School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, United States.
JMIR Hum Factors. 2024 Aug 6;11:e48584. doi: 10.2196/48584.
Health care technology has the ability to change patient outcomes for the betterment when designed appropriately. Automation is becoming smarter and is increasingly being integrated into health care work systems.
This study focuses on investigating trust between patients and an automated cardiac risk assessment tool (CRAT) in a simulated emergency department setting.
A within-subjects experimental study was performed to investigate differences in automation modes for the CRAT: (1) no automation, (2) automation only, and (3) semiautomation. Participants were asked to enter their simulated symptoms for each scenario into the CRAT as instructed by the experimenter, and they would automatically be classified as high, medium, or low risk depending on the symptoms entered. Participants were asked to provide their trust ratings for each combination of risk classification and automation mode on a scale of 1 to 10 (1=absolutely no trust and 10=complete trust).
Results from this study indicate that the participants significantly trusted the semiautomation condition more compared to the automation-only condition (P=.002), and they trusted the no automation condition significantly more than the automation-only condition (P=.03). Additionally, participants significantly trusted the CRAT more in the high-severity scenario compared to the medium-severity scenario (P=.004).
The findings from this study emphasize the importance of the human component of automation when designing automated technology in health care systems. Automation and artificially intelligent systems are becoming more prevalent in health care systems, and this work emphasizes the need to consider the human element when designing automation into care delivery.
当设计得当，医疗技术有能力改善患者的预后。自动化技术正变得越来越智能，并越来越多地融入医疗工作系统。
本研究聚焦于在模拟急诊环境下，调查患者对自动化心脏风险评估工具（CRAT）的信任。
本研究采用单组内实验设计，以调查 CRAT 的三种自动化模式（1）无自动化，（2）仅自动化，和（3）半自动之间的差异。参与者被要求按照实验者的指示，将模拟症状输入到 CRAT 中，然后根据输入的症状自动将其分类为高、中或低风险。参与者被要求对每种风险分类和自动化模式的组合在 1 到 10 分的量表上（1=绝对不信任，10=完全信任）提供他们的信任评级。
本研究结果表明，与仅自动化条件相比，参与者对半自动条件的信任显著更高（P=.002），与仅自动化条件相比，参与者对无自动化条件的信任显著更高（P=.03）。此外，与中严重程度场景相比，参与者在高严重程度场景中对 CRAT 的信任显著更高（P=.004）。
本研究结果强调了在医疗系统设计自动化技术时，自动化中人类因素的重要性。自动化和人工智能系统在医疗系统中越来越普遍，这项工作强调了在设计自动化医疗护理时需要考虑人类因素。
