Data-Driven Approach to assess and identify gaps in healthcare set up in South Asia
<|reference_start|>Data-Driven Approach to assess and identify gaps in healthcare set up in South Asia: Primary healthcare is a crucial strategy for achieving universal health coverage. South Asian countries are working to improve their primary healthcare system through their country specific policies designed in line with WHO health system framework using the six thematic pillars: Health Financing, Health Service delivery, Human Resource for Health, Health Information Systems, Governance, Essential Medicines and Technology, and an addition area of Cross-Sectoral Linkages. Measuring the current accessibility of healthcare facilities and workforce availability is essential for improving healthcare standards and achieving universal health coverage in developing countries. Data-driven surveillance approaches are required that can provide rapid, reliable, and geographically scalable solutions to understand a) which communities and areas are most at risk of inequitable access and when, b) what barriers to health access exist, and c) how they can be overcome in ways tailored to the specific challenges faced by individual communities. We propose to harness current breakthroughs in Earth-observation (EO) technology, which provide the ability to generate accurate, up-to-date, publicly accessible, and reliable data, which is necessary for equitable access planning and resource allocation to ensure that vaccines, and other interventions reach everyone, particularly those in greatest need, during normal and crisis times. This requires collaboration among countries to identify evidence based solutions to shape health policy and interventions, and drive innovations and research in the region.<|reference_end|>
@article{elahi2024data-driven,
    title={Data-Driven Approach to assess and identify gaps in healthcare set up in
  South Asia},
    author={Rusham Elahi, Zia Tahseen, Tehreem Fatima, Syed Wafa Zahra, Hafiz
  Muhammad Abubakar, Tehreem Zafar, Aqs Younas, Muhammad Talha Quddoos, Usman
  Nazir},
    journal={ICONIP 2024},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.14194},
    primaryClass={cs.CY cs.AI}
}