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dc.contributor.advisorSoble-Lernor, Michelleen
dc.contributor.authorMcCusker, Erin
dc.contributor.authorDeSefano, Ashley
dc.contributor.authorSoble-Lernor, Michelle
dc.date.accessioned2016-06-22T21:17:46Z
dc.date.available2016-06-22T21:17:46Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/10150/614254
dc.descriptionClass of 2013 Abstracten
dc.description.abstractSpecific Aims: The purpose of this study was to investigate areas of ambiguity or error in the content of prescriptions generated using DrFirst’s electronic prescribing software Rcopia adetermines whether these quality issues are attributed to the software, physician, or both. Methods: Electronic prescriptions generated by DrFirst electronic prescribing software, Rcopia, from July 2012 through September 2012 were analyzed regarding the following metrics: number of free text prescriptions, quantity unit mismatches, and SIG issues. These metrics were expressed as a percentage of the total number of prescriptions generated for each month and used for descriptive analysis. Main Results: The total number of prescriptions generated were 12,043,268, of which 363,142 (3%) were free text (uncoded) and 11,680,126 (97%) were non-free text. SIG as directed was identified in 227,732 prescriptions, of which 11,208 (3.1%) were free text and 216,524(1.9%) were non-free text. Double SIG was identified in 174,625 prescriptions, of which 75,336 (20.1%) were free text and 1,746,250 (14.1%) were non-free text. A total of 830 (0.23%) of free text prescriptions contained a Latin abbreviation. Of 621,816 prescriptions containing a quantity unit error, 7,684 (2.1%) were free text prescriptions and 614,132 (5.3%) were non-free text prescriptions. Conclusion: The authors concluded that the software and physician are responsible for error. There were errors associated with selections made by the prescriber in the drop down menus and coded medications in Rcopia. Furthermore, errors were found in free text prescriptions which must be manually entered by the physician or their staff. 
dc.language.isoen_USen
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author.en
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectprescriptionen
dc.subjecterroren
dc.subjectfaulten
dc.subject.meshElectronic Prescribing
dc.subject.meshMedication Errors
dc.titleIdentifying Causes of Electronic Prescription Error: is the Software or Physician at Fault?en_US
dc.typetexten
dc.typeElectronic Reporten
dc.contributor.departmentCollege of Pharmacy, The University of Arizonaen
dc.description.collectioninformationThis item is part of the Pharmacy Student Research Projects collection, made available by the College of Pharmacy and the University Libraries at the University of Arizona. For more information about items in this collection, please contact Jennifer Martin, Librarian and Clinical Instructor, Pharmacy Practice and Science, jenmartin@email.arizona.edu.en
html.description.abstractSpecific Aims: The purpose of this study was to investigate areas of ambiguity or error in the content of prescriptions generated using DrFirst’s electronic prescribing software Rcopia adetermines whether these quality issues are attributed to the software, physician, or both. Methods: Electronic prescriptions generated by DrFirst electronic prescribing software, Rcopia, from July 2012 through September 2012 were analyzed regarding the following metrics: number of free text prescriptions, quantity unit mismatches, and SIG issues. These metrics were expressed as a percentage of the total number of prescriptions generated for each month and used for descriptive analysis. Main Results: The total number of prescriptions generated were 12,043,268, of which 363,142 (3%) were free text (uncoded) and 11,680,126 (97%) were non-free text. SIG as directed was identified in 227,732 prescriptions, of which 11,208 (3.1%) were free text and 216,524(1.9%) were non-free text. Double SIG was identified in 174,625 prescriptions, of which 75,336 (20.1%) were free text and 1,746,250 (14.1%) were non-free text. A total of 830 (0.23%) of free text prescriptions contained a Latin abbreviation. Of 621,816 prescriptions containing a quantity unit error, 7,684 (2.1%) were free text prescriptions and 614,132 (5.3%) were non-free text prescriptions. Conclusion: The authors concluded that the software and physician are responsible for error. There were errors associated with selections made by the prescriber in the drop down menus and coded medications in Rcopia. Furthermore, errors were found in free text prescriptions which must be manually entered by the physician or their staff. 


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