Clare L Brown1,2, Helen L Mulcaster1, Katherine L Triffitt1, Dean F Sittig3, Joan S Ash4, Katie Reygate5, Andrew K Husband1, David W Bates6,7,8, Sarah P Slight1,2,6. 1. Division of Pharmacy, School of Medicine, Pharmacy and Health, Durham University, Stockton on Tees, Durham, UK. 2. Newcastle upon Tyne hospitals NHS Foundation Trust, Queen Victoria Road, Newcastle upon Tyne, Tyne and Wear, UK. 3. School of Biomedical Informatics, The University of Texas Health Science Center at Houston, TX, USA. 4. Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA. 5. Health Education KSS Pharmacy, Downsmere Building, Princess Royal Hospital, West Sussex, UK. 6. The Center for Patient Safety Research and Practice, Division of General Internal Medicine, Brigham and Women's Hospital, Boston, MA, USA. 7. Harvard Medical School, Harvard University, Boston, MA, USA. 8. Harvard School of Public Health, Harvard University, Boston, MA, USA.
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.
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.
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