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Using Conjoint Analysis to Model the Preferences of Different Patient Segments for Attributes of Patient-Centered Care

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Abstract

Background: A consensus regarding the components of a patient-centered approach to healthcare does not exist. Although patient-centered care should be predicated on patient preferences, existing models provide little evidence regarding the relative importance of different care processes to patients themselves.

Objective: To involve patients in the design of a model of patient-centered care for a corporation of Canadian teaching hospitals.

Methods: Using themes from focus groups and interviews, a conjoint survey was developed comprising 14 four-level patient-centered care attributes. Sawtooth Software’s Choice Based Conjoint module (version 2.6.7) was used to design the survey. Each participant completed 15 choice tasks, each task presenting a choice between three hospitals described by a different combination of patient-centered care attribute levels. Latent class analysis was used to identify segments of participants with similar patient-centered care choice patterns. Randomized First Choice simulations were used to predict the percentage of participants in each segment who would choose different approaches to improving patient-centered care.

Representative hospital service users were recruited from a corporation of five Canadian teaching hospitals serving a regional population of 2.2 million.

Results: A total of 508 patients and family members of children completed a choice-based conjoint survey. Latent class analysis revealed two segments: an informed care segment and a convenient care segment. Participants in the informed care segment (71.3% of the sample) were more likely to have higher education, be non-immigrants, speak English as a first language, and be outpatients or family members.

The information needed to understand health concerns, an opportunity to learn health improvement skills, teams that communicated effectively, short waiting times, and collaborative treatment planning were more important to the informed care segment than to the convenient care segment. Convenient settings, a welcoming environment, and ease of internal access exerted a greater influence on the choices made by the convenient care segment. Both segments preferred hospitals that provided health information and gave prompt feedback on patient progress.

Conclusions: This study suggests that many patients would exchange an increase in waiting times for prompt feedback, information, and the skills to improve their health.

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Notes

  1. Briefly, Hierarchical Bayes estimates the vector of mean population betas, the matrix of population beta covariances, and the vector of betas for each respondent by drawing from two distributions: (i) a prior distribution drawn from a multivariate Normal distribution, and (ii) a posterior distribution based on a multinomial logit model derived from actual responses.[43] Using an iterative three-step (Gibbs sampling) process and Methopolis Hastings Algorithm,[46] the program re-estimates one set of parameters (α, D, or the betas) conditionally, given current values for the other two sets.[43] Using default estimates of beta and alpha, we computed 2000 burn-in iterations before convergence was assumed. We computed 12 000 iterations, accepting 1000 draws per respondent with a skip factor of 10 to increase the independence of draws and improve the precision of our estimates.

  2. The IIA problem is a property of logit models that results in unrealistic share predictions when highly similar attribute options compete with very different attribute options. To stabilize our share of preference estimates, we computed 100 000 sampling iterations.

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Acknowledgements

This project was supported by the Jack Laidlaw Chair in Patient-Centered Health Care, a Contribution Agreement from CANARIE Inc., and the Institute for Knowledge Innovation and Technology (IKIT) at the University of Toronto. The authors acknowledge the support of the Hamilton Health Sciences’ Patient-Centered Care Task Force. At the time of publication, H. Campbell is employed by the College of Nurses of Ontario, A. Russell is employed by the Michener Institute for Applied Health Sciences, and B. Melnick is employed by Atlantis Systems Corporation.

The authors have no conflicts of interest that are directly relevant to the content of this study.

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Authors and Affiliations

  1. Department of Psychiatry and Behavioural Neurosciences, Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada

    Charles E. Cunningham & Heather Rimas

  2. Hamilton Health Sciences, Hamilton, Ontario, Canada

    Charles E. Cunningham, Heather Campbell, Jennifer Henderson & Anne Matheson

  3. Strategic Market Leadership and Health Services Management, DeGroote School of Business, McMaster University, Hamilton, Ontario, Canada

    Ken Deal

  4. Institute for Knowledge Innovation and Technology (IKIT), University of Toronto, Toronto, Ontario, Canada

    Ann Russell & Blake Melnick

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  1. Charles E. Cunningham
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Cunningham, C.E., Deal, K., Rimas, H. et al. Using Conjoint Analysis to Model the Preferences of Different Patient Segments for Attributes of Patient-Centered Care. Patient-Patient-Centered-Outcome-Res 1, 317–330 (2008). https://doi.org/10.2165/1312067-200801040-00013

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