School of Medicine, Keele University, Keele, Staffordshire, UK
Keele CTU, Keele University, Keele, Staffordshire, UK.
BMJ Open. 2023 Jan 5;13(1):e062389. doi: 10.1136/bmjopen-2022-062389.
To investigate the usefulness of using automated appointment check-in screens to collect brief research data from patients, prior to their general practice consultation.
A descriptive, cross-sectional study.
Nine general practices in the West Midlands, UK. Recruitment commenced in Autumn 2018 and was concluded by 31 March 2019.
All patients aged 18 years and above, self-completing an automated check-in screen prior to their general practice consultation, were invited to participate during a 3-week recruitment period.
The response rate to the use of the automated check-in screen as a research data collection tool was the primary outcome measure. Secondary outcomes included responses to the two research questions and an assessment of impact of check-in completion on general practice operationalisation RESULTS: Over 85% (n=9274) of patients self-completing an automated check-in screen participated in the Automated Check-in Data Collection Study (61.0% (n=5653) women, mean age 55.1 years (range 18-98 years, SD=18.5)). 96.2% (n=8922) of participants answered a 'clinical' research question, reporting the degree of bodily pain experienced during the past 4 weeks: 32.9% (n=2937) experienced no pain, 28.1% (n=2507) very mild or mild pain and 39.0% (n=3478) moderate, severe or very severe pain. 89.3% (n=8285) of participants answered a 'non-clinical' research question on contact regarding future research studies: 46.9% (n=3889) of participants responded 'Yes, I'd be happy for you to contact me about research of relevance to me'.
Using automated check-in facilities to integrate research into routine general practice is a potentially useful way to collect brief research data from patients. With the COVID-19 pandemic initiating an extensive digital transformation in society, now is an ideal time to build on these opportunities and investigate alternative, innovative ways to collect research data.
ISRCTN82531292.
调查在全科医生就诊前使用自动预约登记屏幕从患者处收集简要研究数据的有效性。
描述性、横断面研究。
英国西米德兰兹郡的 9 家全科诊所。招募工作于 2018 年秋季开始，并于 2019 年 3 月 31 日结束。
所有年龄在 18 岁及以上、在全科医生就诊前自行完成自动登记屏幕的患者，在 3 周的招募期内被邀请参与。
使用自动登记屏幕作为研究数据收集工具的应答率是主要的结果测量指标。次要结果包括对两个研究问题的回答以及对登记完成对全科医疗运作的影响的评估。
超过 85%（n=9274）自行完成自动登记屏幕的患者参与了自动登记数据收集研究（61.0%（n=5653）为女性，平均年龄 55.1 岁（范围 18-98 岁，标准差 18.5））。96.2%（n=8922）的参与者回答了一个“临床”研究问题，报告过去 4 周内身体疼痛的程度：32.9%（n=2937）无疼痛，28.1%（n=2507）轻度或轻度疼痛，39.0%（n=3478）中度、重度或非常严重疼痛。89.3%（n=8285）的参与者回答了一个关于未来研究的“非临床”研究问题：46.9%（n=3889）的参与者回答“是的，我很高兴您就与我相关的研究联系我”。
使用自动登记设施将研究纳入常规全科医疗是从患者处收集简要研究数据的一种有潜力的方法。随着 COVID-19 大流行引发了社会的广泛数字化转型，现在是利用这些机会并调查收集研究数据的替代、创新方法的理想时机。
ISRCTN82531292。
