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    <title>maternal and child health on Arun Mitra</title>
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      <title>Mapping Maternal &amp; Child Health Data Sources for Local Decision-Making in Tribal PHCs</title>
      <link>https://arunmitra.com/research/mch-data-ecosystem/</link>
      <pubDate>Mon, 30 Mar 2026 00:00:00 +0000</pubDate>
      
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      <description>Background     Despite heavy investment in digital health information systems, frontline facilities in resource-constrained settings remain paradoxically data-rich yet information-poor. Health information systems built with an upward gaze for accountability reporting often fail to support the decisions that medical officers, data entry operators, and ANMs need to make locally. This work, part of Arun Mitra&amp;rsquo;s PhD thesis on participatory data science in ITDA-Rampachodavaram, Andhra Pradesh, asks how the maternal and child health (MCH) data ecosystem at primary health centre (PHC) level is actually structured, used, and constrained.</description>
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      <title>Participatory Data Science for Maternal &amp; Child Health in Tribal Andhra Pradesh</title>
      <link>https://arunmitra.com/research/participatory-data-science-mch/</link>
      <pubDate>Sat, 01 Jul 2023 00:00:00 +0000</pubDate>
      
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      <description>Background     Tribal primary health centres (PHCs) in India operate within data-rich routine health information systems (RHIS), yet local decision-making for maternal and child health (MCH) remains constrained: data is fragmented, misaligned with local needs, and rarely available in usable, actionable formats. The result is a wide gap between centrally oriented reporting and the ground-level realities of MCH service delivery. This PhD asks how a participatory data-science approach can re-orient routine systems to support PHC-level decisions, transforming under-used data into meaningful, context-specific, and actionable insight.</description>
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