Skip to main content
Top
Published in: The Patient - Patient-Centered Outcomes Research 5/2018

01-10-2018 | Commentary

Key Issues and Potential Solutions for Understanding Healthcare Preference Heterogeneity Free from Patient-Level Scale Confounds

Authors: Catharina G. M. Groothuis-Oudshoorn, Terry N. Flynn, Hong Il Yoo, Jay Magidson, Mark Oppe

Published in: The Patient - Patient-Centered Outcomes Research | Issue 5/2018

Login to get access

Excerpt

Healthcare is becoming increasingly personalized. For instance, the US FDA attempts to incorporate patient preferences into regulatory decision making and is willing to approve treatments even if the benefit–risk profile is acceptable only to a segment of risk-tolerant patients [1]. Countries with extra-welfarist healthcare systems (relying on population preferences) now recognize that heterogeneity in individual preferences may be important conceptually in addressing issues such as child health, social care-related quality of life and carer well-being. …
Literature
5.
go back to reference McFadden D. Conditional logit analysis of qualitative choice behavior. In: Zarembka P, editor. Front Econom. New York: Academic Press; 1974. p. 105–42. McFadden D. Conditional logit analysis of qualitative choice behavior. In: Zarembka P, editor. Front Econom. New York: Academic Press; 1974. p. 105–42.
6.
go back to reference Kamakura WA, Russell G. A probabilistic choice model for market segmentation and elasticity structure. J Mark Res. 1989;26:379–90.CrossRef Kamakura WA, Russell G. A probabilistic choice model for market segmentation and elasticity structure. J Mark Res. 1989;26:379–90.CrossRef
8.
go back to reference McFadden D, Train K. Mixed MNL models of discrete response. J Appl Econ. 2000;15:447–70.CrossRef McFadden D, Train K. Mixed MNL models of discrete response. J Appl Econ. 2000;15:447–70.CrossRef
9.
go back to reference Fiebig D, Keane M, Louviere J, Wasim N. The generalized multinomial logit model: accounting for scale and coefficient heterogeneity. Mark Sci. 2010;29:393–421.CrossRef Fiebig D, Keane M, Louviere J, Wasim N. The generalized multinomial logit model: accounting for scale and coefficient heterogeneity. Mark Sci. 2010;29:393–421.CrossRef
10.
go back to reference Yatchew A, Griliches Z. Specification error in probit models. Rev Econ Stat. 1985;67:134–9.CrossRef Yatchew A, Griliches Z. Specification error in probit models. Rev Econ Stat. 1985;67:134–9.CrossRef
11.
go back to reference Hensher DA, Louviere J. Combining sources of preference data. J Econ. 1999;89:197–221.CrossRef Hensher DA, Louviere J. Combining sources of preference data. J Econ. 1999;89:197–221.CrossRef
13.
go back to reference Magidson J, Vermunt JK. Removing the scale factor confound in multinomial logit choice models to obtain better estimates of preference. In: Sawtooth Software Conference. Sequim, WA; 2007. pp. 139–54. Magidson J, Vermunt JK. Removing the scale factor confound in multinomial logit choice models to obtain better estimates of preference. In: Sawtooth Software Conference. Sequim, WA; 2007. pp. 139–54.
14.
go back to reference Mardia KV, Kent JT, Bibby JM. Cluster analysis. Multivar Anal. London: Academic Press; 1979. p. 360–93. Mardia KV, Kent JT, Bibby JM. Cluster analysis. Multivar Anal. London: Academic Press; 1979. p. 360–93.
15.
go back to reference Van den Bergh M, van Kollenburg GH, Vermunt JK. Deciding on the starting number of classes of a latent class tree. Sociol Methodol. 2018 (in press). Van den Bergh M, van Kollenburg GH, Vermunt JK. Deciding on the starting number of classes of a latent class tree. Sociol Methodol. 2018 (in press).
16.
go back to reference Hole AR, Yoo HI. The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models. J R Stat Soc Ser C. 2017;66:997–1013.CrossRef Hole AR, Yoo HI. The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models. J R Stat Soc Ser C. 2017;66:997–1013.CrossRef
17.
go back to reference Louviere J, Flynn TN, Marley AAJ. Best-worst scaling: theory, methods and applications. 1st ed. Cambridge: Cambridge University Press; 2015.CrossRef Louviere J, Flynn TN, Marley AAJ. Best-worst scaling: theory, methods and applications. 1st ed. Cambridge: Cambridge University Press; 2015.CrossRef
19.
go back to reference Vermunt JK, Magidson J. Technical Guide for Latent Gold 5.1: Basic, Advanced, and Syntax. Belmont: Statistical Innovations Inc.; 2016. Vermunt JK, Magidson J. Technical Guide for Latent Gold 5.1: Basic, Advanced, and Syntax. Belmont: Statistical Innovations Inc.; 2016.
Metadata
Title
Key Issues and Potential Solutions for Understanding Healthcare Preference Heterogeneity Free from Patient-Level Scale Confounds
Authors
Catharina G. M. Groothuis-Oudshoorn
Terry N. Flynn
Hong Il Yoo
Jay Magidson
Mark Oppe
Publication date
01-10-2018
Publisher
Springer International Publishing
Published in
The Patient - Patient-Centered Outcomes Research / Issue 5/2018
Print ISSN: 1178-1653
Electronic ISSN: 1178-1661
DOI
https://doi.org/10.1007/s40271-018-0309-5

Other articles of this Issue 5/2018

The Patient - Patient-Centered Outcomes Research 5/2018 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine