Investigating the usefulness of Automated Check-in Data Collection in general practice (AC DC Study): a multicentre, cross-sectional study in England.

Lawton, Sarah; Mallen, Christian; Muller, Sara; Wathall, Simon; Helliwell, Toby

Abstract

Objectives: To investigate the usefulness of using automated appointment check-in screens to collect brief research data from patients, prior to their general practice consultation.

Design: A descriptive, cross-sectional study.

Setting: Nine general practices in the West Midlands, UK. Recruitment commenced in Autumn 2018 and was concluded by 31 March 2019.

Participants: 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.

Primary and secondary outcome measures: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’.

Conclusions: 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.

Trial registration number ISRCTN82531292.

• Acceptance Date: Oct 20, 2022
• Publication Date: Jan 5, 2023
• Journal: BMJ Open
• Publisher: BMJ Publishing Group
• Volume: 13
• Issue: 1
• Article Number: e062389
• DOI: https://doi.org/10.1136/bmjopen-2022-062389
• Keywords: Humans, Female, Adolescent, Young Adult, Adult, Middle Aged, Aged, Aged, 80 and over, Cross-Sectional Studies, Pandemics, COVID-19, England, General Practice, Data Collection, Health informatics, PRIMARY CARE, PUBLIC HEALTH
• Publisher URL: https://bmjopen.bmj.com/content/13/1/e062389