Using discrete choice modelling in priority setting: an application to clinical service developments

Area of Science:

• Health economics
• Health services research
• Decision science

Background:

• Limited healthcare resources necessitate efficient priority-setting methods.
• Existing techniques may not fully capture complex trade-offs in resource allocation.
• The need for robust tools to guide policy decisions in clinical service development is critical.

Purpose of the Study:

• To explore the application of Discrete Choice Modelling (DCM) in healthcare priority setting.
• To demonstrate how DCM can estimate cost per unit of benefit for clinical service developments.
• To propose an integrated approach using DCM and integer programming for optimal resource allocation.

Main Methods:

• Discrete Choice Modelling (DCM) was employed to model decision-making preferences.
• Cost per unit of benefit ratios were estimated for various clinical service developments.
• Integer programming was utilized in conjunction with DCM to identify optimal service combinations.

Main Results:

• DCM proved capable of estimating cost-effectiveness ratios for competing health interventions.
• The combined DCM and integer programming approach demonstrated internal validity and consistency.
• The study identified potential for DCM to enhance priority-setting processes.

Conclusions:

• Discrete Choice Modelling (DCM) shows promise as a valuable tool for healthcare priority setting.
• Integrating DCM with integer programming offers a systematic method for budget-constrained resource allocation.
• Further research is needed to address methodological challenges and refine DCM applications in this field.