The Role of Data Science in Closing the Implementation Gap
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Updated: Jul 16, 2025

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
Published on: November 22, 2019
Andrew J King1, Jeremy M Kahn2
1Department of Critical Care Medicine, University of Pittsburgh School of Medicine, 3500 Terrace Street, Suite 600, Pittsburgh, PA 15261, USA.
Abstract:
Data science has the potential to greatly enhance efforts to translate evidence into practice in critical care. The intensive care unit is a data-rich environment enabling insight into both patient-level care patterns and clinician-level treatment patterns. By applying artificial intelligence to these novel data sources, implementation strategies can be tailored to individual patients, individual clinicians, and individual situations, revealing when evidence-based practices are missed and facilitating context-sensitive clinical decision support. To achieve these goals, technology developers should work closely with clinicians to create unbiased applications that are integrated into the clinical workflow.
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