Setbacks in Clinical Laboratory Innovations
Date
2021-10-25
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Technological advancements are soaring in healthcare as a whole; however, advancements in the clinical laboratory have fallen behind. Innovation in the clinical laboratory can be complicated and comes with high risks. Consequently, new technology and its acceptance have fallen short. The slow growth of artificial intelligence (AI), machine learning (ML), and deep learning (DL) keeps laboratory technicians working harder and healthcare costs soaring. This technological lag perpetuates analysis delays, unnecessary testing, human errors, suboptimal patient care, and in an untimely fashion.
The goal of this research is to prove the significant need for innovations in laboratory medicine and establish a means to accomplish them. This paper will include analyses of articles, peer reviewed articles, websites, and journals that are no more than three years old to show how laboratory innovations can enhance turnaround times, lower healthcare costs, increase the level of patient care, and allow for greater patient outcomes.
Description
Keywords
Laboratory, clinical, Artificial intelligence, Machine learning, Health record (electronic), Clinical decision support, Point of care testing, Test recommendation tools, Deep learning