TY - JOUR
T1 - Health service design with conjoint optimization
AU - Wang, Xinfang
N1 - Publisher Copyright:
© 2019, © 2019 Operational Research Society.
PY - 2019/7/3
Y1 - 2019/7/3
N2 - Health service providers have been under increasing pressure to consider user preferences in designing their programmes. Some organisations have met this challenge using stated preference methods. The two key fairness principles used in designing health services are Utilitarian and Rawlsian, and we propose a bi-objective integer programme to analyse the trade-off between them. Specifically, we model two types of information flow: bottom-up and top-down. The former is an analyst-driven process that fully examines the trade-off between a loss in a group’s average utility and a specific improvement in utility for the least well-off individuals and vice versa. The latter represents a situation in which preferences are stated by decision makers in hope of finding a best-compromise solution. Tested in a case study, our model yielded significantly more balanced designs than the method in current use. Results reveal that in a bottom-up process, a large gain in minimum utility can be achieved with only a minimal loss in average utility, while a top-down approach based on decision makers’ preferences may lead to a solution that is inferior on both objectives. A simulation study further reveals that the improvement in minimum utility is even greater when user preferences are more heterogeneous.
AB - Health service providers have been under increasing pressure to consider user preferences in designing their programmes. Some organisations have met this challenge using stated preference methods. The two key fairness principles used in designing health services are Utilitarian and Rawlsian, and we propose a bi-objective integer programme to analyse the trade-off between them. Specifically, we model two types of information flow: bottom-up and top-down. The former is an analyst-driven process that fully examines the trade-off between a loss in a group’s average utility and a specific improvement in utility for the least well-off individuals and vice versa. The latter represents a situation in which preferences are stated by decision makers in hope of finding a best-compromise solution. Tested in a case study, our model yielded significantly more balanced designs than the method in current use. Results reveal that in a bottom-up process, a large gain in minimum utility can be achieved with only a minimal loss in average utility, while a top-down approach based on decision makers’ preferences may lead to a solution that is inferior on both objectives. A simulation study further reveals that the improvement in minimum utility is even greater when user preferences are more heterogeneous.
KW - bi-objective optimisation
KW - Conjoint analysis
KW - goal programming
KW - health service
UR - http://www.scopus.com/inward/record.url?scp=85061488656&partnerID=8YFLogxK
U2 - 10.1080/01605682.2018.1489341
DO - 10.1080/01605682.2018.1489341
M3 - Article
AN - SCOPUS:85061488656
SN - 0160-5682
VL - 70
SP - 1091
EP - 1101
JO - Journal of the Operational Research Society
JF - Journal of the Operational Research Society
IS - 7
ER -