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Impact of Poverty Reduction Programs on Healthcare Access in Remote Ar-eas: Fostering Community Development for Sustainable Health Amri, Siskawati; Sihotang , Jonhariono
Law and Economics Vol. 17 No. 3 (2023): October: Law and Economics
Publisher : Institute for Law and Economics Studies

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/laweco.v17i3.43

Abstract

This research investigates the impact of poverty reduction programs on healthcare access in remote areas, aiming to discern their effectiveness in addressing healthcare disparities. Employing a mixed-method approach, the study combines quantitative surveys, qualitative interviews, and focus group discussions to gather comprehensive data. The research reveals promising outcomes, demonstrating a significant increase in healthcare utilization among communities benefiting from poverty reduction initiatives. Improvements in healthcare infrastructure, positive health outcomes, and economic empowerment are evident, indicating the success of these programs in enhancing healthcare access. However, limitations including geographical constraints, potential biases, and sample representativeness are acknowledged. While acknowledging these constraints, the findings emphasize the significance of continued support for poverty reduction programs, policy development, and community involvement to sustain and expand the positive impact on healthcare access in remote areas. This research offers vital insights, contributing to academic knowledge, policy development, and practice, supporting the global agenda of sustainable development goals and advocating for more inclusive and equitable healthcare access in marginalized regions
New Method for Identification and Response to Infectious Disease Patterns Based on Comprehensive Health Service Data Desi Vinsensia; Siskawati Amri; Jonhariono Sihotang; Hengki Tamando Sihotang
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.4000

Abstract

Infectious diseases continue to pose a major threat to global public health and require early detection and effective response strategies. Despite advances in information technology and data analysis, the full potential of health data in identifying disease patterns and trends remains underutilised. This study aims to propose a comprehensive new mathematical model (new method) that utilises health data to identify infectious disease patterns and trends by exploring the potential of data-driven care approaches in addressing public health challenges associated with infectious diseases. The research methods used are exploratory data collection and analytical model development. The research results obtained mathematical models and algorithms that consider data of period, time, patterns, and trends of dangerous diseases, statistical analysis, and recommendations. Data visualisation and in-depth analysis were conducted in the research to improve the ability to respond to infectious disease threats and provide better decision-making solutions in improving outbreak response, as well as improving preparedness in addressing public health challenges. This research contributes to health practitioners and decision-makers.