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Using Data Analytics To Target Preanalytical Errors And Achieve Higher Value-Added Outcomes

13th International Conference on Laboratory Medicine & Pathology

Aparna Jha Ahuja

BD Life Sciences - Preanalytical Systems, NJ, USA

ScientificTracks Abstracts: Diagn Pathol Open

DOI: 10.4172/2476-2024-C1-002

Abstract
Data analytics is evolving into a promising method to provide insight from large amounts of data into improving patient outcomes and reducing healthcare costs. Since most of the information used by healthcare providers for medical decisions is derived from laboratory testing, better use of the critical information within the laboratory�s data system can help to improve efficiency as well. One application for data analytics is to target the errors encountered in the preanalytical phase. These errors include patient/sample misidentification, hemolyzed/clotted specimens, insufficient specimen quantity, and improper test ordering, all of which may increase costs and negatively impact patient care. Reducing these errors can contribute to higher value-added patient outcomes (e.g., enhanced patient safety, fewer repeat blood draws). Additionally, incorporating data analytics can also assess laboratory competency and identify opportunities for overall quality improvement.
Biography

Aparna Jha Ahuja, MD, is currently the Worldwide Vice President, Medical Affairs, BD Life Sciences - Preanalytical Systems, Franklin Lakes, New Jersey, USA. She has more than two decades of laboratory experience, with hands-on experience in Biochemistry, Specialized Chemistry and Molecular Biology. She is a recognized speaker, having presented at many laboratory medicine conferences. Her current focus is on the improvement of quality laboratory testing and increasing awareness of the impact of the preanalytical phase on clinical diagnostic results.

E-mail: Julie_Ravo@bd.com

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