Lindsay Westervelt

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An Argument for Standardized Reference Terminologies

As a National Institutes of Health (NIH) article explains, standardized data is ‘crucial for data exchange between health information systems, epidemiological analysis, quality and research, clinical decision support systems, administrative functions.” Terminology is an important part of medicine. In short, it is a clinicians’ extensive healthcare vocabulary, which they use to describe a patients’ conditions and health events. With the onset of EHRs, clinicians are responsible for documenting patient information in EHRs. This is now properly done with standardized reference terminologies and not home-grown ones.

Lindsay Westervelt

Lindsay Westervelt is a Technical Writer and Project Support Specialist for J P Systems, Inc. At J P Systems, Ms. Westervelt leads social media content production efforts and assists with designing and developing J P Systems’ marketing materials. She also edits project deliverables and manages client onboarding tasks. J P Systems is a Healthcare Information Technology (Health IT) consulting firm that was named one of the 50 Fastest Growing Women-Owned/Led Companies of 2020. The firm specializes in Healthcare Informatics through terminology mapping, data standardization, enterprise data architecture, and data quality improvement.

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The Importance of High Quality Data for AI Reliability

Artificial Intelligence (AI) is a hot topic right now in medical practice. Though there are many reasons why AI solutions have become so popular, one of the biggest reasons is that AI has the potential to reduce clinical burnout and fatigue by improving Clinical Decision Support in electronic health record (EHR) systems. To understand how this can be achieved, we must first understand what AI is and how it works...For Healthcare, AI and Machine Learning algorithms must rely on copious amounts of granular, high-quality data.

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