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Background: As elsewhere in low- and middle-income countries, due to limited fiscal resources, universal health coverage (UHC) remains a challenge in Cambodia. Since 2016, the National Social Security Fund (NSSF) has implemented a social health insurance scheme with a contributory approach for formal sector workers. However, informal sector workers and dependents of formal sector workers are still not covered by this insurance because it is difficult to set an optimal amount of contribution for such individuals as their income levels are inestimable. The present study aims to develop and validate an efficient household income-level assessment model for Cambodia. We aim to help the country implement a financially sustainable social health insurance system in which the insured can pay contributions according to their ability. Methods: This study will use nationally representative data collected by the Cambodia Socio-Economic Survey (CSES), covering the period from 2009 to 2019, and involving a total of 50,016 households. We will employ elastic net regression analysis, with per capita disposable income based on purchasing power parity as the dependent variable, and individual and community-level socioeconomic and demographic characteristics as independent variables. These analyses aim to create efficient income-level assessment models for health insurance contribution estimation. To fully capture socioeconomic heterogeneity, sub-group analyses will be conducted to develop separate income-level assessment models for urban and rural areas, as well as for each province. Discussion: This research will help Cambodia implement a sustainable social health insurance system by collecting optimal amount of contributions from each socioeconomic group of the society. Incorporation of this approach into existing NSSF schemes will enhance the country's current efforts to prevent impoverishing health expenditure and to achieve UHC. [ABSTRACT FROM AUTHOR]

Background: Financial protection is a challenge for low- and middle-income countries, where the fiscal space is limited, and majority of the population is engaged in the informal economy. This study developed and validated household consumption predictive models for Cambodia to collect contributions according to one's ability to pay., Methods: This study used nationally representative survey data collected annually between 2010 and 2017, involving 38,472 households. We developed four alternative models: the manually selected linear model, the linear model with stepwise technique, the mixed effects linear model, and the model with regularisation technique. Subsequently, we performed out-of-sample cross-validation for each model, and evaluated the model prediction performance., Results: Overall, observed and predicted household consumptions were linearly related in all four models. While the prediction performance of the models did not substantially differ, the stepwise linear model showed the best performance. The regularisation and the mixed effects were not particularly effective in these regressions. The household consumption was better predicted for those with lower consumption, and the predictivity declined as the consumption level increased., Conclusions: This study suggests the possibility of predicting household consumption at a reasonable level. This would maximise the contribution revenue, optimise the government subsidy, and ensure equity in healthcare access., (© 2021 John Wiley & Sons Ltd.)