Desirability Optimization Models to Create the Global Healthcare Competitiveness Index

Area of Science:

• Health Economics
• Operations Research
• Public Health Policy

Background:

• Assessing global healthcare competitiveness is crucial for policy and resource allocation.
• Existing models may not fully capture the multifaceted nature of healthcare system performance and accessibility.
• High-income countries (GDP PC > $10,000) represent key markets for healthcare innovation and service delivery.

Purpose of the Study:

• To develop and validate a Global Healthcare Competitiveness Index (GHCI) using desirability optimization.
• To measure and compare the progress and quality of healthcare systems across 53 high-income nations.
• To establish a foundation for future research on global healthcare system competitiveness.

Main Methods:

• Employed statistical analysis alongside optimization models and techniques.
• Determined optimal and feasible factor values influencing healthcare expenditure (HE) and GHCI.
• Calculated GHCI values for 53 countries, ranging from 0 to 6.

Main Results:

• Achieved desirability values between 0.64 and 0.66 for the optimized factors.
• The computed average GHCI across the studied countries is 2.4758.
• Successfully generated GHCI values for all 53 participating countries.

Conclusions:

• The developed GHCI provides a novel metric for evaluating healthcare system competitiveness.
• Findings offer a baseline for comparing healthcare progress and accessibility in high-income countries.
• The methodology serves as a basis for future theoretical advancements in healthcare system assessment.