A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care. (30th August 2016)

• Record Type: Journal Article
• Authors: Brown, Clare L; Mulcaster, Helen L; Triffitt, Katherine L; Sittig, Dean F; Ash, Joan S; Reygate, Katie; Husband, Andrew K; Bates, David W; Slight, Sarah P
• Is Part Of: Journal of the American Medical Informatics Association. Volume 24:Number 2(2017:Mar.)
• Page Start: 432
• Page End: 440
• Publication Date: 2016-08-30
• Subjects: computerized provider order entry -- clinical decision support -- alerts -- medication errors -- patient safety -- decision-making; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocw119
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract : Objective: To 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 Methods: We 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, 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. Results: A total of 1185 publications were identified, of which 34 were included in the review. We identified 8 key themes associated with CPOE-related prescribing errors: computer screen display, drop-down menus and auto-population, wording, default settings, nonintuitive or inflexible ordering, repeat prescriptions and automated processes, users' work processes, and clinical decision support 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 Conclusions: Human 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.