Slight, S.P. (2017) 'A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care.', Journal of the American Medical Informatics Association., 24 (2). pp. 432-440.Further information on publisher's website:https://doi.org/10.1093/jamia/ocw119Publisher's copyright statement:This is a pre-copyedited, author-produced PDF of an article accepted for publication inJournal of the American Medical Informatics Association following peer review. The version of recordis available on the JAMIA website at https://doi.org/10.1093/jamia/ocw119Additional information: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-pro t purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. ABSTRACT ObjectiveTo understand the different types and causes of prescribing errors associated with computerized provider order entry (CPOE) systems, and recommend improvements in these systems. Materials and MethodsWe conducted a systematic review of the literature published between January 2004 and June 2015 using three large databases: the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase and Medline. Studies that reported qualitative data about the types and causes of these errors were included. A narrative synthesis of all eligible studies was undertaken. ResultsA total of 1,185 publications were identified, of which 34were included in the review. We identified eight key themes associated with CPOE-related prescribing errors: computer screen display, drop-down menus and auto-population, wording, default settings, non-intuitive or inflexible ordering, repeat prescriptions and automated processes, users' work processes, and CDS systems. Displaying an incomplete list of a patient's medications on the computer screen often contributed to prescribing errors. Lack of system flexibility resulted in users employing error prone workarounds, such as the addition of contradictory free-text comments. Users' misinterpretations of how text was presented in CPOE systems were also linked with the occurrence of prescribing errors. Discussion and ConclusionsHuman factors design is important to reduce error rates. Drop-down menus should be designed with safeguards to decrease the likelihood of selection errors. Development of more sophisticated clinical decision support, which can perform checks on free-text, may also prevent errors. Further research is needed to ensure that systems minimize error likelihood and meet users' workflow expectations. BACKGROUND AND SIGNIFICANCE
Objectives A key element of the implementation and ongoing use of an electronic prescribing (ePrescribing) system is ensuring that users are, and remain, sufficiently trained to use the system. Studies have suggested that insufficient training is associated with suboptimal use. However, it is not clear from these studies how clinicians are trained to use ePrescribing systems or the effectiveness of different approaches. We sought to describe the various approaches used to train qualified prescribers on ePrescribing systems and to identify whether users were educated about the pitfalls and challenges of using these systems. Methods We performed a literature review, using a systematic approach across three large databases: Cumulative Index Nursing and Allied Health Literature, Embase and Medline were searched for relevant English language articles. Articles that explored the training of qualified prescribers on ePrescribing systems in a hospital setting were included. Key findings Our search of ‘all training’ approaches returned 1155 publications, of which seven were included. A separate search of ‘online’ training found three relevant publications. Training methods in the ‘all training’ category included clinical scenarios, demonstrations and assessments. Regarding ‘online’ training approaches; a team at the University of Victoria in Canada developed a portal containing simulated versions of electronic health records, where individuals could prescribe for fictitious patients. Educating prescribers about the challenges and pitfalls of electronic systems was rarely discussed. Conclusions A number of methods are used to train prescribers; however, the lack of papers retrieved suggests a need for additional studies to inform training methods.
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