Societal preferences for prioritizing patients suffering from breast cancer, deafness, or knee arthrosis for scarce surgical capacity
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective Constraints on surgical capacity due to budgetary and workforce shortages necessitate prioritization. Lessons learned from the COVID-19 pandemic emphasize the societal debate around these decisions and stress the need to align decisions with societal preferences. This study examines societal preferences for prioritizing patients with three conditions—breast cancer, deafness, or knee arthrosis—for scarce surgical capacity. Methods We conducted a labelled discrete choice experiment among 1,046 members of the Dutch public. Respondents completed 14 choice tasks in which they prioritized patients for surgery, based on their condition, age, health-related quality of life (HRQOL) before and after surgery, and waiting time until surgery. We used conditional logit, multinomial logit, and latent class models to examine (heterogeneity in) respondents’ preferences. Results Respondents were more likely to prioritize patients suffering from breast cancer over those with knee arthrosis or deafness. They also prioritized patients with lower levels of HRQOL before surgery, larger surgery-related increases in HRQOL, and longer waiting times. They were less likely to prioritize patients who were older, except in the case of deafness. Observed preference heterogeneity largely resulted from differences in preference strength, rather than direction. Conclusions Our results provide insight into societal preferences for prioritizing patients with different conditions for surgery. This insight aids in understanding public outcry that may follow deviating decisions. Aligning prioritization decisions with societal preferences may increase the legitimacy of such decisions. Further research may examine the relevance of these preferences for physicians and their willingness to be guided by evidence on societal preferences.
Source: Health Policy and Technology
Institutions: Erasmus University Rotterdam, Zorginstituut Nederland
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,000
Funder: Zorginstituut Nederland
OpenAlex ID: W4409911629
