This paper is in the following e-collection/theme issue:

Health Services in Resource-Poor Settings and LMICs (542) Clinical Informatics (1325) mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (717) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1732) Health Care Quality and Health Services Research (337) Demographics of Users, Social & Digital Divide (914)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73731, first published .
Differences in Hemodialysis Claim Patterns Across Membership Types Among Patients With Renal Failure Based on National Health Insurance Data From 2017 to 2022: Cross-Sectional Analysis

Differences in Hemodialysis Claim Patterns Across Membership Types Among Patients With Renal Failure Based on National Health Insurance Data From 2017 to 2022: Cross-Sectional Analysis

Differences in Hemodialysis Claim Patterns Across Membership Types Among Patients With Renal Failure Based on National Health Insurance Data From 2017 to 2022: Cross-Sectional Analysis

Authors of this article:

Aries Munandar1 Author Orcid Image ;   Syarif R Hasibuan2, 3 Author Orcid Image ;   Dian Kusuma4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Aries Munandar   1 ;   Syarif R Hasibuan   2, 3 ;   Dian Kusuma   4

1 Department of Social Welfare, Faculty of Social and Political Science, University of Bengkulu, Bengkulu, Indonesia

2 Faculty of Medicine, Universitas Pembangunan Nasional Veteran Jakarta, Jakarta, Indonesia

3 Center for Health Administration and Policy Studies, Faculty of Public Health, University of Indonesia, Depok, Indonesia

4 Department of Public Health and Epidemiology, College of Medicine and Health Sciences, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates

Corresponding Author:

  • Dian Kusuma
  • Department of Public Health and Epidemiology
  • College of Medicine and Health Sciences
  • Khalifa University of Science and Technology
  • Shakhbout Bin Sultan St
  • Abu Dhabi
  • United Arab Emirates
  • Phone: 971 02 312 3333
  • Email: dian.kusuma@ku.ac.ae