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Assessing the Impact of the Transition to an Enterprise-Wide Health Information System on Pharmacy Performance.
| dc.contributor.advisor | Weibel, Kurt | en |
| dc.contributor.author | Boyles, Steven | |
| dc.contributor.author | Weibel, Kurt | |
| dc.date.accessioned | 2016-06-22T19:21:07Z | |
| dc.date.available | 2016-06-22T19:21:07Z | |
| dc.date.issued | 2014 | |
| dc.identifier.uri | http://hdl.handle.net/10150/614181 | |
| dc.description | Class of 2014 Abstract | en |
| dc.description.abstract | Specific Aims: The purpose of this study is to quantitatively analyze the pharmacy department’s performance before and after the transition from a segmented set of information technology systems to an enterprise wide electronic health record. Methods: This prospective, observational study collected data from both the pre-implementation and post-implementation electronic systems. The enterprise wide electronic system was implemented on November 1, 2013. Medication turnaround time, missing medication requests, and profile-linked automated dispensing cabinet (ADC) override rates were measured before implementation (August and September 2013) and after implementation (November 2013 and January, February, and March 2014). This study did not use patient specific data and does not involve human subjects and therefore was exempt from Institutional Review Board review. Main Results: Average medication turnaround time in November 2013 (1243.6 seconds; 95% CI 1219.55-1267.73) was significantly slower than in September 2013 (697.71 seconds; 95% CI 685.45-709.97; p<0.001). In January 2014, there was no difference (695.45 seconds; 95% CI 678.17-712.73; p = 0.83) and February 2014 showed significant improvement (619.09 seconds; 95% CI 605.18-633.00; p<0.001). There were significantly more missing medication requests in February (19002) and March 2014 (18996) than in August 2013 (1319; p<0.001 for both). The ADC override rate was significantly higher in November 2013 (5.87%) than in August 2013 (3.98%; p<.001) and lower in February 2014 (3.16%; p<0.001). Conclusion: This study suggests that implementation of an enterprise-wide electronic health record has led to improved pharmacy order processing efficiency and allowed for increased communication between healthcare professionals, albeit with a loss of efficiency initially. | |
| dc.language.iso | en_US | en |
| dc.publisher | The University of Arizona. | en |
| dc.rights | Copyright © is held by the author. | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
| dc.subject | Assessing | en |
| dc.subject | health information system | en |
| dc.subject | pharmacy | en |
| dc.subject | performance | en |
| dc.subject.mesh | Pharmacies | |
| dc.subject.mesh | Technology, Pharmaceutical | |
| dc.subject.mesh | Electronic Health Records | |
| dc.title | Assessing the Impact of the Transition to an Enterprise-Wide Health Information System on Pharmacy Performance. | en_US |
| dc.type | text | en |
| dc.type | Electronic Report | en |
| dc.contributor.department | College of Pharmacy, The University of Arizona | en |
| dc.description.collectioninformation | This 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.abstract | Specific Aims: The purpose of this study is to quantitatively analyze the pharmacy department’s performance before and after the transition from a segmented set of information technology systems to an enterprise wide electronic health record. Methods: This prospective, observational study collected data from both the pre-implementation and post-implementation electronic systems. The enterprise wide electronic system was implemented on November 1, 2013. Medication turnaround time, missing medication requests, and profile-linked automated dispensing cabinet (ADC) override rates were measured before implementation (August and September 2013) and after implementation (November 2013 and January, February, and March 2014). This study did not use patient specific data and does not involve human subjects and therefore was exempt from Institutional Review Board review. Main Results: Average medication turnaround time in November 2013 (1243.6 seconds; 95% CI 1219.55-1267.73) was significantly slower than in September 2013 (697.71 seconds; 95% CI 685.45-709.97; p<0.001). In January 2014, there was no difference (695.45 seconds; 95% CI 678.17-712.73; p = 0.83) and February 2014 showed significant improvement (619.09 seconds; 95% CI 605.18-633.00; p<0.001). There were significantly more missing medication requests in February (19002) and March 2014 (18996) than in August 2013 (1319; p<0.001 for both). The ADC override rate was significantly higher in November 2013 (5.87%) than in August 2013 (3.98%; p<.001) and lower in February 2014 (3.16%; p<0.001). Conclusion: This study suggests that implementation of an enterprise-wide electronic health record has led to improved pharmacy order processing efficiency and allowed for increased communication between healthcare professionals, albeit with a loss of efficiency initially. |