Advancing Clinical Documentation with Synthetic Data Technology

EasyChair Preprint 14177

Abstract

Advancing clinical documentation is pivotal for improving patient care and operational efficiency in healthcare systems. However, the sensitive nature of patient data poses significant challenges for data sharing and research. This paper explores the potential of synthetic data technology to revolutionize clinical documentation. By generating artificial data that mirrors the statistical properties of real-world patient data without compromising patient privacy, synthetic data can be leveraged to enhance clinical documentation practices. This study examines the applications of synthetic data in training machine learning models, developing decision support systems, and facilitating research collaborations. It also addresses the ethical considerations and technical challenges associated with synthetic data generation. The findings suggest that synthetic data technology holds substantial promise in transforming clinical documentation, offering a pathway to more accurate, efficient, and secure healthcare information management.

Keyphrases: Clinical Documentation, Data Generation Techniques, Electronic Health Records, data privacy, machine learning, synthetic data

@booklet{EasyChair:14177,
  author    = {Kayode Sheriffdeen},
  title     = {Advancing Clinical Documentation with Synthetic Data Technology},
  howpublished = {EasyChair Preprint 14177},
  year      = {EasyChair, 2024}}