Societal preferences for fertility treatment in Australia: a stated preference discrete choice experiment

Objective: To investigate preferences for fertility treatment from the Australian general population with the aims of calculating the willingness to pay in tax contribution for attributes (characteristics) that make up treatment and for an “ideal” fertility treatment program. We also assessed whether willingness-to-pay varies by the relationship status or sexual orientation of the patient.

Methods: A stated preference discrete choice experiment was administered to a panel of 801 individuals representative of the Australian general population. Seven attributes of fertility treatment under three broad categories were included: outcome, process, and cost. Attributes were identified through published literature, focus group discussions, expert knowledge, and a pilot study. A Bayesian fractional experimental design was used, and data analysis was performed using a generalized multinomial logit model. Further analyses included interaction terms and latent class modeling.

Results: Six of the seven attributes influenced the choice of a treatment program. Under process attributes, individuals preferred: continuity of care of clinic staff, where patients are seen by the same doctor but different nurses at each visit; “alternative” treatments being offered to all patients; and onsite clinic counseling and peer-support groups. Personalization and tailoring of the treatment journey were not important. Among outcome attributes, the improved success rate of having a baby per cycle and significant side-effects were considered important. Cost of treatment also influenced the choice of treatment program. Individual preferences for fertility treatment were not associated with patients’ relationship status or sexual orientation. Latent class modeling revealed sub-groups with distinct fertility treatment preferences.

Conclusion: This study provides important insights into the attributes that influence the preferences of fertility treatment in Australia. It also estimates socially-inclusive willingness-to-pay values in tax contributions for an “ideal” package of treatment. The results can inform economic evaluations of fertility treatment programs.     

Keeping abreast of technology-driven business model evolution: a dynamic patent analysis approach

All firms that depend on technology for their competitive positions recognise that keeping abreast of technology-driven business model evolution is of vital importance. However, previous studies cannot offer a concrete way of profiling trends owing to the lack of quantitative data and systematic processes. We propose a dynamic patent analysis that can identify complex relationships among business method patents and visualise trends in technology-driven business model evolution. At the heart of the suggested approach is morphological analysis (MA) for structuring different types of business models at a technological attribute level and modified formal concept analysis (FCA) for investigating technological changes in business models over time. A case study of business method patents concerning electronic shopping is presented to show the feasibility of the proposed approach. We believe our method can promote consensus-building on up-to-date trends in technology-driven business model evolution, serving as a starting point for a more general model.     

Cost-effectiveness achieved through changing the composition of renal replacement therapy in Japan

Abstract

Objective:

The cost-effectiveness of renal replacement therapy (RRT) is affected by the composition of treatment. This study aimed to estimate the costs and outcomes associated with changing the composition of RRT modality over time.

Methods:

By using clinical and cost data from a systematic review, a Markov model was developed to assess the costs and benefits of the four main treatments available for RRT in Japan. The model included direct health service costs and quality-adjusted life years (QALY). Sensitivity analyses were performed to assess the robustness of the results.

Results:

Over the 15-year period of the model, the current composition of RRT (i.e., the base composition of RRT) was $84,008/QALY. The most cost-effective treatment was when the likelihood of a living donor transplant was increased by 2.4-times ($70,581/QALY). Compared with the base composition of RRT, dominant treatments with respect to cost-effectiveness were when the likelihood of a deceased donor transplant was increased by 22-times and when the likelihood of a pre-emptive living donor transplant was increased by 2.4-times. Little difference was found between these two treatments. One-way sensitivity analysis did not change the cost effectiveness except for costs of chronic hemodialysis and a living donor transplant in subsequent years.

Limitations:

It is difficult to increase the rate of transplant overall in the shorter term nationally and internationally.

Conclusions:

Appropriate distribution of all transplant options and hemodialysis is necessary to achieve the most cost-effective solution.     

Undiscounted optimal growth in the two-sector Robinson-Solow-Srinivasan model: a synthesis of the value-loss approach and dynamic programming

We highlight two features of undiscounted optimal growth in the context of a two-sector model due to Robinson, Solow and Srinivasan. First, we use the value-loss approach of Radner-Gale-McKenzie to show a multiplicity of optimal programs in situations when optimality does not coincide with value-loss minimization. Second, we use a theory of undiscounted dynamic programming, not available in the literature, to derive properties of the optimal policy correspondence. In terms of a methodological perspective, we suggest a synthesis of the two methods for the analysis of problems of optimal intertemporal resource allocationThis essay is dedicated to Mukul Majumdar on the occasion of his sixtieth birthday, with affection and admiration. We would like to thank Robert Becker, Minako Fujio and Ron Jones for useful discussions and to a referee of this journal for very insightful comments. We are grateful to the Center for Analytic Economics at Cornell and to the Center for a Livable Future at Johns Hopkins for research support