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Journal articles on the topic 'Computerised prescriber order entry'

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Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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1

Classen, David, David W. Bates, and Charles R. Denham. "Meaningful Use of Computerized Prescriber Order Entry." Journal of Patient Safety 6, no. 1 (March 2010): 15–23. http://dx.doi.org/10.1097/pts.0b013e3181d108db.

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2

Hastings, Clare. "Reduce errors with computerized prescriber order entry." Nursing Management (Springhouse) 37, no. 12 (December 2006): 68. http://dx.doi.org/10.1097/00006247-200612000-00021.

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3

Lieder, Tzipora R. "Computerized prescriber order entry changes pharmacists’ roles." American Journal of Health-System Pharmacy 58, no. 10 (May 15, 2001): 846–51. http://dx.doi.org/10.1093/ajhp/58.10.846.

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4

Schiff, Gordon D. "Computerized prescriber order entry: Models and hurdles." American Journal of Health-System Pharmacy 59, no. 15 (August 1, 2002): 1456–60. http://dx.doi.org/10.1093/ajhp/59.15.1456.

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5

Gouveia, William A., Rita Shane, and Toby Clark. "Computerized prescriber order entry: power, not Panacea." American Journal of Health-System Pharmacy 60, no. 18 (September 15, 2003): 1838. http://dx.doi.org/10.1093/ajhp/60.18.1838.

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6

Miller, Alicia S. "Quality and Operations Improvement: Order Set Development and Maintenance." Hospital Pharmacy 37, no. 7 (July 2002): 765–69. http://dx.doi.org/10.1177/001857870203700703.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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7

Inquilla, Carmen C., Sheryl Szeinbach, Enrique Seoane-Vazquez, and Karl H. Kappeler. "Pharmacists’ perceptions of computerized prescriber-order-entry systems." American Journal of Health-System Pharmacy 64, no. 15 (August 1, 2007): 1626–32. http://dx.doi.org/10.2146/ajhp060236.

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8

Ballentine, Amanda J., Daniel Kinnaird, and James P. Wilson. "Prescription errors occur despite computerized prescriber order entry." American Journal of Health-System Pharmacy 60, no. 7 (April 1, 2003): 708–9. http://dx.doi.org/10.1093/ajhp/60.7.708.

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9

Jozefczyk, Kenneth G., William Klugh Kennedy, Miranda Jackson Lin, Julie Achatz, Maresa DiMarco Glass, W. Susie Eidam, and Michael J. Melroy. "Computerized Prescriber Order Entry and Opportunities for Medication Errors." Journal of Pharmacy Practice 26, no. 4 (March 5, 2013): 434–37. http://dx.doi.org/10.1177/0897190012465982.

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Purpose: Predefined error opportunity categories were used as a surrogate for medication errors to assess the impact of computerized prescriber order entry (CPOE) on the potential for error in the prescribing and order entry phases of the medication-use process. Methods: This study was performed in a neonatal intensive care unit at a 535-bed tertiary care center. Pre- and post-CPOE implementation incidence of error opportunity was compared by evaluating 500 orders before and after implementation using 18 predefined criteria. Results: A total of 14 913 opportunities for error (OE) existed in our sample of 1000 medication orders. The number of orders with zero OE improved from 42% (n = 209) to 98% (n = 480; P < .0001), in the pre- and postgroups, respectively. The odds ratio with 95% confidence interval was 0.058 (0.036-0.094) in favor of CPOE. Conclusions: The implementation of CPOE was associated with a reduction in OEs in the prescribing phase or order entry phase of the medication-use process.

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10

Hilmas, Elora, and Joseph D. Peoples. "Parenteral Nutrition Prescribing Processes Using Computerized Prescriber Order Entry." Journal of Parenteral and Enteral Nutrition 36, no. 2_suppl (February 2012): 32S—35S. http://dx.doi.org/10.1177/0148607111435510.

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11

Senholzi, Craig, and Jonathan Gottlieb. "Pharmacist interventions after implementation of computerized prescriber order entry." American Journal of Health-System Pharmacy 60, no. 18 (September 15, 2003): 1880–82. http://dx.doi.org/10.1093/ajhp/60.18.1880.

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12

Gray, Michael D., and Bill G. Felkey. "Computerized prescriber order-entry systems: evaluation, selection, and implementation." American Journal of Health-System Pharmacy 61, no. 2 (January 15, 2004): 190–97. http://dx.doi.org/10.1093/ajhp/61.2.190.

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13

Jones, James L. "Implementing Computerized Prescriber Order Entry in a Children's Hospital." American Journal of Health-System Pharmacy 61, no. 22 (November 15, 2004): 2425–29. http://dx.doi.org/10.1093/ajhp/61.22.2425.

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14

Wietholter, Jon, Susan Sitterson, and Steven Allison. "Effects of computerized prescriber order entry on pharmacy order-processing time." American Journal of Health-System Pharmacy 66, no. 15 (August 1, 2009): 1394–98. http://dx.doi.org/10.2146/ajhp080303.

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15

Forrer, C., S. Shaha, and S. Magid. "Duplicate Orders: An Unintended Consequence of Computerized provider/physician order entry (CPOE) Implementation." Applied Clinical Informatics 03, no. 04 (2012): 377–91. http://dx.doi.org/10.4338/aci-2012-01-ra-0002.

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SummaryObjective: Computerized provider/physician order entry (CPOE) with clinical decision support (CDS) is designed to improve patient safety. However, a number of unintended consequences which include duplicate ordering have been reported. The objective of this time-series study was to characterize duplicate orders and devise strategies to minimize them.Methods: Time series design with systematic weekly sampling for 84 weeks. Each week we queried the CPOE database, downloaded all active orders onto a spreadsheet, and highlighted duplicate orders. We noted the following details for each duplicate order: time, order details (e.g. drug, dose, route and frequency), ordering prescriber, including position and role, and whether the orders originated from a single order or from an order set (and the name of the order set). This analysis led to a number of interventions, including changes in: order sets, workflow, prescriber training, pharmacy procedures, and duplicate alerts.Results: Duplicates were more likely to originate from different prescribers than from same prescribers; and from order sets than from single orders. After interventions, there was an 84.8% decrease in the duplication rate from weeks 1 to 84 and a 94.6% decrease from the highest (1) to the lowest week (75). Currently, we have negligible duplicate orders.Conclusions: Duplicate orders can be a significant unintended consequence of CPOE. By analyzing these orders, we were able to devise and implement generalizable strategies that significantly reduced them. The incidence of duplicate orders before CPOE implementation is unknown, and our data originate from a weekly snapshot of active orders, which serves as a sample of total active orders. Thus, it should be noted that this methodology likely under-reports duplicate orders.Citation: Magid S, Forrer C, Shaha S. Duplicate Orders: An unintended consequence of computerized provider/physician order entry (CPOE) implementation. Analysis and mitigation strategies. Appl Clin Inf 2012; 3: 377–391http://dx.doi.org/10.4338/ACI-2012-01-RA-0002

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16

Schreiber, Richard, and Steven H. Shaha. "Computerised Provider Order Entry Adoption Rates Favourably Impact Length of Stay." Journal of Innovation in Health Informatics 23, no. 1 (April 18, 2016): 459. http://dx.doi.org/10.14236/jhi.v23i1.166.

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Background Research regarding return on investment for electronic health records (EHRs) is sparse.Objective To extend previously established research and examine rigorously whether increasing the adoption of computer-based provider/prescriber order entry (CPOE) leads to a decrease in length of stay (LOS), and to demonstrate that the two are inversely and bidirectionally proportional even while other efforts to decrease LOS are in place.Method The study assessed CPOE, LOS and case mix index (CMI) data in a community hospital in the United States, using a mature and nearly fully deployed vendor product EHR. CPOE rates and LOS over 7 years were determined on a per-patient, per-visit and per-discipline basis and compared with concomitant CMI data.Results An inverse relationship of CPOE to LOS was correlated for 13 disciplines out of 19, and organisation wide for all disciplines combined during the first 5 years of study. During the subsequent 2 years, both CPOE and LOS plateaued, except in eight disciplines where CPOE rates at first declined and LOS concurrently rose slightly, and then returned to the baseline plateau levels. CMI increased during the entire period of evaluation. An inflection point at approximately 60% CPOE adoption predicted the greatest improvement in lowering of LOS.Conclusions Rising and falling rates of CPOE correlated with reductions and rises in LOS, respectively. CPOE appeared statistically to be an independent factor in affecting LOS, over and above other efforts to shorten LOS, thus contributing to lower costs and improved efficiency outcomes as measured by LOS, even as CMI rises.

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17

Miller, Alicia S. "Pharmacy Issues: Clinical Screenings and Discharge Prescriptions." Hospital Pharmacy 36, no. 12 (December 2001): 1290–93. http://dx.doi.org/10.1177/001857870103601210.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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18

Miller, Alicia S. "Implementing the Rules Engine." Hospital Pharmacy 37, no. 4 (April 2002): 413–17. http://dx.doi.org/10.1177/001857870203700411.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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19

Miller, Alicia S. "Quality and Operations Improvement: Medication Error Reduction." Hospital Pharmacy 37, no. 5 (May 2002): 534–36. http://dx.doi.org/10.1177/001857870203700512.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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20

Miller, Alicia S. "Quality and Operations Improvement: Medication Turnaround Time." Hospital Pharmacy 37, no. 6 (June 2002): 644–47. http://dx.doi.org/10.1177/001857870203700604.

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Abstract:

This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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21

Miller, Alicia S. "Security Issues." Hospital Pharmacy 37, no. 8 (August 2002): 867–70. http://dx.doi.org/10.1177/001857870203700804.

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Abstract:

This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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22

Miller, Alicia S. "Policy Impact." Hospital Pharmacy 37, no. 9 (September 2002): 985–89. http://dx.doi.org/10.1177/001857870203700905.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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23

Miller, Alicia S. "The Implementation Process (Part 1)." Hospital Pharmacy 37, no. 10 (October 2002): 1104–6. http://dx.doi.org/10.1177/001857870203701003.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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24

Miller, Alicia S. "The Implementation Process (Part 2)." Hospital Pharmacy 37, no. 11 (November 2002): 1218–21. http://dx.doi.org/10.1177/001857870203701104.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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25

Miller, Alicia S. "The Implementation Process (Part 3)." Hospital Pharmacy 37, no. 12 (December 2002): 1343–47. http://dx.doi.org/10.1177/001857870203701204.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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26

Miller, Alicia S. "The Training Process (Part 1)." Hospital Pharmacy 38, no. 1 (January 2003): 84–88. http://dx.doi.org/10.1177/001857870303800104.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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27

Miller, Alicia S. "Support Considerations (Part 1)." Hospital Pharmacy 38, no. 3 (March 2003): 276–78. http://dx.doi.org/10.1177/001857870303800304.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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28

Miller, Alicia S. "Downtime Procedures (Part 2)." Hospital Pharmacy 38, no. 7 (July 2003): 694–97. http://dx.doi.org/10.1177/001857870303800703.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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29

Chaffee, Bruce W. "Future of clinical decision support in computerized prescriber order entry." American Journal of Health-System Pharmacy 67, no. 11 (June 1, 2010): 932–35. http://dx.doi.org/10.2146/ajhp090194.

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30

Kinnaird, Daniel, Tamara Cox, and James P. Wilson. "Unclaimed prescriptions in a clinic with computerized prescriber order entry." American Journal of Health-System Pharmacy 60, no. 14 (July 15, 2003): 1468–70. http://dx.doi.org/10.1093/ajhp/60.13.1468.

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31

Vélez-Díaz-Pallarés, Manuel, Covadonga Pérez-Menéndez-Conde, and Teresa Bermejo-Vicedo. "Systematic review of computerized prescriber order entry and clinical decision support." American Journal of Health-System Pharmacy 75, no. 23 (December 1, 2018): 1909–21. http://dx.doi.org/10.2146/ajhp170870.

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32

Hunteman, Lori, Leah Ward, Diane Read, Mona Jolly, and Michael Heckman. "Analysis of allergy alerts within a computerized prescriber-order-entry system." American Journal of Health-System Pharmacy 66, no. 4 (February 15, 2009): 373–77. http://dx.doi.org/10.2146/ajhp080328.

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33

Cooley, Thomas W., Dianne May, Michael Alwan, and Caron Sue. "Implementation of computerized prescriber order entry in four academic medical centers." American Journal of Health-System Pharmacy 69, no. 24 (December 15, 2012): 2166–73. http://dx.doi.org/10.2146/ajhp120108.

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34

Ney, John P., and Allison L. Weathers. "Computerized prescriber order entry and opiate prescription in ambulatory care visits." Journal of the American Pharmacists Association 59, no. 2 (March 2019): S52—S56. http://dx.doi.org/10.1016/j.japh.2019.01.010.

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35

Drake, Eleni, Pavithra Srinivas, and Tate Trujillo. "Using computerized prescriber order entry to limit overrides from automated dispensing cabinets." American Journal of Health-System Pharmacy 73, no. 14 (July 15, 2016): 1033–35. http://dx.doi.org/10.2146/ajhp150564.

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36

Gaffoor, Mohamed, Vinay Vaidya, Azizeh Sowan, Soeken Karen, Mary Etta Mills, Meg Johantgen, and Elora Hilmas. "COMPUTERIZED PHYSICIAN ORDER ENTRY (CPOE) REDUCES PRESCRIBER ERRORS FOR CONTINUOUS MEDICATION INFUSIONS." Critical Care Medicine 33 (December 2005): A93. http://dx.doi.org/10.1097/00003246-200512002-00328.

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37

Bastani, A., R. Walch, B. Todd, S. Dimsdale, D. Donaldson, B. Dennis, D. Bonanno, and W. Anderson. "253: Computerized Prescriber Order Entry Decreases Patient Satisfaction and Emergency Physician Productivity." Annals of Emergency Medicine 56, no. 3 (September 2010): S83—S84. http://dx.doi.org/10.1016/j.annemergmed.2010.06.302.

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38

Spencer, Donald C., Aaron Leininger, Rowell Daniels, Robert P. Granko, and Remy R. Coeytaux. "Effect of a computerized prescriber-order-entry system on reported medication errors." American Journal of Health-System Pharmacy 62, no. 4 (February 1, 2005): 416–19. http://dx.doi.org/10.1093/ajhp/62.4.0416.

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39

Spencer, Donald C., Aaron Leininger, Rowell Daniels, Robert P. Granko, and Remy R. Coeytaux. "Effect of a computerized prescriber-order-entry system on reported medication errors." American Journal of Health-System Pharmacy 62, no. 4 (February 15, 2005): 416–19. http://dx.doi.org/10.1093/ajhp/62.4.416.

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40

Miller, Alicia S. "The Training Process (Part 2)." Hospital Pharmacy 38, no. 2 (February 2003): 175–77. http://dx.doi.org/10.1177/001857870303800205.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “prescribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center. Questions or suggestions should be addressed to Alicia S. Miller, Department of Pharmacy, The Ohio State University Medical Center, 368 Doan Hall, 410 West 10th Avenue, Columbus, OH 43210. E-mail: miller-4@medctr.osu.edu

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41

McMullen, Carmit K., Tara A. Macey, Jill Pope, Brian Gugerty, Marti Slot, Peter Lundeen, Joan Ash, and Neil Carlson. "Effect of computerized prescriber order entry on pharmacy: Experience of one health system." American Journal of Health-System Pharmacy 72, no. 2 (January 15, 2015): 133–42. http://dx.doi.org/10.2146/ajhp140106.

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42

Chan, Agnes L. F., Hue-Yu Wang, and Henry W. C. Leung. "Incorporation of a gentamicin dosage calculator into a computerized prescriber-order-entry system." American Journal of Health-System Pharmacy 63, no. 14 (July 15, 2006): 1344–45. http://dx.doi.org/10.2146/ajhp050474.

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43

Felkey, Bill G., and Brent I. Fox. "The Dilemma of Interfaced versus Integrated Computerized Prescriber Order Entry and Other Applications." Hospital Pharmacy 47, no. 6 (June 2012): 477–78. http://dx.doi.org/10.1310/hpj4706-477.

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44

Hertz, Sherrie, John Gilks, Leonard Kaizer, Marta Yurcan, and Vishal Kukreti. "Concordance with best-practice guidelines for systemic treatment computerized prescriber order entry systems." Journal of Clinical Oncology 31, no. 31_suppl (November 1, 2013): 245. http://dx.doi.org/10.1200/jco.2013.31.31_suppl.245.

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245 Background: In 2012, Cancer Care Ontario, released evidence-based guidance for the key features, functionalities, and components of a Systemic Treatment Computerized Prescriber Order Entry (ST CPOE) system to ensure safe, high-quality care. Concordance measurement indicators were developed alongside the guidelines and a survey was then conducted to understand the current state in a meaningful and practical manner in the province of Ontario. Methods: A self-assessment survey was distributed to 22 hospital groups, including cancer centres and both academic and community hospitals, using four different ST CPOE systems in Ontario. 52 items were assessed on a four-point Likert scale, and descriptive hospital data was collected. Composite scores were calculated by category (regimen and protocols, functionality, useful alerts, audit logs, system integration, usability) and overall. Local and provincial results were analyzed. Results: Twenty-one (21) responses were received, with the majority (17) of surveys being completed by pharmacists. 48% had been using a ST CPOE system for more than 5 years and 38% for less than one year. 81% responded that they did not, or did not know if, they had local/institutional indicators for monitoring their systems. The mean total concordance score overall was 79% (range 65% to 92%) of a potential 208 total points. The highest mean score was in the category of audit logs (92%) and the lowest in system integration (69%). Approximately half (48%) had a multidisciplinary ST CPOE advisory group. While 16 hospitals were using the same ST CPOE system, there was distinct variability in responses from these sites, indicating the effects of tailored implementations and/or discrepancy in level of knowledge of system functionalities. Conclusions: Current concordance with best practice guidelines for ST CPOE systems in Ontario is incomplete and variable. While ST CPOE systems have potential to improve safety in the chemotherapy delivery, differences in system functionalities and their implementation have been identified. This study will be used to inform specific areas of strength, set benchmarks and potential areas for improvement.

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45

Amato, Mary G., Alejandra Salazar, Thu-Trang T. Hickman, Arbor JL Quist, Lynn A. Volk, Adam Wright, Dustin McEvoy, et al. "Computerized prescriber order entry–related patient safety reports: analysis of 2522 medication errors." Journal of the American Medical Informatics Association 24, no. 2 (September 27, 2016): 316–22. http://dx.doi.org/10.1093/jamia/ocw125.

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Objective: To examine medication errors potentially related to computerized prescriber order entry (CPOE) and refine a previously published taxonomy to classify them. Materials and Methods: We reviewed all patient safety medication reports that occurred in the medication ordering phase from 6 sites participating in a United States Food and Drug Administration–sponsored project examining CPOE safety. Two pharmacists independently reviewed each report to confirm whether the error occurred in the ordering/prescribing phase and was related to CPOE. For those related to CPOE, we assessed whether CPOE facilitated (actively contributed to) the error or failed to prevent the error (did not directly cause it, but optimal systems could have potentially prevented it). A previously developed taxonomy was iteratively refined to classify the reports. Results: Of 2522 medication error reports, 1308 (51.9%) were related to CPOE. Of these, CPOE facilitated the error in 171 (13.1%) and potentially could have prevented the error in 1137 (86.9%). The most frequent categories of “what happened to the patient” were delays in medication reaching the patient, potentially receiving duplicate drugs, or receiving a higher dose than indicated. The most frequent categories for “what happened in CPOE” included orders not routed to or received at the intended location, wrong dose ordered, and duplicate orders. Variations were seen in the format, categorization, and quality of reports, resulting in error causation being assignable in only 403 instances (31%). Discussion and Conclusion: Errors related to CPOE commonly involved transmission errors, erroneous dosing, and duplicate orders. More standardized safety reporting using a common taxonomy could help health care systems and vendors learn and implement prevention strategies.

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46

Ensor, Christopher R., Denise R. Kockler, Richard W. Dugger, and Leigh Anne Hylton-Gravatt. "Erythropoiesis-Stimulating Agents: Creation and Validation of a Computerized Prescriber Order Entry Alert." Annals of Pharmacotherapy 43, no. 6 (May 19, 2009): 1143–44. http://dx.doi.org/10.1345/aph.1l714.

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47

Lee, Justin Y., Kori Leblanc, Olavo A. Fernandes, Jin-Hyeun Huh, Gary G. Wong, Bassem Hamandi, Neil M. Lazar, Dante Morra, Jana M. Bajcar, and Jennifer Harrison. "Medication Reconciliation During Internal Hospital Transfer and Impact of Computerized Prescriber Order Entry." Annals of Pharmacotherapy 44, no. 12 (November 23, 2010): 1887–95. http://dx.doi.org/10.1345/aph.1p314.

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48

Davydov, Liya, Gina C. Caliendo, Lawrence G. Smith, and Bernard Mehl. "Analysis of Clinical Intervention Documentation by Dispensing Pharmacists in a Teaching Hospital." Hospital Pharmacy 38, no. 4 (April 2003): 346–50. http://dx.doi.org/10.1177/001857870303800407.

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Decentralized pharmacists have a valuable role in preventing medication errors. At Mount Sinai Hospital, each pharmacist's contact with a prescriber to correct or clarify a possible prescribing error is documented on the original order. Our pharmacists are also encouraged to document interventions as part of the pharmacist intervention program. The authors undertook a blinded observational study to determine the percentage of prescriber contacts documented as pharmacist clinical interventions. This 2-month study was conducted in two nursing units with computerized physician order entry. All orders from these units were collected and evaluated for possible prescribing errors and documentation of a pharmacist's contact with a prescriber. Additionally, all pharmacist interventions documented in these units during the study period were collected and entered into the pharmacist intervention database. The percentage of all pharmacist interventions vs the number of documented prescriber contacts on original orders was then calculated. A total of 14 pharmacists were involved in the provision of pharmaceutical care to patients in the study units. During the 2-month study period, a total of 221 orders required pharmacists to contact prescribers regarding potential prescribing errors. However, only 109 (49.3%) of these were documented as clinical interventions. The findings indicate a need for improved documentation of clinical services (eg, interventions) performed by pharmacists.

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Miller, Alicia S. "Neonatal Intensive Care Unit Pathway." Hospital Pharmacy 38, no. 8 (August 2003): 794–97. http://dx.doi.org/10.1177/001857870303800803.

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This continuing feature will inform readers about the process of implementing, maintaining, and supporting computerized prescriber order entry (CPOE) at the Ohio State University Medical Center. (By “pre-scribers,” we refer to health care professionals authorized to prescribe medications by their states.) Practical information on what worked and what failed will be provided, along with current updates on the status of CPOE at the Medical Center.

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Emily, Siu. "P40 Impact of an educational intervention program on handwritten prescription errors in a paediatric critical care unit." Archives of Disease in Childhood 103, no. 2 (January 19, 2018): e1.44-e1. http://dx.doi.org/10.1136/archdischild-2017-314584.49.

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IntroductionMedication errors are a major source of concern in the paediatric intensive care unit (PCCU).1 To further improve medication safety on PCCU, we aim to reduce handwritten prescription errors by implementing an educational intervention program and auditing its impact.AimTo audit handwritten prescription errors on the paediatric critical care unit before and after an educational error reduction intervention.MethodHandwritten prescriptions were audited by the ward pharmacist for 2 months prior to the intervention. Errors were defined as incorrect dose for age, weight, indication, incorrect route, missing information, wrong prescription chart, inappropriate prescription. These errors were also categorised by prescriber, medication and nature of the error. Prescribers were alerted to errors at time of identification and explained how to correctly prescribe this in future. After 2 months, an educational intervention program was implemented on the same group of prescribers. This consisted of individual reminders for prescribers who made the error during the pre-intervention audit period and a summary of the most important errors emailed to all PCCU registrars. The audit continued after the intervention for another 2 weeks and collected information on errors as well as prescriptions written correctly for previously incorrectly prescribed medications.ResultOf the 11 prescription errors found in the pre- intervention audit, 9 were by PCCU prescribers. 5 of these errors were selected for dissemination to all prescribers via email based on severity and appropriateness. One of these were prescribed correctly after the intervention by the original prescriber who made the error. The other 4 prescription issues in the email were not encountered during the 2 week audit post intervention. 2 prescription errors were made in the post interventional audit, all by PCCU prescribers. One of these errors were targeted in the educational intervention, and made by a prescriber who did not make the original error in the pre-intervention audit.Conclusion and discussionsThe educational intervention implemented has shown to prevent the prescriber from making the same mistake on one occasion. However, it did not show that it could prevent all other prescribers from making the same error. This could be due to the error being made 1 day after the email summary was sent and the prescribers might not have all read it at the time.Limitations of this audit include the different length of pre and post intervention audit which made comparison of errors numbers difficult. The pre-intervention audit was extended due to small numbers of prescription errors made, which could be related to fewer prescriptions written during the quieter summer season. This resulted in a shortened post intervention audit period. Greater prescriber experience could also have an effect on errors and future audits with other groups of prescribers with no educational intervention may help account for this influence.The implementation of this education intervention has shown mixed effects on reducing handwritten prescription errors on PCCU. We aim to replicate this intervention and audit for a longer period during the winter season to further examine its effects.ReferencePotts AL, Barr FE, Gregory DF, Wright L, Patel NR. Computerised physician order entry and medication errors in a paediatric critical care unit. Pediat2004;113(1):59–63.

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