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加纳用手机支付国家健康保险费的决定因素:一项横断面前瞻性研究。

Determinants of paying national health insurance premium with mobile phone in Ghana: a cross-sectional prospective study.

机构信息

Faculty of Social Sciences, Department of Economics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.

Department of Child Health, Kwame Nkrumah University of Science and Technology School of Medicine and Dentistry, Kumasi, Ghana.

出版信息

Int J Equity Health. 2019 Mar 25;18(1):50. doi: 10.1186/s12939-019-0946-x.

Abstract

INTRODUCTION

In an effort to increase Ghana's National Health Insurance Scheme (NHIS) enrollment and retention rates, the NHIS introduced membership renewal and premium payment by mobile phone. The success of such an innovation dependents on many factors including personal and community characteristics of members.

OBJECTIVE

The objective of the study is to investigate the determinants of renewing membership and paying the NHIS premium through a mobile phone.

METHODOLOGY

The prospective cross-sectional survey was used to solicit the required information from about 1192 respondents living in Kumasi Metropolis, Atwima Nwabiaya and Sekyere Central Districts of Ghana. Logistic regression model was employed to estimate the determinants of paying the NHIS premium with the mobile phone.

RESULTS

The study found that factors including residing in an urban area (Kumasi metropolis), senior high education, tertiary education and informal employees are the determinants of paying the NHIS premium with the mobile phone.

CONCLUSION

It is recommended that the NHIS consider making the mobile payment as simple as possible for the less educated and the rural members to access it.

摘要

简介

为了提高加纳国家健康保险计划(NHIS)的参保率和续保率,NHIS 推出了通过手机进行会员续费和保费缴纳的服务。这种创新的成功取决于许多因素,包括成员的个人和社区特征。

目的

本研究旨在探讨通过手机续会员和缴纳 NHIS 保费的决定因素。

方法

本前瞻性横断面调查使用了从加纳库马西都会区、阿特瓦-恩瓦比亚亚和塞基雷中央区约 1192 名受访者那里收集所需信息。采用逻辑回归模型来估计通过手机缴纳 NHIS 保费的决定因素。

结果

研究发现,居住在城市地区(库马西都会区)、高中教育、高等教育和非正规员工等因素是通过手机缴纳 NHIS 保费的决定因素。

结论

建议 NHIS 考虑使移动支付对受教育程度较低和农村成员更简便,以方便他们使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61db/6434637/d810fa7248a5/12939_2019_946_Fig1_HTML.jpg

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