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Updated: Oct 10, 2025

Movement Retraining using Real-time Feedback of Performance
Published on: January 17, 2013
Identifying factors that promote and limit the effective use of real-time patient experience feedback: a
Mustafa Khanbhai1, Kelsey Flott2, Dave Manton2
1Imperial College London, NIHR Patient and Safety Translational Research Centre, London, UK m.khanbhai@imperial.ac.uk.
Objectives:
The Friends and Family Test (FFT) is commissioned by the National Health Service (NHS) in England to capture patient experience as a real-time feedback initiative for patient-centred quality improvement (QI). The aim of this study was to create a process map in order to identify the factors that promote and limit the effective use of FFT as a real-time feedback initiative for patient-centred QI.
Setting:
This study was conducted at a large London NHS Trust. Services include accident and emergency, inpatient, outpatient and maternity, which routinely collect FFT patient experience data.
Participants:
Healthcare staff and key stakeholders involved in FFT.
Interventions:
Semi-structured interviews were conducted on 15 participants from a broad range of professional groups to evaluate their engagement with the FFT. Interview data were recorded, transcribed and analysed for using deductive thematic analysis.
Results:
Concerns related to inefficiency in the flow of FFT data, lack of time to analyse FFT reports (with emphasis on high level reporting rather than QI), insufficient access to FFT reports and limited training provided to understand FFT reports for frontline staff. The sheer volume of data received was not amenable to manual thematic analysis resulting in inability to acquire insight from the free text. This resulted in staff ambivalence towards FFT as a near real-time feedback initiative.
Conclusions:
The results state that there is too much FFT free text for meaningful analysis, and the output is limited to the provision of sufficient capacity and resource to analyse the data, without consideration of other options, such as text analytics and amending the data collection tool.
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