What public health interventions do people in Canada prefer to fund? A discrete choice experiment

Public preferences for the allocation of societal resources over different healthcare purposes

OBJECTIVE

Increasing healthcare expenditures require governments to make difficult prioritization decisions. Considering public preferences can help raise citizens' support. Previous research has predominantly elicited preferences for the allocation of public resources towards specific treatments or patient groups and principles for resource allocation. This study contributes by examining public preferences for budget allocation over various healthcare purposes in the Netherlands.

METHODS

We conducted a Participatory Value Evaluation (PVE) choice experiment in which 1408 respondents were asked to allocate a hypothetical budget over eight healthcare purposes: general practice and other easily accessible healthcare, hospital care, elderly care, disability care, mental healthcare, preventive care by encouragement, preventive care by discouragement, and new and better medicines. A default expenditure was set for each healthcare purpose, based on current expenditures. Respondents could adjust these default expenditures using sliders and were presented with the implications of their adjustments on health and well-being outcomes, the economy, and the healthcare premium. As a constraint, the maximum increase in the mandatory healthcare premium for adult citizens was €600 per year. The data were analysed using descriptive statistics and a Latent Class Cluster Analysis (LCCA).

RESULTS

On average, respondents preferred to increase total expenditures on all healthcare purposes, but especially on elderly care, new and better medicines, and mental healthcare. Three preference clusters were identified. The largest cluster preferred modest increases in expenditures, the second a much higher increase of expenditures, and the smallest favouring a substantial reduction of the healthcare premium by decreasing the expenditure on all healthcare purposes. The analyses also demonstrated substantial preference heterogeneity between clusters for budget allocation over different healthcare purposes.

CONCLUSIONS

The results of this choice experiment show that most citizens in the Netherlands support increasing healthcare expenditures. However, substantial heterogeneity was identified in preferences for healthcare purposes to prioritize. Considering these preferences may increase public support for prioritization decisions.

Continuing medical education in China: evidence from primary health workers' preferences for continuing traditional Chinese medicine education

BACKGROUND

Continuing Medical Education (CME) is an important part of the training process for health workers worldwide. In China, training in Traditional Chinese Medicine (TCM) not only improves the expertise of medical workers, but also supports the Chinese Government's policy of promoting TCM as an equal treatment to western medicine. CME, including learning Traditional Chinese Medicine Technologies (TCMTs), perform poorly and research into the motivation of health workers to engage in CME is urgently required. Using a discrete choice experiment, this study assessed the CME learning preferences of primary health workers, using TCMT as a case study of CME programs.

METHODS

We conducted a discrete choice experiment among health workers in Shandong Province, Guizhou Province, and Henan provinces from July 1, 2021 to October 1, 2022 on the TCMT learning preferences of primary health workers. The mixed logit model and latent class analysis model were used to analyze primary health workers' TCMT learning preferences.

RESULTS

A total of 1,063 respondents participated in this study, of which 1,001 (94.2%) passed the consistency test and formed the final sample. Our key finding was that there were three distinct classes of TCMT learners. Overall, the relative importance of the seven attributes impacting the learning of TCMTs were: learning expenses, expected TCMT efficacy, TCMT learning difficulty, TCMT mode of learning, TCMT type, time required to learn, and expected frequency of TCMT use. However, these attributes differed significantly across the three distinct classes of TCMT learners. Infrequent users (class 1) were concerned with learning expenses and learning difficulty; workaholics (class 2) focused on the mode of learning; and pragmatists (class 3) paid more attention to the expected TCMT efficacy and the expected frequency of TCMT use. We recommend targeted strategies to motivate TCMT learning suited to the requirements of each class of TCMT learners.

CONCLUSION

Rather than a single TCMT medical education program for primary health workers, CME programs should be targeted at different classes of TCMT learners.