增强髋关节或膝关节置换术患者的临床决策支持:与外科医生的焦点小组和访谈研究。

Sabrina Grant, Emma Tonkin, Ian Craddock, Ashley Blom, Michael Holmes, Andrew Judge, Alessandro Masullo, Miquel Perello Nieto, Hao Song, Michael Whitehouse, Peter Flach, Rachael Gooberman-Hill
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引用次数: 0

摘要

背景:目前对全髋关节或膝关节置换术后恢复的评估主要是基于通过自我报告和临床随访预约的临床观察来测量健康结果。基于家庭活动的监测可以通过在持续的基础上收集更全面的信息来改进对康复的评估。目的:本研究旨在向骨科医生介绍对部署在初次全髋关节或膝关节置换术患者家中的传感器平台产生的患者活动数据的时间序列分析,并了解这些数据在术后临床决策中的潜在作用。方法:采用方便抽样和滚雪球抽样相结合的方法招募骨科医生和登记员。纳入标准是髋关节或膝关节全关节置换术的最低要求经验或熟悉术后恢复评估。排除标准包括缺乏该领域的具体经验。在9名接触的参与者中,6名(67%)骨科医生和3名(33%)注册医师参加了3个焦点小组中的1个或2个访谈中的1个。使用基于行动的方法收集数据,其中刺激材料(模拟数据可视化)与数据提供富有想象力和创造性的交互。使用专题分析方法对数据进行分析。结果:每个数据可视化依次呈现,然后是参与者对关键说明性评论的讨论,最后是焦点小组和访谈数据集出现的关键主题的总结。结论:本研究证据的局限性如下。数据来自1家英国医院。然而,所有数据都反映了遵循标准国家方法和培训的外科医生的观点。虽然使用了方便抽样,但参与者的背景、技能和经验被认为是异质的。被动收集的家庭监测数据提供了一个真正的机会,更客观地描述患者手术后的恢复情况。然而,骨科医生强调,在与患者的短期医疗咨询中导航大量复杂数据相当困难。骨科医生认为,建议的显示信息和决策支持警报的仪表板最适合现有的临床工作流程。由此,制定了以下系统设计指南:最大限度地降低数据误读的风险,表达对数据的信心程度,支持临床医生开发相关技能,因为时间序列数据通常是不熟悉的,并考虑患者未来参与数据的影响。国际注册报告标识符(irrid): RR2-10.1136/bmjopen-2018-021862。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Toward Enhanced Clinical Decision Support for Patients Undergoing a Hip or Knee Replacement: Focus Group and Interview Study With Surgeons.

Background: The current assessment of recovery after total hip or knee replacement is largely based on the measurement of health outcomes through self-report and clinical observations at follow-up appointments in clinical settings. Home activity-based monitoring may improve assessment of recovery by enabling the collection of more holistic information on a continuous basis.

Objective: This study aimed to introduce orthopedic surgeons to time-series analyses of patient activity data generated from a platform of sensors deployed in the homes of patients who have undergone primary total hip or knee replacement and understand the potential role of these data in postoperative clinical decision-making.

Methods: Orthopedic surgeons and registrars were recruited through a combination of convenience and snowball sampling. Inclusion criteria were a minimum required experience in total joint replacement surgery specific to the hip or knee or familiarity with postoperative recovery assessment. Exclusion criteria included a lack of specific experience in the field. Of the 9 approached participants, 6 (67%) orthopedic surgeons and 3 (33%) registrars took part in either 1 of 3 focus groups or 1 of 2 interviews. Data were collected using an action-based approach in which stimulus materials (mock data visualizations) provided imaginative and creative interactions with the data. The data were analyzed using a thematic analysis approach.

Results: Each data visualization was presented sequentially followed by a discussion of key illustrative commentary from participants, ending with a summary of key themes emerging across the focus group and interview data set.

Conclusions: The limitations of the evidence are as follows. The data presented are from 1 English hospital. However, all data reflect the views of surgeons following standard national approaches and training. Although convenience sampling was used, participants' background, skills, and experience were considered heterogeneous. Passively collected home monitoring data offered a real opportunity to more objectively characterize patients' recovery from surgery. However, orthopedic surgeons highlighted the considerable difficulty in navigating large amounts of complex data within short medical consultations with patients. Orthopedic surgeons thought that a proposed dashboard presenting information and decision support alerts would fit best with existing clinical workflows. From this, the following guidelines for system design were developed: minimize the risk of misinterpreting data, express a level of confidence in the data, support clinicians in developing relevant skills as time-series data are often unfamiliar, and consider the impact of patient engagement with data in the future.

International registered report identifier (irrid): RR2-10.1136/bmjopen-2018-021862.

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