Background <p>Children with congenital colorectal conditions require care from multiple health professionals. However, evidence on the value of a multidisciplinary care model is lacking. This study aimed to elicit public preferences and willingness to pay for a multidisciplinary care model for children with congenital colorectal conditions.</p> Methods <p>We developed a discrete choice experiment (DCE) that was administered to 807 members of the Australian public online. A Bayesian D-efficient design consisting of 20 choice tasks was split into 2 blocks of 10 choice tasks per respondent. Five attributes elicited through mixed methods included make-up of the multidisciplinary team; responsibility for care coordination; duration of access; provision of educational information; and cost. Choice data were analysed with a panel error component mixed logit model. Willingness to pay for each DCE attribute and level was estimated using the unconditional population moments estimates.</p> Results <p>The Australian public demonstrated preference for a multidisciplinary care model. They showed preference for long-term access, having a care coordinator and provision of additional information. The public was willing to pay Australian dollars (AU) $64,275 for a multidisciplinary care model comprising an essential multidisciplinary team (including a surgeon, clinical nurse consultants, a psychologist, a social worker, stomal therapists, a child life therapist and a dietitian) with care coordination and information booklets and ongoing care until the child reached adulthood. We observed preference heterogeneity associated with gender, parenthood status and household income.</p> Conclusions <p>The Australian public valued the multidisciplinary care model for children with complex colorectal conditions. Our findings can be used to inform the design of a multidisciplinary care model and to inform cost–benefit analyses as part of broader healthcare system implementation.</p>

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Public Preferences and Willingness to Pay for a Multidisciplinary Colorectal and Pelvic Reconstruction Service

  • Tianxin Pan,
  • Misel Trajanovska,
  • Yan Meng,
  • Stephanie Best,
  • Sebastian K. King,
  • Ilias Goranitis

摘要

Background

Children with congenital colorectal conditions require care from multiple health professionals. However, evidence on the value of a multidisciplinary care model is lacking. This study aimed to elicit public preferences and willingness to pay for a multidisciplinary care model for children with congenital colorectal conditions.

Methods

We developed a discrete choice experiment (DCE) that was administered to 807 members of the Australian public online. A Bayesian D-efficient design consisting of 20 choice tasks was split into 2 blocks of 10 choice tasks per respondent. Five attributes elicited through mixed methods included make-up of the multidisciplinary team; responsibility for care coordination; duration of access; provision of educational information; and cost. Choice data were analysed with a panel error component mixed logit model. Willingness to pay for each DCE attribute and level was estimated using the unconditional population moments estimates.

Results

The Australian public demonstrated preference for a multidisciplinary care model. They showed preference for long-term access, having a care coordinator and provision of additional information. The public was willing to pay Australian dollars (AU) $64,275 for a multidisciplinary care model comprising an essential multidisciplinary team (including a surgeon, clinical nurse consultants, a psychologist, a social worker, stomal therapists, a child life therapist and a dietitian) with care coordination and information booklets and ongoing care until the child reached adulthood. We observed preference heterogeneity associated with gender, parenthood status and household income.

Conclusions

The Australian public valued the multidisciplinary care model for children with complex colorectal conditions. Our findings can be used to inform the design of a multidisciplinary care model and to inform cost–benefit analyses as part of broader healthcare system implementation.