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P18 Prescribing errors in PICU: Identifying prevalence by drug and error type

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Context Patient safety is a priority for healthcare organisations worldwide and is a key factor in providing high quality healthcare. Prescribing medications correctly is critical to ensuring safety, especially in… Click to show full abstract

Context Patient safety is a priority for healthcare organisations worldwide and is a key factor in providing high quality healthcare. Prescribing medications correctly is critical to ensuring safety, especially in the setting of a Paediatric Intensive Care Unit (PICU) where patients are vulnerable to being exposed to incidents due to highly complex care and illness severity. In our 21 bedded PICU, any prescribing errors detected by critical care pharmacists are recorded on a prescribing error database each day (Microsoft Access). Information inputted includes the drug involved in the error, the route of administration, prescriber identifier number, type of error and category of error based on the NCC MERP1 classification system. Information is extracted monthly from this database to further populate a prescribing errors dashboard, highlighting the total number of prescribing errors each month and sub-categorising the number of errors according to drug cause and error type. Data collected in 2021 was analysed by our Trust’s Quality Improvement (QI) Team who generated pareto charts for the highest reported prescribing errors according to drug and error type. Although pharmacist data showed that many drugs were responsible for prescribing errors, pareto analysis by the QI team identified that Teicoplanin, Heparin, Fentanyl, Chloral Hydrate and Octenisan® were the drugs associated with the most frequent number of errors and causing the biggest cumulative impact on our prescribing error data. In terms of error type, pareto analysis identified that 80% of our cumulative errors were attributed to the wrong route, wrong dose or missing route of administration. Conclusion A pareto chart is a graph that indicates the frequency of defects as well as their cumulative impact. By applying this statistical control process to PICU prescribing error data for 2021, we were able to identify the drugs and error types responsible for the majority of our cumulative errors. Using the ‘Brilliant Basics’ methodology,2 we followed a two-step approach in dissecting our data. For step one, we analysed the data that we had and then in step two, using this analysis, we were able to agree and introduce measures to our prescribing systems in order to mitigate the risk of the errors re-occurring. These measures have included redesigning our PICU prescription to add or adapt prescribing recommendations for Teicoplanin, Heparin and Fentanyl, updating prescribing advice in our PICU electronic drugs formulary for Chloral Hydrate and placing an additional daily task on our nurses’ electronic task list to ensure Octenisan® is used. In terms of error type, we have raised awareness of the prevalence of the errors causing the biggest impact on reported prescribing errors, through the medium of pharmacy newsletters, which are disseminated to all PICU staff and by educating new PICU prescribers as part of their induction to the unit. To assess whether the above changes have contributed to an improvement in our reported errors by drug and type, we will continue to perform statistical analysis on prescribing data collected throughout 2022. References National Coordinating Council for Medication Error Reporting and Prevention. 2001. http://www.nccmerp.org/types-medication-errors Accessed 14 June 2022. A Catalyst for Better Health Strategy 2019/22. NHS Business Services Authority (V1) 03 2019. https://www.nhsbsa.nhs.uk/sites/default/files/2019-04/Strategy%202019-22%20%28V1%29%2003.2019.pdf

Keywords: prescribing errors; error type; error; picu; drug

Journal Title: Archives of Disease in Childhood
Year Published: 2023

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