Determining the cause and frequency of prescription reworks in community pharmacies

Abstract

Abstract Introduction When prescriptions are being processed in pharmacies and an activity occurs that requires the return to a previous procedural step to correct the process, this is known as ‘rework’ (1). This may include labelling errors or the incorrect dispensing of medications, and ultimately adds to pharmacists’ workload. Given that increasing community pharmacists’ workload negatively affects their job satisfaction, well-being, and patient care, it is vital that rework is minimised in everyday practice. To date, little is known regarding the prevalence of this rework phenomenon in community pharmacies or how this might be prevented. Aim To evaluate the cause and frequency of prescription rework in community pharmacies. Methods A data collection form was created for community pharmacists to self-record the instances and causes of prescription rework occurring in their workplace across a two-week period. After piloting the form with two pharmacists in different pharmacies, community pharmacists in Ireland were invited to participate in the study using convenience sampling and snowballing. Only participating pharmacists were aware of when data collection was occurring in their pharmacy to minimise the Hawthorne effect with other staff (2). Descriptive statistics were used to describe rework frequency according to the different causes, as well as the pharmacist and pharmacy characteristics. Results Eight participating pharmacists were recruited (four male and four female; median 4 years’ post-qualification experience) from five independent pharmacies and three chain pharmacies. In total, 325 reworks were recorded across 65 days between June 2021 and August 2021. Rework was recorded on 92.9% of the study days, with an average of 5 reworks/day – whereby the average per pharmacist ranged from 1.82 to 15 reworks/day. The data collection form’s pre-specified rework categories captured 91.7% of reworks, with the remainder assigned as ‘other’. The three most frequent rework categories were those due to labelling errors (22.8%), prepared prescriptions which required opening and repackaging (15.1%), and medication owed to patients (13.9%). The people involved in reworks included: pharmacists alone (33.5%), technicians alone (20.3%), pharmacists and technicians (14.8%), pharmacists and patients (10.2%), and pharmacists and prescribers (4%). Conclusion This study shows that rework happens regularly in community pharmacies and has provided an insight into the causes of rework in this setting. While individual pharmacist and pharmacy characteristics may have influenced rework frequency, it was not possible to conclusively establish these associations with the small sample size, due to the difficulty of recruiting pharmacists during the COVID-19 pandemic. These findings are valuable as they highlight areas where pharmacy staff can reduce rework and will help inform strategies to minimise this in future – thus reducing workload and facilitating more time for staff to focus on providing care to patients in community pharmacies. References (1) Nickman NA, Drews FA, Tyler LS, Kelly MP, Ragsdale RJ, Rim M. Use of multiple methods to measure impact of a centralized call center on academic health system community pharmacies. Am J Health Syst Pharm. 2019 Feb 21;76(6):353–9. (2) Sedgwick P, Greenwood N. Understanding the Hawthorne effect. BMJ. 2015 Sep 4;351:h4672.