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

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 co...

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Autores principales: Lawton, Sarah, Mallen, Christian, Muller, Sara, Wathall, Simon, Helliwell, Toby
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827265/
https://www.ncbi.nlm.nih.gov/pubmed/36604124
http://dx.doi.org/10.1136/bmjopen-2022-062389
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author Lawton, Sarah
Mallen, Christian
Muller, Sara
Wathall, Simon
Helliwell, Toby
author_facet Lawton, Sarah
Mallen, Christian
Muller, Sara
Wathall, Simon
Helliwell, Toby
author_sort Lawton, Sarah
collection PubMed
description 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.
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spelling pubmed-98272652023-01-10 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 BMJ Open General practice / Family practice 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. BMJ Publishing Group 2023-01-05 /pmc/articles/PMC9827265/ /pubmed/36604124 http://dx.doi.org/10.1136/bmjopen-2022-062389 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle General practice / Family practice
Lawton, Sarah
Mallen, Christian
Muller, Sara
Wathall, Simon
Helliwell, Toby
Investigating the usefulness of Automated Check-in Data Collection in general practice (AC DC Study): a multicentre, cross-sectional study in England
title Investigating the usefulness of Automated Check-in Data Collection in general practice (AC DC Study): a multicentre, cross-sectional study in England
title_full Investigating the usefulness of Automated Check-in Data Collection in general practice (AC DC Study): a multicentre, cross-sectional study in England
title_fullStr Investigating the usefulness of Automated Check-in Data Collection in general practice (AC DC Study): a multicentre, cross-sectional study in England
title_full_unstemmed Investigating the usefulness of Automated Check-in Data Collection in general practice (AC DC Study): a multicentre, cross-sectional study in England
title_short Investigating the usefulness of Automated Check-in Data Collection in general practice (AC DC Study): a multicentre, cross-sectional study in England
title_sort investigating the usefulness of automated check-in data collection in general practice (ac dc study): a multicentre, cross-sectional study in england
topic General practice / Family practice
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827265/
https://www.ncbi.nlm.nih.gov/pubmed/36604124
http://dx.doi.org/10.1136/bmjopen-2022-062389
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