Exploring the Cost Effectiveness of Shared Decision Making for Choosing between Disease-Modifying Drugs for Relapsing-Remitting Multiple Sclerosis in the Netherlands: A State Transition Model

Ingrid E. H. Kremer, Mickael Hiligsmann, Josh Carlson, Marita Zimmermann, Peter J. Jongen, Silvia M. A. A. Evers, Svenja Petersohn, Xavier G. L. V. Pouwels and Nick Bansback
Additional contact information
Ingrid E. H. Kremer: Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, Limburg, The Netherlands
Mickael Hiligsmann: Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, Limburg, The Netherlands
Josh Carlson: Department of Pharmacy, University of Washington, Seattle, WA, USA
Marita Zimmermann: Institute for Disease Modeling, Bellevue, WA, USA
Peter J. Jongen: MS4 Research Institute, Nijmegen, The Netherlands
Silvia M. A. A. Evers: Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, Limburg, The Netherlands
Svenja Petersohn: Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Centre, Maastricht, Limburg, The Netherlands
Xavier G. L. V. Pouwels: Department of Health Technology & Services Research, Faculty of Behavioral, Management & Social Sciences, University of Twente, Enschede, The Netherlands
Nick Bansback: School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada

Medical Decision Making, 2020, vol. 40, issue 8, 1003-1019

Abstract: Background Up to 31% of patients with relapsing-remitting multiple sclerosis (RRMS) discontinue treatment with disease-modifying drug (DMD) within the first year, and of the patients who do continue, about 40% are nonadherent. Shared decision making may decrease nonadherence and discontinuation rates, but evidence in the context of RRMS is limited. Shared decision making may, however, come at additional costs. This study aimed to explore the potential cost-effectiveness of shared decision making for RRMS in comparison with usual care, from a (limited) societal perspective over a lifetime. Methods An exploratory economic evaluation was conducted by adapting a previously developed state transition model that evaluates the cost-effectiveness of a range of DMDs for RRMS in comparison with the best supportive care. Three potential effects of shared decision making were explored: 1) a change in the initial DMD chosen, 2) a decrease in the patient’s discontinuation in using the DMD, and 3) an increase in adherence to the DMD. One-way and probabilistic sensitivity analyses of a scenario that combined the 3 effects were conducted. Results Each effect separately and the 3 effects combined resulted in higher quality-adjusted life years (QALYs) and costs due to the increased utilization of DMD. A decrease in discontinuation of DMDs influenced the incremental cost-effectiveness ratio (ICER) most. The combined scenario resulted in an ICER of €17,875 per QALY gained. The ICER was sensitive to changes in several parameters. Conclusion This study suggests that shared decision making for DMDs could potentially be cost-effective, especially if shared decision making would help to decrease treatment discontinuation. Our results, however, may depend on the assumed effects on treatment choice, persistence, and adherence, which are actually largely unknown.

Keywords: disease-modifying drugs; early economic evaluation; multiple sclerosis; shared decision making; state transition model (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X20961091 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:40:y:2020:i:8:p:1003-1019

DOI: 10.1177/0272989X20961091

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().