loading page

An e-Delphi study to obtain expert consensus on the level of risk associated with preventable e-prescribing events.
  • +3
  • Sarah Slight,
  • Jude Heed,
  • Stephanie Klein,
  • Neil Watson,
  • Ann Slee,
  • Andy Husband
Sarah Slight
Newcastle University

Corresponding Author:[email protected]

Author Profile
Jude Heed
Newcastle University
Author Profile
Stephanie Klein
Newcastle Upon Tyne Hospitals NHS Foundation Trust
Author Profile
Neil Watson
Newcastle Upon Tyne Hospitals NHS Foundation Trust
Author Profile
Ann Slee
NHSX
Author Profile
Andy Husband
Newcastle University
Author Profile

Abstract

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.
30 Sep 2021Submitted to British Journal of Clinical Pharmacology
01 Oct 2021Submission Checks Completed
01 Oct 2021Assigned to Editor
20 Oct 2021Reviewer(s) Assigned
16 Nov 2021Review(s) Completed, Editorial Evaluation Pending
21 Nov 2021Editorial Decision: Revise Minor
10 Dec 20211st Revision Received
11 Dec 2021Submission Checks Completed
11 Dec 2021Assigned to Editor
11 Dec 2021Review(s) Completed, Editorial Evaluation Pending
26 Jan 2022Editorial Decision: Accept