Silent Data Waste in Public Laboratories: A Conceptual Framework for Sustainable Data‑Driven Management
DOI:
https://doi.org/10.65405/r6tm5v65Keywords:
Data utilization, public laboratories, Silent data waste, Specimen rejection, Sustainable management, Turnaround timeAbstract
Public medical laboratories generate extensive volumes of routine operational data, including test workloads, turnaround times, quality control results, reagent consumption records, and equipment performance indicators. Despite this abundance, a substantial proportion of these data remains underutilized in managerial and strategic decision‑making. This phenomenon is conceptualized in this paper as silent data waste, defined as the systematic loss of informational value arising not from data scarcity, but from weak governance, limited analytical capacity, and fragmented information systems.
This conceptual paper positions silent data waste as a managerial and organizational challenge rather than a purely technical limitation. Drawing on a focused and critical review of recent literature in laboratory management, health data governance, and sustainable healthcare systems, the study develops an integrated conceptual framework linking routine data utilization to quality performance and resource efficiency outcomes. Key operational indicators, such as median turnaround time, specimen rejection rates, and quality control compliance metrics, are used as quantifiable managerial performance measures to illustrate how improved data utilization can support evidence-based management, reduce material and environmental waste, and enhance service reliability. The proposed framework advances the discourse on sustainable laboratory management by reframing routine operational data as a strategic leadership asset. By strengthening data governance structures, analytical tools, and managerial data literacy, public laboratories can transition from reactive operations toward proactive, sustainable, and performance‑oriented management aligned with relevant sustainable development goals.
The review synthesizes evidence indicating that 30–50% of routine laboratory data remains underutilized, with measurable performance and sustainability implications.
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References
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