Introduction
Identifying and addressing neurodevelopmental delays in children can be challenging for families and the healthcare system. Delays in accessing services and early interventions are common. The design and delivery of these services, and associated outcomes for children, may be improved if service provision aligns with families’ needs and preferences for receiving care. The aim of this study is to identify families’ preferences for neurodevelopmental follow-up care for children using an established methodology.
Methods
We used a discrete choice experiment (DCE) to elicit families’ preferences. We collected data from families and caregivers of children with neurodevelopmental needs. The DCE process included four stages. In stage 1, we identified attributes and levels to be included in the DCE using literature review, interviews, and expert advice. The finalised attributes were location, mode of follow-up, out-of-pocket cost per visit, mental health counselling for parents, receiving educational information, managing appointments, and waiting time. In stage 2, we generated choice tasks that contained two alternatives and a ‘neither’ option for respondents to choose from, using a Bayesian
d-
efficient design. These choice tasks were compiled in a survey that also included demographic questions. We conducted pre- and pilot tests to ensure the functionality of the survey and obtain priors. In stage 3, the DCE survey was administered online. We received 301 responses. In stage 4, the analysis was conducted using a latent class model. Additionally, we estimated the relative importance of attributes and performed a scenario analysis.
Results
Two latent classes were observed. More families with full-time employees, higher incomes, postgraduate degrees, and those living in metropolitan areas were in class 1 compared with class 2. Class 1 families preferred accessing local public health clinics, face-to-face follow-up, paying AUD100 to AUD500, mental health support, group educational activities, health service-initiated appointments, and waiting < 3 months. Class 2 families disliked city hospitals when compared with private, preferred paying AUD100 or no cost, and had similar preferences regarding mental health support and wait times as class 1. However, no significant differences were noted in follow-up modality, receiving educational information, and appointment management. The relative importance estimation suggested that location was most important for class 1 (28%), whereas for class 2, cost accounted for nearly half of the importance when selecting an alternative. The expected uptake of follow-up care, estimated under three different hypothetical scenarios, may increase by approximately 24% for class 2 if an ‘ideal’ scenario taking into account preferences was implemented.
Conclusion
This study offers insights into aspects that may be prioritised by health services and policyma...
