Classifying OECD Health Systems by Financing Structure: An Empirical Latent Profile Analysis

Abstract

Background

The classification of health systems by financing structure has long played a central role in comparative health policy research, but typologies have often proceeded deductively from theoretical categories. This study asks how OECD countries cluster empirically when classified using harmonised financing indicators.

Methods

Latent Profile Analysis was applied to 10 financing indicators from the WHO Global Health Expenditure Database for the year 2022, covering all 38 OECD member countries. Indicators were z-standardised, and one-to six-class models were estimated. The retained solution was selected on the joint evaluation of BIC, entropy, class size, parsimony, and substantive interpretability. Between-class separation was examined using Kruskal–Wallis tests and η²[H] effect sizes as descriptive indicators only.

Results

A five-class solution was retained. The five empirical profiles were labelled as a social insurance–oriented public financing profile, a lower-spending private-mix financing profile, a lower-spending mixed social-insurance financing profile, a tax-financed public financing profile, and a high-spending private-financing-dominant profile. Between-class separation was strongest for social insurance contributions, current health expenditure per capita, transfers from general government domestic revenue, and the public and private shares of current health expenditure.

Conclusions

The retained classes describe financing profiles rather than full institutional health system types. They complement, but do not replace, classical and multidimensional typologies, and make the financing dimension of health system classification empirically explicit for comparative analysis of OECD health systems.