considered as a useful policy instrument. It allows gathering more robust evidence regarding effectiveness and cost-effectiveness of new technologies without delaying market access. Nevertheless, the literature suggests that ending reimbursement and provision of a technology when it proves not to be effective or cost-effective in practice may be difficult. Objectives To investigate how policymakers and the general public in the Netherlands value removing a previously reimbursed treatment from the basic benefits package relative to not including a new treatment. Methods To investigate this issue, we used discrete-choice experiments. Mixed multinomial logit models were used to analyze the data. Compensating variation values and changes in probability of acceptance were calculated for withdrawal of reimbursement. Results The results show that, ceteris paribus, both the general public (n = 1169) and policymakers (n = 90) prefer a treatment that is presently reimbursed over one that is presently not yet reimbursed. Conclusions Apparently, ending reimbursement is more difficult than not starting reimbursement in the first place, both for policymakers and for the public. Loss aversion is one of the possible explanations for this result. Policymakers in health care need to be aware of this effect before engaging in conditional reimbursement schemes.
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Making withdrawing treatment similar to withholding treatment from a psychological point of view.
“which makes withdrawing treatment similar to withholding treatment from a psychological point of view [42, 44].”
From What influences the outcome of active disinvestment processes in healthcare? A qualitative interview study on five recent cases of active disinvestment (2021) · cites this paper as [42]
The Introduction (page unavailable) describes withholding reimbursement as maintaining the status quo and withdrawing it as a potential loss, calling the difference psychologically consequential. The Discussion (page unavailable) reports that stopping reimbursement seems more difficult than not starting it, contrary to the claimed psychological similarity. The paper studies reimbursement decisions rather than direct clinical withdrawal of treatment. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredWithdrawal of treatment has been described in the scientific literature as far less acceptable to actors than withholding treatment.
“which has been described in the scientific literature as far less acceptable to actors than withholding treatment [42, 44].”
From What influences the outcome of active disinvestment processes in healthcare? A qualitative interview study on five recent cases of active disinvestment (2021) · cites this paper as [42]
The Discussion says stopping reimbursement seems more difficult than not starting it, based on preferences among the Dutch general public and policymakers. But the study concerns reimbursement decisions, not withdrawal versus withholding of treatment itself; the Results also describe the differences in acceptance as small, so “far less acceptable” overstates the finding. (LLM, conf=0.88)
Experimental — accuracy not yet measuredConditional reimbursement has been proposed as a policy-tool to delay the final reimbursement decision, decreasing the uncertainty on the (cost-)effectiveness and/or budget-impact of new interventions, while making these interventions available to patients at an early stage.
“It has been proposed as a policy-tool to delay the final reimbursement decision, decreasing the uncertainty on the (cost-)effectiveness and/or budget-impact of new interventions, while making these interventions available to patients at an early stage [42, 43].”
From What influences the outcome of active disinvestment processes in healthcare? A qualitative interview study on five recent cases of active disinvestment (2021) · cites this paper as [42]
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Prospect Theory: An Analysis of Decision under Risk
Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524 · see citing works
Prospect theory: An analysis of decision under risk
Kahneman, D. J., & Tversky, A. (1988) · Cambridge University Press eBooks · doi:10.1017/cbo9780511609220.014 · Cited by 32,700 · see citing works
Applied choice analysis a primer
Hensher, D. A., Rose, J. M., & Greene, W. H. (2005) · Cited by 2,619 · see citing works
Hole, A. R., & Kolstad, J. R. (2011) · Empirical Economics · doi:10.1007/s00181-011-0500-1 · Cited by 371 · see citing works
Making Descriptive Use of Prospect Theory to Improve the Prescriptive Use of Expected Utility
Bleichrodt, H., Prades, J. L. P., & Wakker, P. P. (2001) · Management Science · doi:10.1287/mnsc.47.11.1498.10248 · Cited by 322 · see citing works
Resource allocation, social values and the QALY: a review of the debate and empirical evidence
Schwappach, D. L. B. (2002) · Health Expectations · doi:10.1046/j.1369-6513.2002.00182.x · Cited by 183 · see citing works
Lancsar, E., & Savage, E. (2004) · Health Economics · doi:10.1002/hec.870 · Cited by 160 · see citing works
Efficient stated choice experiments for estimating nested logit models
Bliemer, M. C. J., Rose, J. M., & Hensher, D. A. (2008) · Transportation Research Part B Methodological · doi:10.1016/j.trb.2008.05.008 · Cited by 151 · see citing works
van Exel, J. N. A., Baker, R. M., Mason, H., Donaldson, C., & Brouwer, W. B. F. (2014) · Social Science & Medicine · doi:10.1016/j.socscimed.2014.12.023 · Cited by 150 · see citing works
Self-citationCoverage with Evidence Development: An examination of conceptual and policy issues
Hutton, J., Trueman, P., & Henshall, C. (2007) · International Journal of Technology Assessment in Health Care · doi:10.1017/s0266462307070651 · Cited by 146 · see citing works
Walker, S., Sculpher, M., Claxton, K., & Palmer, S. (2012) · Value in Health · doi:10.1016/j.jval.2011.12.013 · Cited by 140 · see citing works
Stafinski, T., McCabe, C. J., & Menon, D. (2010) · PharmacoEconomics · doi:10.2165/11530820-000000000-00000 · Cited by 132 · see citing works
Deriving distributional weights for QALYs through discrete choice experiments
Lancsar, E., Wildman, J., Donaldson, C., Ryan, M., & Baker, R. M. (2011) · Journal of Health Economics · doi:10.1016/j.jhealeco.2011.01.003 · Cited by 107 · see citing works
Coverage with Evidence Development: Applications and issues
Trueman, P., Grainger, D. L., & Downs, K. E. (2010) · International Journal of Technology Assessment in Health Care · doi:10.1017/s0266462309990882 · Cited by 93 · see citing works
Bayesian and classical estimation of mixed logit: An application to genetic testing
Regier, D. A., Ryan, M., Phimister, E., & Marra, C. A. (2008) · Journal of Health Economics · doi:10.1016/j.jhealeco.2008.11.003 · Cited by 84 · see citing works
SIMILARITIES AND DIFFERENCES BETWEEN FIVE EUROPEAN DRUG REIMBURSEMENT SYSTEMS
Franken, M. G., Polain, M. L., Cleemput, I., & Koopmanschap, M. A. (2012) · International Journal of Technology Assessment in Health Care · doi:10.1017/s0266462312000530 · Cited by 75 · see citing works
Lancsar, E., Hall, J. P., King, M. T., Kenny, P. M., Louviere, J. J., Fiebig, D. G., Hossain, I., Thien, F. C. K., Reddel, H. K., & Jenkins, C. R. (2006) · Respirology · doi:10.1111/j.1440-1843.2006.01005.x · Cited by 69 · see citing works
Koopmanschap, M. A., Stolk, E. A., & Koolman, X. (2010) · International Journal of Technology Assessment in Health Care · doi:10.1017/s0266462310000048 · Cited by 68 · see citing works
Societal Preferences for Distributive Justice in the Allocation of Health Care Resources
Skedgel, C. D., Wailoo, A., & Akehurst, R. L. (2014) · Medical Decision Making · doi:10.1177/0272989x14547915 · Cited by 60 · see citing works
McHugh, N., Baker, R. M., Mason, H., Williamson, L., van Exel, J. N. A., Deogaonkar, R., Collins, M., & Donaldson, C. (2015) · BMC Medical Ethics · doi:10.1186/s12910-015-0008-x · Cited by 44 · see citing works
Are some QALYs more equal than others?
van de Wetering, E. J., van Exel, J. N. A., Rose, J. M., Hoefman, R., & Brouwer, W. B. F. (2014) · The European Journal of Health Economics · doi:10.1007/s10198-014-0657-6 · Cited by 42 · see citing works
Self-citationCoverage with evidence development: The Ontario experience
Levin, L., Goeree, R. A., Levine, M. N., Krahn, M. D., Easty, T., Brown, A., & Henry, D. A. (2011) · International Journal of Technology Assessment in Health Care · doi:10.1017/s0266462311000018 · Cited by 41 · see citing works
The National Oncologic PET Registry: Lessons Learned for Coverage With Evidence Development
Tunis, S., & Whicher, D. M. (2009) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2009.01.016 · Cited by 38 · see citing works
Conditional reimbursement within the Dutch drug policy
Niezen, M. G. H., de Bont, A., Stolk, E. A., Eyck, A., Niessen, L. W., & Stoevelaar, H. J. (2007) · Health Policy · doi:10.1016/j.healthpol.2006.11.005 · Cited by 26 · see citing works
Franken, M. G., Koopmanschap, M. A., & Steenhoek, A. (2014) · Zeitschrift für Evidenz Fortbildung und Qualität im Gesundheitswesen · doi:10.1016/j.zefq.2014.06.016 · Cited by 19 · see citing works
Franken, M. G., Gaultney, J. G., Blommestein, H. M., Huijgens, P. C., Sonneveld, P., Redekop, K., & Groot, C. A. U. (2014) · Value in Health · doi:10.1016/j.jval.2013.12.009 · Cited by 11 · see citing works
Spinks, J., & Mortimer, D. (2014) · Social Science & Medicine · doi:10.1016/j.socscimed.2014.11.049 · Cited by 7 · see citing works
Mortimer, D., Li, J. J., Watts, J. J., & Harris, A. (2011) · Health Economics Policy and Law · doi:10.1017/s1744133111000144 · Cited by 7 · see citing works
Menon, D., Stafinski, T., Nardelli, A., Jackson, T. J., & Jhamandas, J. H. (2011) · Healthcare Management Forum · doi:10.1016/j.hcmf.2011.02.008 · Cited by 7 · see citing works
Implications of heterogeneity in discrete choice analysis
Martínez-Cruz, A. L. (2013) · University Libraries (University of Maryland) · Cited by 1 · see citing works
Flagged first, then by citations
1 of the 31 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- [26]26. Train, K.E. Discrete Choice Methods with Simulation Cambridge University Press, Cambridge, UK, 2009 Crossref Scopus (495) Google Scholar
Cited by
Sorted by citations
Discrete Choice Experiments in Health Economics: Past, Present and Future
Soekhai, V., de Bekker-Grob, E. W., Ellis, A. R., & Vass, C. (2018) · PharmacoEconomics · doi:10.1007/s40273-018-0734-2 · Cited by 815 · see citing works
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Dabbous, M., Chachoua, L., Caban, A., & Toumi, M. (2020) · Value in Health · doi:10.1016/j.jval.2019.12.008 · Cited by 115 · see citing works
Koleva‐Kolarova, R., Buchanan, J., Vellekoop, H., Huygens, S. A., Versteegh, M., Mölken, M. R., Szilberhorn, L., Zelei, T., Nagy, B., Wordsworth, S., et al. (2022) · Applied Health Economics and Health Policy · doi:10.1007/s40258-021-00714-9 · Cited by 68 · see citing works
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Dias, C. Z., Godman, B., Gargano, L. P., Azevedo, P. S., Garcia, M. M., Cazarim, M. D. S., Pantuzza, L. L. N., Ribeiro, N. G., Pereira, A. L., Borin, M. C., et al. (2020) · PharmacoEconomics · doi:10.1007/s40273-020-00943-1 · Cited by 57 · see citing works
Michelsen, S., Nachi, S., Dyck, W. V., Simoens, S., & Huys, I. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.594446 · Cited by 54 · see citing works
Bonanno, P. V., Bucsics, A., Simoens, S., Martin, A. P., Oortwijn, W., Gulbinovič, J., Rothe, C. C., Timoney, A., Ferrario, A., Gad, M. M., et al. (2019) · Expert Review of Pharmacoeconomics & Outcomes Research · doi:10.1080/14737167.2019.1575730 · Cited by 48 · see citing works
Felgner, S., Ex, P., & Henschke, C. (2018) · Value in Health · doi:10.1016/j.jval.2018.03.006 · Cited by 46 · see citing works
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Time to reimbursement of novel anticancer drugs in Europe: a case study of seven European countries
Post, H. C., Schutte, T., van Oijen, M. G. H., van Laarhoven, H. W. M., & Hollak, C. E. M. (2023) · ESMO Open · doi:10.1016/j.esmoop.2023.101208 · Cited by 34 · see citing works
Rotteveel, A. H., Lambooij, M., Zuithoff, N. P. A., van Exel, J. N. A., Moons, K. G. M., & de Wit, G. A. (2020) · PharmacoEconomics · doi:10.1007/s40273-020-00890-x · Cited by 33 · see citing works
Enzing, J. J., Knies, S., Boer, B., & Brouwer, W. B. F. (2020) · Health Economics Policy and Law · doi:10.1017/s1744133120000237 · Cited by 33 · see citing works
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- Authors
- van de Wetering, E. J., van Exel, J., & Brouwer, W. B. F.
- Affiliations
- Erasmus University Rotterdam (NL)
- ORCID
- Brouwer, Werner B.F.
- Venue
- Value in Health
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 20
- Issue
- 1
- Pages
- 118-125
- ISSN
- 1098-3015 (ISSN-L)
- OpenAlex
- W2547499331
- Cited by
- 39
- References
- 31
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 7 · 2023: 3 · 2022: 8 · 2021: 6 · 2020: 9 · 2019: 1 · 2018: 2
- FWCI
- 1.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Value in Health (publishedVersion)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic and Environmental Valuation
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Pharmaceutical Economics and Policy
- Keywords
- conditional reimbursement, health technology assessment, loss aversion, public preferences, compensating variation, discrete choice experiment, mixed logit model, cost-effectiveness, market access
- MeSH terms
- Adolescent, Adult, Age Factors, Aged, Cost-Benefit Analysis, Decision Support Techniques, Educational Status, Female, Humans, Insurance, Health, Reimbursement, Male, Middle Aged, Netherlands, Public Opinion, Health Care Rationing, Quality-Adjusted Life Years, Young Adult, Policy
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