Implementing a sustainable health insurance system in Cambodia: a study protocol for developing and validating an efficient household income-level assessment model for equitable premium collection.


Journal

International journal for equity in health
ISSN: 1475-9276
Titre abrégé: Int J Equity Health
Pays: England
ID NLM: 101147692

Informations de publication

Date de publication:
31 01 2020
Historique:
received: 09 10 2019
accepted: 09 01 2020
entrez: 2 2 2020
pubmed: 2 2 2020
medline: 18 4 2020
Statut: epublish

Résumé

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. 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 32005237
doi: 10.1186/s12939-020-1126-8
pii: 10.1186/s12939-020-1126-8
pmc: PMC6995079
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

17

Références

Bioinformatics. 2011 Jan 1;27(1):1-8
pubmed: 21036813
East Mediterr Health J. 2012 Sep;18(9):962-8
pubmed: 23057390
Int J Prev Med. 2014 Jan;5(1):46-51
pubmed: 24554991

Auteurs

Haruyo Nakamura (H)

Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. hnakamura@m.u-tokyo.ac.jp.

Floriano Amimo (F)

Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Faculty of Medicine, Eduardo Mondlane University, Maputo, Mozambique.

Siyan Yi (S)

KHANA Center for Population Health Research, Phnom Penh, Cambodia.
Center for Global Health Research, Touro University California, Vallejo, CA, USA.
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.

Sovannary Tuot (S)

KHANA Center for Population Health Research, Phnom Penh, Cambodia.

Tomoya Yoshida (T)

Japan International Cooperation Agency, Tokyo, Japan.

Makoto Tobe (M)

Japan International Cooperation Agency, Tokyo, Japan.
Research Center for Health Policy and Economics, Hitotsubashi Institute for Advanced Study, Hitotsubashi University, Tokyo, Japan.

Shuhei Nomura (S)

Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.

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