Objectives: The e-prescribing risk and safety evaluation (ePRaSE) tool was developed to support the evaluation of hospital e-prescribing systems. The tool uses fictitious patients alongside previously validated prescribing scenarios to detect whether these systems provide prescribing advice to users, when completing inpatient prescribing tasks. We sought to evaluate the usability and acceptability of ePRaSE for clinical informatics pharmacy staff using different e-prescribing systems in NHS hospitals across England. Materials and methods: All NHS hospitals in England with live e-prescribing systems were invited to participate via an email invitation to the chief pharmacists. Participants were asked to complete the four-stage ePRaSE assessment, whilst verbalising their thoughts and sharing their perspectives on the acceptability and usability of the assessment. The data were transcribed verbatim, coded and analysed using the Framework Approach. Results: Ten participants from ten different hospitals across England conducted the ePRaSE assessment between April and December 2019. They completed the assessment in 2-3 hours and described the tool as easy to use and the prescribing scenarios as clinically relevant. However, some participants experienced difficulties inputting clinical data, such as laboratory results, often due to restricted access to input data into different parts of the electronic health record. Many participants suggested areas for further improvement and suggested more detailed results on completion of ePRaSE was desirable. Conclusions: E-prescribing system users found ePRaSE to be a useful and acceptable tool. Further work to refine the tool is desirable, particularly relating to the provision of results to ePRaSE users.

Objectives We aim to seek expert opinion and gain consensus on the risks associated with a range of prescribing scenarios, preventable using e-prescribing systems, to inform the development of a simulation tool to evaluate the risk and safety of e-prescribing systems (ePRaSE). Methods We conducted a two-round eDelphi survey where expert participants were asked to score pre-designed prescribing scenarios using a five-point Likert scale to ascertain the likelihood of occurrence of the prescribing event, likelihood of occurrence of harm and the severity of the harm. Results Twenty four experts consented to participate with fifteen participants and thirteen participants completing rounds 1 and 2 respectively. Experts agreed on the level of risk associated with 136 out of 178 clinical scenarios with 131 scenarios categorised as high or extreme risk. Discussion We identified 131 extreme or high-risk prescribing scenarios that may be prevented using e-prescribing clinical decision support. The prescribing scenarios represent a variety of categories, with drug-disease contraindications, being the most frequent representing 37 (27%) scenarios and antimicrobial agents being the most common drug class representing 28 (21%) of the scenarios. Conclusion Our eDelphi study has achieved expert consensus on the risk associated with a range of clinical scenarios with most of the scenarios categorised as extreme or high risk. These prescribing scenarios represent the breadth of preventable prescribing error categories involving both basic and advanced clinical decision support. We will use the findings of this study to inform the development of the e-prescribing risk and safety evaluation tool.