scholarly journals Medication-related Clinical Decision Support in Computerized Provider Order Entry Systems: A Review

2007 ◽  
Vol 14 (1) ◽  
pp. 29-40 ◽  
Author(s):  
G. J. Kuperman ◽  
A. Bobb ◽  
T. H. Payne ◽  
A. J. Avery ◽  
T. K. Gandhi ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Order Entry ◽  
Computerized Provider Order Entry ◽  
Order Entry Systems

Verhindern von unerwünschten Arzneimittelereignissen mit Hilfe von elektronischen Entscheidungsunterstützungssystemen

2015 ◽  
Vol 72 (11/12) ◽  
pp. 693-700
Author(s):  
Ali Reza Salili ◽  
Felix Hammann ◽  
Anne B. Taegtmeyer
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Computerized Physician Order Entry ◽  
Order Entry ◽  
Computerized Provider Order Entry ◽  
Unerwünschte Arzneimittelereignisse ◽  
Physician Order Entry

Zusammenfassung. Unerwünschte Arzneimittelereignisse sind ein grosses Risiko für Patienten und ein alltägliches klinisches Problem mit potentiellen Haftungsfolgen. CPOE-Systeme („Computerized Physician Order Entry“ bzw. „Computerized Provider Order Entry“-Systeme) in Kombination mit elektronischen Systemen zur klinischen Entscheidungsunterstützung („Clinical Decision Support System“ = „CDSS“) sind im Trend und zielen nicht nur auf die Reduktion von Verordnungsfehlern, sondern ermöglichen eine rasche Reaktion auf potentiell vermeidbare Arzneimittelinteraktionen. Der effektive Nutzen solcher Systeme ist aber bis dato noch nicht definitiv geklärt. Dieser Artikel fokussiert auf den aktuellen Stand der Entwicklung von CPOE-/CDS-Systemen, deren Nutzen und Risiken, Zukunftsperspektiven und Verbesserungsmöglichkeiten.

scholarly journals A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care

2016 ◽  
Vol 24 (2) ◽  
pp. 432-440 ◽  
Author(s):  
Clare L Brown ◽  
Helen L Mulcaster ◽  
Katherine L Triffitt ◽  
Dean F Sittig ◽  
Joan S Ash ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Error Rates ◽  
Free Text ◽  
Prescribing Errors ◽  
Order Entry ◽  
Computerized Provider Order Entry ◽  
Computer Screen

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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