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. 2019 Oct;85(10):2405-2413.
doi: 10.1111/bcp.14065. Epub 2019 Aug 23.

Pharmacist-led, video-stimulated feedback to reduce prescribing errors in doctors-in-training: A mixed methods evaluation

Affiliations

Pharmacist-led, video-stimulated feedback to reduce prescribing errors in doctors-in-training: A mixed methods evaluation

Hazel Parker et al. Br J Clin Pharmacol. 2019 Oct.

Abstract

Aims: To develop and evaluate a feasible, authentic pharmacist-led prescribing feedback intervention for doctors-in-training, to reduce prescribing errors.

Methods: This was a mixed methods study. Sixteen postgraduate doctors-in training, rotating though the surgical assessment unit of 1 UK hospital, were filmed taking a medication history with a patient and prescribing medications. Each doctor reviewed their video footage and made plans to improve their prescribing, supported by feedback from a pharmacist. Quantitative data in the form of prescribing error prevalence data were collected on 1 day per week before, during and after the intervention period (between November 2015 and March 2017). Qualitative data in the form of individual semi-structured interviews were collected with a subset of participants, to evaluate their experience. Quantitative data were analysed using a statistical process chart and qualitative data were transcribed and analysed thematically.

Results: During the data collection period, 923 patient drug charts were reviewed by pharmacists who identified 1219 prescribing errors overall. Implementation of this feedback approach was associated with a statistically significant reduction in the mean number of prescribing errors, from 19.0/d to 11.7/d (estimated to equate to 38% reduction; P < .0001). Pharmacist-led video-stimulated prescribing feedback was feasible and positively received by participants, who appreciated the reinforcement of good practice as well as the opportunity to reflect on and improve practice.

Conclusions: Feedback to doctors-in-training tends to be infrequent and often negative, but this feasible feedback strategy significantly reduced prescribing errors and was well received by the target audience as a supportive developmental approach.

Keywords: clinical pharmacy; medical education; medication errors; patient safety; prescribing.

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Conflict of interest statement

Financial support for this project was provided as a Medical and Educational Goods and Service by Pfizer Ltd; and the South West Academic Health Science Network. We are grateful for their support, without which this project could not have happened.

Figures

Figure 1
Figure 1
Statistical process chart showing pharmacist interventions per day (each equating to a prescribing error) over 18 months on the surgical admissions unit. The dates are given on the X‐axis. The test phase is shaded white and is when the initial pulse of the intervention was carried out. The baseline data, to the left of this, was collected before the project. The sustain phase, to the right of this, is when the remainder of the participants took part in the intervention. The horizontal lines in the baseline and sustain phases show the mean, with lines above and below this representing 1, 2 and 3 sigma from the mean. The 3 sigma from the mean lines are also called the upper and lower control limits. These statistics show that the mean has significantly reduced in the sustain phase and the variance (sigma) has also reduced, since the lines are closer together
Figure 2
Figure 2
Weekly patient admissions data for the surgical admissions unit over the same time period as the statistical process chart in Figure 1, demonstrating an overall increasing trend (mean weekly admissions is 51.0 during the baseline period, 62.8 during the test period and 69.1 during the sustain period)

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