Impact of a Digital Scribe System on Clinical Documentation Time and Quality: Usability Study.

Autor:	van Buchem MM; CAIRELab (Clinical AI Implementation and Research Lab), Leiden University Medical Center, Leiden, Netherlands., Kant IMJ; Department of Digital Health, University Medical Center Utrecht, Utrecht, Netherlands., King L; Autoscriber B.V., Eindhoven, Netherlands., Kazmaier J; Autoscriber B.V., Eindhoven, Netherlands., Steyerberg EW; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands., Bauer MP; Department of Internal Medicine, Leiden University Medical Center, Leiden, Netherlands.
Jazyk:	angličtina
Zdroj:	JMIR AI [JMIR AI] 2024 Sep 23; Vol. 3, pp. e60020. Date of Electronic Publication: 2024 Sep 23.
DOI:	10.2196/60020
Abstrakt:	Background: Physicians spend approximately half of their time on administrative tasks, which is one of the leading causes of physician burnout and decreased work satisfaction. The implementation of natural language processing-assisted clinical documentation tools may provide a solution. Objective: This study investigates the impact of a commercially available Dutch digital scribe system on clinical documentation efficiency and quality. Methods: Medical students with experience in clinical practice and documentation (n=22) created a total of 430 summaries of mock consultations and recorded the time they spent on this task. The consultations were summarized using 3 methods: manual summaries, fully automated summaries, and automated summaries with manual editing. We then randomly reassigned the summaries and evaluated their quality using a modified version of the Physician Documentation Quality Instrument (PDQI-9). We compared the differences between the 3 methods in descriptive statistics, quantitative text metrics (word count and lexical diversity), the PDQI-9, Recall-Oriented Understudy for Gisting Evaluation scores, and BERTScore. Results: The median time for manual summarization was 202 seconds against 186 seconds for editing an automatic summary. Without editing, the automatic summaries attained a poorer PDQI-9 score than manual summaries (median PDQI-9 score 25 vs 31, P<.001, ANOVA test). Automatic summaries were found to have higher word counts but lower lexical diversity than manual summaries (P<.001, independent t test). The study revealed variable impacts on PDQI-9 scores and summarization time across individuals. Generally, students viewed the digital scribe system as a potentially useful tool, noting its ease of use and time-saving potential, though some criticized the summaries for their greater length and rigid structure. Conclusions: This study highlights the potential of digital scribes in improving clinical documentation processes by offering a first summary draft for physicians to edit, thereby reducing documentation time without compromising the quality of patient records. Furthermore, digital scribes may be more beneficial to some physicians than to others and could play a role in improving the reusability of clinical documentation. Future studies should focus on the impact and quality of such a system when used by physicians in clinical practice. (©Marieke Meija van Buchem, Ilse M J Kant, Liza King, Jacqueline Kazmaier, Ewout W Steyerberg, Martijn P Bauer. Originally published in JMIR AI (https://ai.jmir.org), 23.09.2024.)
Databáze:	MEDLINE
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