Assessing Health Care Professionals’ Perceptions of a New System in Clinical Workflows: Systems Engineering Initiative for Patient Safety–Based Consensual Qualitative Research

This preimplementation, SEIPS-based qualitative evaluation suggests that the successful adoption of an AI-enabled transfusion CDSS depends not only on predictive performance but also on sociotechnical readiness, including user trust, workflow fit, and organizational support. These findings provide practice-based insights to inform staged implementation, training, and governance strategies aimed at safely integrating predictive transfusion CDSSs into EHR-supported surgical workflows.

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Publication Details

Journal
Journal of Medical Internet Research
Published
2025-12-24
DOI
https://doi.org/10.2196/86166
Primary Topic
Patient Safety and Medication Errors
Type
article
Field-Weighted Citation Impact
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article

Assessing Health Care Professionals’ Perceptions of a New System in Clinical Workflows: Systems Engineering Initiative for Patient Safety–Based Consensual Qualitative Research

Ye-Eun Park, Dae-Hyun Ko, Yura Lee, Taezoon Park et al.
Journal of Medical Internet Research
Patient Safety and Medication Errors
article

Assessing Health Care Professionals’ Perceptions of a New System in Clinical Workflows: Systems Engineering Initiative for Patient Safety–Based Consensual Qualitative Research

Ye-Eun Park, Dae-Hyun Ko, Yura Lee, Taezoon Park, Minsu Ock, Hak-Jae Lee, Jae-Ho Lee
article en

Abstract

This preimplementation, SEIPS-based qualitative evaluation suggests that the successful adoption of an AI-enabled transfusion CDSS depends not only on predictive performance but also on sociotechnical readiness, including user trust, workflow fit, and organizational support. These findings provide practice-based insights to inform staged implementation, training, and governance strategies aimed at safely integrating predictive transfusion CDSSs into EHR-supported surgical workflows.

Journal of Medical Internet ResearchVol. 28
Ulsan College (KR), Soongsil University (KR), Samsung (South Korea) (KR), Asan Medical Center (KR), University of Ulsan (KR), Ulsan University Hospital (KR), Sungkyunkwan University (KR)
Openalex Percentile: Top 25%
Patient Safety and Medication Errors
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