Suppr超能文献

在大查房期间通过社交辅助机器人提供计算机化临床决策支持系统的可行性:一项试点研究。

Feasibility of a computerized clinical decision support system delivered via a socially assistive robot during grand rounds: A pilot study.

作者信息

Šafran Valentino, Smrke Urška, Ilijevec Bojan, Horvat Samo, Flis Vojko, Plohl Nejc, Mlakar Izidor

机构信息

Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia.

University Division of Surgery, University Medical Centre Maribor, Maribor, Slovenia.

出版信息

Digit Health. 2025 Apr 30;11:20552076251339012. doi: 10.1177/20552076251339012. eCollection 2025 Jan-Dec.

Abstract

AIMS AND OBJECTIVE

The aim of this study was to explore the feasibility, usability and acceptance of integrating Clinical Decision Support Systems with Socially Assistive Robots into hospital grand rounds.

BACKGROUND

Adopting Clinical Decision Support Systems in healthcare faces challenges such as complexity, poor integration with workflows, and concerns about data privacy and quality. Issues such as too many alerts, confusing errors, and difficulty using the technology in front of patients make adoption challenging and prevent it from fitting into daily workflows. Making Clinical Decision Support System simple, intuitive and user-friendly is essential to enable its use in daily practice to improve patient care and decision-making.

METHODS

This six-month pilot study had two participant groups, with total of 40 participants: a longitudinal intervention group (n = 8) and a single-session evaluation group (n = 32). Participants were medical doctors at the University Clinical Center Maribor. The intervention involved implementing a Clinical Decision Support System delivered via a Socially Assistive Robot during hospital grand rounds. We developed a system that employed the HL7 FHIR standard for integrating data from hospital monitors, electronic health records, and patient-reported outcomes into a single dashboard. A Pepper-based SAR provided patient specific recommendations through a voice and SAR tablet enabled interface. Key evaluation metrics were assessed using the System Usability Scale (SUS) and the Unified Theory of Acceptance, Use of Technology (UTAUT2) questionnaire, including Effort Expectancy, Performance Expectancy and open ended questions. The longitudinal group used the system for 6 months and completed the assessments twice, after one week and at the end of the study. The single-session group completed the assessment once, immediately after the experiment. Qualitative data were gathered through open-ended questions. Data analysis included descriptive statistics, paired t-tests, and thematic analysis.

RESULTS

System usability was rated highly across both groups, with the longitudinal group reporting consistently excellent scores (M = 82.08 at final evaluation) compared to the acceptable scores of the single-session group (M = 68.96). Extended exposure improved user engagement, reflected in significant increases in Effort Expectancy and Habit over time. Participants found the system enjoyable to use, and while no significant changes were seen in Performance Expectancy, feedback emphasized its efficiency in saving time and improving access to clinical data, supporting its feasibility and acceptability.

CONCLUSIONS

This research supports the potential of robotic technologies to transform CDSS into more interactive, efficient, and user-friendly tools for healthcare professionals. The paper also suggests further research directions and technical improvements to maximize the impact of innovative technologies in healthcare.

摘要

目的

本研究旨在探讨将临床决策支持系统与社交辅助机器人集成到医院大查房中的可行性、可用性和可接受性。

背景

在医疗保健中采用临床决策支持系统面临诸多挑战,如复杂性、与工作流程集成不佳以及对数据隐私和质量的担忧。诸如警报过多、错误令人困惑以及在患者面前使用该技术存在困难等问题,使得采用该系统具有挑战性,并阻碍其融入日常工作流程。使临床决策支持系统简单、直观且用户友好,对于在日常实践中使用它以改善患者护理和决策至关重要。

方法

这项为期六个月的试点研究有两个参与组,共40名参与者:一个纵向干预组(n = 8)和一个单 session 评估组(n = 32)。参与者是马里博尔大学临床中心的医生。干预措施包括在医院大查房期间通过社交辅助机器人实施临床决策支持系统。我们开发了一个系统,该系统采用HL7 FHIR标准将来自医院监测器、电子健康记录和患者报告结果的数据集成到一个单一的仪表板中。一个基于Pepper的社交辅助机器人通过语音和社交辅助机器人平板电脑界面提供针对患者的建议。使用系统可用性量表(SUS)和技术接受与使用统一理论(UTAUT2)问卷评估关键评估指标,包括努力期望、绩效期望和开放式问题。纵向组使用该系统6个月,并在一周后和研究结束时完成两次评估。单 session 组在实验结束后立即完成一次评估。通过开放式问题收集定性数据。数据分析包括描述性统计、配对t检验和主题分析。

结果

两组对系统可用性的评价都很高,纵向组报告的分数始终优异(最终评估时M = 82.08),而单 session 组的分数为可接受(M = 68.96)。随着时间的推移,更长时间的接触提高了用户参与度,这反映在努力期望和习惯方面的显著增加。参与者发现该系统使用起来很愉快,虽然绩效期望方面没有显著变化,但反馈强调了其在节省时间和改善临床数据获取方面的效率,支持了其可行性和可接受性。

结论

本研究支持机器人技术将临床决策支持系统转变为医疗保健专业人员更具交互性、高效性和用户友好性工具的潜力。本文还提出了进一步的研究方向和技术改进,以最大限度地发挥创新技术在医疗保健中的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/48b5/12046174/a9f5bc9a04ec/10.1177_20552076251339012-fig1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验