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AMU patient list generation: from junior scribe to junior doctor
Zahra Ravat1, Amil Sinha2, Alistair Jellinek2
1Acute Medical Unit, Sandwell and West Birmingham Hospitals NHS Trust, Birmingham, UK zahra.ravat4@nhs.net.
Abstract:
This quality improvement project (QIP) aimed to assess the impact of automating patient list generation on the acute medical unit (AMU) at Sandwell and West Birmingham Hospitals NHS Trust. The AMU patient list categorises patients requiring 'clerking', 'post-take' (PTWR) and 'post-post-take' (PPTWR) for the morning ward round. During weekdays, this list need only include the patients in AMU. For weekends, this list must include 'outliers', that is, patients transferred to different wards (which may lack resident medical teams over the weekends) but still requiring PTWR/PPTWR. The list is created by the junior doctor on their night shift, a daily necessity due to the high AMU patient turnover.A pilot study, followed by three complete 'plan-do-study-act' (PDSA) cycles, was conducted over 2021/2022. Cycle 1 (pre-intervention) and cycle 2 (post-intervention) assessed the impact of the generator on weekdays. This was adapted for the weekend over cycles 2 and 3. The process measure assessed was the time taken for list generation. The outcome measure was the total number of patients clerked per night. The balancing measure was doctors' attitudes.The intervention reduced the time taken for list generation by an average of 44.3 min (66.3%) during weekdays and 37.8 min (42%) during weekends. Run charts demonstrated significance for the reduction in weekday list generation time. Both weekdays (63.5% decrease, p<0.00001) and weekends (50.5% decrease, p=0.0007) had significant reductions in total negative attitudes. Both weekdays and weekends had 'time-consuming' as the most frequently selected attitude pre-intervention, whereas 'easy to make' was most frequently selected post-intervention. Some junior doctors reported the generator enabled clerking of extra patients, supported by non-significant increases in the averages for this outcome.This QIP demonstrates how the automation of labour-intensive administrative tasks results in notable time-saving outcomes. Thereby improving doctor attitudes and well-being, and facilitating the delivery of quality patient care.
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