ArticleBritish journal of clinical pharmacology2022
An e-Delphi study to obtain expert consensus on the level of risk associated with preventable e-prescribing events.
Article in British journal of clinical pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- A simulation study to quantitatively assess the performance of electronic prescribing systems in English NHS Hospital Trusts.Scientific reports · 2025Article
- Construction of an Index System of the Biosafety Incident Response Capability for Nursing Staff: A Delphi Study.Nursing open · 2025Article
- Development and Implementation of a Clinical Decision Support System to Enhance Efficiency and Accuracy in Medication Prescription Review in a Tertiary Care Hospital: A Retrospective Hospital CDSS Register Study.Journal of multidisciplinary healthcare · 2025Article
- Clinical risk assessment of modelled situations in a pharmaceutical decision support system: a modified e-Delphi exploratory study.International journal of clinical pharmacy · 2024Article
- Orthopedics and Traumatology Skill Matrix for Musculoskeletal System Approach by Medical Graduates.Revista brasileira de ortopedia · 2023Article
- An e-Delphi study to obtain expert consensus on the level of risk associated with preventable e-prescribing events.British journal of clinical pharmacology · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsWe 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).
methodsWe conducted a two-round e-Delphi 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.
resultsTwenty-four experts consented to participate with 15 pand 13 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.
conclusionWe 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. Our e-Delphi 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.
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