Automated Check-in Data Collection (AC DC): a sustainable method for conducting research in general practice
Background: Within primary care settings, and particularly within general practice, time and resources for research are limited. The use of an automated check-in screen to collect brief research data from patients, prior to their appointment, may provide a new option for researchers.
The approach: A pilot-feasibility descriptive cross-sectional study was conducted in general practices within NIHR CRN: West Midlands, to investigate the feasibility of using automated check-in screens for the collection of brief research data from patients. Patients checking in were provided with two research questions. Strong PPIE involvement was gained on the design of the study. The impact of the investigation on general practice operationalisation was captured using diary entries, completed by the participating general practices.
Findings: 9,274 participants were recruited to the Automated Check-in Data Collection (AC DC) Study, from 9 general practices over a 3-week recruitment period. Almost 90% of all patients presented with the opportunity, participated in the research study. 96.2% of participants answered the ‘clinical’ research question, reporting a degree of bodily pain experienced during the past 4 weeks. The severities of pain reported, were comparable with results identified elsewhere. 89.3% of participants answered the ‘non-clinical’ research question, on happiness to be contacted about future research studies. The operational disruption caused by collecting brief research data, at the point of automated check-in, was considered negligible.
Implications: The use of automated check-in facilities, to integrate research into routine general practice has revealed that process automation is one of the enablers, for a sustainable and effective brief data collection methodology. With the COVID-19 pandemic initiating an extensive digital transformation in society, now is an ideal time to investigate other ways in which electronic research data capture can be a sustainable reality.