Journal of Advances in Developmental Research

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Priority-Aware EMR Ingestion Pipelines: A Multi-Experiment and Analytical Study of Scheduling Algorithms for Real-Time Electronic Medical Record Flows

Author(s) Anupam Ojha
Country United States
Abstract The COVID-19 pandemic revealed fundamental limitations in Electronic Medical Record (EMR) ingestion platforms that rely on batch-oriented processing and first-in-first-out (FIFO) scheduling. This paper presents a priority-aware EMR ingestion framework and evaluates multiple scheduling strategies through extensive simulation and queueing-theoretic analysis. We study four approaches: FIFO, strict priority, priority with aging, and adaptive weighted scheduling. Analytical modeling based on M/G/1 priority queues is combined with numerical simulations to quantify tail latency, throughput, and starvation behavior. Results show that priority-aware scheduling with aging reduces high-urgency tail latency by 40–70% under peak load while preserving throughput within 2–6% of FIFO. This study establishes priority semantics as a foundational design principle for next-generation healthcare data
pipelines.
Keywords Electronic Medical Records, Healthcare Data Pipelines, Priority Scheduling, Queueing Theory, Real-Time, Systems, M/G/1 Queues.
Field Engineering
Published In Volume 12, Issue 1, January-June 2021
Published On 2021-01-06
Cite This Priority-Aware EMR Ingestion Pipelines: A Multi-Experiment and Analytical Study of Scheduling Algorithms for Real-Time Electronic Medical Record Flows - Anupam Ojha - IJAIDR Volume 12, Issue 1, January-June 2021. DOI 10.71097/IJAIDR.v12.i1.1778
DOI https://doi.org/10.71097/IJAIDR.v12.i1.1778
Short DOI https://doi.org/hbtv23
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