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. 2024 Jun 1;21(2):1d.
eCollection 2024 Summer.

Improving Clinical Documentation with Artificial Intelligence: A Systematic Review

Scott W Perkins, Justin C Muste, Taseen Alam, Rishi P Singh

Improving Clinical Documentation with Artificial Intelligence: A Systematic Review

Scott W Perkins et al. Perspect Health Inf Manag. .

Abstract

Clinicians dedicate significant time to clinical documentation, incurring opportunity cost. Artificial Intelligence (AI) tools promise to improve documentation quality and efficiency. This systematic review overviews peer-reviewed AI tools to understand how AI may reduce opportunity cost. PubMed, Embase, Scopus, and Web of Science databases were queried for original, English language research studies published during or before July 2024 that report a new development, application, and validation of an AI tool for improving clinical documentation. 129 studies were extracted from 673 candidate studies. AI tools improve documentation by structuring data, annotating notes, evaluating quality, identifying trends, and detecting errors. Other AI-enabled tools assist clinicians in real-time during office visits, but moderate accuracy precludes broad implementation. While a highly accurate end-to-end AI documentation assistant is not currently reported in peer-reviewed literature, existing techniques such as structuring data offer targeted improvements to clinical documentation workflows.

Keywords: Artificial intelligence; automation; clinical guidelines; documentation; electronic health records; informatics.

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Figures

Figure 1
Figure 1
PRISMA diagram of the study selection process[KM3].
Figure 2
Figure 2
Distribution of studies by time and domain[KM4].
Figure 3
Figure 3
Distribution of studies by domain[KM5].
See this image and copyright information in PMC

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